"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Number of ODE steps: 10\n",
+ "Mean RTF:\t\t\t\t0.017228 ± 0.000000\n",
+ "Mean RTF Waveform (incl. vocoder):\t0.021445 ± 0.000000\n"
+ ]
+ }
+ ],
+ "source": [
+ "outputs, rtfs = [], []\n",
+ "rtfs_w = []\n",
+ "for i, text in enumerate(tqdm(texts)):\n",
+ " output = synthesise(text) #, torch.tensor([15], device=device, dtype=torch.long).unsqueeze(0))\n",
+ " output['waveform'] = to_waveform(output['mel'], vocoder)\n",
+ "\n",
+ " # Compute Real Time Factor (RTF) with HiFi-GAN\n",
+ " t = (dt.datetime.now() - output['start_t']).total_seconds()\n",
+ " rtf_w = t * 22050 / (output['waveform'].shape[-1])\n",
+ "\n",
+ " ## Pretty print\n",
+ " print(f\"{'*' * 53}\")\n",
+ " print(f\"Input text - {i}\")\n",
+ " print(f\"{'-' * 53}\")\n",
+ " print(output['x_orig'])\n",
+ " print(f\"{'*' * 53}\")\n",
+ " print(f\"Phonetised text - {i}\")\n",
+ " print(f\"{'-' * 53}\")\n",
+ " print(output['x_phones'])\n",
+ " print(f\"{'*' * 53}\")\n",
+ " print(f\"RTF:\\t\\t{output['rtf']:.6f}\")\n",
+ " print(f\"RTF Waveform:\\t{rtf_w:.6f}\")\n",
+ " rtfs.append(output['rtf'])\n",
+ " rtfs_w.append(rtf_w)\n",
+ "\n",
+ " ## Display the synthesised waveform\n",
+ " ipd.display(ipd.Audio(output['waveform'], rate=22050))\n",
+ "\n",
+ " ## Save the generated waveform\n",
+ " save_to_folder(i, output, OUTPUT_FOLDER)\n",
+ "\n",
+ "print(f\"Number of ODE steps: {n_timesteps}\")\n",
+ "print(f\"Mean RTF:\\t\\t\\t\\t{np.mean(rtfs):.6f} ± {np.std(rtfs):.6f}\")\n",
+ "print(f\"Mean RTF Waveform (incl. vocoder):\\t{np.mean(rtfs_w):.6f} ± {np.std(rtfs_w):.6f}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e3e85c3f-1623-4647-b40c-fa96907656fc",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/almeval/models/glm4voice/web_demo.py b/almeval/models/glm4voice/web_demo.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc183f0c8c41e2076ca4164b41edcd6d04cfe068
--- /dev/null
+++ b/almeval/models/glm4voice/web_demo.py
@@ -0,0 +1,267 @@
+import json
+import os.path
+import tempfile
+import sys
+import re
+import uuid
+import requests
+from argparse import ArgumentParser
+
+import torchaudio
+from transformers import WhisperFeatureExtractor, AutoTokenizer
+from speech_tokenizer.modeling_whisper import WhisperVQEncoder
+
+
+sys.path.insert(0, "./cosyvoice")
+sys.path.insert(0, "./third_party/Matcha-TTS")
+
+from speech_tokenizer.utils import extract_speech_token
+
+import gradio as gr
+import torch
+
+audio_token_pattern = re.compile(r"<\|audio_(\d+)\|>")
+
+from flow_inference import AudioDecoder
+from audio_process import AudioStreamProcessor
+
+if __name__ == "__main__":
+ parser = ArgumentParser()
+ parser.add_argument("--host", type=str, default="0.0.0.0")
+ parser.add_argument("--port", type=int, default="8888")
+ parser.add_argument("--flow-path", type=str, default="./glm-4-voice-decoder")
+ parser.add_argument("--model-path", type=str, default="THUDM/glm-4-voice-9b")
+ parser.add_argument("--tokenizer-path", type= str, default="THUDM/glm-4-voice-tokenizer")
+ args = parser.parse_args()
+
+ flow_config = os.path.join(args.flow_path, "config.yaml")
+ flow_checkpoint = os.path.join(args.flow_path, 'flow.pt')
+ hift_checkpoint = os.path.join(args.flow_path, 'hift.pt')
+ glm_tokenizer = None
+ device = "cuda"
+ audio_decoder: AudioDecoder = None
+ whisper_model, feature_extractor = None, None
+
+
+ def initialize_fn():
+ global audio_decoder, feature_extractor, whisper_model, glm_model, glm_tokenizer
+ if audio_decoder is not None:
+ return
+
+ # GLM
+ glm_tokenizer = AutoTokenizer.from_pretrained(args.model_path, trust_remote_code=True)
+
+ # Flow & Hift
+ audio_decoder = AudioDecoder(config_path=flow_config, flow_ckpt_path=flow_checkpoint,
+ hift_ckpt_path=hift_checkpoint,
+ device=device)
+
+ # Speech tokenizer
+ whisper_model = WhisperVQEncoder.from_pretrained(args.tokenizer_path).eval().to(device)
+ feature_extractor = WhisperFeatureExtractor.from_pretrained(args.tokenizer_path)
+
+
+ def clear_fn():
+ return [], [], '', '', '', None, None
+
+
+ def inference_fn(
+ temperature: float,
+ top_p: float,
+ max_new_token: int,
+ input_mode,
+ audio_path: str | None,
+ input_text: str | None,
+ history: list[dict],
+ previous_input_tokens: str,
+ previous_completion_tokens: str,
+ ):
+
+ if input_mode == "audio":
+ assert audio_path is not None
+ history.append({"role": "user", "content": {"path": audio_path}})
+ audio_tokens = extract_speech_token(
+ whisper_model, feature_extractor, [audio_path]
+ )[0]
+ if len(audio_tokens) == 0:
+ raise gr.Error("No audio tokens extracted")
+ audio_tokens = "".join([f"<|audio_{x}|>" for x in audio_tokens])
+ audio_tokens = "<|begin_of_audio|>" + audio_tokens + "<|end_of_audio|>"
+ user_input = audio_tokens
+ system_prompt = "User will provide you with a speech instruction. Do it step by step. First, think about the instruction and respond in a interleaved manner, with 13 text token followed by 26 audio tokens. "
+
+ else:
+ assert input_text is not None
+ history.append({"role": "user", "content": input_text})
+ user_input = input_text
+ system_prompt = "User will provide you with a text instruction. Do it step by step. First, think about the instruction and respond in a interleaved manner, with 13 text token followed by 26 audio tokens."
+
+
+ # Gather history
+ inputs = previous_input_tokens + previous_completion_tokens
+ inputs = inputs.strip()
+ if "<|system|>" not in inputs:
+ inputs += f"<|system|>\n{system_prompt}"
+ inputs += f"<|user|>\n{user_input}<|assistant|>streaming_transcription\n"
+
+ with torch.no_grad():
+ response = requests.post(
+ "http://localhost:10000/generate_stream",
+ data=json.dumps({
+ "prompt": inputs,
+ "temperature": temperature,
+ "top_p": top_p,
+ "max_new_tokens": max_new_token,
+ }),
+ stream=True
+ )
+ text_tokens, audio_tokens = [], []
+ audio_offset = glm_tokenizer.convert_tokens_to_ids('<|audio_0|>')
+ end_token_id = glm_tokenizer.convert_tokens_to_ids('<|user|>')
+ complete_tokens = []
+ prompt_speech_feat = torch.zeros(1, 0, 80).to(device)
+ flow_prompt_speech_token = torch.zeros(1, 0, dtype=torch.int64).to(device)
+ this_uuid = str(uuid.uuid4())
+ tts_speechs = []
+ tts_mels = []
+ prev_mel = None
+ is_finalize = False
+ block_size_list = [25,50,100,150,200]
+ block_size_idx = 0
+ block_size = block_size_list[block_size_idx]
+ audio_processor = AudioStreamProcessor()
+ for chunk in response.iter_lines():
+ token_id = json.loads(chunk)["token_id"]
+ if token_id == end_token_id:
+ is_finalize = True
+ if len(audio_tokens) >= block_size or (is_finalize and audio_tokens):
+ if block_size_idx < len(block_size_list) - 1:
+ block_size_idx += 1
+ block_size = block_size_list[block_size_idx]
+ tts_token = torch.tensor(audio_tokens, device=device).unsqueeze(0)
+
+ if prev_mel is not None:
+ prompt_speech_feat = torch.cat(tts_mels, dim=-1).transpose(1, 2)
+
+ tts_speech, tts_mel = audio_decoder.token2wav(tts_token, uuid=this_uuid,
+ prompt_token=flow_prompt_speech_token.to(device),
+ prompt_feat=prompt_speech_feat.to(device),
+ finalize=is_finalize)
+ prev_mel = tts_mel
+
+ audio_bytes = audio_processor.process(tts_speech.clone().cpu().numpy()[0], last=is_finalize)
+
+ tts_speechs.append(tts_speech.squeeze())
+ tts_mels.append(tts_mel)
+ if audio_bytes:
+ yield history, inputs, '', '', audio_bytes, None
+ flow_prompt_speech_token = torch.cat((flow_prompt_speech_token, tts_token), dim=-1)
+ audio_tokens = []
+ if not is_finalize:
+ complete_tokens.append(token_id)
+ if token_id >= audio_offset:
+ audio_tokens.append(token_id - audio_offset)
+ else:
+ text_tokens.append(token_id)
+ tts_speech = torch.cat(tts_speechs, dim=-1).cpu()
+ complete_text = glm_tokenizer.decode(complete_tokens, spaces_between_special_tokens=False)
+ with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
+ torchaudio.save(f, tts_speech.unsqueeze(0), 22050, format="wav")
+ history.append({"role": "assistant", "content": {"path": f.name, "type": "audio/wav"}})
+ history.append({"role": "assistant", "content": glm_tokenizer.decode(text_tokens, ignore_special_tokens=False)})
+ yield history, inputs, complete_text, '', None, (22050, tts_speech.numpy())
+
+
+ def update_input_interface(input_mode):
+ if input_mode == "audio":
+ return [gr.update(visible=True), gr.update(visible=False)]
+ else:
+ return [gr.update(visible=False), gr.update(visible=True)]
+
+
+ # Create the Gradio interface
+ with gr.Blocks(title="GLM-4-Voice Demo", fill_height=True) as demo:
+ with gr.Row():
+ temperature = gr.Number(
+ label="Temperature",
+ value=0.2
+ )
+
+ top_p = gr.Number(
+ label="Top p",
+ value=0.8
+ )
+
+ max_new_token = gr.Number(
+ label="Max new tokens",
+ value=2000,
+ )
+
+ chatbot = gr.Chatbot(
+ elem_id="chatbot",
+ bubble_full_width=False,
+ type="messages",
+ scale=1,
+ )
+
+ with gr.Row():
+ with gr.Column():
+ input_mode = gr.Radio(["audio", "text"], label="Input Mode", value="audio")
+ audio = gr.Audio(label="Input audio", type='filepath', show_download_button=True, visible=True)
+ text_input = gr.Textbox(label="Input text", placeholder="Enter your text here...", lines=2, visible=False)
+
+ with gr.Column():
+ submit_btn = gr.Button("Submit")
+ reset_btn = gr.Button("Clear")
+ output_audio = gr.Audio(label="Play", streaming=True,
+ autoplay=True, show_download_button=False)
+ complete_audio = gr.Audio(label="Last Output Audio (If Any)", show_download_button=True)
+
+
+
+ gr.Markdown("""## Debug Info""")
+ with gr.Row():
+ input_tokens = gr.Textbox(
+ label=f"Input Tokens",
+ interactive=False,
+ )
+
+ completion_tokens = gr.Textbox(
+ label=f"Completion Tokens",
+ interactive=False,
+ )
+
+ detailed_error = gr.Textbox(
+ label=f"Detailed Error",
+ interactive=False,
+ )
+
+ history_state = gr.State([])
+
+ respond = submit_btn.click(
+ inference_fn,
+ inputs=[
+ temperature,
+ top_p,
+ max_new_token,
+ input_mode,
+ audio,
+ text_input,
+ history_state,
+ input_tokens,
+ completion_tokens,
+ ],
+ outputs=[history_state, input_tokens, completion_tokens, detailed_error, output_audio, complete_audio]
+ )
+
+ respond.then(lambda s: s, [history_state], chatbot)
+
+ reset_btn.click(clear_fn, outputs=[chatbot, history_state, input_tokens, completion_tokens, detailed_error, output_audio, complete_audio])
+ input_mode.input(clear_fn, outputs=[chatbot, history_state, input_tokens, completion_tokens, detailed_error, output_audio, complete_audio]).then(update_input_interface, inputs=[input_mode], outputs=[audio, text_input])
+
+ initialize_fn()
+ # Launch the interface
+ demo.launch(
+ server_port=args.port,
+ server_name=args.host
+ )
diff --git a/almeval/models/kimi_audio.py b/almeval/models/kimi_audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb3f935474e8673388be68e212725743136feb1c
--- /dev/null
+++ b/almeval/models/kimi_audio.py
@@ -0,0 +1,57 @@
+import sys
+sys.path.insert(0, 'almeval/models/kimi_audio') #noqa
+from kimia_infer.api.kimia import KimiAudio as KimiAudio_hf
+
+from .base import BaseModel
+
+
+
+
+class KimiAudio(BaseModel):
+ NAME = 'Kimi-Audio'
+
+ def __init__(self, model_path='moonshotai/Kimi-Audio-7B-Instruct', **kwargs):
+ assert model_path is not None
+ self.model = KimiAudio_hf(
+ model_path=model_path, load_detokenizer=False)
+
+ self.sampling_params = {
+ 'audio_temperature': 0.8,
+ 'audio_top_k': 10,
+ 'text_temperature': 0.0,
+ 'text_top_k': 5,
+ 'audio_repetition_penalty': 1.0,
+ 'audio_repetition_window_size': 64,
+ 'text_repetition_penalty': 1.1,
+ 'text_repetition_window_size': 16,
+ 'max_new_tokens': -1, # TODO: set it
+ }
+ super().__init__()
+
+ def get_prompt(self, msg: dict):
+ return msg['text']
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+
+ if len(audio) == 1:
+ audio = audio[0]
+ else:
+ raise NotImplementedError(
+ f'Audio length {len(audio)} not supported')
+
+ prompt = self.get_prompt(msg)
+
+ messages = []
+
+ if prompt is not None or prompt.strip() != '':
+ messages.append(
+ {'role': 'user', 'message_type': 'text', 'content': prompt})
+
+ messages.append(
+ {'role': 'user', 'message_type': 'audio', 'content': audio})
+
+ _, text = self.model.generate(
+ messages, **self.sampling_params, output_type='text')
+ return prompt, text
diff --git a/almeval/models/kimi_audio/.gitignore b/almeval/models/kimi_audio/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..399359ceb3a58976318c51c2f4142568d8cc22ae
--- /dev/null
+++ b/almeval/models/kimi_audio/.gitignore
@@ -0,0 +1,179 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python_goose script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+# For a library or package, you might want to ignore these files since the code is
+# intended to run in multiple environments; otherwise, check them in:
+# .python_goose-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+# This is especially recommended for binary packages to ensure reproducibility, and is more
+# commonly ignored for libraries.
+# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+# in version control.
+# https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.env_*
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+# and can be added to the global gitignore or merged into this file. For a more nuclear
+# option (not recommended) you can uncomment the following to ignore the entire idea folder.
+.idea/
+data
+logs
+*.zip
+conf
+.DS_Store
+.ruff_cache
+.log
+*.jsonl
+*.parquet
+*.progress
+# Vscode
+.vscode
+
+*.safetensors
+*.model
+*.pt
+*.pth
+test_audios/output
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/.gitmodules b/almeval/models/kimi_audio/.gitmodules
new file mode 100644
index 0000000000000000000000000000000000000000..4831b099bdd2633233f07224d3b78464298225e2
--- /dev/null
+++ b/almeval/models/kimi_audio/.gitmodules
@@ -0,0 +1,3 @@
+[submodule "kimia_infer/models/tokenizer/glm4"]
+ path = kimia_infer/models/tokenizer/glm4
+ url = https://github.com/THUDM/GLM-4-Voice.git
diff --git a/almeval/models/kimi_audio/Dockerfile b/almeval/models/kimi_audio/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..3dcb5703df5385147971737ac14acf9cb18da9a8
--- /dev/null
+++ b/almeval/models/kimi_audio/Dockerfile
@@ -0,0 +1,28 @@
+FROM nvidia/cuda:12.8.1-cudnn-devel-ubuntu22.04
+
+WORKDIR /app
+
+COPY ./requirements.txt /app/
+RUN apt-get update && apt-get install -y \
+ python3.10 \
+ python3.10-dev \
+ curl \
+ sox \
+ openssh-server \
+ ffmpeg \
+ libgl1-mesa-glx \
+ git \
+ ninja-build \
+ && rm -rf /var/lib/apt/lists/*
+
+# 安装 pip
+RUN curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py \
+ && python3.10 get-pip.py \
+ && rm get-pip.py
+RUN pip install -r requirements.txt
+RUN pip install flash-attn --no-build-isolation
+
+# alias python3 as python
+RUN ln -s /usr/bin/python3 /usr/bin/python
+
+CMD ["/bin/bash"]
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/README.md b/almeval/models/kimi_audio/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..75e73fe5271fa5aa121facba5d058cc2b1be0c4e
--- /dev/null
+++ b/almeval/models/kimi_audio/README.md
@@ -0,0 +1,648 @@
+
+
+
+
+Kimi-Audio-7B 🤗 | Kimi-Audio-7B-Instruct 🤗 | 📑 Paper
+
+
+
+We present Kimi-Audio, an open-source audio foundation model excelling in **audio understanding, generation, and conversation**. This repository contains the official implementation, models, and evaluation toolkit for Kimi-Audio.
+
+## 🔥🔥🔥 News!!
+* April 27, 2025: 👋 We release pretrained model weights of [Kimi-Audio-7B](https://huggingface.co/moonshotai/Kimi-Audio-7B).
+* April 25, 2025: 👋 We release the inference code and model weights of [Kimi-Audio-7B-Instruct](https://huggingface.co/moonshotai/Kimi-Audio-7B-Instruct).
+* April 25, 2025: 👋 We release the audio evaluation toolkit [Kimi-Audio-Evalkit](https://github.com/MoonshotAI/Kimi-Audio-Evalkit). We can easily reproduce the **our results and baselines** by this toolkit!
+* April 25, 2025: 👋 We release the technical report of [Kimi-Audio](https://arxiv.org/pdf/2504.18425).
+
+## Table of Contents
+
+- [Introduction](#introduction)
+- [Architecture Overview](#architecture-overview)
+- [Quick Start](#quick-start)
+- [Evaluation](#evaluation)
+ - [Speech Recognition](#automatic-speech-recognition-asr)
+ - [Audio Understanding](#audio-understanding)
+ - [Audio-to-Text Chat](#audio-to-text-chat)
+ - [Speech Conversation](#speech-conversation)
+- [Evaluation Toolkit](#evaluation-toolkit)
+- [Generation Testset](#generation-testset)
+- [License](#license)
+- [Acknowledgements](#acknowledgements)
+- [Citation](#citation)
+- [Contact Us](#contact-us)
+
+## Introduction
+
+Kimi-Audio is designed as a universal audio foundation model capable of handling a wide variety of audio processing tasks within a single unified framework. Key features include:
+
+* **Universal Capabilities:** Handles diverse tasks like speech recognition (ASR), audio question answering (AQA), audio captioning (AAC), speech emotion recognition (SER), sound event/scene classification (SEC/ASC), and end-to-end speech conversation.
+* **State-of-the-Art Performance:** Achieves SOTA results on numerous audio benchmarks (see [Evaluation](#evaluation) and the [Technical Report](https://arxiv.org/pdf/2504.18425)).
+* **Large-Scale Pre-training:** Pre-trained on over 13 million hours of diverse audio data (speech, music, sounds) and text data, enabling robust audio reasoning and language understanding.
+* **Novel Architecture:** Employs a hybrid audio input (continuous acoustic + discrete semantic tokens) and an LLM core with parallel heads for text and audio token generation.
+* **Efficient Inference:** Features a chunk-wise streaming detokenizer based on flow matching for low-latency audio generation.
+* **Open-Source:** We release the code, model checkpoints for both pretrain and instruction finetuning, and a comprehensive evaluation toolkit to foster community research and development.
+
+## Architecture Overview
+
+
+
+
+Kimi-Audio consists of three main components:
+
+1. **Audio Tokenizer:** Converts input audio into:
+ * Discrete semantic tokens (12.5Hz) using vector quantization.
+ * Continuous acoustic features derived from a Whisper encoder (downsampled to 12.5Hz).
+2. **Audio LLM:** A transformer-based model (initialized from a pre-trained text LLM like Qwen 2.5 7B) with shared layers processing multimodal inputs, followed by parallel heads for autoregressively generating text tokens and discrete audio semantic tokens.
+3. **Audio Detokenizer:** Converts the predicted discrete semantic audio tokens back into high-fidelity waveforms using a flow-matching model and a vocoder (BigVGAN), supporting chunk-wise streaming with a look-ahead mechanism for low latency.
+
+
+
+## Quick Start
+
+This example demonstrates basic usage for generating text from audio (ASR) and generating both text and speech in a conversational turn.
+
+```python
+import soundfile as sf
+from kimia_infer.api.kimia import KimiAudio
+
+# --- 1. Load Model ---
+model_path = "moonshotai/Kimi-Audio-7B-Instruct"
+model = KimiAudio(model_path=model_path, load_detokenizer=True)
+
+# --- 2. Define Sampling Parameters ---
+sampling_params = {
+ "audio_temperature": 0.8,
+ "audio_top_k": 10,
+ "text_temperature": 0.0,
+ "text_top_k": 5,
+ "audio_repetition_penalty": 1.0,
+ "audio_repetition_window_size": 64,
+ "text_repetition_penalty": 1.0,
+ "text_repetition_window_size": 16,
+}
+
+# --- 3. Example 1: Audio-to-Text (ASR) ---
+messages_asr = [
+ # You can provide context or instructions as text
+ {"role": "user", "message_type": "text", "content": "Please transcribe the following audio:"},
+ # Provide the audio file path
+ {"role": "user", "message_type": "audio", "content": "test_audios/asr_example.wav"}
+]
+
+# Generate only text output
+_, text_output = model.generate(messages_asr, **sampling_params, output_type="text")
+print(">>> ASR Output Text: ", text_output) # Expected output: "这并不是告别，这是一个篇章的结束，也是新篇章的开始。"
+
+
+# --- 4. Example 2: Audio-to-Audio/Text Conversation ---
+messages_conversation = [
+ # Start conversation with an audio query
+ {"role": "user", "message_type": "audio", "content": "test_audios/qa_example.wav"}
+]
+
+# Generate both audio and text output
+wav_output, text_output = model.generate(messages_conversation, **sampling_params, output_type="both")
+
+# Save the generated audio
+output_audio_path = "output_audio.wav"
+sf.write(output_audio_path, wav_output.detach().cpu().view(-1).numpy(), 24000) # Assuming 24kHz output
+print(f">>> Conversational Output Audio saved to: {output_audio_path}")
+print(">>> Conversational Output Text: ", text_output) # Expected output: "A."
+
+print("Kimi-Audio inference examples complete.")
+```
+
+## Evaluation
+
+Kimi-Audio achieves state-of-the-art (SOTA) performance across a wide range of audio benchmarks.
+
+The below is the overall performance:
+
+
+
+
+
+
+
+
+
+Here are performances on different benchmarks, you can easily reproduce the **our results and baselines** by our [Kimi-Audio-Evalkit](https://github.com/MoonshotAI/Kimi-Audio-Evalkit) (also see [**Evaluation Toolkit**](#evaluation-toolkit)):
+
+### Automatic Speech Recognition (ASR)
+
+
+
+ Datasets
+ Model
+ Performance (WER↓)
+
+
+
+
+ LibriSpeech Qwen2-Audio-base
+ 1.74 | 4.04
+
+
+ Baichuan-base
+ 3.02 | 6.04
+
+
+ Step-Audio-chat
+ 3.19 | 10.67
+
+
+ Qwen2.5-Omni
+ 2.37 | 4.21
+
+
+ Kimi-Audio
+ 1.28 | 2.42
+
+ Fleurs Qwen2-Audio-base
+ 3.63 | 5.20
+
+
+ Baichuan-base
+ 4.15 | 8.07
+
+
+ Step-Audio-chat
+ 4.26 | 8.56
+
+
+ Qwen2.5-Omni
+ 2.92 | 4.17
+
+
+ Kimi-Audio
+ 2.69 | 4.44
+
+ AISHELL-1 Qwen2-Audio-base
+ 1.52
+
+
+ Baichuan-base
+ 1.93
+
+
+ Step-Audio-chat
+ 2.14
+
+
+ Qwen2.5-Omni
+ 1.13
+
+
+ Kimi-Audio
+ 0.60
+
+ AISHELL-2 iosQwen2-Audio-base
+ 3.08
+
+
+ Baichuan-base
+ 3.87
+
+
+ Step-Audio-chat
+ 3.89
+
+
+ Qwen2.5-Omni
+ 2.56
+
+ Kimi-Audio
+ 2.56
+
+ WenetSpeech Qwen2-Audio-base
+ 8.40 | 7.64
+
+
+ Baichuan-base
+ 13.28 | 10.13
+
+
+ Step-Audio-chat
+ 10.83 | 9.47
+
+
+ Qwen2.5-Omni
+ 7.71 | 6.04
+
+
+ Kimi-Audio
+ 6.28 | 5.37
+
+ Kimi-ASR Internal Testset Qwen2-Audio-base
+ 2.31 | 3.24
+
+
+ Baichuan-base
+ 3.41 | 5.60
+
+
+ Step-Audio-chat
+ 2.82 | 4.74
+
+
+ Qwen2.5-Omni
+ 1.53 | 2.68
+
+
+ Kimi-Audio
+ 1.42 | 2.44
+
+
+
+### Audio Understanding
+
+
+
+ Datasets
+ Model
+ Performance↑
+
+
+
+
+ MMAU Qwen2-Audio-base
+ 58.98 | 69.07 | 52.55
+
+
+ Baichuan-chat
+ 49.10 | 59.46 | 42.47
+
+
+ GLM-4-Voice
+ 38.92 | 43.54 | 32.43
+
+
+ Step-Audio-chat
+ 49.40 | 53.75 | 47.75
+
+
+ Qwen2.5-Omni
+ 62.16 | 67.57 | 53.92
+
+ Kimi-Audio
+ 61.68 | 73.27 | 60.66
+
+
+ ClothoAQA Qwen2-Audio-base
+ 71.73 | 72.63
+
+
+ Baichuan-chat
+ 48.02 | 48.16
+
+
+ Step-Audio-chat
+ 45.84 | 44.98
+
+
+ Qwen2.5-Omni
+ 72.86 | 73.12
+
+ Kimi-Audio
+ 71.24 | 73.18
+
+
+ VocalSound Qwen2-Audio-base
+ 93.82
+
+
+ Baichuan-base
+ 58.17
+
+
+ Step-Audio-chat
+ 28.58
+
+
+ Qwen2.5-Omni
+ 93.73
+
+
+ Kimi-Audio
+ 94.85
+
+ Nonspeech7k Qwen2-Audio-base
+ 87.17
+
+
+ Baichuan-chat
+ 59.03
+
+
+ Step-Audio-chat
+ 21.38
+
+
+ Qwen2.5-Omni
+ 69.89
+
+
+ Kimi-Audio
+ 93.93
+
+ MELD Qwen2-Audio-base
+ 51.23
+
+
+ Baichuan-chat
+ 23.59
+
+
+ Step-Audio-chat
+ 33.54
+
+
+ Qwen2.5-Omni
+ 49.83
+
+
+ Kimi-Audio
+ 59.13
+
+ TUT2017 Qwen2-Audio-base
+ 33.83
+
+
+ Baichuan-base
+ 27.9
+
+
+ Step-Audio-chat
+ 7.41
+
+
+ Qwen2.5-Omni
+ 43.27
+
+
+ Kimi-Audio
+ 65.25
+
+ CochlScene Qwen2-Audio-base
+ 52.69 | 50.96
+
+
+ Baichuan-base
+ 34.93 | 34.56
+
+
+ Step-Audio-chat
+ 10.06 | 10.42
+
+
+ Qwen2.5-Omni
+ 63.82 | 63.82
+
+
+ Kimi-Audio
+ 79.84 | 80.99
+
+
+
+### Audio-to-Text Chat
+
+
+
+
+ Datasets
+ Model
+ Performance↑
+
+
+
+
+ OpenAudioBench Qwen2-Audio-chat
+ 57.19 | 69.67 | 42.77 | 40.30 | 45.20
+
+
+ Baichuan-chat
+ 59.65 | 74.33 | 46.73 | 55.40 | 58.70
+
+
+ GLM-4-Voice
+ 57.89 | 76.00 | 47.43 | 51.80 | 55.40
+
+
+ StepAudio-chat
+ 56.53 | 72.33 | 60.00 | 56.80 | 73.00
+
+
+ Qwen2.5-Omni
+ 72.76 | 75.33 | 63.76 | 57.06 | 62.80
+
+
+ Kimi-Audio
+ 75.73 | 79.33 | 58.02 | 62.10 | 70.20
+
+ VoiceBench Qwen2-Audio-chat
+ 3.69 | 3.40 | 35.35 | 35.43
+
+
+ Baichuan-chat
+ 4.00 | 3.39 | 49.64 | 48.80
+
+
+ GLM-4-Voice
+ 4.06 | 3.48 | 43.31 | 40.11
+
+
+ StepAudio-chat
+ 3.99 | 2.99 | 46.84 | 28.72
+
+
+ Qwen2.5-Omni
+ 4.33 | 3.84 | 57.41 | 56.38
+
+
+ Kimi-Audio
+ 4.46 | 3.97 | 63.12 | 62.17
+
+ VoiceBench Qwen2-Audio-chat
+ 49.01 | 22.57 | 98.85 | 54.72
+
+
+ Baichuan-chat
+ 63.30 | 41.32 | 86.73 | 62.51
+
+
+ GLM-4-Voice
+ 52.97 | 24.91 | 88.08 | 57.17
+
+
+ StepAudio-chat
+ 31.87 | 29.19 | 65.77 | 48.86
+
+
+ Qwen2.5-Omni
+ 79.12 | 53.88 | 99.62 | 72.83
+
+
+ Kimi-Audio
+ 83.52 | 61.10 | 100.00 | 76.93
+
+
+
+### Speech Conversation
+
+ Performance of Kimi-Audio and baseline models on speech conversation.
+
+
+ Model
+ Ability
+
+
+ Speed Control
+ Accent Control
+ Emotion Control
+ Empathy
+ Style Control
+ Avg
+
+
+
+
+ GPT-4o
+ 4.21
+ 3.65 4.05
+ 3.87 4.54 4.06
+
+ Step-Audio-chat
+ 3.25
+ 2.87
+ 3.33
+ 3.05
+ 4.14
+ 3.33
+
+
+ GLM-4-Voice
+ 3.83
+ 3.51
+ 3.77
+ 3.07
+ 4.04
+ 3.65
+
+
+ GPT-4o-mini
+ 3.15
+ 2.71
+ 4.24
+ 3.16
+ 4.01
+ 3.45
+
+
+ Kimi-Audio
+ 4.30 3.45
+ 4.27 3.39
+ 4.09
+ 3.90
+
+
+
+
+
+
+## Evaluation Toolkit
+
+Evaluating and comparing audio foundation models is challenging due to inconsistent metrics, varying inference configurations, and a lack of standardized generation evaluation. To address this, we developed and open-sourced an **Evaluation Toolkit**.
+
+Key features:
+* Integrates Kimi-Audio and other recent audio LLMs.
+* Implements standardized metric calculation and integrates LLMs for intelligent judging (e.g., for AQA).
+* Provides a unified platform for side-by-side comparisons with shareable inference 'recipes' for reproducibility.
+* Includes a benchmark for evaluating speech conversation abilities (control, empathy, style).
+
+We encourage the community to use and contribute to this toolkit to foster more reliable and comparable benchmarking. Find it here: [Kimi-Audio-Evalkit](https://github.com/MoonshotAI/Kimi-Audio-Evalkit).
+
+## Generation Testset
+
+We collect and release [Kimi-Audio-Generation-Testset](https://huggingface.co/datasets/moonshotai/Kimi-Audio-GenTest), which is designed to benchmark and evaluate the conversational capabilities of audio-based dialogue models. It consists of a collection of audio files containing various instructions and conversational prompts. The primary goal is to assess a model's ability to generate not just relevant, but also appropriately styled audio responses. The language in dataset is Chinese.
+
+## License
+
+The model is based and modified from [Qwen 2.5-7B](https://github.com/QwenLM/Qwen2.5). Code derived from Qwen2.5-7B is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). Other parts of the code are licensed under the [MIT License](https://opensource.org/licenses/MIT).
+
+
+
+## Acknowledgements
+
+We would like to thank the following projects and individuals for their contributions to the development of Kimi-Audio:
+
+* [Whisper](https://github.com/openai/whisper)
+* [Transformers](https://github.com/huggingface/transformers)
+* [BigVGAN](https://github.com/NVIDIA/BigVGAN)
+* [GLM-4-Voice](https://github.com/THUDM/GLM-4-Voice)
+
+Thank you to all the open-source projects for their contributions to this project!
+
+
+
+
+## Citation
+
+If you find Kimi-Audio useful in your research or applications, please cite our technical report:
+
+```bibtex
+@misc{kimiteam2025kimiaudiotechnicalreport,
+ title={Kimi-Audio Technical Report},
+ author={KimiTeam and Ding Ding and Zeqian Ju and Yichong Leng and Songxiang Liu and Tong Liu and Zeyu Shang and Kai Shen and Wei Song and Xu Tan and Heyi Tang and Zhengtao Wang and Chu Wei and Yifei Xin and Xinran Xu and Jianwei Yu and Yutao Zhang and Xinyu Zhou and Y. Charles and Jun Chen and Yanru Chen and Yulun Du and Weiran He and Zhenxing Hu and Guokun Lai and Qingcheng Li and Yangyang Liu and Weidong Sun and Jianzhou Wang and Yuzhi Wang and Yuefeng Wu and Yuxin Wu and Dongchao Yang and Hao Yang and Ying Yang and Zhilin Yang and Aoxiong Yin and Ruibin Yuan and Yutong Zhang and Zaida Zhou},
+ year={2025},
+ eprint={2504.18425},
+ archivePrefix={arXiv},
+ primaryClass={eess.AS},
+ url={https://arxiv.org/abs/2504.18425},
+}
+```
+
+## Contact Us
+
+For questions, issues, or collaboration inquiries, please feel free to open an issue on GitHub.
diff --git a/almeval/models/kimi_audio/infer.py b/almeval/models/kimi_audio/infer.py
new file mode 100644
index 0000000000000000000000000000000000000000..a62e0bfc69a78f1c104e268dd98b3ebdddc8b344
--- /dev/null
+++ b/almeval/models/kimi_audio/infer.py
@@ -0,0 +1,53 @@
+from kimia_infer.api.kimia import KimiAudio
+import os
+import soundfile as sf
+
+
+if __name__ == "__main__":
+
+ model = KimiAudio(
+ model_path="moonshotai/Kimi-Audio-7B-Instruct",
+ load_detokenizer=True,
+ )
+
+ sampling_params = {
+ "audio_temperature": 0.8,
+ "audio_top_k": 10,
+ "text_temperature": 0.0,
+ "text_top_k": 5,
+ "audio_repetition_penalty": 1.0,
+ "audio_repetition_window_size": 64,
+ "text_repetition_penalty": 1.0,
+ "text_repetition_window_size": 16,
+ }
+
+ messages = [
+ {"role": "user", "message_type": "text", "content": "请将音频内容转换为文字。"},
+ {
+ "role": "user",
+ "message_type": "audio",
+ "content": "test_audios/asr_example.wav",
+ },
+ ]
+
+ wav, text = model.generate(messages, **sampling_params, output_type="text")
+ print(">>> output text: ", text)
+
+ output_dir = "test_audios/output"
+ os.makedirs(output_dir, exist_ok=True)
+ # audio2audio
+ messages = [
+ {
+ "role": "user",
+ "message_type": "audio",
+ "content": "test_audios/qa_example.wav",
+ }
+ ]
+
+ wav, text = model.generate(messages, **sampling_params, output_type="both")
+ sf.write(
+ os.path.join(output_dir, "output.wav"),
+ wav.detach().cpu().view(-1).numpy(),
+ 24000,
+ )
+ print(">>> output text: ", text)
diff --git a/almeval/models/kimi_audio/kimia_infer/__init__.py b/almeval/models/kimi_audio/kimia_infer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/api/__init__.py b/almeval/models/kimi_audio/kimia_infer/api/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/api/kimia.py b/almeval/models/kimi_audio/kimia_infer/api/kimia.py
new file mode 100644
index 0000000000000000000000000000000000000000..10149d7a2ebf51190fb9f27446216e5221cf2f84
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/api/kimia.py
@@ -0,0 +1,322 @@
+import os
+
+import tqdm
+import torch
+from loguru import logger
+from huggingface_hub import cached_assets_path
+from transformers import AutoModelForCausalLM
+
+from kimia_infer.models.detokenizer import get_audio_detokenizer
+from .prompt_manager import KimiAPromptManager
+from kimia_infer.utils.sampler import KimiASampler
+from huggingface_hub import snapshot_download
+
+class KimiAudio(object):
+ def __init__(self, model_path: str, load_detokenizer: bool = True):
+ logger.info(f"Loading kimi-audio main model")
+
+ if os.path.exists(model_path):
+ # local path
+ cache_path = model_path
+ else:
+ # cache everything if model_path is a model-id
+ cache_path = snapshot_download(model_path)
+
+ logger.info(f"Looking for resources in {cache_path}")
+ logger.info(f"Loading whisper model")
+ self.alm = AutoModelForCausalLM.from_pretrained(
+ cache_path, torch_dtype=torch.bfloat16, trust_remote_code=True
+ )
+ self.alm = self.alm.to(torch.cuda.current_device())
+
+ model_config = self.alm.config
+ self.kimia_token_offset = model_config.kimia_token_offset
+
+ self.prompt_manager = KimiAPromptManager(
+ model_path=cache_path, kimia_token_offset=self.kimia_token_offset
+ )
+
+ if load_detokenizer:
+ logger.info(f"Loading detokenizer")
+ # need to compile extension moudules for the first time, it may take several minutes.
+ self.detokenizer = get_audio_detokenizer(cache_path)
+ else:
+ # in this case, you're not allowed to generate audio(wav)
+ self.detokenizer = None
+
+ self.extra_tokens = self.prompt_manager.extra_tokens
+ self.kimia_text_audiodelaytokens = 6
+ self.eod_ids = [self.extra_tokens.msg_end, self.extra_tokens.media_end]
+
+ @torch.inference_mode()
+ def _generate_loop(
+ self,
+ audio_input_ids: torch.Tensor, # input audio tokens
+ text_input_ids: torch.Tensor = None, # input text tokens if use multi-input
+ max_new_tokens: int = 50,
+ audio_top_k: int = 5,
+ audio_temperature: float = 0.0,
+ audio_repetition_penalty: float = 1.0,
+ audio_repetition_window_size: int = 64,
+ text_top_k: int = 5,
+ text_temperature: float = 0.0,
+ text_repetition_penalty: float = 1.0,
+ text_repetition_window_size: int = 16,
+ is_continuous_mask: torch.Tensor = None,
+ continous_feature: torch.Tensor = None,
+ output_type: str = "text",
+ ):
+
+ sampler = KimiASampler(
+ audio_top_k=audio_top_k,
+ audio_temperature=audio_temperature,
+ audio_repetition_penalty=audio_repetition_penalty,
+ audio_repetition_window_size=audio_repetition_window_size,
+ text_top_k=text_top_k,
+ text_temperature=text_temperature,
+ text_repetition_penalty=text_repetition_penalty,
+ text_repetition_window_size=text_repetition_window_size,
+ )
+
+ text_stream_is_finished = False
+ previous_audio_tokens = torch.zeros(
+ (4096,),
+ dtype=torch.int,
+ device=torch.cuda.current_device(),
+ )
+ text_previous_tokens = torch.zeros(
+ (4096,),
+ dtype=torch.int,
+ device=torch.cuda.current_device(),
+ )
+
+ decoder_input_audio_ids = audio_input_ids.clone()
+ decoder_input_text_ids = text_input_ids.clone()
+ decoder_position_ids = (
+ torch.arange(
+ 0, decoder_input_audio_ids.shape[1], device=torch.cuda.current_device()
+ )
+ .unsqueeze(0)
+ .long()
+ )
+ decoder_input_whisper_feature = continous_feature
+ decoder_is_continuous_mask = is_continuous_mask
+ past_key_values = None
+
+ last_position_id = decoder_input_audio_ids.shape[1] - 1
+
+ valid_text_length = 0
+ valid_audio_length = 0
+
+ for i in tqdm.tqdm(
+ range(max_new_tokens), desc="Generating tokens", disable=False
+ ):
+ audio_logits, text_logits, past_key_values = self.alm.forward(
+ input_ids=decoder_input_audio_ids,
+ text_input_ids=decoder_input_text_ids,
+ whisper_input_feature=decoder_input_whisper_feature,
+ is_continuous_mask=decoder_is_continuous_mask,
+ position_ids=decoder_position_ids,
+ past_key_values=past_key_values,
+ return_dict=False,
+ )
+
+ # Sample text token using the sampler
+ next_token_text = sampler.sample_text_logits(
+ text_logits, recent_tokens=text_previous_tokens[:i] if i > 0 else None
+ )
+
+ # Sample audio token using the sampler
+ next_audio_token = sampler.sample_audio_logits(
+ audio_logits, recent_tokens=previous_audio_tokens[:i] if i > 0 else None
+ )
+
+ if text_stream_is_finished:
+ next_token_text.fill_(self.extra_tokens.kimia_text_blank)
+ elif next_token_text.item() == self.extra_tokens.kimia_text_eos:
+ text_stream_is_finished = True
+ else:
+ valid_text_length += 1
+
+ text_previous_tokens[i : i + 1] = next_token_text
+
+ if i < self.kimia_text_audiodelaytokens:
+ next_audio_token.fill_(self.extra_tokens.kimia_text_blank)
+ else:
+ if output_type == "text":
+ next_audio_token.fill_(self.extra_tokens.kimia_text_blank)
+ else:
+ valid_audio_length += 1
+
+ previous_audio_tokens[i : i + 1] = next_audio_token
+
+ audio_stream_is_finished = next_audio_token.item() in self.eod_ids
+
+ if (
+ output_type == "text"
+ and text_stream_is_finished
+ or output_type == "both"
+ and audio_stream_is_finished
+ ):
+ return_text_tokens = (
+ text_previous_tokens[:valid_text_length]
+ .detach()
+ .cpu()
+ .numpy()
+ .tolist()
+ )
+ return_audio_tokens = (
+ previous_audio_tokens[
+ self.kimia_text_audiodelaytokens : valid_audio_length
+ + self.kimia_text_audiodelaytokens
+ ]
+ .detach()
+ .cpu()
+ .numpy()
+ .tolist()
+ )
+ return return_audio_tokens, return_text_tokens
+ else:
+ decoder_input_audio_ids = next_audio_token.unsqueeze(1)
+ decoder_input_text_ids = next_token_text.unsqueeze(1)
+
+ decoder_position_ids = (
+ torch.zeros(1, 1, device=torch.cuda.current_device())
+ .fill_(last_position_id + 1)
+ .long()
+ .view(1, 1)
+ )
+ last_position_id += 1
+
+ decoder_input_whisper_feature = None
+ decoder_is_continuous_mask = None
+
+ return_text_tokens = (
+ text_previous_tokens[:valid_text_length].detach().cpu().numpy().tolist()
+ )
+ return_audio_tokens = (
+ previous_audio_tokens[
+ self.kimia_text_audiodelaytokens : valid_audio_length
+ + self.kimia_text_audiodelaytokens
+ ]
+ .detach()
+ .cpu()
+ .numpy()
+ .tolist()
+ )
+ return return_audio_tokens, return_text_tokens
+
+ @torch.inference_mode()
+ def generate(
+ self,
+ chats: list[dict],
+ output_type="text",
+ audio_temperature=0.0,
+ audio_top_k=5,
+ text_temperature=0.0,
+ text_top_k=5,
+ audio_repetition_penalty=1.0,
+ audio_repetition_window_size=64,
+ text_repetition_penalty=1.0,
+ text_repetition_window_size=16,
+ max_new_tokens=-1,
+ ):
+ ## TODO: 需要一个check函数，检查输入的history格式是否合法
+ ## 比如，对于ASR任务，一定是: text-instruction/audio-instruction + audio-content, 我理解content和instruction是不能换位置的
+ ## assistant前必须有user等等，我觉得最好做一下check
+
+ assert output_type in ["text", "both"]
+
+ history = self.prompt_manager.get_prompt(chats, output_type=output_type)
+
+ audio_input_ids, text_input_ids, is_continuous_mask = history.to_tensor()
+ audio_features = history.continuous_feature
+
+ generated_wav_tokens = []
+ generated_text_tokens = []
+
+ if output_type == "both":
+ max_new_tokens = int(12.5 * 120) - audio_input_ids.shape[1]
+ else:
+ if max_new_tokens == -1:
+ max_new_tokens = 7500 - audio_input_ids.shape[1]
+
+ audio_input_ids = audio_input_ids.to(torch.cuda.current_device())
+ text_input_ids = text_input_ids.to(torch.cuda.current_device())
+ is_continuous_mask = is_continuous_mask.to(torch.cuda.current_device())
+ audio_features = [f.to(torch.cuda.current_device()) for f in audio_features]
+
+ generated_wav_tokens, generated_text_tokens = self._generate_loop(
+ audio_input_ids=audio_input_ids,
+ text_input_ids=text_input_ids,
+ max_new_tokens=max_new_tokens,
+ audio_temperature=audio_temperature,
+ audio_top_k=audio_top_k,
+ audio_repetition_penalty=audio_repetition_penalty,
+ audio_repetition_window_size=audio_repetition_window_size,
+ text_top_k=text_top_k,
+ text_temperature=text_temperature,
+ text_repetition_penalty=text_repetition_penalty,
+ text_repetition_window_size=text_repetition_window_size,
+ is_continuous_mask=is_continuous_mask,
+ continous_feature=audio_features,
+ output_type=output_type,
+ )
+
+ generated_wav_tokens = [
+ t for t in generated_wav_tokens if t >= self.kimia_token_offset
+ ] # filter out the illegal tokens
+
+ generated_wav_tokens = torch.tensor(generated_wav_tokens).unsqueeze(0)
+ generated_wav_tokens = generated_wav_tokens - self.kimia_token_offset
+
+ generated_text_tokens = [
+ t for t in generated_text_tokens if t < self.kimia_token_offset
+ ]
+ generated_text = self.detokenize_text(generated_text_tokens)
+ if self.detokenizer is not None and output_type == "both":
+ generated_wav = self.detokenize_audio(generated_wav_tokens)
+ else:
+ generated_wav = None
+
+ return generated_wav, generated_text
+
+ def detokenize_audio(self, audio_tokens):
+ if self.detokenizer is None:
+ raise ValueError("Detokenizer is not initialized")
+ self.detokenizer.clear_states()
+ chunk_size = 30 # hard-coded right now
+ first_chunk_size = 30
+ cache_speech_collection = []
+ audio_tokens = audio_tokens.to(torch.cuda.current_device())
+ audio_tokens = audio_tokens.long()
+ num_audio_tokens = audio_tokens.size(1)
+ first_chunk_semantic_tokens = audio_tokens[:, :first_chunk_size]
+ gen_speech = self.detokenizer.detokenize_streaming(
+ first_chunk_semantic_tokens,
+ is_final=(num_audio_tokens <= first_chunk_size),
+ upsample_factor=4,
+ )
+ cache_speech_collection.append(gen_speech)
+
+ if num_audio_tokens > first_chunk_size:
+ res_semantic_tokens = audio_tokens[:, first_chunk_size:]
+ for i in range(0, res_semantic_tokens.size(1), chunk_size):
+ chunk_semantic_tokens = res_semantic_tokens[:, i : i + chunk_size]
+ gen_speech = self.detokenizer.detokenize_streaming(
+ chunk_semantic_tokens,
+ upsample_factor=4,
+ is_final=(i + chunk_size >= res_semantic_tokens.size(1)),
+ )
+ cache_speech_collection.append(gen_speech)
+
+ gen_speech = torch.cat(cache_speech_collection, dim=-1)
+ return gen_speech
+
+ def detokenize_text(self, text_tokens):
+ valid_text_ids = []
+ for x in text_tokens:
+ if x == self.extra_tokens.kimia_text_eos:
+ break
+ valid_text_ids.append(x)
+ return self.prompt_manager.text_tokenizer.decode(valid_text_ids)
diff --git a/almeval/models/kimi_audio/kimia_infer/api/prompt_manager.py b/almeval/models/kimi_audio/kimia_infer/api/prompt_manager.py
new file mode 100644
index 0000000000000000000000000000000000000000..35e6c177f65ad96f243d502aaf1c2b541e8a00a8
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/api/prompt_manager.py
@@ -0,0 +1,211 @@
+from typing import List, Dict
+import os
+
+import librosa
+import torch
+from loguru import logger
+from transformers import AutoTokenizer
+
+
+from kimia_infer.models.tokenizer.whisper_Lv3.whisper import WhisperEncoder
+from kimia_infer.models.tokenizer.glm4_tokenizer import Glm4Tokenizer
+from kimia_infer.utils.data import KimiAContent
+from kimia_infer.utils.special_tokens import instantiate_extra_tokens
+
+class KimiAPromptManager:
+ def __init__(self, model_path: str, kimia_token_offset: int):
+ self.audio_tokenizer = Glm4Tokenizer("THUDM/glm-4-voice-tokenizer")
+ self.audio_tokenizer = self.audio_tokenizer.to(torch.cuda.current_device())
+
+ logger.info(f"Looking for resources in {model_path}")
+ logger.info(f"Loading whisper model")
+
+ self.whisper_model = WhisperEncoder(
+ os.path.join(model_path, "whisper-large-v3"), mel_batch_size=20
+ )
+ self.whisper_model = self.whisper_model.to(torch.cuda.current_device())
+ self.whisper_model = self.whisper_model.bfloat16()
+ self.whisper_model.eval()
+
+ logger.info(f"Loading text tokenizer")
+ self.text_tokenizer = AutoTokenizer.from_pretrained(
+ model_path, trust_remote_code=True
+ )
+
+ self.extra_tokens = instantiate_extra_tokens(self.text_tokenizer)
+
+ self.kimia_token_offset = kimia_token_offset
+
+ def _tokenize_text(self, text):
+ if text is None:
+ return None
+ token_ids = self.text_tokenizer.encode(text, bos=False, eos=False)
+ return token_ids
+
+ def _tokenize_audio(self, wav_path):
+ wav_tokens = self.audio_tokenizer.tokenize(audio_path=wav_path)
+ wav_tokens = wav_tokens + self.kimia_token_offset
+ wav_tokens_list = wav_tokens.squeeze(0).cpu().numpy().tolist()
+ return wav_tokens_list
+
+ def extract_whisper_feat(self, wav: torch.Tensor | str):
+ if isinstance(wav, str):
+ wav = librosa.load(wav, sr=16000)[0]
+
+ wav_tensor = torch.tensor(wav).unsqueeze(0)[:, :]
+ elif isinstance(wav, torch.Tensor):
+ wav_tensor = wav
+ else:
+ raise ValueError(f"Invalid wav type: {type(wav)}")
+ assert self.whisper_model is not None
+ wav_tensor = wav_tensor.to(torch.cuda.current_device())
+ continous_feature = self.whisper_model.tokenize_waveform(wav_tensor)
+ continous_feature = continous_feature.reshape(
+ continous_feature.shape[0],
+ int(continous_feature.shape[1] // 4),
+ continous_feature.shape[2] * 4,
+ )
+ return continous_feature
+
+ def tokenize_message(
+ self,
+ message,
+ tokenize_role=True,
+ has_ct_token=False,
+ has_msg_end_token=False,
+ extract_whisper_feature=False,
+ output_type: str = "text",
+ ):
+ kimia_content_msg = KimiAContent()
+
+ role = message["role"]
+
+ if tokenize_role:
+ if role == "user":
+ kimia_content_msg.audio_append(self.extra_tokens.kimia_user_msg_start)
+ kimia_content_msg.text_append(self.extra_tokens.kimia_text_blank)
+ elif role == "assistant":
+ kimia_content_msg.audio_append(
+ self.extra_tokens.kimia_assistant_msg_start
+ )
+ kimia_content_msg.text_append(self.extra_tokens.kimia_text_blank)
+ else:
+ raise NotImplementedError(f"role: {role}")
+
+ if message["message_type"] == "text":
+ text = message["content"]
+ text_tokens = self._tokenize_text(text)
+
+ kimia_content_msg.text_extend(text_tokens)
+ kimia_content_msg.audio_extend(
+ [self.extra_tokens.kimia_text_blank] * len(text_tokens)
+ )
+
+ elif message["message_type"] == "audio":
+ audio_path = message["content"]
+ speech_tokens = self._tokenize_audio(audio_path)
+
+ kimia_content_msg.audio_append(self.extra_tokens.media_begin)
+ kimia_content_msg.audio_extend(speech_tokens, is_continuous=True)
+ kimia_content_msg.audio_append(self.extra_tokens.media_end)
+ kimia_content_msg.text_extend(
+ [self.extra_tokens.kimia_text_blank] * (len(speech_tokens) + 2)
+ )
+
+ if has_ct_token:
+ if output_type == "text":
+ kimia_content_msg.audio_append(self.extra_tokens.kimia_speech_ct_id)
+ else:
+ kimia_content_msg.audio_append(
+ self.extra_tokens.kimia_speech_ctd_id
+ )
+ kimia_content_msg.text_append(self.extra_tokens.kimia_text_blank)
+
+ if extract_whisper_feature:
+ whisper_feature = self.extract_whisper_feat(audio_path)
+ kimia_content_msg.continuous_feature.append(whisper_feature)
+ elif message["message_type"] == None:
+ pass
+ else:
+ raise NotImplementedError(f"message_type: {message['message_type']}")
+
+ if has_msg_end_token:
+ kimia_content_msg.audio_append(self.extra_tokens.msg_end)
+ kimia_content_msg.text_append(self.extra_tokens.kimia_text_blank)
+
+ assert (
+ kimia_content_msg.is_valid()
+ ), f"kimia_content_msg is not valid: {kimia_content_msg}"
+
+ return kimia_content_msg
+
+ def get_prompt(
+ self, messages: List[Dict], output_type: str = "text"
+ ) -> KimiAContent:
+ """
+ messages: List[Dict]
+ messages[i] = {
+ "role": "user" | "assistant" | "system",
+ "content": str
+ }
+ """
+ assert output_type in ["text", "both"]
+
+ msgs: List[KimiAContent] = []
+ tokenize_role = True
+ has_ct_token = False
+ has_msg_end_token = False
+
+ previous_role = None
+ for msg_idx, message in enumerate(messages):
+ assert message["role"] in ["user", "assistant"]
+
+ if previous_role is None:
+ tokenize_role = True
+ else:
+ if message["role"] == previous_role:
+ tokenize_role = False
+ else:
+ tokenize_role = True
+
+ if msg_idx == len(messages) - 1:
+ has_ct_token = True
+ has_msg_end_token = True
+ else:
+ if messages[msg_idx + 1]["role"] != message["role"]:
+ has_ct_token = True
+ has_msg_end_token = True
+ else:
+ has_ct_token = False
+ has_msg_end_token = False
+
+ previous_role = message["role"]
+
+ msg = self.tokenize_message(
+ message=message,
+ tokenize_role=tokenize_role,
+ has_ct_token=has_ct_token,
+ has_msg_end_token=has_msg_end_token,
+ extract_whisper_feature=True,
+ output_type=output_type,
+ )
+ msgs.append(msg)
+
+ assistant_start_msg = self.tokenize_message(
+ message={
+ "role": "assistant",
+ "message_type": None,
+ },
+ tokenize_role=True,
+ has_ct_token=False,
+ has_msg_end_token=False,
+ )
+
+ msgs.append(assistant_start_msg)
+
+ ret_msg = msgs[0]
+
+ for msg in msgs[1:]:
+ ret_msg.merge(msg)
+
+ return ret_msg
diff --git a/almeval/models/kimi_audio/kimia_infer/models/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5a83601ad7958c992b1ba2a1119d35d71eb9531a
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/__init__.py
@@ -0,0 +1,368 @@
+import torch
+import os
+from .bigvgan_wrapper import BigVGANWrapper
+from .semantic_fm_prefix_streaming import StreamingSemanticFMWrapper
+
+
+class PrefixStreamingFlowMatchingDetokenizer:
+ def __init__(
+ self,
+ vocoder: BigVGANWrapper,
+ fm: StreamingSemanticFMWrapper,
+ look_ahead_tokens: int = 0,
+ ) -> None:
+ self.dtype = torch.bfloat16
+
+ print("Currently using bfloat16 for PrefixFlowMatchingDetokenizer")
+
+ self.vocoder = vocoder
+ self.vocoder.to_dtype(self.dtype)
+
+ self.semantic_fm = fm
+
+ # initialize mel_spec
+ self.max_pos_size = 4096
+ self.is_timbre_semantic_token = False
+ self.pre_mel = None
+ self.frame_size = 480 # how many samples in a frame
+ self.pre_wav = None
+ self.state_dict_backup = None
+ self.hamming_window_cache = {}
+ self.previous_chunk_left = None
+ self.look_ahead_tokens = look_ahead_tokens
+
+ self.clear_states()
+
+ @classmethod
+ def from_pretrained(
+ cls,
+ vocoder_config,
+ vocoder_ckpt,
+ fm_config,
+ fm_ckpt,
+ device,
+ look_ahead_tokens=0,
+ max_prompt_chunk=2,
+ max_kv_cache_tokens=900,
+ use_cfg=False,
+ use_cfg_rescale=True,
+ cfg_init=1.5,
+ cfg_scale=7.5,
+ cfg_schedule="linear",
+ ):
+ bigvgan = BigVGANWrapper.from_pretrained(vocoder_config, vocoder_ckpt, device)
+ semantic_fm = StreamingSemanticFMWrapper.from_pretrained(
+ fm_config,
+ fm_ckpt,
+ device,
+ max_prompt_chunk=max_prompt_chunk,
+ max_kv_cache_tokens=max_kv_cache_tokens,
+ use_cfg=use_cfg,
+ cfg_scale=cfg_scale,
+ use_cfg_rescale=use_cfg_rescale,
+ cfg_init=cfg_init,
+ cfg_schedule=cfg_schedule,
+ )
+ return cls(bigvgan, semantic_fm, look_ahead_tokens=look_ahead_tokens)
+
+ @torch.inference_mode()
+ def prefill(
+ self, timbre_speech, timbre_semantic_token, chunk_size: int, timbre_mel=None
+ ):
+ """
+ Arguments:
+ timbre_speech: torch.Tensor, shape [B, N_speech_24k]
+ timbre_semantic_token: torch.Tensor, shape [B, N]
+ chunk_size: int, chunk size for prefilling
+ timbre_mel: torch.Tensor, shape [B, N, 80], optional, if not None, use this mel spectrogram instead of extracting from timbre_speech
+ """
+ if timbre_mel is None:
+ assert (
+ timbre_speech is not None
+ ), "timbre_speech should not be None if timbre_mel is not None"
+ assert (
+ len(timbre_semantic_token.shape) == 2
+ and len(timbre_speech.shape) == 2
+ and chunk_size > 0
+ )
+ assert timbre_speech.shape[0] == 1 and timbre_semantic_token.shape[0] == 1
+
+ mel_spec = self.vocoder.extract_mel_from_wav(
+ wav_data=timbre_speech.squeeze(0)
+ )
+ else:
+ assert (
+ len(timbre_mel.shape) == 3
+ and len(timbre_semantic_token.shape) == 2
+ and chunk_size > 0
+ )
+ assert timbre_mel.shape[0] == 1 and timbre_semantic_token.shape[0] == 1
+ mel_spec = timbre_mel.squeeze(0)
+
+ if mel_spec.shape[0] < timbre_semantic_token.shape[1]:
+ # pad mel_spec
+ mel_spec = torch.nn.functional.pad(
+ mel_spec, (0, 0, 0, timbre_semantic_token.shape[1] - mel_spec.shape[0])
+ )
+ elif mel_spec.shape[0] > timbre_semantic_token.shape[1]:
+ # truncate mel_spec
+ mel_spec = mel_spec[: timbre_semantic_token.shape[1], :]
+
+ # clear all states
+ self.semantic_fm.clear_all_states()
+ self.semantic_fm.prefill(
+ mel_spec,
+ timbre_semantic_token.squeeze(0),
+ chunk_size=chunk_size,
+ verbose=False,
+ )
+ self.state_dict_backup = self.semantic_fm.state_dict()
+
+ @torch.inference_mode()
+ def detokenize_streaming(
+ self,
+ semantic_token,
+ ode_step=30,
+ verbose=False,
+ ode_solver="neural_ode_euler",
+ is_final=False,
+ upsample_factor=1,
+ ):
+ assert len(semantic_token.shape) == 2 and ode_step > 0
+ assert semantic_token.shape[0] == 1
+
+ semantic_token = semantic_token.repeat_interleave(upsample_factor, dim=1)
+
+ semantic_token = semantic_token.squeeze(0)
+
+ if self.look_ahead_tokens != 0 and self.previous_chunk_left is not None:
+ semantic_token_previous = self.previous_chunk_left["semantic_token"]
+ semantic_token = torch.cat(
+ [semantic_token_previous, semantic_token], dim=-1
+ )
+
+ x_t_chunk = (
+ torch.randn(semantic_token.shape[0], 80)
+ .to(semantic_token.device)
+ .to(self.dtype)
+ )
+
+ if self.look_ahead_tokens != 0 and self.previous_chunk_left is None:
+ self.previous_chunk_left = {"semantic_token": None}
+
+ speech_mel = self.semantic_fm.infer_chunk(
+ xt_chunk=x_t_chunk,
+ semantic_tokens_chunk=semantic_token,
+ start_position_id=self.semantic_fm.start_position_id,
+ ode_steps=ode_step,
+ verbose=verbose,
+ look_ahead_tokens=(
+ self.look_ahead_tokens * upsample_factor if not is_final else 0
+ ),
+ cache=self.previous_chunk_left,
+ ode_solver=ode_solver,
+ )
+
+ chunk_size = speech_mel.shape[0]
+ length = speech_mel.shape[0]
+ self.semantic_fm.start_position_id += length
+ self.semantic_fm.update_incremental_state()
+ self.semantic_fm.reserve_kv_cache_tokens += (
+ self.semantic_fm.ode_wrapper.kv_cache_tokens
+ )
+
+ # smoothing
+
+ # I will maintain the history of seqlen wav
+ # For the first chunk, I will only return the half chunk wav, and save the res half chunk in history
+ # For the rest requests, I will concat the generated wav with the history, output one chunk of the history, save the
+
+ if self.pre_mel is None: # first chunk, related to TTFB
+ concat_mel = speech_mel
+ concat_reconstructed_wav = self.vocoder.decode_mel(concat_mel)
+ if is_final:
+ self.clear_states()
+ self.state_dict_backup = None
+ ret_wav = concat_reconstructed_wav.float()
+ else:
+ reconstructed_wav = concat_reconstructed_wav[
+ :, : int(self.frame_size * chunk_size // 2)
+ ] # return the first half chunk
+
+ self.pre_wav = concat_reconstructed_wav[
+ :, -int(self.frame_size * chunk_size // 2) :
+ ] # log the last half chunk for next generation step
+ self.pre_mel = speech_mel[-chunk_size // 2 :, :]
+
+ ret_wav = reconstructed_wav.float()
+ else:
+ concat_mel = torch.cat([self.pre_mel, speech_mel], dim=0)
+ concat_reconstructed_wav = self.vocoder.decode_mel(concat_mel)
+
+ if is_final:
+ self.clear_states()
+ self.state_dict_backup = None
+ ret_wav = concat_reconstructed_wav.float()
+ else:
+ # fetch history
+ prev_speech_len = self.pre_wav.shape[1]
+
+ if concat_reconstructed_wav.shape[1] > prev_speech_len * 2:
+ gen_speech_len = prev_speech_len * 2
+ else:
+ gen_speech_len = concat_reconstructed_wav.shape[1] // 2
+
+ reconstructed_wav = concat_reconstructed_wav[
+ :, :gen_speech_len
+ ] # return the first half chunk
+
+ if gen_speech_len not in self.hamming_window_cache:
+ self.hamming_window_cache[gen_speech_len] = (
+ torch.hamming_window(gen_speech_len)
+ .to(self.dtype)
+ .to(semantic_token.device)
+ .unsqueeze(0)
+ )
+
+ hamming_window = self.hamming_window_cache[gen_speech_len]
+
+ # apply smoothing of the first half chunk
+ reconstructed_wav[:, : int(gen_speech_len // 2)] = (
+ self.pre_wav[:, : int(gen_speech_len // 2)]
+ * hamming_window[:, -int(gen_speech_len // 2) :]
+ + reconstructed_wav[:, : int(gen_speech_len // 2)]
+ * hamming_window[:, : int(gen_speech_len // 2)]
+ )
+
+ res_speech_len = concat_reconstructed_wav.shape[1] - gen_speech_len
+ res_mel_len = res_speech_len // self.frame_size
+
+ self.pre_wav = concat_reconstructed_wav[:, -res_speech_len:]
+ self.pre_mel = speech_mel[-res_mel_len:, :]
+ ret_wav = reconstructed_wav.float()
+
+ if (
+ not is_final
+ and self.semantic_fm.start_position_id + 2 * chunk_size > self.max_pos_size
+ ):
+ # out of position id,
+ self.semantic_fm.clear_all_states()
+ self.semantic_fm.load_state_dict(self.state_dict_backup)
+
+ return ret_wav
+
+ def clear_states(self):
+ self.semantic_fm.clear_all_states()
+ self.previous_chunk_left = None
+ self.pre_mel = None
+ self.pre_wav = None
+
+
+def get_audio_detokenizer(model_path):
+ fm_model_config = os.path.join(model_path, "audio_detokenizer", "config.yaml")
+ fm_ckpt_path = os.path.join(model_path, "audio_detokenizer", "model.pt")
+
+ bigvgan_config_file = os.path.join(model_path, "vocoder", "config.json")
+ bigvgan_ckpt_path = os.path.join(model_path, "vocoder", "model.pt")
+
+ device = torch.cuda.current_device()
+ detokenizer = PrefixStreamingFlowMatchingDetokenizer.from_pretrained(
+ vocoder_config=bigvgan_config_file,
+ vocoder_ckpt=bigvgan_ckpt_path,
+ max_prompt_chunk=10, # 10 * 3 = 30s
+ fm_config=fm_model_config,
+ fm_ckpt=fm_ckpt_path,
+ device=device,
+ use_cfg=False,
+ look_ahead_tokens=12,
+ )
+
+ return detokenizer
+
+
+def detokenize(detokenizer, tokens, ref_wav, ref_tokens):
+ with torch.no_grad():
+ detokenizer.clear_states()
+ detokenizer.prefill(ref_wav, ref_tokens, chunk_size=150)
+ cache_speech_collection = []
+ chunk_size = 150
+ first_chunk_size = 100
+ first_chunk_tokens = tokens[:, :first_chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ first_chunk_tokens, is_final=tokens.size(1) <= first_chunk_size
+ )
+ cache_speech_collection.append(gen_speech)
+ res_tokens = tokens[:, first_chunk_size:]
+ for i in range(0, res_tokens.size(1), chunk_size):
+ chunk_tokens = res_tokens[:, i : i + chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ chunk_tokens, is_final=(i + chunk_size >= res_tokens.size(1))
+ )
+ cache_speech_collection.append(gen_speech)
+
+ gen_speech_all = torch.cat(cache_speech_collection, dim=-1)
+ return gen_speech_all
+
+
+def detokenize_streaming(detokenizer, tokens, ref_wav, ref_tokens):
+ with torch.no_grad():
+ detokenizer.clear_states()
+ detokenizer.prefill(ref_wav, ref_tokens, chunk_size=150)
+ cache_speech_collection = []
+ chunk_size = 150
+ first_chunk_size = 100
+ first_chunk_tokens = tokens[:, :first_chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ first_chunk_tokens, is_final=tokens.size(1) <= first_chunk_size
+ )
+ yield gen_speech
+ res_tokens = tokens[:, first_chunk_size:]
+ for i in range(0, res_tokens.size(1), chunk_size):
+ chunk_tokens = res_tokens[:, i : i + chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ chunk_tokens, is_final=(i + chunk_size >= res_tokens.size(1))
+ )
+ yield gen_speech
+
+
+def detokenize_noref(detokenizer, tokens):
+ with torch.no_grad():
+ detokenizer.clear_states()
+ cache_speech_collection = []
+ chunk_size = 150
+ first_chunk_size = 100
+ first_chunk_tokens = tokens[:, :first_chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ first_chunk_tokens, is_final=tokens.size(1) <= first_chunk_size
+ )
+ cache_speech_collection.append(gen_speech)
+ res_tokens = tokens[:, first_chunk_size:]
+ for i in range(0, res_tokens.size(1), chunk_size):
+ chunk_tokens = res_tokens[:, i : i + chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ chunk_tokens, is_final=(i + chunk_size >= res_tokens.size(1))
+ )
+ cache_speech_collection.append(gen_speech)
+
+ gen_speech_all = torch.cat(cache_speech_collection, dim=-1)
+ return gen_speech_all
+
+
+def detokenize_noref_streaming(detokenizer, tokens):
+ with torch.no_grad():
+ detokenizer.clear_states()
+ cache_speech_collection = []
+ chunk_size = 150
+ first_chunk_size = 100
+ first_chunk_tokens = tokens[:, :first_chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ first_chunk_tokens, is_final=tokens.size(1) <= first_chunk_size
+ )
+ yield gen_speech
+ res_tokens = tokens[:, first_chunk_size:]
+ for i in range(0, res_tokens.size(1), chunk_size):
+ chunk_tokens = res_tokens[:, i : i + chunk_size]
+ gen_speech = detokenizer.detokenize_streaming(
+ chunk_tokens, is_final=(i + chunk_size >= res_tokens.size(1))
+ )
+ yield gen_speech
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/bigvgan_wrapper.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/bigvgan_wrapper.py
new file mode 100644
index 0000000000000000000000000000000000000000..2044f4b9c40de28e6d818b0070e858b4c5e55590
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/bigvgan_wrapper.py
@@ -0,0 +1,109 @@
+import os
+import json
+import logging
+
+import librosa
+import torch
+
+from .vocoder.bigvgan import BigVGAN
+from .vocoder.utils import get_melspec, AttrDict, load_checkpoint
+
+logger = logging.getLogger(__name__)
+
+
+class BigVGANWrapper:
+ def __init__(
+ self, vocoder: BigVGAN, device: torch.device, h: AttrDict, dtype=None
+ ) -> None:
+ self.vocoder = vocoder.to(device)
+ if dtype is not None:
+ self.vocoder = self.vocoder.to(dtype)
+ self.vocoder = self.vocoder.eval()
+ self.device = device
+ self.h = h
+
+ def to_dtype(self, dtype):
+ self.vocoder = self.vocoder.to(dtype)
+
+ def extract_mel_from_wav(self, wav_path=None, wav_data=None):
+ """
+ params:
+ wav_path: str, path of the wav, should be 24k
+ wav_data: torch.tensor or numpy array, shape [T], wav data, should be 24k
+ return:
+ mel: [T, num_mels], torch.tensor
+ """
+ if wav_data is None:
+ wav_data, _ = librosa.load(wav_path, sr=self.h["sampling_rate"])
+
+ wav_data = torch.tensor(wav_data).unsqueeze(0)
+
+ mel = get_melspec(
+ y=wav_data,
+ n_fft=self.h["n_fft"],
+ num_mels=self.h["num_mels"],
+ sampling_rate=self.h["sampling_rate"],
+ hop_size=self.h["hop_size"],
+ win_size=self.h["win_size"],
+ fmin=self.h["fmin"],
+ fmax=self.h["fmax"],
+ )
+ return mel.squeeze(0).transpose(0, 1)
+
+ @torch.inference_mode()
+ def extract_mel_from_wav_batch(self, wav_data):
+ """
+ params:
+ wav_data: torch.tensor or numpy array, shape [Batch, T], wav data, should be 24k
+ return:
+ mel: [Batch, T, num_mels], torch.tensor
+ """
+
+ wav_data = torch.tensor(wav_data)
+
+ mel = get_melspec(
+ wav=wav_data,
+ n_fft=self.h["n_fft"],
+ num_mels=self.h["num_mels"],
+ sampling_rate=self.h["sampling_rate"],
+ hop_size=self.h["hop_size"],
+ win_size=self.h["win_size"],
+ fmin=self.h["fmin"],
+ fmax=self.h["fmax"],
+ )
+ return mel.transpose(1, 2)
+
+ def decode_mel(self, mel):
+ """
+ params:
+ mel: [T, num_mels], torch.tensor
+ return:
+ wav: [1, T], torch.tensor
+ """
+ mel = mel.transpose(0, 1).unsqueeze(0).to(self.device)
+ wav = self.vocoder(mel)
+ return wav.squeeze(0)
+
+ def decode_mel_batch(self, mel):
+ """
+ params:
+ mel: [B, T, num_mels], torch.tensor
+ return:
+ wav: [B, 1, T], torch.tensor
+ """
+ mel = mel.transpose(1, 2).to(self.device)
+ wav = self.vocoder(mel)
+ return wav
+
+ @classmethod
+ def from_pretrained(cls, model_config, ckpt_path, device):
+ with open(model_config) as f:
+ data = f.read()
+ json_config = json.loads(data)
+ h = AttrDict(json_config)
+ vocoder = BigVGAN(h, True)
+ state_dict_g = load_checkpoint(ckpt_path, "cpu")
+ vocoder.load_state_dict(state_dict_g["generator"])
+
+ logger.info(">>> Load vocoder from {}".format(ckpt_path))
+ return cls(vocoder, device, h)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/dit_block.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/dit_block.py
new file mode 100644
index 0000000000000000000000000000000000000000..f60c1d39a96981d35bd30d3848954497622078f9
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/dit_block.py
@@ -0,0 +1,297 @@
+import torch
+import torch.nn as nn
+
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from flash_attn import flash_attn_varlen_func, flash_attn_varlen_qkvpacked_func
+
+
+def reshape_for_broadcast(freqs_cis: torch.Tensor, x: torch.Tensor):
+ # x shape: bsz, seqlen, self.n_local_heads, self.head_hidden_dim / 2
+ # the last shape is "self.hidden_dim / 2" because we convert to complex
+ assert x.ndim == 4
+ assert freqs_cis.shape == (
+ x.shape[0],
+ x.shape[1],
+ x.shape[-1],
+ ), f"x shape: {x.shape}, freqs_cis shape: {freqs_cis.shape}"
+
+ # reshape freq cis to match and apply pointwise multiply
+ # new shape: bsz, seq_len, 1, self.head_hidden_dim / 2
+ shape = [x.shape[0], x.shape[1], 1, x.shape[-1]]
+ return freqs_cis.view(*shape)
+
+
+def apply_rotary_emb(
+ xq: torch.Tensor,
+ xk: torch.Tensor,
+ freqs_cis: torch.Tensor,
+):
+ xq_ = torch.view_as_complex(xq.float().reshape(*xq.shape[:-1], -1, 2))
+ xk_ = torch.view_as_complex(xk.float().reshape(*xk.shape[:-1], -1, 2))
+
+ freqs_cis = reshape_for_broadcast(freqs_cis, xq_)
+ xq_out = torch.view_as_real(xq_ * freqs_cis).flatten(3)
+ xk_out = torch.view_as_real(xk_ * freqs_cis).flatten(3)
+ return xq_out.type_as(xq), xk_out.type_as(xk)
+
+
+class Attention(nn.Module):
+
+ def __init__(
+ self,
+ dim: int,
+ num_heads: int = 8,
+ qkv_bias: bool = False,
+ qk_norm: bool = False,
+ attn_drop: float = 0.0,
+ proj_drop: float = 0.0,
+ norm_layer: nn.Module = nn.LayerNorm,
+ flash_attention: bool = True,
+ ) -> None:
+ super().__init__()
+ assert dim % num_heads == 0, "dim should be divisible by num_heads"
+ self.num_heads = num_heads
+ self.head_dim = dim // num_heads
+ self.scale = self.head_dim**-0.5
+ self.fused_attn = flash_attention
+
+ self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias)
+ self.qk_norm = qk_norm
+ self.q_norm = norm_layer(self.head_dim) if qk_norm else nn.Identity()
+ self.k_norm = norm_layer(self.head_dim) if qk_norm else nn.Identity()
+ self.attn_drop = nn.Dropout(attn_drop)
+ self.proj = nn.Linear(dim, dim)
+ self.proj_drop = nn.Dropout(proj_drop)
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ seq_len,
+ cu_seqlens,
+ max_seqlen,
+ cu_seqlens_k,
+ max_seqlen_k,
+ rotary_pos_emb=None,
+ incremental_state=None,
+ nopadding=True,
+ ) -> torch.Tensor:
+ B, N, C = x.shape
+
+ if self.fused_attn:
+ if nopadding:
+ qkv = self.qkv(x)
+ qkv = qkv.view(B * N, self.num_heads * 3, self.head_dim)
+ q, k, v = qkv.split([self.num_heads] * 3, dim=1)
+ q, k = self.q_norm(q), self.k_norm(k)
+
+ q = q.view(B, N, self.num_heads, self.head_dim)
+ k = k.view(B, N, self.num_heads, self.head_dim)
+ v = v.view(B, N, self.num_heads, self.head_dim)
+
+ if rotary_pos_emb is not None:
+ q, k = apply_rotary_emb(q, k, rotary_pos_emb)
+
+ if incremental_state is not None:
+ if "prev_k" in incremental_state:
+ prev_k = incremental_state["prev_k"]
+ k = torch.cat([prev_k, k], dim=1)
+
+ if "cur_k" not in incremental_state:
+ incremental_state["cur_k"] = {}
+ incremental_state["cur_k"] = k
+
+ if "prev_v" in incremental_state:
+ prev_v = incremental_state["prev_v"]
+ v = torch.cat([prev_v, v], dim=1)
+
+ if "cur_v" not in incremental_state:
+ incremental_state["cur_v"] = {}
+ incremental_state["cur_v"] = v
+
+ q = q.view(B * N, self.num_heads, self.head_dim)
+ k = k.view(-1, self.num_heads, self.head_dim)
+ v = v.view(-1, self.num_heads, self.head_dim)
+
+ x = flash_attn_varlen_func(
+ q=q,
+ k=k,
+ v=v,
+ cu_seqlens_q=cu_seqlens,
+ cu_seqlens_k=cu_seqlens_k,
+ max_seqlen_q=max_seqlen,
+ max_seqlen_k=max_seqlen_k,
+ dropout_p=self.attn_drop.p if self.training else 0.0,
+ )
+ else:
+
+ if incremental_state is not None:
+ raise NotImplementedError(
+ "It is designed for batching inference. AR-chunk is not supported currently."
+ )
+
+ qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, self.head_dim)
+ if self.qk_norm:
+ q, k, v = qkv.unbind(2)
+ q, k = self.q_norm(q), self.k_norm(k)
+ # re-bind
+ qkv = torch.stack((q, k, v), dim=2)
+
+ # pack qkv with seq_len
+ qkv_collect = []
+ for i in range(qkv.shape[0]):
+ qkv_collect.append(qkv[i, : seq_len[i], :, :, :])
+
+ qkv = torch.cat(qkv_collect, dim=0)
+
+ x = flash_attn_varlen_qkvpacked_func(
+ qkv=qkv,
+ cu_seqlens=cu_seqlens,
+ max_seqlen=max_seqlen,
+ dropout_p=self.attn_drop.p if self.training else 0.0,
+ )
+
+ # unpack and pad 0
+ x_collect = []
+ for i in range(B):
+ x_collect.append(x[cu_seqlens[i] : cu_seqlens[i + 1], :, :])
+ x = torch.nn.utils.rnn.pad_sequence(
+ x_collect, batch_first=True, padding_value=0
+ )
+
+ else:
+ q = q * self.scale
+ attn = q @ k.transpose(-2, -1)
+ attn = attn.softmax(dim=-1)
+ attn = self.attn_drop(attn)
+ x = attn @ v
+ x = x.transpose(1, 2)
+
+ x = x.reshape(B, N, C)
+ x = self.proj(x)
+ x = self.proj_drop(x)
+ return x
+
+
+def modulate(x, shift, scale):
+ return x * (1 + scale) + shift
+
+
+class FinalLayer(nn.Module):
+ """
+ The final layer of DiT.
+ """
+
+ def __init__(self, hidden_size, out_channels):
+ super().__init__()
+ self.norm_final = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)
+ self.linear = nn.Linear(hidden_size, out_channels, bias=True)
+ self.adaLN_modulation = nn.Sequential(
+ nn.SiLU(), nn.Linear(hidden_size, 2 * hidden_size, bias=True)
+ )
+
+ def forward(self, x, c):
+ shift, scale = self.adaLN_modulation(c).chunk(2, dim=2)
+ x = modulate(self.norm_final(x), shift, scale)
+ x = self.linear(x)
+ return x
+
+
+class DiTBlock(nn.Module):
+ """
+ A DiT block with adaptive layer norm zero (adaLN-Zero) conditioning.
+ """
+
+ def __init__(
+ self,
+ hidden_size,
+ num_heads,
+ mlp_ratio=4.0,
+ ffn_type="conv1d_conv1d",
+ ffn_gated_glu=True,
+ ffn_act_layer="gelu",
+ ffn_conv_kernel_size=5,
+ **block_kwargs,
+ ):
+ super().__init__()
+ self.norm1 = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)
+ self.attn = Attention(
+ hidden_size, num_heads=num_heads, qkv_bias=True, **block_kwargs
+ )
+
+ self.norm2 = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)
+
+ if ffn_type == "vanilla_mlp":
+ from timm.models.vision_transformer import Mlp
+
+ mlp_hidden_dim = int(hidden_size * mlp_ratio)
+ approx_gelu = lambda: nn.GELU(approximate="tanh")
+ self.mlp = Mlp(
+ in_features=hidden_size,
+ hidden_features=mlp_hidden_dim,
+ act_layer=approx_gelu,
+ drop=0,
+ )
+ else:
+ raise NotImplementedError(f"FFN type {ffn_type} is not implemented")
+
+ self.adaLN_modulation = nn.Sequential(
+ nn.SiLU(), nn.Linear(hidden_size, 6 * hidden_size, bias=True)
+ )
+
+ def forward(
+ self,
+ x,
+ c,
+ seq_len,
+ cu_seqlens,
+ cu_maxlen,
+ cu_seqlens_k,
+ cu_maxlen_k,
+ mask,
+ rotary_pos_emb=None,
+ incremental_state=None,
+ nopadding=True,
+ ):
+ shift_msa, scale_msa, gate_msa, shift_mlp, scale_mlp, gate_mlp = (
+ self.adaLN_modulation(c).chunk(6, dim=2)
+ )
+
+ x_ = modulate(self.norm1(x), shift_msa, scale_msa)
+
+ if incremental_state is not None:
+ if "attn_kvcache" not in incremental_state:
+ incremental_state["attn_kvcache"] = {}
+ inc_attn = incremental_state["attn_kvcache"]
+ else:
+ inc_attn = None
+
+ x_ = self.attn(
+ x_,
+ seq_len=seq_len,
+ cu_seqlens=cu_seqlens,
+ max_seqlen=cu_maxlen,
+ cu_seqlens_k=cu_seqlens_k,
+ max_seqlen_k=cu_maxlen_k,
+ rotary_pos_emb=rotary_pos_emb,
+ incremental_state=inc_attn,
+ nopadding=nopadding,
+ )
+
+ if not nopadding:
+ x_ = x_ * mask[:, :, None]
+
+ x = x + gate_msa * x_
+
+ x_ = modulate(self.norm2(x), shift_mlp, scale_mlp)
+
+ x_ = self.mlp(x_)
+
+ if not nopadding:
+ x_ = x_ * mask[:, :, None]
+
+ x = x + gate_mlp * x_
+ return x
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/model.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..9d55d9c2af0265e345cc50d413c0ad8ebc136233
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/model.py
@@ -0,0 +1,365 @@
+import torch
+import torch.nn as nn
+import math
+from .dit_block import DiTBlock, FinalLayer
+
+
+def precompute_freqs_cis(
+ dim: int,
+ end: int,
+ theta: float = 10000.0,
+ interpolation_factor: int = 1,
+ max_seq_length: int = 4096,
+):
+ print(
+ f"using rope base theta = {theta}, interpolation factor = {interpolation_factor}"
+ )
+ freqs = 1.0 / (theta ** (torch.arange(0, dim, 2)[: (dim // 2)].float() / dim))
+
+ # ROPE type-A extention
+ # we choose to use interpolation rather than extrapolation for better position encoding
+ # for scale purposes, t should be a float tensor
+ t = torch.arange(end, device=freqs.device).float()
+ scale = 1.0 / float(interpolation_factor)
+ t *= scale
+
+ freqs = torch.outer(t, freqs).float() # type: ignore
+ freqs_cis = torch.polar(torch.ones_like(freqs), freqs) # complex64
+
+ # Sometimes, we don't need so many rope emb as seq_len is smaller than max_pos_emb
+ # e.g. rope 1M but seqlen 32k, this will cause gpu memory waste
+ if max_seq_length < end:
+ freqs_cis = freqs_cis[:max_seq_length,].clone()
+ return freqs_cis
+
+
+class TimestepEmbedder(nn.Module):
+ """
+ Embeds scalar timesteps into vector representations.
+ """
+
+ def __init__(self, hidden_size, frequency_embedding_size=256):
+ super().__init__()
+ self.mlp = nn.Sequential(
+ nn.Linear(frequency_embedding_size, hidden_size, bias=True),
+ nn.SiLU(),
+ nn.Linear(hidden_size, hidden_size, bias=True),
+ )
+ self.frequency_embedding_size = frequency_embedding_size
+
+ @staticmethod
+ def timestep_embedding(t, dim, max_period=10000):
+ """
+ Create sinusoidal timestep embeddings.
+ :param t: a 1-D Tensor of N indices, one per batch element.
+ These may be fractional.
+ :param dim: the dimension of the output.
+ :param max_period: controls the minimum frequency of the embeddings.
+ :return: an (N, D) Tensor of positional embeddings.
+ """
+ # https://github.com/openai/glide-text2im/blob/main/glide_text2im/nn.py
+ half = dim // 2
+ freqs = (
+ torch.exp(
+ -math.log(max_period)
+ * torch.arange(start=0, end=half, dtype=torch.float32)
+ / half
+ )
+ .float()
+ .to(device=t.device)
+ )
+ args = t[:, None].float() * freqs[None]
+ embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1)
+ if dim % 2:
+ embedding = torch.cat(
+ [embedding, torch.zeros_like(embedding[:, :1])], dim=-1
+ )
+ return embedding
+
+ def forward(self, t):
+ t_freq = self.timestep_embedding(t, self.frequency_embedding_size)
+ t_emb = self.mlp(t_freq.to(self.mlp[0].weight.dtype))
+ return t_emb
+
+
+class SinusoidalPositionalEmbedding(nn.Module):
+ """This module produces sinusoidal positional embeddings of any length.
+
+ Padding symbols are ignored.
+ """
+
+ def __init__(self, embedding_dim, padding_idx, init_size=1024):
+ super().__init__()
+ self.embedding_dim = embedding_dim
+ self.padding_idx = padding_idx
+ self.weights = SinusoidalPositionalEmbedding.get_embedding(
+ init_size,
+ embedding_dim,
+ padding_idx,
+ )
+ self.register_buffer("_float_tensor", torch.FloatTensor(1))
+
+ @staticmethod
+ def get_embedding(num_embeddings, embedding_dim, padding_idx=None):
+ """Build sinusoidal embeddings.
+
+ This matches the implementation in tensor2tensor, but differs slightly
+ from the description in Section 3.5 of "Attention Is All You Need".
+ """
+ half_dim = embedding_dim // 2 # d/2
+ emb = math.log(10000) / (half_dim - 1) # 2*log(10000)/(d-2)
+ emb = torch.exp(
+ torch.arange(half_dim, dtype=torch.float) * -emb
+ ) # -2i/(d-2)*log(10000); i from 0 to (d-2)/2; shape: (d/2, )
+ emb = torch.arange(num_embeddings, dtype=torch.float).unsqueeze(
+ 1
+ ) * emb.unsqueeze(
+ 0
+ ) # pos/[1000 ** (2i/(d-2))]; shape: (num_embeddings, d/2)
+ emb = torch.cat([torch.sin(emb), torch.cos(emb)], dim=1).view(
+ num_embeddings, -1
+ ) # shape: (num_embeddings, d)
+ if embedding_dim % 2 == 1:
+ # zero pad
+ emb = torch.cat([emb, torch.zeros(num_embeddings, 1)], dim=1)
+ if padding_idx is not None:
+ emb[padding_idx, :] = 0
+ return emb
+
+ def forward(self, input, incremental_state=None, timestep=None, **kwargs):
+ """Input is expected to be of size [bsz x seqlen]."""
+ bsz, seq_len = input.shape[:2]
+ max_pos = self.padding_idx + 1 + seq_len
+ if self.weights is None or max_pos > self.weights.size(0):
+ # recompute/expand embeddings if needed
+ self.weights = SinusoidalPositionalEmbedding.get_embedding(
+ max_pos,
+ self.embedding_dim,
+ self.padding_idx,
+ )
+ self.weights = self.weights.to(self._float_tensor)
+
+ if incremental_state is not None:
+ # positions is the same for every token when decoding a single step
+ pos = timestep.view(-1)[0] + 1 if timestep is not None else seq_len
+ return self.weights[self.padding_idx + pos, :].expand(bsz, 1, -1)
+
+ positions = self.make_positions(input, self.padding_idx)
+ return (
+ self.weights.index_select(0, positions.view(-1))
+ .view(bsz, seq_len, -1)
+ .detach()
+ ) # (B, T, dim)
+
+ def max_positions(self):
+ """Maximum number of supported positions."""
+ return int(1e5) # an arbitrary large number
+
+ def make_positions(self, tensor, padding_idx):
+ """Replace non-padding symbols with their position numbers.
+
+ Position numbers begin at padding_idx+1. Padding symbols are ignored.
+ """
+ # The series of casts and type-conversions here are carefully
+ # balanced to both work with ONNX export and XLA. In particular XLA
+ # prefers ints, cumsum defaults to output longs, and ONNX doesn't know
+ # how to handle the dtype kwarg in cumsum.
+ mask = tensor.ne(padding_idx).int()
+ return (torch.cumsum(mask, dim=1).type_as(mask) * mask).long() + padding_idx
+
+
+class DiTPrefix(nn.Module):
+ """
+ Diffusion model with a Transformer backbone.
+ """
+
+ def __init__(
+ self,
+ input_size,
+ output_size,
+ semantic_vocab_size,
+ hidden_size=1024,
+ depth=12,
+ num_heads=4,
+ # mlp related
+ mlp_ratio=4.0,
+ ffn_type="conv1d_conv1d",
+ ffn_gated_glu=True,
+ ffn_act_layer="gelu",
+ ffn_conv_kernel_size=5,
+ # rope
+ use_rope=False,
+ rope_params={
+ "max_position_embeddings": 4096,
+ "rope_base": 10000.0,
+ "rope_interpolation_factor": 1.0,
+ },
+ position_embedding_type="sincos",
+ max_seq_len=4096,
+ prompt_cfg_dropout=0.0,
+ ):
+ super().__init__()
+ self.num_heads = num_heads
+
+ self.prompt_cfg_dropout = prompt_cfg_dropout
+
+ self.t_embedder = TimestepEmbedder(hidden_size)
+
+ self.semantic_token_embedding = nn.Embedding(semantic_vocab_size, hidden_size)
+
+ self.input_linear = nn.Linear(input_size, hidden_size)
+
+ # position embedding
+ if position_embedding_type == "learnable":
+ self.position_embedding = nn.Embedding(max_seq_len + 1, hidden_size)
+ elif position_embedding_type == "sincos":
+ self.position_embedding = SinusoidalPositionalEmbedding(
+ hidden_size, 0, max_seq_len + 1
+ )
+ elif position_embedding_type == "skip":
+ self.position_embedding = None
+ else:
+ raise NotImplementedError(
+ "Position embedding type: {} not implemented.".format(
+ position_embedding_type
+ )
+ )
+
+ self.use_rope = use_rope
+
+ if self.use_rope:
+
+ assert (
+ hidden_size % num_heads == 0
+ ), "Hidden size must be divisible by num_heads for rope position embedding."
+ rope_dim = hidden_size // num_heads
+
+ self.rotary_pos_emb = precompute_freqs_cis(
+ rope_dim,
+ rope_params["max_position_embeddings"],
+ theta=rope_params["rope_base"],
+ interpolation_factor=rope_params["rope_interpolation_factor"],
+ max_seq_length=max_seq_len,
+ )
+
+ self.blocks = nn.ModuleList(
+ [
+ DiTBlock(
+ hidden_size,
+ num_heads,
+ mlp_ratio=mlp_ratio,
+ ffn_type=ffn_type,
+ ffn_conv_kernel_size=ffn_conv_kernel_size,
+ ffn_gated_glu=ffn_gated_glu,
+ ffn_act_layer=ffn_act_layer,
+ )
+ for _ in range(depth)
+ ]
+ )
+ self.final_layer = FinalLayer(hidden_size, output_size)
+ self.initialize_weights()
+
+ def initialize_weights(self):
+ # Initialize transformer layers:
+ def _basic_init(module):
+ if isinstance(module, nn.Linear):
+ torch.nn.init.xavier_uniform_(module.weight)
+ if module.bias is not None:
+ nn.init.constant_(module.bias, 0)
+
+ self.apply(_basic_init)
+
+ # Initialize timestep embedding MLP:
+ nn.init.normal_(self.t_embedder.mlp[0].weight, std=0.02)
+ nn.init.normal_(self.t_embedder.mlp[2].weight, std=0.02)
+
+ # Zero-out adaLN modulation layers in DiT blocks:
+ for block in self.blocks:
+ nn.init.constant_(block.adaLN_modulation[-1].weight, 0)
+ nn.init.constant_(block.adaLN_modulation[-1].bias, 0)
+
+ # Zero-out output layers:
+ nn.init.constant_(self.final_layer.adaLN_modulation[-1].weight, 0)
+ nn.init.constant_(self.final_layer.adaLN_modulation[-1].bias, 0)
+ nn.init.constant_(self.final_layer.linear.weight, 0)
+ nn.init.constant_(self.final_layer.linear.bias, 0)
+
+ def forward(
+ self,
+ x,
+ position_ids,
+ t,
+ condition,
+ seq_len,
+ cu_seqlens,
+ cu_maxlen,
+ cu_seqlens_k,
+ cu_maxlen_k,
+ mask,
+ incremental_state=None,
+ nopadding=True,
+ ):
+ """
+ Forward pass of DiT.
+ x: (N, T, C) tensor of inputs (latent representations of speech)
+ position_ids: (N, T) tensor of positional indices
+ t: (N,) tensor of diffusion timesteps
+ condition: (N, T) tensor of semantic tokens
+ seq_len: (N,) tensor of sequence lengths
+ """
+
+ condition = self.semantic_token_embedding(condition) # (N, T, D)
+
+ x = self.input_linear(x)
+
+ if self.position_embedding is not None:
+ position_emb = self.position_embedding(position_ids)
+ x = x + position_emb
+
+ # ROPE
+ if self.use_rope:
+ bsz, seqlen = position_ids.shape
+ if self.rotary_pos_emb.device != position_ids.device:
+ self.rotary_pos_emb = self.rotary_pos_emb.to(position_ids.device)
+ rotary_pos_emb = torch.zeros(
+ (bsz, seqlen, self.rotary_pos_emb.shape[1]),
+ dtype=self.rotary_pos_emb.dtype,
+ device=self.rotary_pos_emb.device,
+ )
+ for b in range(bsz):
+ cur_rope = rotary_pos_emb[b]
+ cur_position_ids = position_ids[b]
+ cur_rope[:] = self.rotary_pos_emb[cur_position_ids]
+ else:
+ rotary_pos_emb = None
+
+ t = self.t_embedder(t) # (N, D)
+ c = t.unsqueeze(1) + condition # (N, T, D)
+
+ for block_idx, block in enumerate(self.blocks):
+ # x = block(x, c, attn_mask) # (N, T, D)
+ # XXX mask could be None because we always use full mask
+
+ if incremental_state is not None:
+ if block_idx not in incremental_state:
+ incremental_state[block_idx] = {}
+ incr = incremental_state[block_idx]
+ else:
+ incr = None
+
+ x = block(
+ x=x,
+ c=c,
+ seq_len=seq_len,
+ cu_seqlens=cu_seqlens,
+ cu_maxlen=cu_maxlen,
+ cu_seqlens_k=cu_seqlens_k,
+ cu_maxlen_k=cu_maxlen_k,
+ mask=mask,
+ rotary_pos_emb=rotary_pos_emb,
+ incremental_state=incr,
+ nopadding=nopadding,
+ )
+
+ x = self.final_layer(x, c) # (N, T, C)
+ return x
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/ode_wrapper.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/ode_wrapper.py
new file mode 100644
index 0000000000000000000000000000000000000000..81dee5af54bd4f09bbee77d283c93de64db7aaf7
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/ode_wrapper.py
@@ -0,0 +1,239 @@
+import torch
+import torch.nn as nn
+from functools import lru_cache
+import copy
+
+
+@lru_cache(maxsize=1)
+def get_cached_zeros(numel, device="cpu", dtype=torch.float32):
+ return torch.zeros(numel, device=device, dtype=dtype)
+
+
+class StreamingODEWrapperForPrefix(nn.Module):
+ def __init__(
+ self,
+ net,
+ x_mask,
+ x_cond,
+ use_cfg=False,
+ use_cfg_rescale=True,
+ cfg_init=1.0,
+ cfg_scale=4.0,
+ cfg_schedule="linear",
+ cfg_token_id=0,
+ ):
+ super(StreamingODEWrapperForPrefix, self).__init__()
+ self.net = net
+ self.x_mask = x_mask
+ self.x_cond = x_cond
+
+ assert use_cfg == False, "cfg is not supported in streaming detokenizer"
+
+ self.use_cfg = use_cfg
+ self.use_cfg_rescale = use_cfg_rescale
+ self.cfg_init = cfg_init
+ self.cfg_scale = cfg_scale
+ self.cfg_token_id = cfg_token_id
+ self.cfg_schedule = cfg_schedule
+ self.position_ids = None
+ self.seq_len = None
+
+ self.incremental_state = {}
+ self.kv_cache_tokens = 0
+ self.cu_seqlens = None
+ self.cu_maxlen = None
+
+ self.cu_seqlens_k = None
+ self.cu_maxlen_k = None
+ self.previous_seqlen = None
+
+ def clear_all_states(self):
+ self.incremental_state = {}
+ self.kv_cache_tokens = 0
+ self.cu_seqlens = None
+ self.cu_maxlen = None
+
+ self.cu_seqlens_k = None
+ self.cu_maxlen_k = None
+ self.previous_seqlen = None
+
+ def state_dict(self):
+ return {
+ "incremental_state": copy.deepcopy(self.incremental_state),
+ "kv_cache_tokens": copy.deepcopy(self.kv_cache_tokens),
+ "cu_seqlens": copy.deepcopy(self.cu_seqlens),
+ "cu_maxlen": copy.deepcopy(self.cu_maxlen),
+ "cu_seqlens_k": copy.deepcopy(self.cu_seqlens_k),
+ "cu_maxlen_k": copy.deepcopy(self.cu_maxlen_k),
+ "previous_seqlen": copy.deepcopy(self.previous_seqlen),
+ }
+
+ def load_state_dict(self, state_dict):
+ self.incremental_state = state_dict["incremental_state"]
+ self.kv_cache_tokens = state_dict["kv_cache_tokens"]
+ self.cu_seqlens = state_dict["cu_seqlens"]
+ self.cu_maxlen = state_dict["cu_maxlen"]
+ self.cu_seqlens_k = state_dict["cu_seqlens_k"]
+ self.cu_maxlen_k = state_dict["cu_maxlen_k"]
+ self.previous_seqlen = state_dict["previous_seqlen"]
+
+ def set_conditions(self, x_mask, x_cond, start_position_id, cache={}):
+ if not self.use_cfg:
+ self.x_mask = x_mask
+ self.x_cond = x_cond
+ else:
+ self.x_cond = torch.cat((x_cond, x_cond), dim=0)
+ self.x_mask = torch.cat((x_mask, x_mask), dim=0)
+
+ position_ids_cur = [
+ i
+ for i in range(start_position_id, self.x_cond.shape[1] + start_position_id)
+ ]
+ position_ids = torch.tensor([position_ids_cur])
+
+ if not self.use_cfg:
+ self.position_ids = position_ids.to(self.x_cond.device).long()
+ self.seq_len = (
+ torch.Tensor([position_ids.shape[1]]).to(self.x_cond.device).long()
+ )
+ else:
+ self.position_ids = (
+ torch.cat((position_ids, position_ids), dim=0)
+ .to(self.x_cond.device)
+ .long()
+ )
+ self.seq_len = (
+ torch.Tensor([position_ids.shape[1], position_ids.shape[1]])
+ .to(self.x_cond.device)
+ .long()
+ )
+
+ cu_seqlens = torch.cumsum(self.seq_len, dim=0)
+ self.cu_seqlens = torch.cat(
+ [torch.Tensor([0]).to(cu_seqlens.device), cu_seqlens], dim=0
+ ).int()
+ self.cu_maxlen = self.seq_len.cpu().max()
+
+ if self.cu_seqlens_k is None:
+ self.cu_seqlens_k = self.cu_seqlens
+ self.cu_maxlen_k = self.cu_maxlen
+ previous_seqlen = self.seq_len
+ else:
+ previous_seqlen_old = cache["previous_seqlen"]
+ previous_seqlen = previous_seqlen_old + self.seq_len
+ # calculate cu_seqlens_k
+ cu_seqlens_k = torch.cumsum(previous_seqlen, dim=0)
+ self.cu_seqlens_k = torch.cat(
+ [torch.Tensor([0]).to(cu_seqlens_k.device), cu_seqlens_k], dim=0
+ ).int()
+ self.cu_maxlen_k = previous_seqlen.cpu().max()
+ self.previous_seqlen = previous_seqlen
+ ret_cache = {"previous_seqlen": previous_seqlen}
+ return ret_cache
+
+ def update_incremental_state(
+ self,
+ reserve_kv_cache_tokens=0,
+ max_kv_cache_tokens=900,
+ condition_cache={"previous_seqlen"},
+ ):
+
+ assert (
+ reserve_kv_cache_tokens <= max_kv_cache_tokens
+ ), "reserve_kv_cache_tokens should be less than or equal to max_kv_cache_tokens"
+
+ for layer_idx, layer_cache in self.incremental_state.items():
+ # update attention kv cache
+ layer_cache["attn_kvcache"]["prev_k"] = layer_cache["attn_kvcache"]["cur_k"]
+ layer_cache["attn_kvcache"]["prev_v"] = layer_cache["attn_kvcache"]["cur_v"]
+
+ self.kv_cache_tokens = layer_cache["attn_kvcache"]["prev_k"].shape[1]
+
+ if self.kv_cache_tokens > max_kv_cache_tokens:
+ # drop old tokens from reserve kv cache tokens to max_kv_cache_tokens
+ reserve_tokens_excludeprompt = (
+ max_kv_cache_tokens - reserve_kv_cache_tokens
+ )
+
+ if reserve_kv_cache_tokens == 0:
+ layer_cache["attn_kvcache"]["prev_k"] = layer_cache["attn_kvcache"][
+ "prev_k"
+ ][:, -reserve_tokens_excludeprompt:]
+ layer_cache["attn_kvcache"]["prev_v"] = layer_cache["attn_kvcache"][
+ "prev_v"
+ ][:, -reserve_tokens_excludeprompt:]
+ elif reserve_tokens_excludeprompt == 0:
+ layer_cache["attn_kvcache"]["prev_k"] = layer_cache["attn_kvcache"][
+ "prev_k"
+ ][:, :reserve_kv_cache_tokens]
+ layer_cache["attn_kvcache"]["prev_v"] = layer_cache["attn_kvcache"][
+ "prev_v"
+ ][:, :reserve_kv_cache_tokens]
+ else:
+ layer_cache["attn_kvcache"]["prev_k"] = torch.cat(
+ [
+ layer_cache["attn_kvcache"]["prev_k"][
+ :, :reserve_kv_cache_tokens
+ ],
+ layer_cache["attn_kvcache"]["prev_k"][
+ :, -reserve_tokens_excludeprompt:
+ ],
+ ],
+ dim=1,
+ )
+
+ layer_cache["attn_kvcache"]["prev_v"] = torch.cat(
+ [
+ layer_cache["attn_kvcache"]["prev_v"][
+ :, :reserve_kv_cache_tokens
+ ],
+ layer_cache["attn_kvcache"]["prev_v"][
+ :, -reserve_tokens_excludeprompt:
+ ],
+ ],
+ dim=1,
+ )
+
+ bsz = layer_cache["attn_kvcache"]["prev_k"].shape[0]
+ self.previous_seqlen = (
+ torch.Tensor(
+ [
+ layer_cache["attn_kvcache"]["prev_k"].shape[1]
+ for i in range(bsz)
+ ]
+ )
+ .to(layer_cache["attn_kvcache"]["prev_k"].device)
+ .long()
+ )
+ condition_cache["previous_seqlen"] = self.previous_seqlen
+ self.kv_cache_tokens = layer_cache["attn_kvcache"]["prev_k"].shape[1]
+
+ # clear current cache
+ layer_cache["attn_kvcache"].pop("cur_k")
+ layer_cache["attn_kvcache"].pop("cur_v")
+
+ def forward(self, t, x, args=None):
+ # t = torch.tensor([t * 1000] * x.shape[0], device=x.device, dtype=x.dtype).long()
+ t = (
+ get_cached_zeros(x.shape[0], device=x.device, dtype=torch.long)
+ + (t * 1000).long()
+ )
+
+ if self.use_cfg:
+ raise NotImplementedError("cfg is not supported in streaming detokenizer.")
+ else:
+ pred_noise = self.net(
+ x=x,
+ condition=self.x_cond,
+ t=t,
+ position_ids=self.position_ids,
+ cu_seqlens=self.cu_seqlens,
+ cu_maxlen=self.cu_maxlen,
+ cu_seqlens_k=self.cu_seqlens_k,
+ cu_maxlen_k=self.cu_maxlen_k,
+ incremental_state=self.incremental_state,
+ nopadding=True,
+ mask=None,
+ seq_len=None,
+ )
+ return pred_noise
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/scheduler.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/scheduler.py
new file mode 100644
index 0000000000000000000000000000000000000000..d88a69cdea12d63ceeb1446c0332a331a66cf706
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/flow_matching/scheduler.py
@@ -0,0 +1,98 @@
+import torch
+from abc import abstractmethod, ABC
+
+try:
+ from torchdyn.core import NeuralODE
+
+ NEURALODE_INSTALLED = True
+except ImportError:
+ NEURALODE_INSTALLED = False
+
+
+class SchedulerBase(ABC):
+ def __init__(self) -> None:
+ pass
+
+ @abstractmethod
+ def set_timesteps(self):
+ pass
+
+ @abstractmethod
+ def step(self):
+ pass
+
+ @abstractmethod
+ def add_noise(self):
+ pass
+
+
+class StreamingFlowMatchingScheduler(SchedulerBase):
+ def __init__(
+ self,
+ timesteps=1000,
+ sigma_min=1e-4,
+ ) -> None:
+ super().__init__()
+
+ self.sigma_min = sigma_min
+ self.timesteps = timesteps
+ self.t_min = 0
+ self.t_max = 1 - self.sigma_min
+
+ self.neural_ode = None
+
+ def set_timesteps(self, timesteps=15):
+ self.timesteps = timesteps
+
+ def step(self, xt, predicted_v):
+
+ h = (self.t_max - self.t_min) / self.timesteps
+ h = h * torch.ones(xt.shape[0], dtype=xt.dtype, device=xt.device)
+
+ xt = xt + h * predicted_v
+ return xt
+
+ def sample(self, ode_wrapper, time_steps, xt, verbose=False, x0=None):
+ h = (self.t_max - self.t_min) / self.timesteps
+ h = h * torch.ones(xt.shape[0], dtype=xt.dtype, device=xt.device)
+
+ if verbose:
+ gt_v = x0 - xt
+
+ for t in time_steps:
+ predicted_v = ode_wrapper(t, xt)
+ if verbose:
+ dist = torch.mean(torch.nn.functional.l1_loss(gt_v, predicted_v))
+ print("Time: {}, Distance: {}".format(t, dist))
+ xt = xt + h * predicted_v
+ return xt
+
+ def sample_by_neuralode(self, ode_wrapper, time_steps, xt, verbose=False, x0=None):
+ if not NEURALODE_INSTALLED:
+ raise ImportError("NeuralODE is not installed, please install it first.")
+
+ if self.neural_ode is None:
+ self.neural_ode = NeuralODE(
+ ode_wrapper,
+ solver="euler",
+ sensitivity="adjoint",
+ atol=self.sigma_min,
+ rtol=self.sigma_min,
+ )
+
+ eval_points, traj = self.neural_ode(xt, time_steps)
+ return traj[-1]
+
+ def add_noise(
+ self,
+ original_samples: torch.FloatTensor,
+ noise: torch.FloatTensor,
+ timesteps: torch.IntTensor,
+ ):
+ ut = original_samples - (1 - self.sigma_min) * noise # 和ut的梯度没关系
+ t_unsqueeze = timesteps.unsqueeze(1).unsqueeze(1).float() / self.timesteps
+ x_noisy = (
+ t_unsqueeze * original_samples
+ + (1.0 - (1 - self.sigma_min) * t_unsqueeze) * noise
+ )
+ return x_noisy, ut
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/semantic_fm_prefix_streaming.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/semantic_fm_prefix_streaming.py
new file mode 100644
index 0000000000000000000000000000000000000000..cf3e3ae928b94c6b586394659f3d305222bdc4d2
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/semantic_fm_prefix_streaming.py
@@ -0,0 +1,389 @@
+import yaml
+import logging
+import time
+
+import os
+import torch
+
+from .flow_matching.ode_wrapper import StreamingODEWrapperForPrefix
+from .flow_matching.model import DiTPrefix
+from .flow_matching.scheduler import StreamingFlowMatchingScheduler
+
+
+logger = logging.getLogger(__name__)
+
+
+class StreamingSemanticFMWrapper:
+ def __init__(
+ self,
+ speech_model: DiTPrefix,
+ max_kv_cache_tokens=900,
+ max_prompt_chunk=2,
+ use_cfg=True,
+ use_cfg_rescale=True,
+ cfg_init=1.5,
+ cfg_scale=7.5,
+ cfg_schedule="linear",
+ cfg_token_id=0,
+ normalize_mel=False,
+ mel_mean=None,
+ mel_std=None,
+ device: torch.device = torch.device("cpu"),
+ ) -> None:
+
+ self.dtype = torch.bfloat16
+ self.speech_model = speech_model.to(device).to(self.dtype)
+ self.speech_model = self.speech_model.eval()
+ self.device = device
+ self.normalize_mel = normalize_mel
+ self.mel_mean = mel_mean
+ self.mel_std = mel_std
+
+ self.use_cfg = use_cfg
+ self.use_cfg_rescale = use_cfg_rescale
+ self.cfg_init = cfg_init
+ self.cfg_scale = cfg_scale
+ self.cfg_schedule = cfg_schedule
+
+ self.incremental_state = {}
+ self.condition_cache = {"previous_seqlen": 0}
+
+ logger.info(
+ f">>> SemanticFMWrapper initialized with use_cfg={use_cfg}, use_cfg_rescale={use_cfg_rescale}, cfg_init={cfg_init}, cfg_scale={cfg_scale}, cfg_schedule={cfg_schedule}"
+ )
+
+ self.scheduler = StreamingFlowMatchingScheduler()
+ self.ode_wrapper = StreamingODEWrapperForPrefix(
+ net=self.speech_model,
+ x_mask=None,
+ x_cond=None,
+ use_cfg=use_cfg,
+ use_cfg_rescale=use_cfg_rescale,
+ cfg_init=cfg_init,
+ cfg_scale=cfg_scale,
+ cfg_schedule=cfg_schedule,
+ cfg_token_id=cfg_token_id,
+ )
+
+ self.max_kv_cache_tokens = max_kv_cache_tokens
+ self.max_prompt_chunk = max_prompt_chunk
+ self.reserve_kv_cache_tokens = 0
+
+ @torch.inference_mode()
+ def infer_chunk(
+ self,
+ xt_chunk,
+ semantic_tokens_chunk,
+ start_position_id,
+ cache=None,
+ look_ahead_tokens=0,
+ ode_steps=15,
+ verbose=False,
+ ode_solver="neural_ode_euler",
+ ):
+ """
+ semantic_tokens: [T_1], torch.LongTensor
+ xt: [T_2, 80], torch.Tensor, DO NOT normalize it outside
+ ode_steps: int, number of ode steps, default 15
+ verbose: bool, default False
+ ode_solver: str, ode solver, expected in ("neural_ode_euler", "naive_euler"), default "neural_ode_euler"
+ """
+ bs = 1
+
+ self.scheduler.set_timesteps(ode_steps)
+
+ semantic_tokens_chunk = semantic_tokens_chunk.unsqueeze(0).to(self.device)
+ xt_chunk = xt_chunk.unsqueeze(0).to(self.device).to(self.dtype)
+
+ t_span = torch.linspace(0, 1, self.scheduler.timesteps)
+
+ x_mask = torch.zeros(bs, xt_chunk.shape[1], device=self.device).bool()
+
+ cache_ret = self.ode_wrapper.set_conditions(
+ x_mask=x_mask,
+ x_cond=semantic_tokens_chunk,
+ start_position_id=start_position_id,
+ cache=self.condition_cache,
+ )
+
+ if verbose:
+ t_start = time.time()
+ if ode_solver == "neural_ode_euler":
+ x_t = self.scheduler.sample_by_neuralode(
+ self.ode_wrapper, time_steps=t_span, xt=xt_chunk, verbose=False
+ )
+ elif ode_solver == "naive_euler":
+ x_t = self.scheduler.sample(
+ ode_wrapper=self.ode_wrapper,
+ time_steps=t_span,
+ xt=xt_chunk,
+ verbose=False,
+ )
+ else:
+ raise NotImplementedError(
+ "ode_solver should be in ('neural_ode_euler', 'naive_euler')"
+ )
+
+ if look_ahead_tokens > 0:
+ semantic_tokens_left = semantic_tokens_chunk.view(-1)[-look_ahead_tokens:]
+ cache["semantic_token"] = semantic_tokens_left
+ x_t_ret = x_t[:, :-look_ahead_tokens, :]
+ else:
+ x_t_ret = x_t
+
+ if look_ahead_tokens > 0:
+ x_mask = torch.zeros(
+ bs, xt_chunk.shape[1] - look_ahead_tokens, device=self.device
+ ).bool()
+ self.condition_cache = self.ode_wrapper.set_conditions(
+ x_mask=x_mask,
+ x_cond=semantic_tokens_chunk[:, :-look_ahead_tokens],
+ start_position_id=start_position_id,
+ cache=self.condition_cache,
+ )
+ self.ode_wrapper(torch.Tensor([0.999]).to(x_t_ret.device), x_t_ret)
+ else:
+ self.condition_cache = cache_ret
+
+ if verbose:
+ t_end = time.time()
+ logger.info(f"[ODE Chunk] Time cost: {t_end - t_start}")
+
+ if self.normalize_mel:
+ x_t_ret = x_t_ret * self.mel_std + self.mel_mean
+ return x_t_ret.squeeze(0)
+
+ @torch.inference_mode()
+ def infer_mel(
+ self,
+ semantic_tokens,
+ ode_steps=15,
+ chunk_size=150,
+ verbose=False,
+ ode_solver="neural_ode_euler",
+ ):
+ """
+ semantic_tokens: [T_1], torch.LongTensor
+ prompt: [T_2, 80], torch.Tensor, DO NOT normalize it outside
+ prompt_semantic_tokens, [T_2], torch.LongTensor
+ ode_steps: int, number of ode steps, default 15
+ verbose: bool, default False
+ ode_solver: str, ode solver, expected in ("neural_ode_euler", "naive_euler"), default "neural_ode_euler"
+ """
+ assert semantic_tokens.dim() == 1
+
+ x_t = torch.randn(semantic_tokens.shape[0], 80).to(self.device).to(self.dtype)
+
+ seq_len = semantic_tokens.shape[0]
+
+ num_chunks = seq_len // chunk_size
+ if seq_len % chunk_size != 0:
+ num_chunks += 1
+
+ x_pred_collect = []
+
+ if verbose:
+ t_start = time.time()
+
+ for chunk_id in range(num_chunks):
+ start = chunk_id * chunk_size
+ end = min(start + chunk_size, seq_len)
+ semantic_tokens_chunk = semantic_tokens[start:end]
+ x_t_chunk = x_t[start:end, :]
+
+ x_pred = self.infer_chunk(
+ xt_chunk=x_t_chunk,
+ semantic_tokens_chunk=semantic_tokens_chunk,
+ start_position_id=self.start_position_id,
+ ode_steps=ode_steps,
+ verbose=verbose,
+ ode_solver=ode_solver,
+ )
+ self.start_position_id += end - start
+ self.update_incremental_state()
+
+ x_pred_collect.append(x_pred)
+
+ if verbose:
+ t_end = time.time()
+ logger.info(f"[ODE] Time cost: {t_end - t_start}")
+
+ x_pred = torch.cat(x_pred_collect, dim=0)
+
+ return x_pred
+
+ def clear_all_states(self):
+ self.start_position_id = 0
+ self.condition_cache = {"previous_seqlen": 0}
+ self.ode_wrapper.clear_all_states()
+
+ def state_dict(self):
+ return {
+ "start_position_id": self.start_position_id,
+ "ode_wrapper": self.ode_wrapper.state_dict(),
+ "condition_cache": self.condition_cache,
+ }
+
+ def load_state_dict(self, state_dict):
+ if state_dict is not None:
+ self.start_position_id = state_dict["start_position_id"]
+ self.ode_wrapper.load_state_dict(state_dict["ode_wrapper"])
+ self.condition_cache = state_dict["condition_cache"]
+
+ def update_incremental_state(self):
+ self.ode_wrapper.update_incremental_state(
+ reserve_kv_cache_tokens=0,
+ max_kv_cache_tokens=self.max_kv_cache_tokens,
+ condition_cache=self.condition_cache,
+ )
+
+ @torch.inference_mode()
+ def prefill(self, mel, semantic_token, chunk_size=150, verbose=False):
+ """
+ mel: [T, 80], torch.Tensor
+ semantic_token: [T], torch.LongTensor
+ chunk_size: int, default 150
+ """
+ assert mel.dim() == 2
+ assert semantic_token.dim() == 1
+ assert (
+ semantic_token.shape[0] == mel.shape[0]
+ ), "Semantic token and mel shape mismatch"
+ seq_len = mel.shape[0]
+ num_chunks = min(seq_len // chunk_size, self.max_prompt_chunk)
+ start_pos = seq_len - num_chunks * chunk_size
+
+ res_mel = mel[:start_pos, :]
+ res_semantic_token = semantic_token[:start_pos]
+ self.prefill_chunk(
+ res_mel, res_semantic_token, start_position_id=self.start_position_id
+ )
+ self.start_position_id += start_pos
+ self.update_incremental_state()
+ self.reserve_kv_cache_tokens += self.ode_wrapper.kv_cache_tokens
+
+ if verbose:
+ logger.info("Prefilling prompt with {} chunks".format(num_chunks))
+ start_time = time.time()
+
+ for chunk_id in range(num_chunks):
+ start = start_pos + chunk_id * chunk_size
+ end = start + chunk_size
+ mel_chunk = mel[start:end, :]
+ semantic_token_chunk = semantic_token[start:end]
+
+ self.prefill_chunk(
+ mel_chunk,
+ semantic_token_chunk,
+ start_position_id=self.start_position_id,
+ )
+ self.start_position_id += end - start
+
+ self.update_incremental_state()
+ self.reserve_kv_cache_tokens += self.ode_wrapper.kv_cache_tokens
+
+ if verbose:
+ logger.info(
+ "Prefilling done in {:.2f} seconds".format(time.time() - start_time)
+ )
+
+ def prefill_chunk(self, mel_chunk, semantic_tokens_chunk, start_position_id=0):
+ """
+ mel_chunk: [T, 80], torch.Tensor, T is the chunk size
+ semantic_tokens_chunk: [T], torch.LongTensor
+ start_position_id: int, default 0
+ """
+ bs = 1
+
+ semantic_tokens_chunk = semantic_tokens_chunk.unsqueeze(0).to(self.device)
+ mel_chunk = mel_chunk.unsqueeze(0).to(self.device).to(self.dtype)
+
+ if self.normalize_mel:
+ mel_chunk = (mel_chunk - self.mel_mean) / self.mel_std
+
+ x_mask = torch.zeros(bs, mel_chunk.shape[1], device=self.device).bool()
+
+ self.condition_cache = self.ode_wrapper.set_conditions(
+ x_mask=x_mask,
+ x_cond=semantic_tokens_chunk,
+ start_position_id=start_position_id,
+ cache=self.condition_cache,
+ )
+
+ x_t = torch.Tensor([0.999]).to(self.device)
+
+ self.ode_wrapper(x_t, mel_chunk)
+
+ @classmethod
+ def from_pretrained(
+ cls,
+ model_config,
+ ckpt_path,
+ device,
+ max_prompt_chunk=2,
+ max_kv_cache_tokens=900,
+ use_cfg=True,
+ use_cfg_rescale=True,
+ cfg_init=1.5,
+ cfg_scale=7.5,
+ cfg_schedule="linear",
+ ):
+
+ # open yaml file
+ with open(model_config, "r") as f:
+ config = yaml.safe_load(f)
+ model_config = config["model"]["dit"]
+ dit = DiTPrefix(
+ input_size=model_config["input_size"],
+ semantic_vocab_size=model_config["semantic_vocab_size"] + 1,
+ hidden_size=model_config["hidden_size"],
+ depth=model_config["depth"],
+ num_heads=model_config["num_heads"],
+ mlp_ratio=model_config["mlp_ratio"],
+ ffn_type=model_config.get("ffn_type", "conv1d_conv1d"),
+ ffn_gated_glu=model_config.get("ffn_gated_glu", True),
+ ffn_act_layer=model_config.get("ffn_act_layer", "gelu"),
+ ffn_conv_kernel_size=model_config.get("ffn_conv_kernel_size", 5),
+ use_rope=model_config.get("use_rope", False),
+ rope_params=model_config.get(
+ "rope_params",
+ {
+ "max_position_embeddings": 4096,
+ "rope_base": 10000,
+ "rope_interpolation_factor": 1,
+ },
+ ),
+ position_embedding_type=model_config["position_embedding_type"],
+ max_seq_len=model_config["max_seq_len"],
+ output_size=model_config["input_size"],
+ prompt_cfg_dropout=0,
+ )
+ cfg_semantic_token_id = model_config["semantic_vocab_size"]
+
+ # load state_dict
+ state_dict = torch.load(ckpt_path, map_location="cpu", weights_only=True)[
+ "state_dict"
+ ]
+ speech_model_params = {
+ k.replace("speech_model.", ""): v
+ for k, v in state_dict.items()
+ if "speech_model" in k
+ }
+ dit.load_state_dict(speech_model_params, strict=True)
+ logger.info(f">>> Loaded checkpoint from {ckpt_path}")
+
+ return cls(
+ speech_model=dit,
+ device=device,
+ normalize_mel=config["normalize_mel"],
+ mel_mean=config["mel_mean"],
+ mel_std=config["mel_std"],
+ max_prompt_chunk=max_prompt_chunk,
+ max_kv_cache_tokens=max_kv_cache_tokens,
+ use_cfg=use_cfg,
+ use_cfg_rescale=use_cfg_rescale,
+ cfg_init=cfg_init,
+ cfg_scale=cfg_scale,
+ cfg_schedule=cfg_schedule,
+ cfg_token_id=cfg_semantic_token_id,
+ )
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/activations.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/activations.py
new file mode 100644
index 0000000000000000000000000000000000000000..dbc62f728ae0ce6b9bd1229ff12b310faaebe8a1
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/activations.py
@@ -0,0 +1,123 @@
+import torch
+from torch import nn, sin, pow
+from torch.nn import Parameter
+
+
+class Snake(nn.Module):
+ """
+ Implementation of a sine-based periodic activation function
+ Shape:
+ - Input: (B, C, T)
+ - Output: (B, C, T), same shape as the input
+ Parameters:
+ - alpha - trainable parameter
+ References:
+ - This activation function is from this paper by Liu Ziyin, Tilman Hartwig, Masahito Ueda:
+ https://arxiv.org/abs/2006.08195
+ Examples:
+ >>> a1 = snake(256)
+ >>> x = torch.randn(256)
+ >>> x = a1(x)
+ """
+
+ def __init__(
+ self, in_features, alpha=1.0, alpha_trainable=True, alpha_logscale=False
+ ):
+ """
+ Initialization.
+ INPUT:
+ - in_features: shape of the input
+ - alpha: trainable parameter
+ alpha is initialized to 1 by default, higher values = higher-frequency.
+ alpha will be trained along with the rest of your model.
+ """
+ super(Snake, self).__init__()
+ self.in_features = in_features
+
+ # Initialize alpha
+ self.alpha_logscale = alpha_logscale
+ if self.alpha_logscale: # Log scale alphas initialized to zeros
+ self.alpha = Parameter(torch.zeros(in_features) * alpha)
+ else: # Linear scale alphas initialized to ones
+ self.alpha = Parameter(torch.ones(in_features) * alpha)
+
+ self.alpha.requires_grad = alpha_trainable
+
+ self.no_div_by_zero = 0.000000001
+
+ def forward(self, x):
+ """
+ Forward pass of the function.
+ Applies the function to the input elementwise.
+ Snake ∶= x + 1/a * sin^2 (xa)
+ """
+ alpha = self.alpha.unsqueeze(0).unsqueeze(-1) # Line up with x to [B, C, T]
+ if self.alpha_logscale:
+ alpha = torch.exp(alpha)
+ x = x + (1.0 / (alpha + self.no_div_by_zero)) * pow(sin(x * alpha), 2)
+
+ return x
+
+
+class SnakeBeta(nn.Module):
+ """
+ A modified Snake function which uses separate parameters for the magnitude of the periodic components
+ Shape:
+ - Input: (B, C, T)
+ - Output: (B, C, T), same shape as the input
+ Parameters:
+ - alpha - trainable parameter that controls frequency
+ - beta - trainable parameter that controls magnitude
+ References:
+ - This activation function is a modified version based on this paper by Liu Ziyin, Tilman Hartwig, Masahito Ueda:
+ https://arxiv.org/abs/2006.08195
+ Examples:
+ >>> a1 = snakebeta(256)
+ >>> x = torch.randn(256)
+ >>> x = a1(x)
+ """
+
+ def __init__(
+ self, in_features, alpha=1.0, alpha_trainable=True, alpha_logscale=False
+ ):
+ """
+ Initialization.
+ INPUT:
+ - in_features: shape of the input
+ - alpha - trainable parameter that controls frequency
+ - beta - trainable parameter that controls magnitude
+ alpha is initialized to 1 by default, higher values = higher-frequency.
+ beta is initialized to 1 by default, higher values = higher-magnitude.
+ alpha will be trained along with the rest of your model.
+ """
+ super(SnakeBeta, self).__init__()
+ self.in_features = in_features
+
+ # Initialize alpha
+ self.alpha_logscale = alpha_logscale
+ if self.alpha_logscale: # Log scale alphas initialized to zeros
+ self.alpha = Parameter(torch.zeros(in_features) * alpha)
+ self.beta = Parameter(torch.zeros(in_features) * alpha)
+ else: # Linear scale alphas initialized to ones
+ self.alpha = Parameter(torch.ones(in_features) * alpha)
+ self.beta = Parameter(torch.ones(in_features) * alpha)
+
+ self.alpha.requires_grad = alpha_trainable
+ self.beta.requires_grad = alpha_trainable
+
+ self.no_div_by_zero = 0.000000001
+
+ def forward(self, x):
+ """
+ Forward pass of the function.
+ Applies the function to the input elementwise.
+ SnakeBeta ∶= x + 1/b * sin^2 (xa)
+ """
+ alpha = self.alpha.unsqueeze(0).unsqueeze(-1) # Line up with x to [B, C, T]
+ beta = self.beta.unsqueeze(0).unsqueeze(-1)
+ if self.alpha_logscale:
+ alpha = torch.exp(alpha)
+ beta = torch.exp(beta)
+ x = x + (1.0 / (beta + self.no_div_by_zero)) * pow(sin(x * alpha), 2)
+
+ return x
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/activation1d.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/activation1d.py
new file mode 100644
index 0000000000000000000000000000000000000000..e222d1419f740daff55cb08d8b42a1eedaf18f30
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/activation1d.py
@@ -0,0 +1,77 @@
+# Copyright (c) 2024 NVIDIA CORPORATION.
+# Licensed under the MIT license.
+
+import torch
+import torch.nn as nn
+from ..torch.resample import UpSample1d, DownSample1d
+
+# load fused CUDA kernel: this enables importing anti_alias_activation_cuda
+from . import load
+
+anti_alias_activation_cuda = load.load()
+
+
+class FusedAntiAliasActivation(torch.autograd.Function):
+ """
+ Assumes filter size 12, replication padding on upsampling/downsampling, and logscale alpha/beta parameters as inputs.
+ The hyperparameters are hard-coded in the kernel to maximize speed.
+ NOTE: The fused kenrel is incorrect for Activation1d with different hyperparameters.
+ """
+
+ @staticmethod
+ def forward(ctx, inputs, up_ftr, down_ftr, alpha, beta):
+ activation_results = anti_alias_activation_cuda.forward(
+ inputs, up_ftr, down_ftr, alpha, beta
+ )
+
+ return activation_results
+
+ @staticmethod
+ def backward(ctx, output_grads):
+ raise NotImplementedError
+ return output_grads, None, None
+
+
+class Activation1d(nn.Module):
+ def __init__(
+ self,
+ activation,
+ up_ratio: int = 2,
+ down_ratio: int = 2,
+ up_kernel_size: int = 12,
+ down_kernel_size: int = 12,
+ fused: bool = True,
+ ):
+ super().__init__()
+ self.up_ratio = up_ratio
+ self.down_ratio = down_ratio
+ self.act = activation
+ self.upsample = UpSample1d(up_ratio, up_kernel_size)
+ self.downsample = DownSample1d(down_ratio, down_kernel_size)
+
+ self.fused = fused # Whether to use fused CUDA kernel or not
+
+ def forward(self, x):
+ if not self.fused:
+ x = self.upsample(x)
+ x = self.act(x)
+ x = self.downsample(x)
+ return x
+ else:
+ if self.act.__class__.__name__ == "Snake":
+ beta = self.act.alpha.data # Snake uses same params for alpha and beta
+ else:
+ beta = (
+ self.act.beta.data
+ ) # Snakebeta uses different params for alpha and beta
+ alpha = self.act.alpha.data
+ if (
+ not self.act.alpha_logscale
+ ): # Exp baked into cuda kernel, cancel it out with a log
+ alpha = torch.log(alpha)
+ beta = torch.log(beta)
+
+ x = FusedAntiAliasActivation.apply(
+ x, self.upsample.filter, self.downsample.lowpass.filter, alpha, beta
+ )
+ return x
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/anti_alias_activation.cpp b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/anti_alias_activation.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..c5651f77143bd678169eb11564a7cf7a7969a59e
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/anti_alias_activation.cpp
@@ -0,0 +1,23 @@
+/* coding=utf-8
+ * Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+ #include
+
+extern "C" torch::Tensor fwd_cuda(torch::Tensor const &input, torch::Tensor const &up_filter, torch::Tensor const &down_filter, torch::Tensor const &alpha, torch::Tensor const &beta);
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+ m.def("forward", &fwd_cuda, "Anti-Alias Activation forward (CUDA)");
+}
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/anti_alias_activation_cuda.cu b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/anti_alias_activation_cuda.cu
new file mode 100644
index 0000000000000000000000000000000000000000..8c442334869fe72d639ec203fa4fac07f96a0ee1
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/anti_alias_activation_cuda.cu
@@ -0,0 +1,246 @@
+/* coding=utf-8
+ * Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include
+#include
+#include
+#include
+#include
+#include
+#include
+#include "type_shim.h"
+#include
+#include
+#include
+#include
+#include
+
+namespace
+{
+ // Hard-coded hyperparameters
+ // WARP_SIZE and WARP_BATCH must match the return values batches_per_warp and
+ constexpr int ELEMENTS_PER_LDG_STG = 1; //(WARP_ITERATIONS < 4) ? 1 : 4;
+ constexpr int BUFFER_SIZE = 32;
+ constexpr int FILTER_SIZE = 12;
+ constexpr int HALF_FILTER_SIZE = 6;
+ constexpr int UPSAMPLE_REPLICATION_PAD = 5; // 5 on each side, matching torch impl
+ constexpr int DOWNSAMPLE_REPLICATION_PAD_LEFT = 5; // matching torch impl
+ constexpr int DOWNSAMPLE_REPLICATION_PAD_RIGHT = 6; // matching torch impl
+
+ template
+ __global__ void anti_alias_activation_forward(
+ output_t *dst,
+ const input_t *src,
+ const input_t *up_ftr,
+ const input_t *down_ftr,
+ const input_t *alpha,
+ const input_t *beta,
+ int batch_size,
+ int channels,
+ int seq_len)
+ {
+ // Up and downsample filters
+ input_t up_filter[FILTER_SIZE];
+ input_t down_filter[FILTER_SIZE];
+
+ // Load data from global memory including extra indices reserved for replication paddings
+ input_t elements[2 * FILTER_SIZE + 2 * BUFFER_SIZE + 2 * UPSAMPLE_REPLICATION_PAD] = {0};
+ input_t intermediates[2 * FILTER_SIZE + 2 * BUFFER_SIZE + DOWNSAMPLE_REPLICATION_PAD_LEFT + DOWNSAMPLE_REPLICATION_PAD_RIGHT] = {0};
+
+ // Output stores downsampled output before writing to dst
+ output_t output[BUFFER_SIZE];
+
+ // blockDim/threadIdx = (128, 1, 1)
+ // gridDim/blockIdx = (seq_blocks, channels, batches)
+ int block_offset = (blockIdx.x * 128 * BUFFER_SIZE + seq_len * (blockIdx.y + gridDim.y * blockIdx.z));
+ int local_offset = threadIdx.x * BUFFER_SIZE;
+ int seq_offset = blockIdx.x * 128 * BUFFER_SIZE + local_offset;
+
+ // intermediate have double the seq_len
+ int intermediate_local_offset = threadIdx.x * BUFFER_SIZE * 2;
+ int intermediate_seq_offset = blockIdx.x * 128 * BUFFER_SIZE * 2 + intermediate_local_offset;
+
+ // Get values needed for replication padding before moving pointer
+ const input_t *right_most_pntr = src + (seq_len * (blockIdx.y + gridDim.y * blockIdx.z));
+ input_t seq_left_most_value = right_most_pntr[0];
+ input_t seq_right_most_value = right_most_pntr[seq_len - 1];
+
+ // Move src and dst pointers
+ src += block_offset + local_offset;
+ dst += block_offset + local_offset;
+
+ // Alpha and beta values for snake activatons. Applies exp by default
+ alpha = alpha + blockIdx.y;
+ input_t alpha_val = expf(alpha[0]);
+ beta = beta + blockIdx.y;
+ input_t beta_val = expf(beta[0]);
+
+ #pragma unroll
+ for (int it = 0; it < FILTER_SIZE; it += 1)
+ {
+ up_filter[it] = up_ftr[it];
+ down_filter[it] = down_ftr[it];
+ }
+
+ // Apply replication padding for upsampling, matching torch impl
+ #pragma unroll
+ for (int it = -HALF_FILTER_SIZE; it < BUFFER_SIZE + HALF_FILTER_SIZE; it += 1)
+ {
+ int element_index = seq_offset + it; // index for element
+ if ((element_index < 0) && (element_index >= -UPSAMPLE_REPLICATION_PAD))
+ {
+ elements[2 * (HALF_FILTER_SIZE + it)] = 2 * seq_left_most_value;
+ }
+ if ((element_index >= seq_len) && (element_index < seq_len + UPSAMPLE_REPLICATION_PAD))
+ {
+ elements[2 * (HALF_FILTER_SIZE + it)] = 2 * seq_right_most_value;
+ }
+ if ((element_index >= 0) && (element_index < seq_len))
+ {
+ elements[2 * (HALF_FILTER_SIZE + it)] = 2 * src[it];
+ }
+ }
+
+ // Apply upsampling strided convolution and write to intermediates. It reserves DOWNSAMPLE_REPLICATION_PAD_LEFT for replication padding of the downsampilng conv later
+ #pragma unroll
+ for (int it = 0; it < (2 * BUFFER_SIZE + 2 * FILTER_SIZE); it += 1)
+ {
+ input_t acc = 0.0;
+ int element_index = intermediate_seq_offset + it; // index for intermediate
+ #pragma unroll
+ for (int f_idx = 0; f_idx < FILTER_SIZE; f_idx += 1)
+ {
+ if ((element_index + f_idx) >= 0)
+ {
+ acc += up_filter[f_idx] * elements[it + f_idx];
+ }
+ }
+ intermediates[it + DOWNSAMPLE_REPLICATION_PAD_LEFT] = acc;
+ }
+
+ // Apply activation function. It reserves DOWNSAMPLE_REPLICATION_PAD_LEFT and DOWNSAMPLE_REPLICATION_PAD_RIGHT for replication padding of the downsampilng conv later
+ double no_div_by_zero = 0.000000001;
+ #pragma unroll
+ for (int it = 0; it < 2 * BUFFER_SIZE + 2 * FILTER_SIZE; it += 1)
+ {
+ intermediates[it + DOWNSAMPLE_REPLICATION_PAD_LEFT] += (1.0 / (beta_val + no_div_by_zero)) * sinf(intermediates[it + DOWNSAMPLE_REPLICATION_PAD_LEFT] * alpha_val) * sinf(intermediates[it + DOWNSAMPLE_REPLICATION_PAD_LEFT] * alpha_val);
+ }
+
+ // Apply replication padding before downsampling conv from intermediates
+ #pragma unroll
+ for (int it = 0; it < DOWNSAMPLE_REPLICATION_PAD_LEFT; it += 1)
+ {
+ intermediates[it] = intermediates[DOWNSAMPLE_REPLICATION_PAD_LEFT];
+ }
+ #pragma unroll
+ for (int it = DOWNSAMPLE_REPLICATION_PAD_LEFT + 2 * BUFFER_SIZE + 2 * FILTER_SIZE; it < DOWNSAMPLE_REPLICATION_PAD_LEFT + 2 * BUFFER_SIZE + 2 * FILTER_SIZE + DOWNSAMPLE_REPLICATION_PAD_RIGHT; it += 1)
+ {
+ intermediates[it] = intermediates[DOWNSAMPLE_REPLICATION_PAD_LEFT + 2 * BUFFER_SIZE + 2 * FILTER_SIZE - 1];
+ }
+
+ // Apply downsample strided convolution (assuming stride=2) from intermediates
+ #pragma unroll
+ for (int it = 0; it < BUFFER_SIZE; it += 1)
+ {
+ input_t acc = 0.0;
+ #pragma unroll
+ for (int f_idx = 0; f_idx < FILTER_SIZE; f_idx += 1)
+ {
+ // Add constant DOWNSAMPLE_REPLICATION_PAD_RIGHT to match torch implementation
+ acc += down_filter[f_idx] * intermediates[it * 2 + f_idx + DOWNSAMPLE_REPLICATION_PAD_RIGHT];
+ }
+ output[it] = acc;
+ }
+
+ // Write output to dst
+ #pragma unroll
+ for (int it = 0; it < BUFFER_SIZE; it += ELEMENTS_PER_LDG_STG)
+ {
+ int element_index = seq_offset + it;
+ if (element_index < seq_len)
+ {
+ dst[it] = output[it];
+ }
+ }
+
+ }
+
+ template
+ void dispatch_anti_alias_activation_forward(
+ output_t *dst,
+ const input_t *src,
+ const input_t *up_ftr,
+ const input_t *down_ftr,
+ const input_t *alpha,
+ const input_t *beta,
+ int batch_size,
+ int channels,
+ int seq_len)
+ {
+ if (seq_len == 0)
+ {
+ return;
+ }
+ else
+ {
+ // Use 128 threads per block to maximimize gpu utilization
+ constexpr int threads_per_block = 128;
+ constexpr int seq_len_per_block = 4096;
+ int blocks_per_seq_len = (seq_len + seq_len_per_block - 1) / seq_len_per_block;
+ dim3 blocks(blocks_per_seq_len, channels, batch_size);
+ dim3 threads(threads_per_block, 1, 1);
+
+ anti_alias_activation_forward
+ <<>>(dst, src, up_ftr, down_ftr, alpha, beta, batch_size, channels, seq_len);
+ }
+ }
+}
+
+extern "C" torch::Tensor fwd_cuda(torch::Tensor const &input, torch::Tensor const &up_filter, torch::Tensor const &down_filter, torch::Tensor const &alpha, torch::Tensor const &beta)
+{
+ // Input is a 3d tensor with dimensions [batches, channels, seq_len]
+ const int batches = input.size(0);
+ const int channels = input.size(1);
+ const int seq_len = input.size(2);
+
+ // Output
+ auto act_options = input.options().requires_grad(false);
+
+ torch::Tensor anti_alias_activation_results =
+ torch::empty({batches, channels, seq_len}, act_options);
+
+ void *input_ptr = static_cast(input.data_ptr());
+ void *up_filter_ptr = static_cast(up_filter.data_ptr());
+ void *down_filter_ptr = static_cast(down_filter.data_ptr());
+ void *alpha_ptr = static_cast(alpha.data_ptr());
+ void *beta_ptr = static_cast(beta.data_ptr());
+ void *anti_alias_activation_results_ptr = static_cast(anti_alias_activation_results.data_ptr());
+
+ DISPATCH_FLOAT_HALF_AND_BFLOAT(
+ input.scalar_type(),
+ "dispatch anti alias activation_forward",
+ dispatch_anti_alias_activation_forward(
+ reinterpret_cast(anti_alias_activation_results_ptr),
+ reinterpret_cast(input_ptr),
+ reinterpret_cast(up_filter_ptr),
+ reinterpret_cast(down_filter_ptr),
+ reinterpret_cast(alpha_ptr),
+ reinterpret_cast(beta_ptr),
+ batches,
+ channels,
+ seq_len););
+ return anti_alias_activation_results;
+}
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/compat.h b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/compat.h
new file mode 100644
index 0000000000000000000000000000000000000000..25818b2edf4cb0dc9130e62c7c4de8d16a01baa5
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/compat.h
@@ -0,0 +1,29 @@
+/* coding=utf-8
+ * Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/*This code is copied fron NVIDIA apex:
+ * https://github.com/NVIDIA/apex
+ * with minor changes. */
+
+#ifndef TORCH_CHECK
+#define TORCH_CHECK AT_CHECK
+#endif
+
+#ifdef VERSION_GE_1_3
+#define DATA_PTR data_ptr
+#else
+#define DATA_PTR data
+#endif
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/load.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/load.py
new file mode 100644
index 0000000000000000000000000000000000000000..ca5d01de398249e75e9e2298958764acb436edba
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/load.py
@@ -0,0 +1,86 @@
+# Copyright (c) 2024 NVIDIA CORPORATION.
+# Licensed under the MIT license.
+
+import os
+import pathlib
+import subprocess
+
+from torch.utils import cpp_extension
+
+"""
+Setting this param to a list has a problem of generating different compilation commands (with diferent order of architectures) and leading to recompilation of fused kernels.
+Set it to empty stringo avoid recompilation and assign arch flags explicity in extra_cuda_cflags below
+"""
+os.environ["TORCH_CUDA_ARCH_LIST"] = ""
+
+
+def load():
+ # Check if cuda 11 is installed for compute capability 8.0
+ cc_flag = []
+ _, bare_metal_major, _ = _get_cuda_bare_metal_version(cpp_extension.CUDA_HOME)
+ if int(bare_metal_major) >= 11:
+ cc_flag.append("-gencode")
+ cc_flag.append("arch=compute_80,code=sm_80")
+
+ # Build path
+ srcpath = pathlib.Path(__file__).parent.absolute()
+ buildpath = srcpath / "build"
+ _create_build_dir(buildpath)
+
+ # Helper function to build the kernels.
+ def _cpp_extention_load_helper(name, sources, extra_cuda_flags):
+ return cpp_extension.load(
+ name=name,
+ sources=sources,
+ build_directory=buildpath,
+ extra_cflags=[
+ "-O3",
+ ],
+ extra_cuda_cflags=[
+ "-O3",
+ "-gencode",
+ "arch=compute_70,code=sm_70",
+ "--use_fast_math",
+ ]
+ + extra_cuda_flags
+ + cc_flag,
+ verbose=True,
+ )
+
+ extra_cuda_flags = [
+ "-U__CUDA_NO_HALF_OPERATORS__",
+ "-U__CUDA_NO_HALF_CONVERSIONS__",
+ "--expt-relaxed-constexpr",
+ "--expt-extended-lambda",
+ ]
+
+ sources = [
+ srcpath / "anti_alias_activation.cpp",
+ srcpath / "anti_alias_activation_cuda.cu",
+ ]
+ anti_alias_activation_cuda = _cpp_extention_load_helper(
+ "anti_alias_activation_cuda", sources, extra_cuda_flags
+ )
+
+ return anti_alias_activation_cuda
+
+
+def _get_cuda_bare_metal_version(cuda_dir):
+ raw_output = subprocess.check_output(
+ [cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True
+ )
+ output = raw_output.split()
+ release_idx = output.index("release") + 1
+ release = output[release_idx].split(".")
+ bare_metal_major = release[0]
+ bare_metal_minor = release[1][0]
+
+ return raw_output, bare_metal_major, bare_metal_minor
+
+
+def _create_build_dir(buildpath):
+ try:
+ os.mkdir(buildpath)
+ except OSError:
+ if not os.path.isdir(buildpath):
+ print(f"Creation of the build directory {buildpath} failed")
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/type_shim.h b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/type_shim.h
new file mode 100644
index 0000000000000000000000000000000000000000..5db7e8a397e982d4d30d16ab6060814b98b7ab83
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/cuda/type_shim.h
@@ -0,0 +1,92 @@
+/* coding=utf-8
+ * Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include
+#include "compat.h"
+
+#define DISPATCH_FLOAT_HALF_AND_BFLOAT(TYPE, NAME, ...) \
+ switch (TYPE) \
+ { \
+ case at::ScalarType::Float: \
+ { \
+ using scalar_t = float; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ case at::ScalarType::Half: \
+ { \
+ using scalar_t = at::Half; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ case at::ScalarType::BFloat16: \
+ { \
+ using scalar_t = at::BFloat16; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ default: \
+ AT_ERROR(#NAME, " not implemented for '", toString(TYPE), "'"); \
+ }
+
+#define DISPATCH_FLOAT_HALF_AND_BFLOAT_INOUT_TYPES(TYPEIN, TYPEOUT, NAME, ...) \
+ switch (TYPEIN) \
+ { \
+ case at::ScalarType::Float: \
+ { \
+ using scalar_t_in = float; \
+ switch (TYPEOUT) \
+ { \
+ case at::ScalarType::Float: \
+ { \
+ using scalar_t_out = float; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ case at::ScalarType::Half: \
+ { \
+ using scalar_t_out = at::Half; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ case at::ScalarType::BFloat16: \
+ { \
+ using scalar_t_out = at::BFloat16; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ default: \
+ AT_ERROR(#NAME, " not implemented for '", toString(TYPEOUT), "'"); \
+ } \
+ break; \
+ } \
+ case at::ScalarType::Half: \
+ { \
+ using scalar_t_in = at::Half; \
+ using scalar_t_out = at::Half; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ case at::ScalarType::BFloat16: \
+ { \
+ using scalar_t_in = at::BFloat16; \
+ using scalar_t_out = at::BFloat16; \
+ __VA_ARGS__; \
+ break; \
+ } \
+ default: \
+ AT_ERROR(#NAME, " not implemented for '", toString(TYPEIN), "'"); \
+ }
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f756ed83f87f9839e457b240f60469bc187707d
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/__init__.py
@@ -0,0 +1,6 @@
+# Adapted from https://github.com/junjun3518/alias-free-torch under the Apache License 2.0
+# LICENSE is in incl_licenses directory.
+
+from .filter import *
+from .resample import *
+from .act import *
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/act.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/act.py
new file mode 100644
index 0000000000000000000000000000000000000000..a6693aac602d7b331d6149522685dd512a26d277
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/act.py
@@ -0,0 +1,30 @@
+# Adapted from https://github.com/junjun3518/alias-free-torch under the Apache License 2.0
+# LICENSE is in incl_licenses directory.
+
+import torch.nn as nn
+from .resample import UpSample1d, DownSample1d
+
+
+class Activation1d(nn.Module):
+ def __init__(
+ self,
+ activation,
+ up_ratio: int = 2,
+ down_ratio: int = 2,
+ up_kernel_size: int = 12,
+ down_kernel_size: int = 12,
+ ):
+ super().__init__()
+ self.up_ratio = up_ratio
+ self.down_ratio = down_ratio
+ self.act = activation
+ self.upsample = UpSample1d(up_ratio, up_kernel_size)
+ self.downsample = DownSample1d(down_ratio, down_kernel_size)
+
+ # x: [B,C,T]
+ def forward(self, x):
+ x = self.upsample(x)
+ x = self.act(x)
+ x = self.downsample(x)
+
+ return x
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/filter.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/filter.py
new file mode 100644
index 0000000000000000000000000000000000000000..0fa35b0d5ddf8d6cb04cd9d47364ca033cebcd32
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/filter.py
@@ -0,0 +1,101 @@
+# Adapted from https://github.com/junjun3518/alias-free-torch under the Apache License 2.0
+# LICENSE is in incl_licenses directory.
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import math
+
+if "sinc" in dir(torch):
+ sinc = torch.sinc
+else:
+ # This code is adopted from adefossez's julius.core.sinc under the MIT License
+ # https://adefossez.github.io/julius/julius/core.html
+ # LICENSE is in incl_licenses directory.
+ def sinc(x: torch.Tensor):
+ """
+ Implementation of sinc, i.e. sin(pi * x) / (pi * x)
+ __Warning__: Different to julius.sinc, the input is multiplied by `pi`!
+ """
+ return torch.where(
+ x == 0,
+ torch.tensor(1.0, device=x.device, dtype=x.dtype),
+ torch.sin(math.pi * x) / math.pi / x,
+ )
+
+
+# This code is adopted from adefossez's julius.lowpass.LowPassFilters under the MIT License
+# https://adefossez.github.io/julius/julius/lowpass.html
+# LICENSE is in incl_licenses directory.
+def kaiser_sinc_filter1d(
+ cutoff, half_width, kernel_size
+): # return filter [1,1,kernel_size]
+ even = kernel_size % 2 == 0
+ half_size = kernel_size // 2
+
+ # For kaiser window
+ delta_f = 4 * half_width
+ A = 2.285 * (half_size - 1) * math.pi * delta_f + 7.95
+ if A > 50.0:
+ beta = 0.1102 * (A - 8.7)
+ elif A >= 21.0:
+ beta = 0.5842 * (A - 21) ** 0.4 + 0.07886 * (A - 21.0)
+ else:
+ beta = 0.0
+ window = torch.kaiser_window(kernel_size, beta=beta, periodic=False)
+
+ # ratio = 0.5/cutoff -> 2 * cutoff = 1 / ratio
+ if even:
+ time = torch.arange(-half_size, half_size) + 0.5
+ else:
+ time = torch.arange(kernel_size) - half_size
+ if cutoff == 0:
+ filter_ = torch.zeros_like(time)
+ else:
+ filter_ = 2 * cutoff * window * sinc(2 * cutoff * time)
+ """
+ Normalize filter to have sum = 1, otherwise we will have a small leakage of the constant component in the input signal.
+ """
+ filter_ /= filter_.sum()
+ filter = filter_.view(1, 1, kernel_size)
+
+ return filter
+
+
+class LowPassFilter1d(nn.Module):
+ def __init__(
+ self,
+ cutoff=0.5,
+ half_width=0.6,
+ stride: int = 1,
+ padding: bool = True,
+ padding_mode: str = "replicate",
+ kernel_size: int = 12,
+ ):
+ """
+ kernel_size should be even number for stylegan3 setup, in this implementation, odd number is also possible.
+ """
+ super().__init__()
+ if cutoff < -0.0:
+ raise ValueError("Minimum cutoff must be larger than zero.")
+ if cutoff > 0.5:
+ raise ValueError("A cutoff above 0.5 does not make sense.")
+ self.kernel_size = kernel_size
+ self.even = kernel_size % 2 == 0
+ self.pad_left = kernel_size // 2 - int(self.even)
+ self.pad_right = kernel_size // 2
+ self.stride = stride
+ self.padding = padding
+ self.padding_mode = padding_mode
+ filter = kaiser_sinc_filter1d(cutoff, half_width, kernel_size)
+ self.register_buffer("filter", filter)
+
+ # Input [B, C, T]
+ def forward(self, x):
+ _, C, _ = x.shape
+
+ if self.padding:
+ x = F.pad(x, (self.pad_left, self.pad_right), mode=self.padding_mode)
+ out = F.conv1d(x, self.filter.expand(C, -1, -1), stride=self.stride, groups=C)
+
+ return out
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/resample.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/resample.py
new file mode 100644
index 0000000000000000000000000000000000000000..a35380f5a2b0767069d8e3a64e01e090299ee2ab
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/alias_free_activation/torch/resample.py
@@ -0,0 +1,58 @@
+# Adapted from https://github.com/junjun3518/alias-free-torch under the Apache License 2.0
+# LICENSE is in incl_licenses directory.
+
+import torch.nn as nn
+from torch.nn import functional as F
+from .filter import LowPassFilter1d
+from .filter import kaiser_sinc_filter1d
+
+
+class UpSample1d(nn.Module):
+ def __init__(self, ratio=2, kernel_size=None):
+ super().__init__()
+ self.ratio = ratio
+ self.kernel_size = (
+ int(6 * ratio // 2) * 2 if kernel_size is None else kernel_size
+ )
+ self.stride = ratio
+ self.pad = self.kernel_size // ratio - 1
+ self.pad_left = self.pad * self.stride + (self.kernel_size - self.stride) // 2
+ self.pad_right = (
+ self.pad * self.stride + (self.kernel_size - self.stride + 1) // 2
+ )
+ filter = kaiser_sinc_filter1d(
+ cutoff=0.5 / ratio, half_width=0.6 / ratio, kernel_size=self.kernel_size
+ )
+ self.register_buffer("filter", filter)
+
+ # x: [B, C, T]
+ def forward(self, x):
+ _, C, _ = x.shape
+
+ x = F.pad(x, (self.pad, self.pad), mode="replicate")
+ x = self.ratio * F.conv_transpose1d(
+ x, self.filter.expand(C, -1, -1), stride=self.stride, groups=C
+ )
+ x = x[..., self.pad_left : -self.pad_right]
+
+ return x
+
+
+class DownSample1d(nn.Module):
+ def __init__(self, ratio=2, kernel_size=None):
+ super().__init__()
+ self.ratio = ratio
+ self.kernel_size = (
+ int(6 * ratio // 2) * 2 if kernel_size is None else kernel_size
+ )
+ self.lowpass = LowPassFilter1d(
+ cutoff=0.5 / ratio,
+ half_width=0.6 / ratio,
+ stride=ratio,
+ kernel_size=self.kernel_size,
+ )
+
+ def forward(self, x):
+ xx = self.lowpass(x)
+
+ return xx
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/bigvgan.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/bigvgan.py
new file mode 100644
index 0000000000000000000000000000000000000000..f1614a328f5d450bf3e52c43ac26f7d1dcd53b4e
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/bigvgan.py
@@ -0,0 +1,486 @@
+# Copyright (c) 2024 NVIDIA CORPORATION.
+# Licensed under the MIT license.
+
+# Adapted from https://github.com/jik876/hifi-gan under the MIT license.
+# LICENSE is in incl_licenses directory.
+
+import os
+import json
+from pathlib import Path
+from typing import Optional, Union, Dict
+
+import torch
+import torch.nn as nn
+from torch.nn import Conv1d, ConvTranspose1d
+from torch.nn.utils import weight_norm, remove_weight_norm
+
+from .activations import Snake, SnakeBeta
+from .utils import init_weights, get_padding
+from .alias_free_activation.torch.act import Activation1d as TorchActivation1d
+from .utils import AttrDict
+
+from huggingface_hub import PyTorchModelHubMixin, hf_hub_download
+
+
+def load_hparams_from_json(path) -> AttrDict:
+ with open(path) as f:
+ data = f.read()
+ return AttrDict(json.loads(data))
+
+
+class AMPBlock1(torch.nn.Module):
+ """
+ AMPBlock applies Snake / SnakeBeta activation functions with trainable parameters that control periodicity, defined for each layer.
+ AMPBlock1 has additional self.convs2 that contains additional Conv1d layers with a fixed dilation=1 followed by each layer in self.convs1
+
+ Args:
+ h (AttrDict): Hyperparameters.
+ channels (int): Number of convolution channels.
+ kernel_size (int): Size of the convolution kernel. Default is 3.
+ dilation (tuple): Dilation rates for the convolutions. Each dilation layer has two convolutions. Default is (1, 3, 5).
+ activation (str): Activation function type. Should be either 'snake' or 'snakebeta'. Default is None.
+ """
+
+ def __init__(
+ self,
+ h: AttrDict,
+ channels: int,
+ kernel_size: int = 3,
+ dilation: tuple = (1, 3, 5),
+ activation: str = None,
+ ):
+ super().__init__()
+
+ self.h = h
+
+ self.convs1 = nn.ModuleList(
+ [
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ stride=1,
+ dilation=d,
+ padding=get_padding(kernel_size, d),
+ )
+ )
+ for d in dilation
+ ]
+ )
+ self.convs1.apply(init_weights)
+
+ self.convs2 = nn.ModuleList(
+ [
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ stride=1,
+ dilation=1,
+ padding=get_padding(kernel_size, 1),
+ )
+ )
+ for _ in range(len(dilation))
+ ]
+ )
+ self.convs2.apply(init_weights)
+
+ self.num_layers = len(self.convs1) + len(
+ self.convs2
+ ) # Total number of conv layers
+
+ # Select which Activation1d, lazy-load cuda version to ensure backward compatibility
+ if self.h.get("use_cuda_kernel", False):
+ from .alias_free_activation.cuda.activation1d import (
+ Activation1d as CudaActivation1d,
+ )
+
+ Activation1d = CudaActivation1d
+ else:
+ Activation1d = TorchActivation1d
+
+ # Activation functions
+ if activation == "snake":
+ self.activations = nn.ModuleList(
+ [
+ Activation1d(
+ activation=Snake(channels, alpha_logscale=h.snake_logscale)
+ )
+ for _ in range(self.num_layers)
+ ]
+ )
+ elif activation == "snakebeta":
+ self.activations = nn.ModuleList(
+ [
+ Activation1d(
+ activation=SnakeBeta(channels, alpha_logscale=h.snake_logscale)
+ )
+ for _ in range(self.num_layers)
+ ]
+ )
+ else:
+ raise NotImplementedError(
+ "activation incorrectly specified. check the config file and look for 'activation'."
+ )
+
+ def forward(self, x):
+ acts1, acts2 = self.activations[::2], self.activations[1::2]
+ for c1, c2, a1, a2 in zip(self.convs1, self.convs2, acts1, acts2):
+ xt = a1(x)
+ xt = c1(xt)
+ xt = a2(xt)
+ xt = c2(xt)
+ x = xt + x
+
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.convs1:
+ remove_weight_norm(l)
+ for l in self.convs2:
+ remove_weight_norm(l)
+
+
+class AMPBlock2(torch.nn.Module):
+ """
+ AMPBlock applies Snake / SnakeBeta activation functions with trainable parameters that control periodicity, defined for each layer.
+ Unlike AMPBlock1, AMPBlock2 does not contain extra Conv1d layers with fixed dilation=1
+
+ Args:
+ h (AttrDict): Hyperparameters.
+ channels (int): Number of convolution channels.
+ kernel_size (int): Size of the convolution kernel. Default is 3.
+ dilation (tuple): Dilation rates for the convolutions. Each dilation layer has two convolutions. Default is (1, 3, 5).
+ activation (str): Activation function type. Should be either 'snake' or 'snakebeta'. Default is None.
+ """
+
+ def __init__(
+ self,
+ h: AttrDict,
+ channels: int,
+ kernel_size: int = 3,
+ dilation: tuple = (1, 3, 5),
+ activation: str = None,
+ ):
+ super().__init__()
+
+ self.h = h
+
+ self.convs = nn.ModuleList(
+ [
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ stride=1,
+ dilation=d,
+ padding=get_padding(kernel_size, d),
+ )
+ )
+ for d in dilation
+ ]
+ )
+ self.convs.apply(init_weights)
+
+ self.num_layers = len(self.convs) # Total number of conv layers
+
+ # Select which Activation1d, lazy-load cuda version to ensure backward compatibility
+ if self.h.get("use_cuda_kernel", False):
+ from .alias_free_activation.cuda.activation1d import (
+ Activation1d as CudaActivation1d,
+ )
+
+ Activation1d = CudaActivation1d
+ else:
+ Activation1d = TorchActivation1d
+
+ # Activation functions
+ if activation == "snake":
+ self.activations = nn.ModuleList(
+ [
+ Activation1d(
+ activation=Snake(channels, alpha_logscale=h.snake_logscale)
+ )
+ for _ in range(self.num_layers)
+ ]
+ )
+ elif activation == "snakebeta":
+ self.activations = nn.ModuleList(
+ [
+ Activation1d(
+ activation=SnakeBeta(channels, alpha_logscale=h.snake_logscale)
+ )
+ for _ in range(self.num_layers)
+ ]
+ )
+ else:
+ raise NotImplementedError(
+ "activation incorrectly specified. check the config file and look for 'activation'."
+ )
+
+ def forward(self, x):
+ for c, a in zip(self.convs, self.activations):
+ xt = a(x)
+ xt = c(xt)
+ x = xt + x
+
+ def remove_weight_norm(self):
+ for l in self.convs:
+ remove_weight_norm(l)
+
+
+class BigVGAN(
+ torch.nn.Module,
+ PyTorchModelHubMixin,
+ library_name="bigvgan",
+ repo_url="https://github.com/NVIDIA/BigVGAN",
+ docs_url="https://github.com/NVIDIA/BigVGAN/blob/main/README.md",
+ pipeline_tag="audio-to-audio",
+ license="mit",
+ tags=["neural-vocoder", "audio-generation", "arxiv:2206.04658"],
+):
+ """
+ BigVGAN is a neural vocoder model that applies anti-aliased periodic activation for residual blocks (resblocks).
+ New in BigVGAN-v2: it can optionally use optimized CUDA kernels for AMP (anti-aliased multi-periodicity) blocks.
+
+ Args:
+ h (AttrDict): Hyperparameters.
+ use_cuda_kernel (bool): If set to True, loads optimized CUDA kernels for AMP. This should be used for inference only, as training is not supported with CUDA kernels.
+
+ Note:
+ - The `use_cuda_kernel` parameter should be used for inference only, as training with CUDA kernels is not supported.
+ - Ensure that the activation function is correctly specified in the hyperparameters (h.activation).
+ """
+
+ def __init__(self, h: AttrDict, use_cuda_kernel: bool = False):
+ super().__init__()
+ self.h = h
+ self.h["use_cuda_kernel"] = use_cuda_kernel
+
+ # Select which Activation1d, lazy-load cuda version to ensure backward compatibility
+ if self.h.get("use_cuda_kernel", False):
+ from .alias_free_activation.cuda.activation1d import (
+ Activation1d as CudaActivation1d,
+ )
+
+ Activation1d = CudaActivation1d
+ else:
+ Activation1d = TorchActivation1d
+
+ self.num_kernels = len(h.resblock_kernel_sizes)
+ self.num_upsamples = len(h.upsample_rates)
+
+ # Pre-conv
+ self.conv_pre = weight_norm(
+ Conv1d(h.num_mels, h.upsample_initial_channel, 7, 1, padding=3)
+ )
+
+ # Define which AMPBlock to use. BigVGAN uses AMPBlock1 as default
+ if h.resblock == "1":
+ resblock_class = AMPBlock1
+ elif h.resblock == "2":
+ resblock_class = AMPBlock2
+ else:
+ raise ValueError(
+ f"Incorrect resblock class specified in hyperparameters. Got {h.resblock}"
+ )
+
+ # Transposed conv-based upsamplers. does not apply anti-aliasing
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(h.upsample_rates, h.upsample_kernel_sizes)):
+ self.ups.append(
+ nn.ModuleList(
+ [
+ weight_norm(
+ ConvTranspose1d(
+ h.upsample_initial_channel // (2**i),
+ h.upsample_initial_channel // (2 ** (i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ ]
+ )
+ )
+
+ # Residual blocks using anti-aliased multi-periodicity composition modules (AMP)
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = h.upsample_initial_channel // (2 ** (i + 1))
+ for j, (k, d) in enumerate(
+ zip(h.resblock_kernel_sizes, h.resblock_dilation_sizes)
+ ):
+ self.resblocks.append(
+ resblock_class(h, ch, k, d, activation=h.activation)
+ )
+
+ # Post-conv
+ activation_post = (
+ Snake(ch, alpha_logscale=h.snake_logscale)
+ if h.activation == "snake"
+ else (
+ SnakeBeta(ch, alpha_logscale=h.snake_logscale)
+ if h.activation == "snakebeta"
+ else None
+ )
+ )
+ if activation_post is None:
+ raise NotImplementedError(
+ "activation incorrectly specified. check the config file and look for 'activation'."
+ )
+
+ self.activation_post = Activation1d(activation=activation_post)
+
+ # Whether to use bias for the final conv_post. Default to True for backward compatibility
+ self.use_bias_at_final = h.get("use_bias_at_final", True)
+ self.conv_post = weight_norm(
+ Conv1d(ch, 1, 7, 1, padding=3, bias=self.use_bias_at_final)
+ )
+
+ # Weight initialization
+ for i in range(len(self.ups)):
+ self.ups[i].apply(init_weights)
+ self.conv_post.apply(init_weights)
+
+ # Final tanh activation. Defaults to True for backward compatibility
+ self.use_tanh_at_final = h.get("use_tanh_at_final", True)
+
+ def forward(self, x):
+ # Pre-conv
+ x = self.conv_pre(x)
+
+ for i in range(self.num_upsamples):
+ # Upsampling
+ for i_up in range(len(self.ups[i])):
+ x = self.ups[i][i_up](x)
+ # AMP blocks
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+
+ # Post-conv
+ x = self.activation_post(x)
+ x = self.conv_post(x)
+ # Final tanh activation
+ if self.use_tanh_at_final:
+ x = torch.tanh(x)
+ else:
+ x = torch.clamp(x, min=-1.0, max=1.0) # Bound the output to [-1, 1]
+
+ return x
+
+ def remove_weight_norm(self):
+ try:
+ print("Removing weight norm...")
+ for l in self.ups:
+ for l_i in l:
+ remove_weight_norm(l_i)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+ remove_weight_norm(self.conv_pre)
+ remove_weight_norm(self.conv_post)
+ except ValueError:
+ print("[INFO] Model already removed weight norm. Skipping!")
+ pass
+
+ # Additional methods for huggingface_hub support
+ def _save_pretrained(self, save_directory: Path) -> None:
+ """Save weights and config.json from a Pytorch model to a local directory."""
+
+ model_path = save_directory / "bigvgan_generator.pt"
+ torch.save({"generator": self.state_dict()}, model_path)
+
+ config_path = save_directory / "config.json"
+ with open(config_path, "w") as config_file:
+ json.dump(self.h, config_file, indent=4)
+
+ @classmethod
+ def _from_pretrained(
+ cls,
+ *,
+ model_id: str,
+ revision: str,
+ cache_dir: str,
+ force_download: bool,
+ proxies: Optional[Dict],
+ resume_download: bool,
+ local_files_only: bool,
+ token: Union[str, bool, None],
+ map_location: str = "cpu", # Additional argument
+ strict: bool = False, # Additional argument
+ use_cuda_kernel: bool = False,
+ **model_kwargs,
+ ):
+ """Load Pytorch pretrained weights and return the loaded model."""
+
+ # Download and load hyperparameters (h) used by BigVGAN
+ if os.path.isdir(model_id):
+ print("Loading config.json from local directory")
+ config_file = os.path.join(model_id, "config.json")
+ else:
+ config_file = hf_hub_download(
+ repo_id=model_id,
+ filename="config.json",
+ revision=revision,
+ cache_dir=cache_dir,
+ force_download=force_download,
+ proxies=proxies,
+ resume_download=resume_download,
+ token=token,
+ local_files_only=local_files_only,
+ )
+ h = load_hparams_from_json(config_file)
+
+ # instantiate BigVGAN using h
+ if use_cuda_kernel:
+ print(
+ f"[WARNING] You have specified use_cuda_kernel=True during BigVGAN.from_pretrained(). Only inference is supported (training is not implemented)!"
+ )
+ print(
+ f"[WARNING] You need nvcc and ninja installed in your system that matches your PyTorch build is using to build the kernel. If not, the model will fail to initialize or generate incorrect waveform!"
+ )
+ print(
+ f"[WARNING] For detail, see the official GitHub repository: https://github.com/NVIDIA/BigVGAN?tab=readme-ov-file#using-custom-cuda-kernel-for-synthesis"
+ )
+ model = cls(h, use_cuda_kernel=use_cuda_kernel)
+
+ # Download and load pretrained generator weight
+ if os.path.isdir(model_id):
+ print("Loading weights from local directory")
+ model_file = os.path.join(model_id, "bigvgan_generator.pt")
+ else:
+ print(f"Loading weights from {model_id}")
+ model_file = hf_hub_download(
+ repo_id=model_id,
+ filename="bigvgan_generator.pt",
+ revision=revision,
+ cache_dir=cache_dir,
+ force_download=force_download,
+ proxies=proxies,
+ resume_download=resume_download,
+ token=token,
+ local_files_only=local_files_only,
+ )
+
+ checkpoint_dict = torch.load(
+ model_file, map_location=map_location, weights_only=True
+ )
+
+ try:
+ model.load_state_dict(checkpoint_dict["generator"])
+ except RuntimeError:
+ print(
+ f"[INFO] the pretrained checkpoint does not contain weight norm. Loading the checkpoint after removing weight norm!"
+ )
+ model.remove_weight_norm()
+ model.load_state_dict(checkpoint_dict["generator"])
+
+ return model
diff --git a/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/utils.py b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..fd3f245226ff20bbb8f73b31bcc5de8f103285a8
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/detokenizer/vocoder/utils.py
@@ -0,0 +1,110 @@
+from librosa.filters import mel as librosa_mel_fn
+import torch
+import os
+
+mel_basis_cache = {}
+hann_window_cache = {}
+
+
+def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
+ return torch.log(torch.clamp(x, min=clip_val) * C)
+
+
+def spectral_normalize_torch(magnitudes):
+ return dynamic_range_compression_torch(magnitudes)
+
+
+def get_melspec(
+ y: torch.Tensor,
+ n_fft: int,
+ num_mels: int,
+ sampling_rate: int,
+ hop_size: int,
+ win_size: int,
+ fmin: int,
+ fmax: int = None,
+ center: bool = False,
+) -> torch.Tensor:
+ """
+ Calculate the mel spectrogram of an input signal.
+ This function uses slaney norm for the librosa mel filterbank (using librosa.filters.mel) and uses Hann window for STFT (using torch.stft).
+
+ Args:
+ y (torch.Tensor): Input signal.
+ n_fft (int): FFT size.
+ num_mels (int): Number of mel bins.
+ sampling_rate (int): Sampling rate of the input signal.
+ hop_size (int): Hop size for STFT.
+ win_size (int): Window size for STFT.
+ fmin (int): Minimum frequency for mel filterbank.
+ fmax (int): Maximum frequency for mel filterbank. If None, defaults to half the sampling rate (fmax = sr / 2.0) inside librosa_mel_fn
+ center (bool): Whether to pad the input to center the frames. Default is False.
+
+ Returns:
+ torch.Tensor: Mel spectrogram.
+ """
+ if torch.min(y) < -1.0:
+ print(f"[WARNING] Min value of input waveform signal is {torch.min(y)}")
+ if torch.max(y) > 1.0:
+ print(f"[WARNING] Max value of input waveform signal is {torch.max(y)}")
+
+ device = y.device
+ key = f"{n_fft}_{num_mels}_{sampling_rate}_{hop_size}_{win_size}_{fmin}_{fmax}_{device}"
+
+ if key not in mel_basis_cache:
+ mel = librosa_mel_fn(
+ sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax
+ )
+ mel_basis_cache[key] = torch.from_numpy(mel).float().to(device)
+ hann_window_cache[key] = torch.hann_window(win_size).to(device)
+
+ mel_basis = mel_basis_cache[key]
+ hann_window = hann_window_cache[key]
+
+ padding = (n_fft - hop_size) // 2
+ y = torch.nn.functional.pad(
+ y.unsqueeze(1), (padding, padding), mode="reflect"
+ ).squeeze(1)
+
+ spec = torch.stft(
+ y,
+ n_fft,
+ hop_length=hop_size,
+ win_length=win_size,
+ window=hann_window,
+ center=center,
+ pad_mode="reflect",
+ normalized=False,
+ onesided=True,
+ return_complex=True,
+ )
+ spec = torch.sqrt(torch.view_as_real(spec).pow(2).sum(-1) + 1e-9)
+
+ mel_spec = torch.matmul(mel_basis, spec)
+ mel_spec = spectral_normalize_torch(mel_spec)
+
+ return mel_spec
+
+
+class AttrDict(dict):
+ def __init__(self, *args, **kwargs):
+ super(AttrDict, self).__init__(*args, **kwargs)
+ self.__dict__ = self
+
+
+def load_checkpoint(filepath, device):
+ assert os.path.isfile(filepath)
+ print(f"Loading '{filepath}'")
+ checkpoint_dict = torch.load(filepath, map_location=device, weights_only=True)
+ print("Complete.")
+ return checkpoint_dict
+
+
+def init_weights(m, mean=0.0, std=0.01):
+ classname = m.__class__.__name__
+ if classname.find("Conv") != -1:
+ m.weight.data.normal_(mean, std)
+
+
+def get_padding(kernel_size, dilation=1):
+ return int((kernel_size * dilation - dilation) / 2)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/.gitignore b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..fde4a0f933013c504e94c78dcaec1b81ac5e2402
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/.gitignore
@@ -0,0 +1,4 @@
+*venv
+*.DS_Store
+*.idea/
+test*
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/.gitmodules b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/.gitmodules
new file mode 100644
index 0000000000000000000000000000000000000000..0ea47296b5ff8dd013e09b0c5cb336ab1af8f18f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/.gitmodules
@@ -0,0 +1,3 @@
+[submodule "third_party/Matcha-TTS"]
+ path = third_party/Matcha-TTS
+ url = https://github.com/shivammehta25/Matcha-TTS
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/LICENSE b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..ec8f5895574bc1e0c78b3ca95cefeeb484f10106
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/LICENSE
@@ -0,0 +1,201 @@
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
+ "License" shall mean the terms and conditions for use, reproduction,
+ and distribution as defined by Sections 1 through 9 of this document.
+
+ "Licensor" shall mean the copyright owner or entity authorized by
+ the copyright owner that is granting the License.
+
+ "Legal Entity" shall mean the union of the acting entity and all
+ other entities that control, are controlled by, or are under common
+ control with that entity. For the purposes of this definition,
+ "control" means (i) the power, direct or indirect, to cause the
+ direction or management of such entity, whether by contract or
+ otherwise, or (ii) ownership of fifty percent (50%) or more of the
+ outstanding shares, or (iii) beneficial ownership of such entity.
+
+ "You" (or "Your") shall mean an individual or Legal Entity
+ exercising permissions granted by this License.
+
+ "Source" form shall mean the preferred form for making modifications,
+ including but not limited to software source code, documentation
+ source, and configuration files.
+
+ "Object" form shall mean any form resulting from mechanical
+ transformation or translation of a Source form, including but
+ not limited to compiled object code, generated documentation,
+ and conversions to other media types.
+
+ "Work" shall mean the work of authorship, whether in Source or
+ Object form, made available under the License, as indicated by a
+ copyright notice that is included in or attached to the work
+ (an example is provided in the Appendix below).
+
+ "Derivative Works" shall mean any work, whether in Source or Object
+ form, that is based on (or derived from) the Work and for which the
+ editorial revisions, annotations, elaborations, or other modifications
+ represent, as a whole, an original work of authorship. For the purposes
+ of this License, Derivative Works shall not include works that remain
+ separable from, or merely link (or bind by name) to the interfaces of,
+ the Work and Derivative Works thereof.
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+ "Contribution" shall mean any work of authorship, including
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+ 9. Accepting Warranty or Additional Liability. While redistributing
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+ END OF TERMS AND CONDITIONS
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+ APPENDIX: How to apply the Apache License to your work.
+
+ To apply the Apache License to your work, attach the following
+ boilerplate notice, with the fields enclosed by brackets "[]"
+ replaced with your own identifying information. (Don't include
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+ Copyright 2024 GLM-4-Voice Model Team @ Zhipu AI
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diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/README.md b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e10aaccfe5e247b6f6d4dabadeb32ef0bedd6c88
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/README.md
@@ -0,0 +1,159 @@
+# GLM-4-Voice
+
+📄 Report • 🤗 HF Repo • 🤖 Demo • 🐦 Twitter
+
+
+Read this in [English](./README_en.md)
+
+GLM-4-Voice 是智谱 AI 推出的端到端语音模型。GLM-4-Voice 能够直接理解和生成中英文语音，进行实时语音对话，并且能够遵循用户的指令要求改变语音的情感、语调、语速、方言等属性。
+
+## Model Architecture
+
+
+GLM-4-Voice 由三个部分组成：
+* GLM-4-Voice-Tokenizer: 通过在 [Whisper](https://github.com/openai/whisper) 的 Encoder 部分增加 Vector Quantization 并在 ASR 数据上有监督训练，将连续的语音输入转化为离散的 token。每秒音频平均只需要用 12.5 个离散 token 表示。
+* GLM-4-Voice-Decoder: 基于 [CosyVoice](https://github.com/FunAudioLLM/CosyVoice) 的 Flow Matching 模型结构训练的支持流式推理的语音解码器，将离散化的语音 token 转化为连续的语音输出。最少只需要 10 个语音 token 即可开始生成，降低端到端对话延迟。
+* GLM-4-Voice-9B: 在 [GLM-4-9B](https://github.com/THUDM/GLM-4) 的基础上进行语音模态的预训练和对齐，从而能够理解和生成离散化的语音 token。
+
+预训练方面，为了攻克模型在语音模态下的智商和合成表现力两个难关，我们将 Speech2Speech 任务解耦合为“根据用户音频做出文本回复”和“根据文本回复和用户语音合成回复语音”两个任务，并设计两种预训练目标，分别基于文本预训练数据和无监督音频数据合成语音-文本交错数据以适配这两种任务形式。GLM-4-Voice-9B 在 GLM-4-9B 的基座模型基础之上，经过了数百万小时音频和数千亿 token 的音频文本交错数据预训练，拥有很强的音频理解和建模能力。
+
+对齐方面，为了支持高质量的语音对话，我们设计了一套流式思考架构：根据用户语音，GLM-4-Voice 可以流式交替输出文本和语音两个模态的内容，其中语音模态以文本作为参照保证回复内容的高质量，并根据用户的语音指令要求做出相应的声音变化，在最大程度保留语言模型智商的情况下仍然具有端到端建模的能力，同时具备低延迟性，最低只需要输出 20 个 token 便可以合成语音。
+
+## Model List
+
+| Model | Type | Download |
+|:---------------------:|:----------------:|:------------------------------------------------------------------------------------------------------------------------------------------------:|
+| GLM-4-Voice-Tokenizer | Speech Tokenizer | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-voice-tokenizer) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-voice-tokenizer) |
+| GLM-4-Voice-9B | Chat Model | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-voice-9b) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-voice-9b) |
+| GLM-4-Voice-Decoder | Speech Decoder | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-voice-decoder) [🤖 ModelScope](https://modelscope.cn/models/ZhipuAI/glm-4-voice-decoder) |
+
+## Usage
+我们提供了可以直接启动的 Web Demo。用户可以输入语音或文本，模型会同时给出语音和文字回复。
+
+
+
+### Preparation
+
+首先下载仓库
+```shell
+git clone --recurse-submodules https://github.com/THUDM/GLM-4-Voice
+cd GLM-4-Voice
+```
+然后安装依赖。也可以使用我们提供的镜像 `zhipuai/glm-4-voice:0.1` 以跳过这一步。
+```shell
+pip install -r requirements.txt
+```
+由于 Decoder 模型不支持通过 `transformers` 初始化，因此 checkpoint 需要单独下载。
+
+```shell
+# git 模型下载，请确保已安装 git-lfs
+git lfs install
+git clone https://huggingface.co/THUDM/glm-4-voice-decoder
+```
+
+### Launch Web Demo
+
+1. 启动模型服务
+
+```shell
+python model_server.py --host localhost --model-path THUDM/glm-4-voice-9b --port 10000 --dtype bfloat16 --device cuda:0
+```
+
+如果你需要使用 Int4 精度启动，请运行
+
+```shell
+python model_server.py --host localhost --model-path THUDM/glm-4-voice-9b --port 10000 --dtype int4 --device cuda:0
+```
+
+此命令会自动下载 `glm-4-voice-9b`。如果网络条件不好，也手动下载之后通过 `--model-path` 指定本地的路径。
+
+2. 启动 web 服务
+
+```shell
+python web_demo.py --tokenizer-path THUDM/glm-4-voice-tokenizer --model-path THUDM/glm-4-voice-9b --flow-path ./glm-4-voice-decoder
+```
+
+即可在 http://127.0.0.1:8888 访问 web demo。
+
+此命令会自动下载 `glm-4-voice-tokenizer` 和 `glm-4-voice-9b`。 请注意，`glm-4-voice-decoder` 需要手动下载。
+
+如果网络条件不好，可以手动下载这三个模型之后通过 `--tokenizer-path`, `--flow-path` 和 `--model-path` 指定本地的路径。
+
+### Known Issues
+
+* Gradio 的流式音频播放效果不稳定。在生成完成后点击对话框中的音频质量会更高。
+
+## Cases
+
+我们提供了 GLM-4-Voice 的部分对话案例，包括控制情绪、改变语速、生成方言等。
+
+* 用轻柔的声音引导我放松
+
+https://github.com/user-attachments/assets/4e3d9200-076d-4c28-a641-99df3af38eb0
+
+* 用激动的声音解说足球比赛
+
+https://github.com/user-attachments/assets/0163de2d-e876-4999-b1bc-bbfa364b799b
+
+* 用哀怨的声音讲一个鬼故事
+
+https://github.com/user-attachments/assets/a75b2087-d7bc-49fa-a0c5-e8c99935b39a
+
+* 用东北话介绍一下冬天有多冷
+
+https://github.com/user-attachments/assets/91ba54a1-8f5c-4cfe-8e87-16ed1ecf4037
+
+* 用重庆话念“吃葡萄不吐葡萄皮”
+
+https://github.com/user-attachments/assets/7eb72461-9e84-4d8e-9c58-1809cf6a8a9b
+
+* 用北京话念一句绕口令
+
+https://github.com/user-attachments/assets/a9bb223e-9c0a-440d-8537-0a7f16e31651
+
+ * 加快语速
+
+https://github.com/user-attachments/assets/c98a4604-366b-4304-917f-3c850a82fe9f
+
+ * 再快一点
+
+https://github.com/user-attachments/assets/d5ff0815-74f8-4738-b0f1-477cfc8dcc2d
+
+## Acknowledgements
+
+本项目的部分代码来自：
+* [CosyVoice](https://github.com/FunAudioLLM/CosyVoice)
+* [transformers](https://github.com/huggingface/transformers)
+* [GLM-4](https://github.com/THUDM/GLM-4)
+
+## 协议
+
++ GLM-4 模型的权重的使用则需要遵循 [模型协议](https://huggingface.co/THUDM/glm-4-voice-9b/blob/main/LICENSE)。
+
++ 本开源仓库的代码则遵循 [Apache 2.0](LICENSE) 协议。
+
+## 引用
+
+```
+@misc{zeng2024glm4,
+ title={GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot},
+ author={Aohan Zeng and Zhengxiao Du and Mingdao Liu and Kedong Wang and Shengmin Jiang and Lei Zhao and Yuxiao Dong and Jie Tang},
+ year={2024},
+ eprint={2412.02612},
+ archivePrefix={arXiv},
+ primaryClass={cs.CL},
+ url={https://arxiv.org/abs/2412.02612},
+}
+```
+
+```
+@misc{zeng2024scaling,
+ title={Scaling Speech-Text Pre-training with Synthetic Interleaved Data},
+ author={Aohan Zeng and Zhengxiao Du and Mingdao Liu and Lei Zhang and Shengmin Jiang and Yuxiao Dong and Jie Tang},
+ year={2024},
+ eprint={2411.17607},
+ archivePrefix={arXiv},
+ primaryClass={cs.CL},
+ url={https://arxiv.org/abs/2411.17607},
+}
+```
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/README_en.md b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/README_en.md
new file mode 100644
index 0000000000000000000000000000000000000000..58ef3a8b0e5ded1f317b8e10914bc45787ccd6f0
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/README_en.md
@@ -0,0 +1,148 @@
+# GLM-4-Voice
+
+📄 Report • 🤗 HF Repo • 🤖 Demo • 🐦 Twitter
+
+
+GLM-4-Voice is an end-to-end voice model launched by Zhipu AI. GLM-4-Voice can directly understand and generate Chinese and English speech, engage in real-time voice conversations, and change attributes such as emotion, intonation, speech rate, and dialect based on user instructions.
+
+## Model Architecture
+
+
+We provide the three components of GLM-4-Voice:
+* GLM-4-Voice-Tokenizer: Trained by adding vector quantization to the encoder part of [Whisper](https://github.com/openai/whisper), converting continuous speech input into discrete tokens. Each second of audio is converted into 12.5 discrete tokens.
+* GLM-4-Voice-9B: Pre-trained and aligned on speech modality based on [GLM-4-9B](https://github.com/THUDM/GLM-4), enabling understanding and generation of discretized speech.
+* GLM-4-Voice-Decoder: A speech decoder supporting streaming inference, retrained based on [CosyVoice](https://github.com/FunAudioLLM/CosyVoice), converting discrete speech tokens into continuous speech output. Generation can start with as few as 10 audio tokens, reducing conversation latency.
+
+## Model List
+
+| Model | Type | Download |
+|:---------------------:|:----------------:|:--------------------------------------------------------------------:|
+| GLM-4-Voice-Tokenizer | Speech Tokenizer | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-voice-tokenizer) |
+| GLM-4-Voice-9B | Chat Model | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-voice-9b) |
+| GLM-4-Voice-Decoder | Speech Decoder | [🤗 Huggingface](https://huggingface.co/THUDM/glm-4-voice-decoder) |
+
+## Usage
+We provide a Web Demo that can be launched directly. Users can input speech or text, and the model will respond with both speech and text.
+
+
+
+### Preparation
+
+First, download the repository
+```shell
+git clone --recurse-submodules https://github.com/THUDM/GLM-4-Voice
+cd GLM-4-Voice
+```
+Then, install the dependencies. You can also use our pre-built docker image `zhipuai/glm-4-voice:0.1` to skip the step.
+```shell
+pip install -r requirements.txt
+```
+Since the Decoder model does not support initialization via `transformers`, the checkpoint needs to be downloaded separately.
+
+```shell
+# Git model download, please ensure git-lfs is installed
+git clone https://huggingface.co/THUDM/glm-4-voice-decoder
+```
+
+### Launch Web Demo
+
+1. Start the model server
+
+```shell
+python model_server.py --host localhost --model-path THUDM/glm-4-voice-9b --port 10000 --dtype bfloat16 --device cuda:0
+```
+
+If you need to launch with Int4 precision, run
+
+```shell
+python model_server.py --host localhost --model-path THUDM/glm-4-voice-9b --port 10000 --dtype int4 --device cuda:0
+```
+
+This command will automatically download `glm-4-voice-9b`. If network conditions are poor, you can manually download it and specify the local path using `--model-path`.
+
+2. Start the web service
+
+```shell
+python web_demo.py --tokenizer-path THUDM/glm-4-voice-tokenizer --model-path THUDM/glm-4-voice-9b --flow-path ./glm-4-voice-decoder
+```
+
+You can access the web demo at [http://127.0.0.1:8888](http://127.0.0.1:8888).
+This command will automatically download `glm-4-voice-tokenizer` and `glm-4-voice-9b`. Please note that `glm-4-voice-decoder` needs to be downloaded manually.
+If the network connection is poor, you can manually download these three models and specify the local paths using `--tokenizer-path`, `--flow-path`, and `--model-path`.
+
+### Known Issues
+* Gradio’s streaming audio playback can be unstable. The audio quality will be higher when clicking on the audio in the dialogue box after generation is complete.
+
+## Examples
+We provide some dialogue cases for GLM-4-Voice, including emotion control, speech rate alteration, dialect generation, etc. (The examples are in Chinese.)
+
+* Use a gentle voice to guide me to relax
+
+https://github.com/user-attachments/assets/4e3d9200-076d-4c28-a641-99df3af38eb0
+
+* Use an excited voice to commentate a football match
+
+https://github.com/user-attachments/assets/0163de2d-e876-4999-b1bc-bbfa364b799b
+
+* Tell a ghost story with a mournful voice
+
+https://github.com/user-attachments/assets/a75b2087-d7bc-49fa-a0c5-e8c99935b39a
+
+* Introduce how cold winter is with a Northeastern dialect
+
+https://github.com/user-attachments/assets/91ba54a1-8f5c-4cfe-8e87-16ed1ecf4037
+
+* Say "Eat grapes without spitting out the skins" in Chongqing dialect
+
+https://github.com/user-attachments/assets/7eb72461-9e84-4d8e-9c58-1809cf6a8a9b
+
+* Recite a tongue twister with a Beijing accent
+
+https://github.com/user-attachments/assets/a9bb223e-9c0a-440d-8537-0a7f16e31651
+
+ * Increase the speech rate
+
+https://github.com/user-attachments/assets/c98a4604-366b-4304-917f-3c850a82fe9f
+
+ * Even faster
+
+https://github.com/user-attachments/assets/d5ff0815-74f8-4738-b0f1-477cfc8dcc2d
+
+## Acknowledgements
+
+Some code in this project is from:
+* [CosyVoice](https://github.com/FunAudioLLM/CosyVoice)
+* [transformers](https://github.com/huggingface/transformers)
+* [GLM-4](https://github.com/THUDM/GLM-4)
+
+## License Agreement
+
++ The use of GLM-4 model weights must follow the [Model License Agreement](https://huggingface.co/THUDM/glm-4-voice-9b/blob/main/LICENSE).
+
++ The code in this open-source repository is licensed under the [Apache 2.0](LICENSE) License.
+
+## Citation
+
+```
+@misc{zeng2024glm4,
+ title={GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot},
+ author={Aohan Zeng and Zhengxiao Du and Mingdao Liu and Kedong Wang and Shengmin Jiang and Lei Zhao and Yuxiao Dong and Jie Tang},
+ year={2024},
+ eprint={2412.02612},
+ archivePrefix={arXiv},
+ primaryClass={cs.CL},
+ url={https://arxiv.org/abs/2412.02612},
+}
+```
+
+```
+@misc{zeng2024scaling,
+ title={Scaling Speech-Text Pre-training with Synthetic Interleaved Data},
+ author={Aohan Zeng and Zhengxiao Du and Mingdao Liu and Lei Zhang and Shengmin Jiang and Yuxiao Dong and Jie Tang},
+ year={2024},
+ eprint={2411.17607},
+ archivePrefix={arXiv},
+ primaryClass={cs.CL},
+ url={https://arxiv.org/abs/2411.17607},
+}
+```
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/audio_process.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/audio_process.py
new file mode 100644
index 0000000000000000000000000000000000000000..53ad617567a7f5cca386324c5f07d47182939a03
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/audio_process.py
@@ -0,0 +1,93 @@
+import os
+import librosa
+import soundfile as sf
+import numpy as np
+from pathlib import Path
+import io
+
+# Split audio stream at silence points to prevent playback stuttering issues
+# caused by AAC encoder frame padding when streaming audio through Gradio audio components.
+class AudioStreamProcessor:
+ def __init__(self, sr=22050, min_silence_duration=0.1, threshold_db=-40):
+ self.sr = sr
+ self.min_silence_duration = min_silence_duration
+ self.threshold_db = threshold_db
+ self.buffer = np.array([])
+
+
+ def process(self, audio_data, last=False):
+ """
+ Add audio data and process it
+ params:
+ audio_data: audio data in numpy array
+ last: whether this is the last chunk of data
+ returns:
+ Processed audio data, returns None if no split point is found
+ """
+
+ # Add new data to buffer
+ self.buffer = np.concatenate([self.buffer, audio_data]) if len(self.buffer) > 0 else audio_data
+
+ if last:
+ result = self.buffer
+ self.buffer = np.array([])
+ return self._to_wav_bytes(result)
+
+ # Find silence boundary
+ split_point = self._find_silence_boundary(self.buffer)
+
+ if split_point is not None:
+ # Modified: Extend split point to the end of silence
+ silence_end = self._find_silence_end(split_point)
+ result = self.buffer[:silence_end]
+ self.buffer = self.buffer[silence_end:]
+ return self._to_wav_bytes(result)
+
+ return None
+
+ def _find_silence_boundary(self, audio):
+ """
+ Find the starting point of silence boundary in audio
+ """
+ # Convert audio to decibels
+ db = librosa.amplitude_to_db(np.abs(audio), ref=np.max)
+
+ # Find points below threshold
+ silence_points = np.where(db < self.threshold_db)[0]
+
+ if len(silence_points) == 0:
+ return None
+
+ # Calculate minimum silence samples
+ min_silence_samples = int(self.min_silence_duration * self.sr)
+
+ # Search backwards for continuous silence segment starting point
+ for i in range(len(silence_points) - min_silence_samples, -1, -1):
+ if i < 0:
+ break
+ if np.all(np.diff(silence_points[i:i+min_silence_samples]) == 1):
+ return silence_points[i]
+
+ return None
+
+ def _find_silence_end(self, start_point):
+ """
+ Find the end point of silence segment
+ """
+ db = librosa.amplitude_to_db(np.abs(self.buffer[start_point:]), ref=np.max)
+ silence_points = np.where(db >= self.threshold_db)[0]
+
+ if len(silence_points) == 0:
+ return len(self.buffer)
+
+ return start_point + silence_points[0]
+
+ def _to_wav_bytes(self, audio_data):
+ """
+ trans_to_wav_bytes
+ """
+ wav_buffer = io.BytesIO()
+ sf.write(wav_buffer, audio_data, self.sr, format='WAV')
+ return wav_buffer.getvalue()
+
+
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/bin/inference.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/bin/inference.py
new file mode 100644
index 0000000000000000000000000000000000000000..6b777fa1cba925f9786db60b7efa15dcd189adeb
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/bin/inference.py
@@ -0,0 +1,114 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import argparse
+import logging
+logging.getLogger('matplotlib').setLevel(logging.WARNING)
+import os
+
+import torch
+from torch.utils.data import DataLoader
+import torchaudio
+from hyperpyyaml import load_hyperpyyaml
+from tqdm import tqdm
+from cosyvoice.cli.model import CosyVoiceModel
+
+from cosyvoice.dataset.dataset import Dataset
+
+def get_args():
+ parser = argparse.ArgumentParser(description='inference with your model')
+ parser.add_argument('--config', required=True, help='config file')
+ parser.add_argument('--prompt_data', required=True, help='prompt data file')
+ parser.add_argument('--prompt_utt2data', required=True, help='prompt data file')
+ parser.add_argument('--tts_text', required=True, help='tts input file')
+ parser.add_argument('--llm_model', required=True, help='llm model file')
+ parser.add_argument('--flow_model', required=True, help='flow model file')
+ parser.add_argument('--hifigan_model', required=True, help='hifigan model file')
+ parser.add_argument('--gpu',
+ type=int,
+ default=-1,
+ help='gpu id for this rank, -1 for cpu')
+ parser.add_argument('--mode',
+ default='sft',
+ choices=['sft', 'zero_shot'],
+ help='inference mode')
+ parser.add_argument('--result_dir', required=True, help='asr result file')
+ args = parser.parse_args()
+ print(args)
+ return args
+
+
+def main():
+ args = get_args()
+ logging.basicConfig(level=logging.DEBUG,
+ format='%(asctime)s %(levelname)s %(message)s')
+ os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu)
+
+ # Init cosyvoice models from configs
+ use_cuda = args.gpu >= 0 and torch.cuda.is_available()
+ device = torch.device('cuda' if use_cuda else 'cpu')
+ with open(args.config, 'r') as f:
+ configs = load_hyperpyyaml(f)
+
+ model = CosyVoiceModel(configs['llm'], configs['flow'], configs['hift'])
+ model.load(args.llm_model, args.flow_model, args.hifigan_model)
+
+ test_dataset = Dataset(args.prompt_data, data_pipeline=configs['data_pipeline'], mode='inference', shuffle=False, partition=False, tts_file=args.tts_text, prompt_utt2data=args.prompt_utt2data)
+ test_data_loader = DataLoader(test_dataset, batch_size=None, num_workers=0)
+
+ del configs
+ os.makedirs(args.result_dir, exist_ok=True)
+ fn = os.path.join(args.result_dir, 'wav.scp')
+ f = open(fn, 'w')
+ with torch.no_grad():
+ for batch_idx, batch in tqdm(enumerate(test_data_loader)):
+ utts = batch["utts"]
+ assert len(utts) == 1, "inference mode only support batchsize 1"
+ text = batch["text"]
+ text_token = batch["text_token"].to(device)
+ text_token_len = batch["text_token_len"].to(device)
+ tts_text = batch["tts_text"]
+ tts_index = batch["tts_index"]
+ tts_text_token = batch["tts_text_token"].to(device)
+ tts_text_token_len = batch["tts_text_token_len"].to(device)
+ speech_token = batch["speech_token"].to(device)
+ speech_token_len = batch["speech_token_len"].to(device)
+ speech_feat = batch["speech_feat"].to(device)
+ speech_feat_len = batch["speech_feat_len"].to(device)
+ utt_embedding = batch["utt_embedding"].to(device)
+ spk_embedding = batch["spk_embedding"].to(device)
+ if args.mode == 'sft':
+ model_input = {'text': tts_text_token, 'text_len': tts_text_token_len,
+ 'llm_embedding': spk_embedding, 'flow_embedding': spk_embedding}
+ else:
+ model_input = {'text': tts_text_token, 'text_len': tts_text_token_len,
+ 'prompt_text': text_token, 'prompt_text_len': text_token_len,
+ 'llm_prompt_speech_token': speech_token, 'llm_prompt_speech_token_len': speech_token_len,
+ 'flow_prompt_speech_token': speech_token, 'flow_prompt_speech_token_len': speech_token_len,
+ 'prompt_speech_feat': speech_feat, 'prompt_speech_feat_len': speech_feat_len,
+ 'llm_embedding': utt_embedding, 'flow_embedding': utt_embedding}
+ model_output = model.inference(**model_input)
+ tts_key = '{}_{}'.format(utts[0], tts_index[0])
+ tts_fn = os.path.join(args.result_dir, '{}.wav'.format(tts_key))
+ torchaudio.save(tts_fn, model_output['tts_speech'], sample_rate=22050)
+ f.write('{} {}\n'.format(tts_key, tts_fn))
+ f.flush()
+ f.close()
+ logging.info('Result wav.scp saved in {}'.format(fn))
+
+
+if __name__ == '__main__':
+ main()
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/bin/train.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/bin/train.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f4c9fee8415823f26ae7d11a3b81ee24b6f31ea
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/bin/train.py
@@ -0,0 +1,140 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+import argparse
+import datetime
+import logging
+logging.getLogger('matplotlib').setLevel(logging.WARNING)
+from copy import deepcopy
+import torch
+import torch.distributed as dist
+# import deepspeed
+import pdb
+from hyperpyyaml import load_hyperpyyaml
+
+from torch.distributed.elastic.multiprocessing.errors import record
+
+from cosyvoice.utils.executor import Executor
+from cosyvoice.utils.train_utils import (
+ init_distributed,
+ init_dataset_and_dataloader,
+ init_optimizer_and_scheduler,
+ init_summarywriter, save_model,
+ wrap_cuda_model, check_modify_and_save_config)
+
+
+def get_args():
+ parser = argparse.ArgumentParser(description='training your network')
+ parser.add_argument('--train_engine',
+ default='torch_ddp',
+ choices=['torch_ddp', 'deepspeed'],
+ help='Engine for paralleled training')
+ parser.add_argument('--model', required=True, help='model which will be trained')
+ parser.add_argument('--config', required=True, help='config file')
+ parser.add_argument('--train_data', required=True, help='train data file')
+ parser.add_argument('--cv_data', required=True, help='cv data file')
+ parser.add_argument('--checkpoint', help='checkpoint model')
+ parser.add_argument('--model_dir', required=True, help='save model dir')
+ parser.add_argument('--tensorboard_dir',
+ default='tensorboard',
+ help='tensorboard log dir')
+ parser.add_argument('--ddp.dist_backend',
+ dest='dist_backend',
+ default='nccl',
+ choices=['nccl', 'gloo'],
+ help='distributed backend')
+ parser.add_argument('--num_workers',
+ default=0,
+ type=int,
+ help='num of subprocess workers for reading')
+ parser.add_argument('--prefetch',
+ default=100,
+ type=int,
+ help='prefetch number')
+ parser.add_argument('--pin_memory',
+ action='store_true',
+ default=False,
+ help='Use pinned memory buffers used for reading')
+ parser.add_argument('--deepspeed.save_states',
+ dest='save_states',
+ default='model_only',
+ choices=['model_only', 'model+optimizer'],
+ help='save model/optimizer states')
+ parser.add_argument('--timeout',
+ default=30,
+ type=int,
+ help='timeout (in seconds) of cosyvoice_join.')
+ # parser = deepspeed.add_config_arguments(parser)
+ args = parser.parse_args()
+ return args
+
+
+@record
+def main():
+ args = get_args()
+ logging.basicConfig(level=logging.DEBUG,
+ format='%(asctime)s %(levelname)s %(message)s')
+
+ override_dict = {k: None for k in ['llm', 'flow', 'hift'] if k != args.model}
+ with open(args.config, 'r') as f:
+ configs = load_hyperpyyaml(f, overrides=override_dict)
+ configs['train_conf'].update(vars(args))
+
+ # Init env for ddp
+ init_distributed(args)
+
+ # Get dataset & dataloader
+ train_dataset, cv_dataset, train_data_loader, cv_data_loader = \
+ init_dataset_and_dataloader(args, configs)
+
+ # Do some sanity checks and save config to arsg.model_dir
+ configs = check_modify_and_save_config(args, configs)
+
+ # Tensorboard summary
+ writer = init_summarywriter(args)
+
+ # load checkpoint
+ model = configs[args.model]
+ if args.checkpoint is not None:
+ model.load_state_dict(torch.load(args.checkpoint, map_location='cpu'))
+
+ # Dispatch model from cpu to gpu
+ model = wrap_cuda_model(args, model)
+
+ # Get optimizer & scheduler
+ model, optimizer, scheduler = init_optimizer_and_scheduler(args, configs, model)
+ # pdb.set_trace()
+ # Save init checkpoints
+ info_dict = deepcopy(configs['train_conf'])
+ save_model(model, 'init', info_dict)
+
+ # Get executor
+ executor = Executor()
+
+ # Start training loop
+ for epoch in range(info_dict['max_epoch']):
+ executor.epoch = epoch
+ train_dataset.set_epoch(epoch)
+ dist.barrier()
+ # try:
+ # dist.barrier()
+ # except RuntimeError as e:
+ # logging.info('except RuntimeError as e: {}'.format(e))
+ group_join = dist.new_group(backend="gloo", timeout=datetime.timedelta(seconds=args.timeout))
+ executor.train_one_epoc(model, optimizer, scheduler, train_data_loader, cv_data_loader, writer, info_dict, group_join)
+ dist.destroy_process_group(group_join)
+
+if __name__ == '__main__':
+ main()
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/cosyvoice.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/cosyvoice.py
new file mode 100644
index 0000000000000000000000000000000000000000..ea8c4482891a62df6cbac39faa88972c81f5412f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/cosyvoice.py
@@ -0,0 +1,83 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import os
+import torch
+from hyperpyyaml import load_hyperpyyaml
+from modelscope import snapshot_download
+from cosyvoice.cli.frontend import CosyVoiceFrontEnd
+from cosyvoice.cli.model import CosyVoiceModel
+
+class CosyVoice:
+
+ def __init__(self, model_dir):
+ instruct = True if '-Instruct' in model_dir else False
+ self.model_dir = model_dir
+ if not os.path.exists(model_dir):
+ model_dir = snapshot_download(model_dir)
+ with open('{}/cosyvoice.yaml'.format(model_dir), 'r') as f:
+ configs = load_hyperpyyaml(f)
+ self.frontend = CosyVoiceFrontEnd(configs['get_tokenizer'],
+ configs['feat_extractor'],
+ '{}/campplus.onnx'.format(model_dir),
+ '{}/speech_tokenizer_v1.onnx'.format(model_dir),
+ '{}/spk2info.pt'.format(model_dir),
+ instruct,
+ configs['allowed_special'])
+ self.model = CosyVoiceModel(configs['llm'], configs['flow'], configs['hift'])
+ self.model.load('{}/llm.pt'.format(model_dir),
+ '{}/flow.pt'.format(model_dir),
+ '{}/hift.pt'.format(model_dir))
+ del configs
+
+ def list_avaliable_spks(self):
+ spks = list(self.frontend.spk2info.keys())
+ return spks
+
+ def inference_sft(self, tts_text, spk_id):
+ tts_speeches = []
+ for i in self.frontend.text_normalize(tts_text, split=True):
+ model_input = self.frontend.frontend_sft(i, spk_id)
+ model_output = self.model.inference(**model_input)
+ tts_speeches.append(model_output['tts_speech'])
+ return {'tts_speech': torch.concat(tts_speeches, dim=1)}
+
+ def inference_zero_shot(self, tts_text, prompt_text, prompt_speech_16k):
+ prompt_text = self.frontend.text_normalize(prompt_text, split=False)
+ tts_speeches = []
+ for i in self.frontend.text_normalize(tts_text, split=True):
+ model_input = self.frontend.frontend_zero_shot(i, prompt_text, prompt_speech_16k)
+ model_output = self.model.inference(**model_input)
+ tts_speeches.append(model_output['tts_speech'])
+ return {'tts_speech': torch.concat(tts_speeches, dim=1)}
+
+ def inference_cross_lingual(self, tts_text, prompt_speech_16k):
+ if self.frontend.instruct is True:
+ raise ValueError('{} do not support cross_lingual inference'.format(self.model_dir))
+ tts_speeches = []
+ for i in self.frontend.text_normalize(tts_text, split=True):
+ model_input = self.frontend.frontend_cross_lingual(i, prompt_speech_16k)
+ model_output = self.model.inference(**model_input)
+ tts_speeches.append(model_output['tts_speech'])
+ return {'tts_speech': torch.concat(tts_speeches, dim=1)}
+
+ def inference_instruct(self, tts_text, spk_id, instruct_text):
+ if self.frontend.instruct is False:
+ raise ValueError('{} do not support instruct inference'.format(self.model_dir))
+ instruct_text = self.frontend.text_normalize(instruct_text, split=False)
+ tts_speeches = []
+ for i in self.frontend.text_normalize(tts_text, split=True):
+ model_input = self.frontend.frontend_instruct(i, spk_id, instruct_text)
+ model_output = self.model.inference(**model_input)
+ tts_speeches.append(model_output['tts_speech'])
+ return {'tts_speech': torch.concat(tts_speeches, dim=1)}
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/frontend.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/frontend.py
new file mode 100644
index 0000000000000000000000000000000000000000..3ed85500cd3ab65f8f4f7540c084adb0c648186f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/frontend.py
@@ -0,0 +1,168 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from functools import partial
+import onnxruntime
+import torch
+import numpy as np
+import whisper
+from typing import Callable
+import torchaudio.compliance.kaldi as kaldi
+import torchaudio
+import os
+import re
+import inflect
+try:
+ import ttsfrd
+ use_ttsfrd = True
+except ImportError:
+ print("failed to import ttsfrd, use WeTextProcessing instead")
+ from tn.chinese.normalizer import Normalizer as ZhNormalizer
+ from tn.english.normalizer import Normalizer as EnNormalizer
+ use_ttsfrd = False
+from cosyvoice.utils.frontend_utils import contains_chinese, replace_blank, replace_corner_mark, remove_bracket, spell_out_number, split_paragraph
+
+
+class CosyVoiceFrontEnd:
+
+ def __init__(self,
+ get_tokenizer: Callable,
+ feat_extractor: Callable,
+ campplus_model: str,
+ speech_tokenizer_model: str,
+ spk2info: str = '',
+ instruct: bool = False,
+ allowed_special: str = 'all'):
+ self.tokenizer = get_tokenizer()
+ self.feat_extractor = feat_extractor
+ self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+ option = onnxruntime.SessionOptions()
+ option.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
+ option.intra_op_num_threads = 1
+ self.campplus_session = onnxruntime.InferenceSession(campplus_model, sess_options=option, providers=["CPUExecutionProvider"])
+ self.speech_tokenizer_session = onnxruntime.InferenceSession(speech_tokenizer_model, sess_options=option, providers=["CUDAExecutionProvider"if torch.cuda.is_available() else "CPUExecutionProvider"])
+ if os.path.exists(spk2info):
+ self.spk2info = torch.load(spk2info, map_location=self.device)
+ self.instruct = instruct
+ self.allowed_special = allowed_special
+ self.inflect_parser = inflect.engine()
+ self.use_ttsfrd = use_ttsfrd
+ if self.use_ttsfrd:
+ self.frd = ttsfrd.TtsFrontendEngine()
+ ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
+ assert self.frd.initialize('{}/../../pretrained_models/CosyVoice-ttsfrd/resource'.format(ROOT_DIR)) is True, 'failed to initialize ttsfrd resource'
+ self.frd.set_lang_type('pinyin')
+ self.frd.enable_pinyin_mix(True)
+ self.frd.set_breakmodel_index(1)
+ else:
+ self.zh_tn_model = ZhNormalizer(remove_erhua=False, full_to_half=False)
+ self.en_tn_model = EnNormalizer()
+
+ def _extract_text_token(self, text):
+ text_token = self.tokenizer.encode(text, allowed_special=self.allowed_special)
+ text_token = torch.tensor([text_token], dtype=torch.int32).to(self.device)
+ text_token_len = torch.tensor([text_token.shape[1]], dtype=torch.int32).to(self.device)
+ return text_token, text_token_len
+
+ def _extract_speech_token(self, speech):
+ feat = whisper.log_mel_spectrogram(speech, n_mels=128)
+ speech_token = self.speech_tokenizer_session.run(None, {self.speech_tokenizer_session.get_inputs()[0].name: feat.detach().cpu().numpy(),
+ self.speech_tokenizer_session.get_inputs()[1].name: np.array([feat.shape[2]], dtype=np.int32)})[0].flatten().tolist()
+ speech_token = torch.tensor([speech_token], dtype=torch.int32).to(self.device)
+ speech_token_len = torch.tensor([speech_token.shape[1]], dtype=torch.int32).to(self.device)
+ return speech_token, speech_token_len
+
+ def _extract_spk_embedding(self, speech):
+ feat = kaldi.fbank(speech,
+ num_mel_bins=80,
+ dither=0,
+ sample_frequency=16000)
+ feat = feat - feat.mean(dim=0, keepdim=True)
+ embedding = self.campplus_session.run(None, {self.campplus_session.get_inputs()[0].name: feat.unsqueeze(dim=0).cpu().numpy()})[0].flatten().tolist()
+ embedding = torch.tensor([embedding]).to(self.device)
+ return embedding
+
+ def _extract_speech_feat(self, speech):
+ speech_feat = self.feat_extractor(speech).squeeze(dim=0).transpose(0, 1).to(self.device)
+ speech_feat = speech_feat.unsqueeze(dim=0)
+ speech_feat_len = torch.tensor([speech_feat.shape[1]], dtype=torch.int32).to(self.device)
+ return speech_feat, speech_feat_len
+
+ def text_normalize(self, text, split=True):
+ text = text.strip()
+ if contains_chinese(text):
+ if self.use_ttsfrd:
+ text = self.frd.get_frd_extra_info(text, 'input')
+ else:
+ text = self.zh_tn_model.normalize(text)
+ text = text.replace("\n", "")
+ text = replace_blank(text)
+ text = replace_corner_mark(text)
+ text = text.replace(".", "、")
+ text = text.replace(" - ", "，")
+ text = remove_bracket(text)
+ text = re.sub(r'[，,]+$', '。', text)
+ texts = [i for i in split_paragraph(text, partial(self.tokenizer.encode, allowed_special=self.allowed_special), "zh", token_max_n=80,
+ token_min_n=60, merge_len=20,
+ comma_split=False)]
+ else:
+ if self.use_ttsfrd:
+ text = self.frd.get_frd_extra_info(text, 'input')
+ else:
+ text = self.en_tn_model.normalize(text)
+ text = spell_out_number(text, self.inflect_parser)
+ texts = [i for i in split_paragraph(text, partial(self.tokenizer.encode, allowed_special=self.allowed_special), "en", token_max_n=80,
+ token_min_n=60, merge_len=20,
+ comma_split=False)]
+ if split is False:
+ return text
+ return texts
+
+ def frontend_sft(self, tts_text, spk_id):
+ tts_text_token, tts_text_token_len = self._extract_text_token(tts_text)
+ embedding = self.spk2info[spk_id]['embedding']
+ model_input = {'text': tts_text_token, 'text_len': tts_text_token_len, 'llm_embedding': embedding, 'flow_embedding': embedding}
+ return model_input
+
+ def frontend_zero_shot(self, tts_text, prompt_text, prompt_speech_16k):
+ tts_text_token, tts_text_token_len = self._extract_text_token(tts_text)
+ prompt_text_token, prompt_text_token_len = self._extract_text_token(prompt_text)
+ prompt_speech_22050 = torchaudio.transforms.Resample(orig_freq=16000, new_freq=22050)(prompt_speech_16k)
+ speech_feat, speech_feat_len = self._extract_speech_feat(prompt_speech_22050)
+ speech_token, speech_token_len = self._extract_speech_token(prompt_speech_16k)
+ embedding = self._extract_spk_embedding(prompt_speech_16k)
+ model_input = {'text': tts_text_token, 'text_len': tts_text_token_len,
+ 'prompt_text': prompt_text_token, 'prompt_text_len': prompt_text_token_len,
+ 'llm_prompt_speech_token': speech_token, 'llm_prompt_speech_token_len': speech_token_len,
+ 'flow_prompt_speech_token': speech_token, 'flow_prompt_speech_token_len': speech_token_len,
+ 'prompt_speech_feat': speech_feat, 'prompt_speech_feat_len': speech_feat_len,
+ 'llm_embedding': embedding, 'flow_embedding': embedding}
+ return model_input
+
+ def frontend_cross_lingual(self, tts_text, prompt_speech_16k):
+ model_input = self.frontend_zero_shot(tts_text, '', prompt_speech_16k)
+ # in cross lingual mode, we remove prompt in llm
+ del model_input['prompt_text']
+ del model_input['prompt_text_len']
+ del model_input['llm_prompt_speech_token']
+ del model_input['llm_prompt_speech_token_len']
+ return model_input
+
+ def frontend_instruct(self, tts_text, spk_id, instruct_text):
+ model_input = self.frontend_sft(tts_text, spk_id)
+ # in instruct mode, we remove spk_embedding in llm due to information leakage
+ del model_input['llm_embedding']
+ instruct_text_token, instruct_text_token_len = self._extract_text_token(instruct_text + '')
+ model_input['prompt_text'] = instruct_text_token
+ model_input['prompt_text_len'] = instruct_text_token_len
+ return model_input
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/model.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..446a84e079dcef74a018ef7fe6b2038709b97b0f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/cli/model.py
@@ -0,0 +1,95 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import torch
+
+class CosyVoiceModel:
+
+ def __init__(self,
+ llm: torch.nn.Module,
+ flow: torch.nn.Module,
+ hift: torch.nn.Module):
+ self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+ self.llm = llm
+ self.flow = flow
+ self.hift = hift
+
+ def load(self, llm_model, flow_model, hift_model):
+ self.llm.load_state_dict(torch.load(llm_model, map_location=self.device))
+ self.llm.to(self.device).eval()
+ self.flow.load_state_dict(torch.load(flow_model, map_location=self.device))
+ self.flow.to(self.device).eval()
+ self.hift.load_state_dict(torch.load(hift_model, map_location=self.device))
+ self.hift.to(self.device).eval()
+
+ def inference(self, text, text_len, flow_embedding, llm_embedding=torch.zeros(0, 192),
+ prompt_text=torch.zeros(1, 0, dtype=torch.int32), prompt_text_len=torch.zeros(1, dtype=torch.int32),
+ llm_prompt_speech_token=torch.zeros(1, 0, dtype=torch.int32), llm_prompt_speech_token_len=torch.zeros(1, dtype=torch.int32),
+ flow_prompt_speech_token=torch.zeros(1, 0, dtype=torch.int32), flow_prompt_speech_token_len=torch.zeros(1, dtype=torch.int32),
+ prompt_speech_feat=torch.zeros(1, 0, 80), prompt_speech_feat_len=torch.zeros(1, dtype=torch.int32)):
+ tts_speech_token = self.llm.inference(text=text.to(self.device),
+ text_len=text_len.to(self.device),
+ prompt_text=prompt_text.to(self.device),
+ prompt_text_len=prompt_text_len.to(self.device),
+ prompt_speech_token=llm_prompt_speech_token.to(self.device),
+ prompt_speech_token_len=llm_prompt_speech_token_len.to(self.device),
+ embedding=llm_embedding.to(self.device),
+ beam_size=1,
+ sampling=25,
+ max_token_text_ratio=30,
+ min_token_text_ratio=3)
+ tts_mel = self.flow.inference(token=tts_speech_token,
+ token_len=torch.tensor([tts_speech_token.size(1)], dtype=torch.int32).to(self.device),
+ prompt_token=flow_prompt_speech_token.to(self.device),
+ prompt_token_len=flow_prompt_speech_token_len.to(self.device),
+ prompt_feat=prompt_speech_feat.to(self.device),
+ prompt_feat_len=prompt_speech_feat_len.to(self.device),
+ embedding=flow_embedding.to(self.device))
+ tts_speech = self.hift.inference(mel=tts_mel).cpu()
+ torch.cuda.empty_cache()
+ return {'tts_speech': tts_speech}
+
+ def text_to_token(self, text, text_len, flow_embedding, llm_embedding=torch.zeros(0, 192),
+ prompt_text=torch.zeros(1, 0, dtype=torch.int32), prompt_text_len=torch.zeros(1, dtype=torch.int32),
+ llm_prompt_speech_token=torch.zeros(1, 0, dtype=torch.int32), llm_prompt_speech_token_len=torch.zeros(1, dtype=torch.int32),
+ flow_prompt_speech_token=torch.zeros(1, 0, dtype=torch.int32), flow_prompt_speech_token_len=torch.zeros(1, dtype=torch.int32),
+ prompt_speech_feat=torch.zeros(1, 0, 80), prompt_speech_feat_len=torch.zeros(1, dtype=torch.int32)):
+ tts_speech_token = self.llm.inference(text=text.to(self.device),
+ text_len=text_len.to(self.device),
+ prompt_text=prompt_text.to(self.device),
+ prompt_text_len=prompt_text_len.to(self.device),
+ prompt_speech_token=llm_prompt_speech_token.to(self.device),
+ prompt_speech_token_len=llm_prompt_speech_token_len.to(self.device),
+ embedding=llm_embedding.to(self.device),
+ beam_size=1,
+ sampling=25,
+ max_token_text_ratio=30,
+ min_token_text_ratio=3)
+ return tts_speech_token
+
+ def token_to_speech(self, tts_speech_token, flow_embedding, llm_embedding=torch.zeros(0, 192),
+ prompt_text=torch.zeros(1, 0, dtype=torch.int32), prompt_text_len=torch.zeros(1, dtype=torch.int32),
+ llm_prompt_speech_token=torch.zeros(1, 0, dtype=torch.int32), llm_prompt_speech_token_len=torch.zeros(1, dtype=torch.int32),
+ flow_prompt_speech_token=torch.zeros(1, 0, dtype=torch.int32), flow_prompt_speech_token_len=torch.zeros(1, dtype=torch.int32),
+ prompt_speech_feat=torch.zeros(1, 0, 80), prompt_speech_feat_len=torch.zeros(1, dtype=torch.int32)):
+
+ tts_mel = self.flow.inference(token=tts_speech_token,
+ token_len=torch.tensor([tts_speech_token.size(1)], dtype=torch.int32).to(self.device),
+ prompt_token=flow_prompt_speech_token.to(self.device),
+ prompt_token_len=flow_prompt_speech_token_len.to(self.device),
+ prompt_feat=prompt_speech_feat.to(self.device),
+ prompt_feat_len=prompt_speech_feat_len.to(self.device),
+ embedding=flow_embedding.to(self.device))
+ tts_speech = self.hift.inference(mel=tts_mel).cpu()
+ torch.cuda.empty_cache()
+ return {'tts_speech': tts_speech}
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/dataset.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/dataset.py
new file mode 100644
index 0000000000000000000000000000000000000000..6681504383f73ac9ba1609b9d48bdec7aae23f28
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/dataset.py
@@ -0,0 +1,160 @@
+# Copyright (c) 2021 Mobvoi Inc. (authors: Binbin Zhang)
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import random
+import json
+import math
+from functools import partial
+
+import torch
+import torch.distributed as dist
+from torch.utils.data import IterableDataset
+from cosyvoice.utils.file_utils import read_lists, read_json_lists
+
+
+class Processor(IterableDataset):
+
+ def __init__(self, source, f, *args, **kw):
+ assert callable(f)
+ self.source = source
+ self.f = f
+ self.args = args
+ self.kw = kw
+
+ def set_epoch(self, epoch):
+ self.source.set_epoch(epoch)
+
+ def __iter__(self):
+ """ Return an iterator over the source dataset processed by the
+ given processor.
+ """
+ assert self.source is not None
+ assert callable(self.f)
+ return self.f(iter(self.source), *self.args, **self.kw)
+
+ def apply(self, f):
+ assert callable(f)
+ return Processor(self, f, *self.args, **self.kw)
+
+
+class DistributedSampler:
+
+ def __init__(self, shuffle=True, partition=True):
+ self.epoch = -1
+ self.update()
+ self.shuffle = shuffle
+ self.partition = partition
+
+ def update(self):
+ assert dist.is_available()
+ if dist.is_initialized():
+ self.rank = dist.get_rank()
+ self.world_size = dist.get_world_size()
+ else:
+ self.rank = 0
+ self.world_size = 1
+ worker_info = torch.utils.data.get_worker_info()
+ if worker_info is None:
+ self.worker_id = 0
+ self.num_workers = 1
+ else:
+ self.worker_id = worker_info.id
+ self.num_workers = worker_info.num_workers
+ return dict(rank=self.rank,
+ world_size=self.world_size,
+ worker_id=self.worker_id,
+ num_workers=self.num_workers)
+
+ def set_epoch(self, epoch):
+ self.epoch = epoch
+
+ def sample(self, data):
+ """ Sample data according to rank/world_size/num_workers
+
+ Args:
+ data(List): input data list
+
+ Returns:
+ List: data list after sample
+ """
+ data = list(range(len(data)))
+ # force datalist even
+ if self.partition:
+ if self.shuffle:
+ random.Random(self.epoch).shuffle(data)
+ if len(data) < self.world_size:
+ data = data * math.ceil(self.world_size / len(data))
+ data = data[:self.world_size]
+ data = data[self.rank::self.world_size]
+ if len(data) < self.num_workers:
+ data = data * math.ceil(self.num_workers / len(data))
+ data = data[:self.num_workers]
+ data = data[self.worker_id::self.num_workers]
+ return data
+
+
+class DataList(IterableDataset):
+
+ def __init__(self, lists, shuffle=True, partition=True):
+ self.lists = lists
+ self.sampler = DistributedSampler(shuffle, partition)
+
+ def set_epoch(self, epoch):
+ self.sampler.set_epoch(epoch)
+
+ def __iter__(self):
+ sampler_info = self.sampler.update()
+ indexes = self.sampler.sample(self.lists)
+ for index in indexes:
+ data = dict(src=self.lists[index])
+ data.update(sampler_info)
+ yield data
+
+
+def Dataset(data_list_file,
+ data_pipeline,
+ mode='train',
+ shuffle=True,
+ partition=True,
+ tts_file='',
+ prompt_utt2data=''):
+ """ Construct dataset from arguments
+
+ We have two shuffle stage in the Dataset. The first is global
+ shuffle at shards tar/raw file level. The second is global shuffle
+ at training samples level.
+
+ Args:
+ data_type(str): raw/shard
+ tokenizer (BaseTokenizer): tokenizer to tokenize
+ partition(bool): whether to do data partition in terms of rank
+ """
+ assert mode in ['train', 'inference']
+ lists = read_lists(data_list_file)
+ # import pdb
+ # pdb.set_trace()
+ if mode == 'inference':
+ with open(tts_file) as f:
+ tts_data = json.load(f)
+ utt2lists = read_json_lists(prompt_utt2data)
+ # filter unnecessary file in inference mode
+ lists = list(set([utt2lists[utt] for utt in tts_data.keys() if utt2lists[utt] in lists]))
+ dataset = DataList(lists,shuffle=shuffle,partition=partition)
+ if mode == 'inference':
+ # map partial arg tts_data in inference mode
+ data_pipeline[0] = partial(data_pipeline[0], tts_data=tts_data)
+ for func in data_pipeline:
+ dataset = Processor(dataset, func, mode=mode)
+ return dataset
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/processor.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/processor.py
new file mode 100644
index 0000000000000000000000000000000000000000..8c8c743fdbe03139a9703ba635e31ab74c459c67
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/dataset/processor.py
@@ -0,0 +1,965 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import logging
+import random
+import json
+import tarfile
+import json
+import io
+import pyarrow.parquet as pq
+from io import BytesIO
+import torch
+import torchaudio
+from torch.nn.utils.rnn import pad_sequence
+import torch.nn.functional as F
+import tarfile
+import json
+import io
+import wave
+import numpy as np
+import torchaudio
+import os
+import sys
+import json
+import random
+import pickle
+import argparse
+import itertools
+import mmap
+import struct
+import collections
+
+
+
+import shutil
+import multiprocessing as mp
+from pathlib import Path
+
+from tqdm import tqdm
+from collections import defaultdict
+from copy import deepcopy
+from datetime import datetime
+import pickle
+
+from wids import wids
+import math
+
+torchaudio.set_audio_backend('soundfile')
+
+AUDIO_FORMAT_SETS = set(['flac', 'mp3', 'm4a', 'ogg', 'opus', 'wav', 'wma'])
+
+try:
+ MAIN_SPK_EMBEDDING=torch.load("/workspace/audio_checkpoints/flow_model/spk_embedding/0909/mean_embedding.pt")
+ GPT_SPK_EMBEDDING=torch.load("/workspace/audio_checkpoints/flow_model/spk_embedding/0909/spk_mean_embeddings.pt")
+except:
+ MAIN_SPK_EMBEDDING=torch.zeros(1,192)
+ GPT_SPK_EMBEDDING=torch.zeros(1,192)
+
+def parquet_opener(data, mode='train', tts_data={}):
+ """ Give url or local file, return file descriptor
+ Inplace operation.
+
+ Args:
+ data(Iterable[str]): url or local file list
+
+ Returns:
+ Iterable[{src, stream}]
+ """
+ for sample in data:
+ assert 'src' in sample
+ url = sample['src']
+ try:
+ df = pq.read_table(url).to_pandas()
+ for i in range(len(df)):
+ if mode == 'inference' and df.loc[i, 'utt'] not in tts_data:
+ continue
+ sample.update(dict(df.loc[i]))
+ if mode == 'train':
+ # NOTE do not return sample directly, must initialize a new dict
+ yield {**sample}
+ else:
+ for index, text in enumerate(tts_data[df.loc[i, 'utt']]):
+ yield {**sample, 'tts_index': index, 'tts_text': text}
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(url, ex))
+
+
+
+
+def parse_tar_header(header_bytes):
+ header = struct.unpack("!100s8s8s8s12s12s8s1s100s6s2s32s32s8s8s155s", header_bytes)
+ return TarHeader(*header)
+
+TarHeader = collections.namedtuple(
+ "TarHeader",
+ [
+ "name",
+ "mode",
+ "uid",
+ "gid",
+ "size",
+ "mtime",
+ "chksum",
+ "typeflag",
+ "linkname",
+ "magic",
+ "version",
+ "uname",
+ "gname",
+ "devmajor",
+ "devminor",
+ "prefix",
+ ],
+)
+
+class MMTar:
+ def __init__(self, file_path: Path | str):
+ self.stream = open(file_path, "rb")
+ self.mmap = mmap.mmap(self.stream.fileno(), 0, access=mmap.ACCESS_READ)
+
+ def __del__(self):
+ try:
+ self.mmap.close()
+ self.stream.close()
+ except: # noqa
+ pass
+
+ def get_at_offset(self, offset) -> tuple[str, bytes]:
+ header = parse_tar_header(self.mmap[offset : offset + 500])
+ name = header.name.decode("utf-8").strip("\x00")
+ start = offset + 512
+ end = start + int(header.size.decode("utf-8")[:-1], 8)
+ return name, self.mmap[start:end]
+
+
+class Tar:
+ def __init__(self, path: Path):
+ self.tar = MMTar(path)
+ indices_path = path.with_suffix(".index")
+ self.index = pickle.loads(indices_path.read_bytes())
+ self.name_mapping = {}
+ for name, offset, _ in self.index:
+ self.name_mapping[name] = offset
+
+ def read(self, name: str) -> bytes:
+ return self.tar.get_at_offset(self.name_mapping[name])[1]
+
+def cosy_jsonl_opener(data, mode='train', tts_data={}):
+ """ Give url or local file, return file descriptor
+ Inplace operation.
+
+ Args:
+ data(Iterable[str]): url or local file list
+
+ Returns:
+ Iterable[{src, stream}]
+ """
+ for sample in data:
+ assert 'src' in sample
+ cosy_jsonl_path = sample['src']
+ tar_file_path=cosy_jsonl_path.replace(".vq0907.jsonl",".tar")
+ try:
+ tar_data=Tar(Path(tar_file_path))
+ with open(cosy_jsonl_path, 'r') as f:
+ for line in f:
+ item=json.loads(line)
+ cosy_token = item['cosy_token']
+ sample['speech_token']=torch.tensor(cosy_token)
+ sample['speech'], sample['sample_rate']= torchaudio.load(io.BytesIO(tar_data.read(item['filename'])))
+ # print(item['filename'])
+ yield {**sample}
+
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(cosy_jsonl_path, ex))
+
+
+def cosy_jsonl_opener_vq0918_nopool(data, mode='train', tts_data={}):
+ """ Give url or local file, return file descriptor
+ Inplace operation.
+
+ Args:
+ data(Iterable[str]): url or local file list
+
+ Returns:
+ Iterable[{src, stream}]
+ """
+ for sample in data:
+ assert 'src' in sample
+ cosy_jsonl_path = sample['src']
+ tar_file_path=cosy_jsonl_path.replace(".vq0918-nopool.jsonl",".tar")
+
+
+ try:
+ tar_data=Tar(Path(tar_file_path))
+ with open(cosy_jsonl_path, 'r') as f:
+ # cosy_data = [json.loads(line) for line in f]
+ for line in f:
+ item=json.loads(line)
+ cosy_token = item['cosy_token']
+ sample['speech_token']=torch.tensor(cosy_token)
+ sample['speech'], sample['sample_rate']= torchaudio.load(io.BytesIO(tar_data.read(item['filename'])))
+ # print(item['filename'])
+ yield {**sample}
+
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(cosy_jsonl_path, ex))
+
+
+
+def cosy_jsonl_opener_vq0918_pool2(data, mode='train', tts_data={}):
+ """ Give url or local file, return file descriptor
+ Inplace operation.
+
+ Args:
+ data(Iterable[str]): url or local file list
+
+ Returns:
+ Iterable[{src, stream}]
+ """
+ for sample in data:
+ assert 'src' in sample
+ cosy_jsonl_path = sample['src']
+ tar_file_path=cosy_jsonl_path.replace(".vq0918-pool2.jsonl",".tar")
+
+ try:
+ tar_data=Tar(Path(tar_file_path))
+ with open(cosy_jsonl_path, 'r') as f:
+ for line in f:
+ item=json.loads(line)
+ cosy_token = item['cosy_token']
+ sample['speech_token']=torch.tensor(cosy_token)
+ sample['speech'], sample['sample_rate']= torchaudio.load(io.BytesIO(tar_data.read(item['filename'])))
+
+ yield {**sample}
+
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(cosy_jsonl_path, ex))
+
+
+def cosy_jsonl_opener_vq0918_pool4(data, mode='train', tts_data={}):
+ """ Give url or local file, return file descriptor
+ Inplace operation.
+
+ Args:
+ data(Iterable[str]): url or local file list
+
+ Returns:
+ Iterable[{src, stream}]
+ """
+ for sample in data:
+ assert 'src' in sample
+ cosy_jsonl_path = sample['src']
+ tar_file_path=cosy_jsonl_path.replace(".vq0918-pool4.jsonl",".tar")
+ try:
+ tar_data=Tar(Path(tar_file_path))
+ with open(cosy_jsonl_path, 'r') as f:
+ # cosy_data = [json.loads(line) for line in f]
+ for line in f:
+ item=json.loads(line)
+ cosy_token = item['cosy_token']
+ sample['speech_token']=torch.tensor(cosy_token)
+ sample['speech'], sample['sample_rate']= torchaudio.load(io.BytesIO(tar_data.read(item['filename'])))
+ # print(item['filename'])
+ yield {**sample}
+
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(cosy_jsonl_path, ex))
+
+
+def cosy_jsonl_opener_vq0918_pool8(data, mode='train', tts_data={}):
+ """ Give url or local file, return file descriptor
+ Inplace operation.
+
+ Args:
+ data(Iterable[str]): url or local file list
+
+ Returns:
+ Iterable[{src, stream}]
+ """
+ for sample in data:
+ assert 'src' in sample
+ cosy_jsonl_path = sample['src']
+ tar_file_path=cosy_jsonl_path.replace(".vq0918-pool8.jsonl",".tar")
+
+ try:
+ tar_data=Tar(Path(tar_file_path))
+ with open(cosy_jsonl_path, 'r') as f:
+ # cosy_data = [json.loads(line) for line in f]
+ for line in f:
+ item=json.loads(line)
+ cosy_token = item['cosy_token']
+ sample['speech_token']=torch.tensor(cosy_token)
+ sample['speech'], sample['sample_rate']= torchaudio.load(io.BytesIO(tar_data.read(item['filename'])))
+ # print(item['filename'])
+ yield {**sample}
+
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(cosy_jsonl_path, ex))
+
+
+
+def process_sft_vq0918_pool4(data, mode='train', tts_data={}):
+ for sample in data:
+ assert 'src' in sample
+
+ token_npy_path = sample['src']
+ wav_path=token_npy_path.replace(".vq0918-pool4.npy","")
+
+ # wav_path,token_npy_path=sample['src'].split(' ')
+ try:
+ sample['speech_token']=torch.tensor(np.load(token_npy_path))
+ sample['speech'], sample['sample_rate']= torchaudio.load(wav_path)
+ if sample['speech'].shape[0] > 1:
+ sample['speech'] = sample['speech'].mean(dim=0, keepdim=True)
+ sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+ yield {**sample}
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(wav_path, ex))
+ logging.warning('Failed to open {}'.format(wav_path))
+
+
+def process_sft_vq0918_pool4_split(data, mode='train',split_token=25, tts_data={}):
+ for sample in data:
+ assert 'src' in sample
+
+ token_npy_path = sample['src']
+ wav_path=token_npy_path.replace(".vq0918-pool4.npy","")
+
+ # wav_path,token_npy_path=sample['src'].split(' ')
+ try:
+ # sample['speech_token']=torch.tensor(np.load(token_npy_path))
+ # sample['speech'], sample['sample_rate']= torchaudio.load(wav_path)
+ # if sample['speech'].shape[0] > 1:
+ # sample['speech'] = sample['speech'].mean(dim=0, keepdim=True)
+
+
+ # sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+
+
+ speech_token=torch.tensor(np.load(token_npy_path))
+ speech,sample_rate= torchaudio.load(wav_path)
+ # split_speech=int(split_token / 12.5 * sample_rate)
+ if speech.shape[0] > 1:
+ speech = speech.mean(dim=0, keepdim=True)
+
+ sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+ sample['sample_rate']=sample_rate
+
+ num_splits = (speech_token.size(0) + split_token - 1) // split_token
+
+ for split_id in range(num_splits):
+ end_token_idx = min((split_id + 1) * split_token, speech_token.size(0))
+ end_speech_idx=int(np.ceil(end_token_idx / 12.5 * sample_rate))
+ sample['speech_token']=speech_token[:end_token_idx]
+ sample['speech']=speech[:,:end_speech_idx]
+ print(sample['speech_token'].size(),sample['speech'].size())
+ yield {**sample}
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(wav_path, ex))
+ logging.warning('Failed to open {}'.format(wav_path))
+
+
+def process_sft_vq0918_pool2(data, mode='train', tts_data={}):
+ for sample in data:
+ assert 'src' in sample
+
+ token_npy_path = sample['src'].replace(".vq0918-pool4.npy",".vq0918-pool2.npy")
+ wav_path=token_npy_path.replace(".vq0918-pool2.npy","")
+
+ # wav_path,token_npy_path=sample['src'].split(' ')
+ try:
+ sample['speech_token']=torch.tensor(np.load(token_npy_path))
+ sample['speech'], sample['sample_rate']= torchaudio.load(wav_path)
+ if sample['speech'].shape[0] > 1:
+ sample['speech'] = sample['speech'].mean(dim=0, keepdim=True)
+
+ sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+ yield {**sample}
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(wav_path, ex))
+ logging.warning('Failed to open {}'.format(wav_path))
+
+
+def process_sft_vq0918_pool2_split(data, mode='train',split_token=50, tts_data={}):
+ for sample in data:
+ assert 'src' in sample
+
+ token_npy_path = sample['src']
+ wav_path=token_npy_path.replace(".vq0918-pool2.npy","")
+
+ # wav_path,token_npy_path=sample['src'].split(' ')
+ try:
+ # sample['speech_token']=torch.tensor(np.load(token_npy_path))
+ # sample['speech'], sample['sample_rate']= torchaudio.load(wav_path)
+ # if sample['speech'].shape[0] > 1:
+ # sample['speech'] = sample['speech'].mean(dim=0, keepdim=True)
+
+
+ # sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+
+
+ speech_token=torch.tensor(np.load(token_npy_path))
+ speech,sample_rate= torchaudio.load(wav_path)
+ # split_speech=int(split_token / 12.5 * sample_rate)
+ if speech.shape[0] > 1:
+ speech = speech.mean(dim=0, keepdim=True)
+
+ sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+ sample['sample_rate']=sample_rate
+
+ num_splits = (speech_token.size(0) + split_token - 1) // split_token
+
+ for split_id in range(num_splits):
+ end_token_idx = min((split_id + 1) * split_token, speech_token.size(0))
+ end_speech_idx=int(np.ceil(end_token_idx / 25 * sample_rate))
+ sample['speech_token']=speech_token[:end_token_idx]
+ sample['speech']=speech[:,:end_speech_idx]
+ print(sample['speech_token'].size(),sample['speech'].size())
+ yield {**sample}
+ except Exception as ex:
+ logging.warning('Failed to open {}, ex info {}'.format(wav_path, ex))
+ logging.warning('Failed to open {}'.format(wav_path))
+
+def process_sft_vq0918_pool4_gpt(data, mode='train', tts_data={}):
+ for sample in data:
+ assert 'src' in sample
+ try:
+ entry=json.loads(sample['src'])
+ sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+
+ for conv in entry["conversations"]:
+ if "response_wav" in conv:
+ wav_path = f"/workspace/audio_data/sft/{conv['response_wav']}"
+ token_npy_path=wav_path.replace(".wav",".wav.vq0918-pool4.npy")
+ sample['speech_token']=torch.tensor(np.load(token_npy_path))
+ sample['speech'], sample['sample_rate']= torchaudio.load(wav_path)
+ if sample['speech'].shape[0] > 1:
+ sample['speech'] = sample['speech'].mean(dim=0, keepdim=True)
+ sample['spk_embedding']=spk_embedding
+ yield {**sample}
+ except Exception as ex:
+ # logging.warning('Failed to open {}, ex info {}'.format(wav_path, ex))
+ logging.warning('Failed to open {}'.format(wav_path))
+
+
+def process_sft_vq0918_pool4_gpt_1010(data, mode='train', tts_data={}):
+ for sample in data:
+ assert 'src' in sample
+ try:
+ entry=json.loads(sample['src'])
+ sample['spk_embedding']=torch.zeros_like(MAIN_SPK_EMBEDDING)
+
+ for conv in entry["conversations"]:
+ if "response_wav" in conv:
+ wav_path = f"/workspace/audio_data/sft/{conv['response_wav']}"
+ token_npy_path=wav_path.replace(".wav",".wav.vq0918-pool4.npy")
+ sample['speech_token']=torch.tensor(np.load(token_npy_path))
+ sample['speech'], sample['sample_rate']= torchaudio.load(wav_path)
+ if sample['speech'].shape[0] > 1:
+ sample['speech'] = sample['speech'].mean(dim=0, keepdim=True)
+ sample['spk_embedding']=spk_embedding
+ yield {**sample}
+ if "prompt_wav" in conv:
+ wav_path = f"/workspace/audio_data/sft/{conv['response_wav']}"
+ token_npy_path=wav_path.replace(".wav",".wav.vq0918-pool4.npy")
+ sample['speech_token']=torch.tensor(np.load(token_npy_path))
+ sample['speech'], sample['sample_rate']= torchaudio.load(wav_path)
+ if sample['speech'].shape[0] > 1:
+ sample['speech'] = sample['speech'].mean(dim=0, keepdim=True)
+ sample['spk_embedding']=spk_embedding
+ yield {**sample}
+ except Exception as ex:
+ # logging.warning('Failed to open {}, ex info {}'.format(wav_path, ex))
+ logging.warning('Failed to open {}'.format(wav_path))
+
+
+def filter(data,
+ max_length=10240,
+ min_length=10,
+ token_max_length=200,
+ token_min_length=1,
+ min_output_input_ratio=0.0005,
+ max_output_input_ratio=1,
+ mode='train'):
+ """ Filter sample according to feature and label length
+ Inplace operation.
+
+ Args::
+ data: Iterable[{key, wav, label, sample_rate}]
+ max_length: drop utterance which is greater than max_length(10ms)
+ min_length: drop utterance which is less than min_length(10ms)
+ token_max_length: drop utterance which is greater than
+ token_max_length, especially when use char unit for
+ english modeling
+ token_min_length: drop utterance which is
+ less than token_max_length
+ min_output_input_ratio: minimal ration of
+ token_length / feats_length(10ms)
+ max_output_input_ratio: maximum ration of
+ token_length / feats_length(10ms)
+
+ Returns:
+ Iterable[{key, wav, label, sample_rate}]
+ """
+ for sample in data:
+ # sample['speech'], sample['sample_rate'] = torchaudio.load(BytesIO(sample['audio_data']))
+ # del sample['audio_data']
+ # sample['wav'] is torch.Tensor, we have 100 frames every second
+ num_frames = sample['speech'].size(1) / sample['sample_rate'] * 100
+ if num_frames < min_length:
+ continue
+ if num_frames > max_length:
+ continue
+ if len(sample['text_token']) < token_min_length:
+ continue
+ if len(sample['text_token']) > token_max_length:
+ continue
+ if len(sample['speech_token']) == 0:
+ continue
+ if num_frames != 0:
+ if len(sample['text_token']) / num_frames < min_output_input_ratio:
+ continue
+ if len(sample['text_token']) / num_frames > max_output_input_ratio:
+ continue
+ yield sample
+
+
+def filter_speech_token(data,
+ max_length=10240,
+ min_length=10,
+ token_max_length=5000,
+ token_min_length=1,
+ min_output_input_ratio=0.0005,
+ max_output_input_ratio=30,
+ mode='train'):
+ """ Filter sample according to feature and label length
+ Inplace operation.
+
+ Args::
+ data: Iterable[{key, wav, label, sample_rate}]
+ max_length: drop utterance which is greater than max_length(10ms)
+ min_length: drop utterance which is less than min_length(10ms)
+ token_max_length: drop utterance which is greater than
+ token_max_length, especially when use char unit for
+ english modeling
+ token_min_length: drop utterance which is
+ less than token_max_length
+ min_output_input_ratio: minimal ration of
+ token_length / feats_length(10ms)
+ max_output_input_ratio: maximum ration of
+ token_length / feats_length(10ms)
+
+ Returns:
+ Iterable[{key, wav, label, sample_rate}]
+ """
+ for sample in data:
+ # sample['speech'], sample['sample_rate'] = torchaudio.load(BytesIO(sample['audio_data']))
+ # del sample['audio_data']
+ # sample['wav'] is torch.Tensor, we have 100 frames every second
+ num_frames = sample['speech'].size(1) / sample['sample_rate'] * 100
+ if num_frames < min_length:
+ continue
+ if num_frames > max_length:
+ continue
+ if len(sample['speech_token']) < token_min_length:
+ continue
+ if len(sample['speech_token']) > token_max_length:
+ continue
+ if len(sample['speech_token']) == 0:
+ continue
+ if num_frames != 0:
+ if len(sample['speech_token']) / num_frames < min_output_input_ratio:
+ continue
+ if len(sample['speech_token']) / num_frames > max_output_input_ratio:
+ continue
+ yield sample
+
+
+def resample(data, resample_rate=22050, min_sample_rate=16000, mode='train'):
+ """ Resample data.
+ Inplace operation.
+
+ Args:
+ data: Iterable[{key, wav, label, sample_rate}]
+ resample_rate: target resample rate
+
+ Returns:
+ Iterable[{key, wav, label, sample_rate}]
+ """
+ for sample in data:
+ assert 'sample_rate' in sample
+ assert 'speech' in sample
+ sample_rate = sample['sample_rate']
+ waveform = sample['speech']
+ if sample_rate != resample_rate:
+ if sample_rate < min_sample_rate:
+ continue
+ sample['sample_rate'] = resample_rate
+ sample['speech'] = torchaudio.transforms.Resample(
+ orig_freq=sample_rate, new_freq=resample_rate)(waveform)
+ max_val = sample['speech'].abs().max()
+ if max_val > 1:
+ sample['speech'] /= max_val
+ yield sample
+
+
+def compute_fbank(data,
+ feat_extractor,
+ mode='train'):
+ """ Extract fbank
+
+ Args:
+ data: Iterable[{key, wav, label, sample_rate}]
+
+ Returns:
+ Iterable[{key, feat, label}]
+ """
+ for sample in data:
+ assert 'sample_rate' in sample
+ assert 'speech' in sample
+ # assert 'utt' in sample
+ # assert 'text_token' in sample
+ waveform = sample['speech']
+ mat = feat_extractor(waveform).squeeze(dim=0).transpose(0, 1)
+ sample['speech_feat'] = mat
+ del sample['speech']
+ yield sample
+
+
+def parse_embedding(data, normalize, mode='train'):
+ """ Parse utt_embedding/spk_embedding
+
+ Args:
+ data: Iterable[{key, wav, label, sample_rate}]
+
+ Returns:
+ Iterable[{key, feat, label}]
+ """
+ for sample in data:
+ sample['utt_embedding'] = torch.tensor(sample['utt_embedding'], dtype=torch.float32)
+ sample['spk_embedding'] = torch.tensor(sample['spk_embedding'], dtype=torch.float32)
+ if normalize:
+ sample['utt_embedding'] = F.normalize(sample['utt_embedding'], dim=0)
+ sample['spk_embedding'] = F.normalize(sample['spk_embedding'], dim=0)
+ yield sample
+
+
+def tokenize(data, get_tokenizer, allowed_special, mode='train'):
+ """ Decode text to chars or BPE
+ Inplace operation
+
+ Args:
+ data: Iterable[{key, wav, txt, sample_rate}]
+
+ Returns:
+ Iterable[{key, wav, txt, tokens, label, sample_rate}]
+ """
+ tokenizer = get_tokenizer()
+ for sample in data:
+ assert 'text' in sample
+ sample['text_token'] = tokenizer.encode(sample['text'], allowed_special=allowed_special)
+ if mode == 'inference':
+ sample['tts_text_token'] = tokenizer.encode(sample['tts_text'], allowed_special=allowed_special)
+ yield sample
+
+
+def shuffle(data, shuffle_size=10000, mode='train'):
+ """ Local shuffle the data
+
+ Args:
+ data: Iterable[{key, feat, label}]
+ shuffle_size: buffer size for shuffle
+
+ Returns:
+ Iterable[{key, feat, label}]
+ """
+ buf = []
+ for sample in data:
+ buf.append(sample)
+ if len(buf) >= shuffle_size:
+ random.shuffle(buf)
+ for x in buf:
+ yield x
+ buf = []
+ # The sample left over
+ random.shuffle(buf)
+ for x in buf:
+ yield x
+
+
+def sort(data, sort_size=500, mode='train'):
+ """ Sort the data by feature length.
+ Sort is used after shuffle and before batch, so we can group
+ utts with similar lengths into a batch, and `sort_size` should
+ be less than `shuffle_size`
+
+ Args:
+ data: Iterable[{key, feat, label}]
+ sort_size: buffer size for sort
+
+ Returns:
+ Iterable[{key, feat, label}]
+ """
+
+ buf = []
+ for sample in data:
+ buf.append(sample)
+ if len(buf) >= sort_size:
+ buf.sort(key=lambda x: x['speech_feat'].size(0))
+ for x in buf:
+ yield x
+ buf = []
+ # The sample left over
+ buf.sort(key=lambda x: x['speech_feat'].size(0))
+ for x in buf:
+ yield x
+
+
+def static_batch(data, batch_size=16):
+ """ Static batch the data by `batch_size`
+
+ Args:
+ data: Iterable[{key, feat, label}]
+ batch_size: batch size
+
+ Returns:
+ Iterable[List[{key, feat, label}]]
+ """
+ buf = []
+ for sample in data:
+ buf.append(sample)
+ if len(buf) >= batch_size:
+ yield buf
+ buf = []
+ if len(buf) > 0:
+ yield buf
+
+
+def dynamic_batch(data, max_frames_in_batch=12000, mode='train'):
+ """ Dynamic batch the data until the total frames in batch
+ reach `max_frames_in_batch`
+
+ Args:
+ data: Iterable[{key, feat, label}]
+ max_frames_in_batch: max_frames in one batch
+
+ Returns:
+ Iterable[List[{key, feat, label}]]
+ """
+ buf = []
+ longest_frames = 0
+ for sample in data:
+ assert 'speech_feat' in sample
+ assert isinstance(sample['speech_feat'], torch.Tensor)
+ new_sample_frames = sample['speech_feat'].size(0)
+ longest_frames = max(longest_frames, new_sample_frames)
+ frames_after_padding = longest_frames * (len(buf) + 1)
+ if frames_after_padding > max_frames_in_batch:
+ yield buf
+ buf = [sample]
+ longest_frames = new_sample_frames
+ else:
+ buf.append(sample)
+ if len(buf) > 0:
+ yield buf
+
+
+def batch(data, batch_type='static', batch_size=16, max_frames_in_batch=12000, mode='train'):
+ """ Wrapper for static/dynamic batch
+ """
+ if mode == 'inference':
+ return static_batch(data, 1)
+ else:
+ if batch_type == 'static':
+ return static_batch(data, batch_size)
+ elif batch_type == 'dynamic':
+ return dynamic_batch(data, max_frames_in_batch)
+ else:
+ logging.fatal('Unsupported batch type {}'.format(batch_type))
+
+
+def padding(data, use_spk_embedding, mode='train'):
+ """ Padding the data into training data
+
+ Args:
+ data: Iterable[List[{key, feat, label}]]
+
+ Returns:
+ Iterable[Tuple(keys, feats, labels, feats lengths, label lengths)]
+ """
+ for sample in data:
+ assert isinstance(sample, list)
+ speech_feat_len = torch.tensor([x['speech_feat'].size(1) for x in sample],
+ dtype=torch.int32)
+ order = torch.argsort(speech_feat_len, descending=True)
+
+ utts = [sample[i]['utt'] for i in order]
+ speech_token = [torch.tensor(sample[i]['speech_token']) for i in order]
+ speech_token_len = torch.tensor([i.size(0) for i in speech_token], dtype=torch.int32)
+ speech_token = pad_sequence(speech_token,
+ batch_first=True,
+ padding_value=0)
+ speech_feat = [sample[i]['speech_feat'] for i in order]
+ speech_feat_len = torch.tensor([i.size(0) for i in speech_feat], dtype=torch.int32)
+ speech_feat = pad_sequence(speech_feat,
+ batch_first=True,
+ padding_value=0)
+ text = [sample[i]['text'] for i in order]
+ text_token = [torch.tensor(sample[i]['text_token']) for i in order]
+ text_token_len = torch.tensor([i.size(0) for i in text_token], dtype=torch.int32)
+ text_token = pad_sequence(text_token, batch_first=True, padding_value=0)
+ utt_embedding = torch.stack([sample[i]['utt_embedding'] for i in order], dim=0)
+ spk_embedding = torch.stack([sample[i]['spk_embedding'] for i in order], dim=0)
+ batch = {
+ "utts": utts,
+ "speech_token": speech_token,
+ "speech_token_len": speech_token_len,
+ "speech_feat": speech_feat,
+ "speech_feat_len": speech_feat_len,
+ "text": text,
+ "text_token": text_token,
+ "text_token_len": text_token_len,
+ "utt_embedding": utt_embedding,
+ "spk_embedding": spk_embedding,
+ }
+ if mode == 'inference':
+ tts_text = [sample[i]['tts_text'] for i in order]
+ tts_index = [sample[i]['tts_index'] for i in order]
+ tts_text_token = [torch.tensor(sample[i]['tts_text_token']) for i in order]
+ tts_text_token_len = torch.tensor([i.size(0) for i in tts_text_token], dtype=torch.int32)
+ tts_text_token = pad_sequence(tts_text_token, batch_first=True, padding_value=-1)
+ batch.update({'tts_text': tts_text,
+ 'tts_index': tts_index,
+ 'tts_text_token': tts_text_token,
+ 'tts_text_token_len': tts_text_token_len})
+ if use_spk_embedding is True:
+ batch["embedding"] = batch["spk_embedding"]
+ else:
+ batch["embedding"] = batch["utt_embedding"]
+ yield batch
+
+
+
+def padding_speech_token(data, use_spk_embedding, mode='train'):
+ """ Padding the data into training data
+
+ Args:
+ data: Iterable[List[{key, feat, label}]]
+
+ Returns:
+ Iterable[Tuple(keys, feats, labels, feats lengths, label lengths)]
+ """
+ for sample in data:
+ assert isinstance(sample, list)
+ speech_feat_len = torch.tensor([x['speech_feat'].size(1) for x in sample],
+ dtype=torch.int32)
+ order = torch.argsort(speech_feat_len, descending=True)
+
+ # utts = [sample[i]['utt'] for i in order]
+ # speech_token = [torch.tensor(sample[i]['speech_token']) for i in order]
+ try:
+ speech_token = [sample[i]['speech_token'].clone().detach() for i in order]
+ speech_token_len = torch.tensor([i.size(0) for i in speech_token], dtype=torch.int32)
+ speech_token = pad_sequence(speech_token,
+ batch_first=True,
+ padding_value=0)
+ speech_feat = [sample[i]['speech_feat'] for i in order]
+ speech_feat_len = torch.tensor([i.size(0) for i in speech_feat], dtype=torch.int32)
+ speech_feat = pad_sequence(speech_feat,
+ batch_first=True,
+ padding_value=0)
+ batch = {
+ "speech_token": speech_token,
+ "speech_token_len": speech_token_len,
+ "speech_feat": speech_feat,
+ "speech_feat_len": speech_feat_len,
+ }
+ if mode == 'inference':
+ tts_text = [sample[i]['tts_text'] for i in order]
+ tts_index = [sample[i]['tts_index'] for i in order]
+ tts_text_token = [torch.tensor(sample[i]['tts_text_token']) for i in order]
+ tts_text_token_len = torch.tensor([i.size(0) for i in tts_text_token], dtype=torch.int32)
+ tts_text_token = pad_sequence(tts_text_token, batch_first=True, padding_value=-1)
+ batch.update({'tts_text': tts_text,
+ 'tts_index': tts_index,
+ 'tts_text_token': tts_text_token,
+ 'tts_text_token_len': tts_text_token_len})
+ # if use_spk_embedding is True:
+ # batch["embedding"] = batch["spk_embedding"]
+ # else:
+ # batch["embedding"] = batch["utt_embedding"]
+ batch["embedding"]=torch.zeros((batch["speech_feat"].size(0),192),device=batch["speech_feat"].device)
+ yield batch
+ except Exception as ex:
+ logging.warning(' ex info {}'.format(ex))
+ # assert False
+
+
+
+def padding_speech_token_spk(data, use_spk_embedding, mode='train'):
+ """ Padding the data into training data
+
+ Args:
+ data: Iterable[List[{key, feat, label}]]
+
+ Returns:
+ Iterable[Tuple(keys, feats, labels, feats lengths, label lengths)]
+ """
+ for sample in data:
+ assert isinstance(sample, list)
+ speech_feat_len = torch.tensor([x['speech_feat'].size(1) for x in sample],
+ dtype=torch.int32)
+ order = torch.argsort(speech_feat_len, descending=True)
+
+ # utts = [sample[i]['utt'] for i in order]
+ # speech_token = [torch.tensor(sample[i]['speech_token']) for i in order]
+ try:
+ speech_token = [sample[i]['speech_token'].clone().detach() for i in order]
+ speech_token_len = torch.tensor([i.size(0) for i in speech_token], dtype=torch.int32)
+ speech_token = pad_sequence(speech_token,
+ batch_first=True,
+ padding_value=0)
+ speech_feat = [sample[i]['speech_feat'] for i in order]
+ speech_feat_len = torch.tensor([i.size(0) for i in speech_feat], dtype=torch.int32)
+ speech_feat = pad_sequence(speech_feat,
+ batch_first=True,
+ padding_value=0)
+ spk_embedding = torch.stack([sample[i]['spk_embedding'] for i in order], dim=0)
+ batch = {
+ "speech_token": speech_token,
+ "speech_token_len": speech_token_len,
+ "speech_feat": speech_feat,
+ "speech_feat_len": speech_feat_len,
+ "spk_embedding": spk_embedding,
+ }
+ if mode == 'inference':
+ tts_text = [sample[i]['tts_text'] for i in order]
+ tts_index = [sample[i]['tts_index'] for i in order]
+ tts_text_token = [torch.tensor(sample[i]['tts_text_token']) for i in order]
+ tts_text_token_len = torch.tensor([i.size(0) for i in tts_text_token], dtype=torch.int32)
+ tts_text_token = pad_sequence(tts_text_token, batch_first=True, padding_value=-1)
+ batch.update({'tts_text': tts_text,
+ 'tts_index': tts_index,
+ 'tts_text_token': tts_text_token,
+ 'tts_text_token_len': tts_text_token_len})
+ # if use_spk_embedding is True:
+ # batch["embedding"] = batch["spk_embedding"]
+ # else:
+ # batch["embedding"] = batch["utt_embedding"]
+ # batch["embedding"]=torch.zeros((batch["speech_feat"].size(0),192),device=batch["speech_feat"].device)
+ batch["embedding"] = batch["spk_embedding"]
+ yield batch
+ except Exception as ex:
+ logging.warning(' ex info {}'.format(ex))
+ # assert False
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/decoder.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/decoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..43492799390b44a2843bc53604603842754799f9
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/decoder.py
@@ -0,0 +1,222 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import torch
+import torch.nn as nn
+from einops import pack, rearrange, repeat
+from matcha.models.components.decoder import SinusoidalPosEmb, Block1D, ResnetBlock1D, Downsample1D, TimestepEmbedding, Upsample1D
+from matcha.models.components.transformer import BasicTransformerBlock
+
+
+class ConditionalDecoder(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ out_channels,
+ channels=(256, 256),
+ dropout=0.05,
+ attention_head_dim=64,
+ n_blocks=1,
+ num_mid_blocks=2,
+ num_heads=4,
+ act_fn="snake",
+ ):
+ """
+ This decoder requires an input with the same shape of the target. So, if your text content
+ is shorter or longer than the outputs, please re-sampling it before feeding to the decoder.
+ """
+ super().__init__()
+ channels = tuple(channels)
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+
+ self.time_embeddings = SinusoidalPosEmb(in_channels)
+ time_embed_dim = channels[0] * 4
+ self.time_mlp = TimestepEmbedding(
+ in_channels=in_channels,
+ time_embed_dim=time_embed_dim,
+ act_fn="silu",
+ )
+ self.down_blocks = nn.ModuleList([])
+ self.mid_blocks = nn.ModuleList([])
+ self.up_blocks = nn.ModuleList([])
+
+ output_channel = in_channels
+ for i in range(len(channels)): # pylint: disable=consider-using-enumerate
+ input_channel = output_channel
+ output_channel = channels[i]
+ is_last = i == len(channels) - 1
+ resnet = ResnetBlock1D(dim=input_channel, dim_out=output_channel, time_emb_dim=time_embed_dim)
+ transformer_blocks = nn.ModuleList(
+ [
+ BasicTransformerBlock(
+ dim=output_channel,
+ num_attention_heads=num_heads,
+ attention_head_dim=attention_head_dim,
+ dropout=dropout,
+ activation_fn=act_fn,
+ )
+ for _ in range(n_blocks)
+ ]
+ )
+ downsample = (
+ Downsample1D(output_channel) if not is_last else nn.Conv1d(output_channel, output_channel, 3, padding=1)
+ )
+ self.down_blocks.append(nn.ModuleList([resnet, transformer_blocks, downsample]))
+
+ for i in range(num_mid_blocks):
+ input_channel = channels[-1]
+ out_channels = channels[-1]
+ resnet = ResnetBlock1D(dim=input_channel, dim_out=output_channel, time_emb_dim=time_embed_dim)
+
+ transformer_blocks = nn.ModuleList(
+ [
+ BasicTransformerBlock(
+ dim=output_channel,
+ num_attention_heads=num_heads,
+ attention_head_dim=attention_head_dim,
+ dropout=dropout,
+ activation_fn=act_fn,
+ )
+ for _ in range(n_blocks)
+ ]
+ )
+
+ self.mid_blocks.append(nn.ModuleList([resnet, transformer_blocks]))
+
+ channels = channels[::-1] + (channels[0],)
+ for i in range(len(channels) - 1):
+ input_channel = channels[i] * 2
+ output_channel = channels[i + 1]
+ is_last = i == len(channels) - 2
+ resnet = ResnetBlock1D(
+ dim=input_channel,
+ dim_out=output_channel,
+ time_emb_dim=time_embed_dim,
+ )
+ transformer_blocks = nn.ModuleList(
+ [
+ BasicTransformerBlock(
+ dim=output_channel,
+ num_attention_heads=num_heads,
+ attention_head_dim=attention_head_dim,
+ dropout=dropout,
+ activation_fn=act_fn,
+ )
+ for _ in range(n_blocks)
+ ]
+ )
+ upsample = (
+ Upsample1D(output_channel, use_conv_transpose=True)
+ if not is_last
+ else nn.Conv1d(output_channel, output_channel, 3, padding=1)
+ )
+ self.up_blocks.append(nn.ModuleList([resnet, transformer_blocks, upsample]))
+ self.final_block = Block1D(channels[-1], channels[-1])
+ self.final_proj = nn.Conv1d(channels[-1], self.out_channels, 1)
+ self.initialize_weights()
+
+
+ def initialize_weights(self):
+ for m in self.modules():
+ if isinstance(m, nn.Conv1d):
+ nn.init.kaiming_normal_(m.weight, nonlinearity="relu")
+ if m.bias is not None:
+ nn.init.constant_(m.bias, 0)
+ elif isinstance(m, nn.GroupNorm):
+ nn.init.constant_(m.weight, 1)
+ nn.init.constant_(m.bias, 0)
+ elif isinstance(m, nn.Linear):
+ nn.init.kaiming_normal_(m.weight, nonlinearity="relu")
+ if m.bias is not None:
+ nn.init.constant_(m.bias, 0)
+
+ def forward(self, x, mask, mu, t, spks=None, cond=None):
+ """Forward pass of the UNet1DConditional model.
+
+ Args:
+ x (torch.Tensor): shape (batch_size, in_channels, time)
+ mask (_type_): shape (batch_size, 1, time)
+ t (_type_): shape (batch_size)
+ spks (_type_, optional): shape: (batch_size, condition_channels). Defaults to None.
+ cond (_type_, optional): placeholder for future use. Defaults to None.
+
+ Raises:
+ ValueError: _description_
+ ValueError: _description_
+
+ Returns:
+ _type_: _description_
+ """
+
+ t = self.time_embeddings(t)
+ t = self.time_mlp(t)
+
+ x = pack([x, mu], "b * t")[0]
+
+ if spks is not None:
+ spks = repeat(spks, "b c -> b c t", t=x.shape[-1])
+ x = pack([x, spks], "b * t")[0]
+ if cond is not None:
+ x = pack([x, cond], "b * t")[0]
+
+ hiddens = []
+ masks = [mask]
+ for resnet, transformer_blocks, downsample in self.down_blocks:
+ mask_down = masks[-1]
+ x = resnet(x, mask_down, t)
+ x = rearrange(x, "b c t -> b t c").contiguous()
+ attn_mask = torch.matmul(mask_down.transpose(1, 2).contiguous(), mask_down)
+ for transformer_block in transformer_blocks:
+ x = transformer_block(
+ hidden_states=x,
+ attention_mask=attn_mask,
+ timestep=t,
+ )
+ x = rearrange(x, "b t c -> b c t").contiguous()
+ hiddens.append(x) # Save hidden states for skip connections
+ x = downsample(x * mask_down)
+ masks.append(mask_down[:, :, ::2])
+ masks = masks[:-1]
+ mask_mid = masks[-1]
+
+ for resnet, transformer_blocks in self.mid_blocks:
+ x = resnet(x, mask_mid, t)
+ x = rearrange(x, "b c t -> b t c").contiguous()
+ attn_mask = torch.matmul(mask_mid.transpose(1, 2).contiguous(), mask_mid)
+ for transformer_block in transformer_blocks:
+ x = transformer_block(
+ hidden_states=x,
+ attention_mask=attn_mask,
+ timestep=t,
+ )
+ x = rearrange(x, "b t c -> b c t").contiguous()
+
+ for resnet, transformer_blocks, upsample in self.up_blocks:
+ mask_up = masks.pop()
+ skip = hiddens.pop()
+ x = pack([x[:, :, :skip.shape[-1]], skip], "b * t")[0]
+ x = resnet(x, mask_up, t)
+ x = rearrange(x, "b c t -> b t c").contiguous()
+ attn_mask = torch.matmul(mask_up.transpose(1, 2).contiguous(), mask_up)
+ for transformer_block in transformer_blocks:
+ x = transformer_block(
+ hidden_states=x,
+ attention_mask=attn_mask,
+ timestep=t,
+ )
+ x = rearrange(x, "b t c -> b c t").contiguous()
+ x = upsample(x * mask_up)
+ x = self.final_block(x, mask_up)
+ output = self.final_proj(x * mask_up)
+ return output * mask
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow.py
new file mode 100644
index 0000000000000000000000000000000000000000..415b2a98872c29f82a9a49b89fba7996c10c042d
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow.py
@@ -0,0 +1,144 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import logging
+import random
+from typing import Dict, Optional
+import torch
+import torch.nn as nn
+from torch.nn import functional as F
+from omegaconf import DictConfig
+from cosyvoice.utils.mask import make_pad_mask
+
+
+class MaskedDiffWithXvec(torch.nn.Module):
+ def __init__(self,
+ input_size: int = 512,
+ output_size: int = 80,
+ spk_embed_dim: int = 192,
+ output_type: str = "mel",
+ vocab_size: int = 4096,
+ input_frame_rate: int = 50,
+ only_mask_loss: bool = True,
+ encoder: torch.nn.Module = None,
+ length_regulator: torch.nn.Module = None,
+ decoder: torch.nn.Module = None,
+ decoder_conf: Dict = {'in_channels': 240, 'out_channel': 80, 'spk_emb_dim': 80, 'n_spks': 1, 'cfm_params': DictConfig({'sigma_min': 1e-06, 'solver': 'euler', 't_scheduler': 'cosine', 'training_cfg_rate': 0.2, 'inference_cfg_rate': 0.7, 'reg_loss_type': 'l1'}), 'decoder_params': {'channels': [256, 256], 'dropout': 0.0, 'attention_head_dim': 64, 'n_blocks': 4, 'num_mid_blocks': 12, 'num_heads': 8, 'act_fn': 'gelu'}},
+ mel_feat_conf: Dict = {'n_fft': 1024, 'num_mels': 80, 'sampling_rate': 22050, 'hop_size': 256, 'win_size': 1024, 'fmin': 0, 'fmax': 8000}):
+ super().__init__()
+ self.input_size = input_size
+ self.output_size = output_size
+ self.decoder_conf = decoder_conf
+ self.mel_feat_conf = mel_feat_conf
+ self.vocab_size = vocab_size
+ self.output_type = output_type
+ self.input_frame_rate = input_frame_rate
+ logging.info(f"input frame rate={self.input_frame_rate}")
+ self.input_embedding = nn.Embedding(vocab_size, input_size)
+ self.spk_embed_affine_layer = torch.nn.Linear(spk_embed_dim, output_size)
+ self.encoder = encoder
+ self.encoder_proj = torch.nn.Linear(self.encoder.output_size(), output_size)
+ self.decoder = decoder
+ self.length_regulator = length_regulator
+ self.only_mask_loss = only_mask_loss
+
+ def forward(
+ self,
+ batch: dict,
+ device: torch.device,
+ ) -> Dict[str, Optional[torch.Tensor]]:
+ token = batch['speech_token'].to(device)
+ token_len = batch['speech_token_len'].to(device)
+ feat = batch['speech_feat'].to(device)
+ feat_len = batch['speech_feat_len'].to(device)
+ embedding = batch['embedding'].to(device)
+
+ # xvec projection
+ embedding = F.normalize(embedding, dim=1)
+ embedding = self.spk_embed_affine_layer(embedding)
+ # embedding=None
+
+ # concat text and prompt_text
+ mask = (~make_pad_mask(token_len)).float().unsqueeze(-1).to(device)
+ # print(token.max(),self.input_embedding)
+ token = self.input_embedding(torch.clamp(token, min=0)) * mask
+
+
+ # text encode
+ h, h_lengths = self.encoder(token, token_len)
+ h = self.encoder_proj(h)
+ h, h_lengths = self.length_regulator(h, feat_len)
+
+ # get conditions
+ conds = torch.zeros(feat.shape, device=token.device)
+ for i, j in enumerate(feat_len):
+ if random.random() < 0.5:
+ continue
+ index = random.randint(0, int(0.8 * j))
+ conds[i, :index] = feat[i, :index]
+ conds = conds.transpose(1, 2)
+
+ mask = (~make_pad_mask(feat_len)).to(h)
+ feat = F.interpolate(feat.unsqueeze(dim=1), size=h.shape[1:], mode="nearest").squeeze(dim=1)
+ loss, _ = self.decoder.compute_loss(
+ feat.transpose(1, 2).contiguous(),
+ mask.unsqueeze(1),
+ h.transpose(1, 2).contiguous(),
+ embedding,
+ cond=conds
+ )
+ return {'loss': loss}
+
+ @torch.inference_mode()
+ def inference(self,
+ token,
+ token_len,
+ prompt_token,
+ prompt_token_len,
+ prompt_feat,
+ prompt_feat_len,
+ embedding):
+ assert token.shape[0] == 1
+ # xvec projection
+ embedding = F.normalize(embedding, dim=1)
+ embedding = self.spk_embed_affine_layer(embedding)
+
+ # concat text and prompt_text
+ token, token_len = torch.concat([prompt_token, token], dim=1), prompt_token_len + token_len
+ mask = (~make_pad_mask(token_len)).float().unsqueeze(-1).to(embedding)
+ token = self.input_embedding(torch.clamp(token, min=0)) * mask
+
+ # text encode
+ h, h_lengths = self.encoder(token, token_len)
+ h = self.encoder_proj(h)
+ feat_len = (token_len / self.input_frame_rate * 22050 / 256).int()
+ h, h_lengths = self.length_regulator(h, feat_len)
+
+ # get conditions
+ conds = torch.zeros([1, feat_len.max().item(), self.output_size], device=token.device)
+ if prompt_feat.shape[1] != 0:
+ for i, j in enumerate(prompt_feat_len):
+ conds[i, :j] = prompt_feat[i]
+ conds = conds.transpose(1, 2)
+
+ mask = (~make_pad_mask(feat_len)).to(h)
+ feat = self.decoder(
+ mu=h.transpose(1, 2).contiguous(),
+ mask=mask.unsqueeze(1),
+ spks=embedding,
+ cond=conds,
+ n_timesteps=10
+ )
+ if prompt_feat.shape[1] != 0:
+ feat = feat[:, :, prompt_feat.shape[1]:]
+ return feat
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_gradtts.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_gradtts.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e558c0ff65a0c6befd1c5aa49c20464307e82b1
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_gradtts.py
@@ -0,0 +1,142 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import logging
+import random
+from typing import Dict, Optional
+import torch
+import torch.nn as nn
+from torch.nn import functional as F
+from omegaconf import DictConfig
+from cosyvoice.utils.mask import make_pad_mask
+
+
+class MaskedDiffWithXvec(torch.nn.Module):
+ def __init__(self,
+ input_size: int = 512,
+ output_size: int = 80,
+ spk_embed_dim: int = 192,
+ output_type: str = "mel",
+ vocab_size: int = 4096,
+ input_frame_rate: int = 50,
+ only_mask_loss: bool = True,
+ encoder: torch.nn.Module = None,
+ length_regulator: torch.nn.Module = None,
+ decoder: torch.nn.Module = None,
+ decoder_conf: Dict = {'in_channels': 240, 'out_channel': 80, 'spk_emb_dim': 80, 'n_spks': 1, 'cfm_params': DictConfig({'sigma_min': 1e-06, 'solver': 'euler', 't_scheduler': 'cosine', 'training_cfg_rate': 0.2, 'inference_cfg_rate': 0.7, 'reg_loss_type': 'l1'}), 'decoder_params': {'channels': [256, 256], 'dropout': 0.0, 'attention_head_dim': 64, 'n_blocks': 4, 'num_mid_blocks': 12, 'num_heads': 8, 'act_fn': 'gelu'}},
+ mel_feat_conf: Dict = {'n_fft': 1024, 'num_mels': 80, 'sampling_rate': 22050, 'hop_size': 256, 'win_size': 1024, 'fmin': 0, 'fmax': 8000}):
+ super().__init__()
+ self.input_size = input_size
+ self.output_size = output_size
+ self.decoder_conf = decoder_conf
+ self.mel_feat_conf = mel_feat_conf
+ self.vocab_size = vocab_size
+ self.output_type = output_type
+ self.input_frame_rate = input_frame_rate
+ logging.info(f"input frame rate={self.input_frame_rate}")
+ self.input_embedding = nn.Embedding(vocab_size, input_size)
+ self.spk_embed_affine_layer = torch.nn.Linear(spk_embed_dim, output_size)
+ self.encoder = encoder
+ self.encoder_proj = torch.nn.Linear(self.encoder.output_size(), output_size)
+ self.decoder = decoder
+ self.length_regulator = length_regulator
+ self.only_mask_loss = only_mask_loss
+
+ def forward(
+ self,
+ batch: dict,
+ device: torch.device,
+ ) -> Dict[str, Optional[torch.Tensor]]:
+ token = batch['speech_token'].to(device)
+ token_len = batch['speech_token_len'].to(device)
+ feat = batch['speech_feat'].to(device)
+ feat_len = batch['speech_feat_len'].to(device)
+ embedding = batch['embedding'].to(device)
+
+ # xvec projection
+ embedding = F.normalize(embedding, dim=1)
+ embedding = self.spk_embed_affine_layer(embedding)
+ # embedding=None
+
+ # concat text and prompt_text
+ mask = (~make_pad_mask(token_len)).float().unsqueeze(-1).to(device)
+ token = self.input_embedding(torch.clamp(token, min=0)) * mask
+
+ # text encode
+ h, h_lengths = self.encoder(token, token_len)
+ h = self.encoder_proj(h)
+ h, h_lengths = self.length_regulator(h, feat_len)
+
+ # get conditions
+ conds = torch.zeros(feat.shape, device=token.device)
+ # for i, j in enumerate(feat_len):
+ # if random.random() < 0.5:
+ # continue
+ # index = random.randint(0, int(0.3 * j))
+ # conds[i, :index] = feat[i, :index]
+ conds = conds.transpose(1, 2)
+
+ mask = (~make_pad_mask(feat_len)).to(h)
+ feat = F.interpolate(feat.unsqueeze(dim=1), size=h.shape[1:], mode="nearest").squeeze(dim=1)
+ loss, _ = self.decoder.compute_loss(
+ feat.transpose(1, 2).contiguous(),
+ mask.unsqueeze(1),
+ h.transpose(1, 2).contiguous(),
+ embedding,
+ cond=conds
+ )
+ return {'loss': loss}
+
+ @torch.inference_mode()
+ def inference(self,
+ token,
+ token_len,
+ prompt_token,
+ prompt_token_len,
+ prompt_feat,
+ prompt_feat_len,
+ embedding):
+ assert token.shape[0] == 1
+ # xvec projection
+ embedding = F.normalize(embedding, dim=1)
+ embedding = self.spk_embed_affine_layer(embedding)
+
+ # concat text and prompt_text
+ token, token_len = torch.concat([prompt_token, token], dim=1), prompt_token_len + token_len
+ mask = (~make_pad_mask(token_len)).float().unsqueeze(-1).to(embedding)
+ token = self.input_embedding(torch.clamp(token, min=0)) * mask
+
+ # text encode
+ h, h_lengths = self.encoder(token, token_len)
+ h = self.encoder_proj(h)
+ feat_len = (token_len / self.input_frame_rate * 22050 / 256).int()
+ h, h_lengths = self.length_regulator(h, feat_len)
+
+ # get conditions
+ conds = torch.zeros([1, feat_len.max().item(), self.output_size], device=token.device)
+ if prompt_feat.shape[1] != 0:
+ for i, j in enumerate(prompt_feat_len):
+ conds[i, :j] = prompt_feat[i]
+ conds = conds.transpose(1, 2)
+
+ mask = (~make_pad_mask(feat_len)).to(h)
+ feat = self.decoder(
+ mu=h.transpose(1, 2).contiguous(),
+ mask=mask.unsqueeze(1),
+ spks=embedding,
+ cond=conds,
+ n_timesteps=10
+ )
+ if prompt_feat.shape[1] != 0:
+ feat = feat[:, :, prompt_feat.shape[1]:]
+ return feat
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_matching.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_matching.py
new file mode 100644
index 0000000000000000000000000000000000000000..ec487d7d8effbf9c7284624b839184e43df40b9c
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_matching.py
@@ -0,0 +1,142 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import torch
+import torch.nn.functional as F
+from matcha.models.components.flow_matching import BASECFM
+
+class ConditionalCFM(BASECFM):
+ def __init__(self, in_channels, cfm_params, n_spks=1, spk_emb_dim=64, estimator: torch.nn.Module = None):
+ super().__init__(
+ n_feats=in_channels,
+ cfm_params=cfm_params,
+ n_spks=n_spks,
+ spk_emb_dim=spk_emb_dim,
+ )
+ self.t_scheduler = cfm_params.t_scheduler
+ self.training_cfg_rate = cfm_params.training_cfg_rate
+ self.inference_cfg_rate = cfm_params.inference_cfg_rate
+ in_channels = in_channels + (spk_emb_dim if n_spks > 0 else 0)
+ # Just change the architecture of the estimator here
+ self.estimator = estimator
+
+ @torch.inference_mode()
+ def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, cond=None):
+ """Forward diffusion
+
+ Args:
+ mu (torch.Tensor): output of encoder
+ shape: (batch_size, n_feats, mel_timesteps)
+ mask (torch.Tensor): output_mask
+ shape: (batch_size, 1, mel_timesteps)
+ n_timesteps (int): number of diffusion steps
+ temperature (float, optional): temperature for scaling noise. Defaults to 1.0.
+ spks (torch.Tensor, optional): speaker ids. Defaults to None.
+ shape: (batch_size, spk_emb_dim)
+ cond: Not used but kept for future purposes
+
+ Returns:
+ sample: generated mel-spectrogram
+ shape: (batch_size, n_feats, mel_timesteps)
+ """
+ torch.manual_seed(42)
+
+ z = torch.randn_like(mu) * temperature
+
+ t_span = torch.linspace(0, 1, n_timesteps + 1, device=mu.device)
+ if self.t_scheduler == 'cosine':
+ t_span = 1 - torch.cos(t_span * 0.5 * torch.pi)
+ return self.solve_euler(z, t_span=t_span, mu=mu, mask=mask, spks=spks, cond=cond)
+
+ def solve_euler(self, x, t_span, mu, mask, spks, cond):
+ """
+ Fixed euler solver for ODEs.
+ Args:
+ x (torch.Tensor): random noise
+ t_span (torch.Tensor): n_timesteps interpolated
+ shape: (n_timesteps + 1,)
+ mu (torch.Tensor): output of encoder
+ shape: (batch_size, n_feats, mel_timesteps)
+ mask (torch.Tensor): output_mask
+ shape: (batch_size, 1, mel_timesteps)
+ spks (torch.Tensor, optional): speaker ids. Defaults to None.
+ shape: (batch_size, spk_emb_dim)
+ cond: Not used but kept for future purposes
+ """
+ t, _, dt = t_span[0], t_span[-1], t_span[1] - t_span[0]
+
+ # I am storing this because I can later plot it by putting a debugger here and saving it to a file
+ # Or in future might add like a return_all_steps flag
+ sol = []
+
+ for step in range(1, len(t_span)):
+ dphi_dt = self.estimator(x, mask, mu, t, spks, cond)
+ # Classifier-Free Guidance inference introduced in VoiceBox
+ if self.inference_cfg_rate > 0:
+ cfg_dphi_dt = self.estimator(
+ x, mask,
+ torch.zeros_like(mu), t,
+ torch.zeros_like(spks) if spks is not None else None,
+ torch.zeros_like(cond)
+ )
+ dphi_dt = ((1.0 + self.inference_cfg_rate) * dphi_dt -
+ self.inference_cfg_rate * cfg_dphi_dt)
+ x = x + dt * dphi_dt
+ t = t + dt
+
+ sol.append(x)
+ if step < len(t_span) - 1:
+ dt = t_span[step + 1] - t
+
+ return sol[-1]
+
+ def compute_loss(self, x1, mask, mu, spks=None, cond=None):
+ """Computes diffusion loss
+
+ Args:
+ x1 (torch.Tensor): Target
+ shape: (batch_size, n_feats, mel_timesteps)
+ mask (torch.Tensor): target mask
+ shape: (batch_size, 1, mel_timesteps)
+ mu (torch.Tensor): output of encoder
+ shape: (batch_size, n_feats, mel_timesteps)
+ spks (torch.Tensor, optional): speaker embedding. Defaults to None.
+ shape: (batch_size, spk_emb_dim)
+
+ Returns:
+ loss: conditional flow matching loss
+ y: conditional flow
+ shape: (batch_size, n_feats, mel_timesteps)
+ """
+ b, _, t = mu.shape
+
+ # random timestep
+ t = torch.rand([b, 1, 1], device=mu.device, dtype=mu.dtype)
+ if self.t_scheduler == 'cosine':
+ t = 1 - torch.cos(t * 0.5 * torch.pi)
+ # sample noise p(x_0)
+ z = torch.randn_like(x1)
+
+ y = (1 - (1 - self.sigma_min) * t) * z + t * x1
+ u = x1 - (1 - self.sigma_min) * z
+
+ # during training, we randomly drop condition to trade off mode coverage and sample fidelity
+ if self.training_cfg_rate > 0:
+ cfg_mask = torch.rand(b, device=x1.device) > self.training_cfg_rate
+ mu = mu * cfg_mask.view(-1, 1, 1)
+ spks = spks * cfg_mask.view(-1, 1)
+ cond = cond * cfg_mask.view(-1, 1, 1)
+
+ pred = self.estimator(y, mask, mu, t.squeeze(), spks, cond)
+ loss = F.mse_loss(pred * mask, u * mask, reduction="sum") / (torch.sum(mask) * u.shape[1])
+ return loss, y
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_matching_dit.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_matching_dit.py
new file mode 100644
index 0000000000000000000000000000000000000000..abadcc218cc3b30bd5c8da829079974b60f09b47
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/flow_matching_dit.py
@@ -0,0 +1,180 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pdb
+
+import torch
+import torch.nn.functional as F
+from matcha.models.components.flow_matching import BASECFM
+
+
+class ConditionalCFM(BASECFM):
+ def __init__(self, in_channels, cfm_params, n_spks=1, spk_emb_dim=64, estimator: torch.nn.Module = None):
+ super().__init__(
+ n_feats=in_channels,
+ cfm_params=cfm_params,
+ n_spks=n_spks,
+ spk_emb_dim=spk_emb_dim,
+ )
+ self.t_scheduler = cfm_params.t_scheduler
+ self.training_cfg_rate = cfm_params.training_cfg_rate
+ self.inference_cfg_rate = cfm_params.inference_cfg_rate
+ in_channels = in_channels + (spk_emb_dim if n_spks > 0 else 0)
+ # Just change the architecture of the estimator here
+
+ io_channels = 80
+ input_concat_dim = 80
+ embed_dim = 768
+ depth = 24
+ num_heads = 24
+ project_cond_tokens = False
+ transformer_type = "continuous_transformer"
+ self.estimator = estimator
+
+ @torch.inference_mode()
+ def forward(self, mu, mask, n_timesteps, temperature=1.0, spks=None, cond=None):
+ """Forward diffusion
+
+ Args:
+ mu (torch.Tensor): output of encoder
+ shape: (batch_size, n_feats, mel_timesteps)
+ mask (torch.Tensor): output_mask
+ shape: (batch_size, 1, mel_timesteps)
+ n_timesteps (int): number of diffusion steps
+ temperature (float, optional): temperature for scaling noise. Defaults to 1.0.
+ spks (torch.Tensor, optional): speaker ids. Defaults to None.
+ shape: (batch_size, spk_emb_dim)
+ cond: Not used but kept for future purposes
+
+ Returns:
+ sample: generated mel-spectrogram
+ shape: (batch_size, n_feats, mel_timesteps)
+ """
+ z = torch.randn_like(mu) * temperature
+ t_span = torch.linspace(0, 1, n_timesteps + 1, device=mu.device)
+ if self.t_scheduler == 'cosine':
+ t_span = 1 - torch.cos(t_span * 0.5 * torch.pi)
+ return self.solve_euler(z, t_span=t_span, mu=mu, mask=mask, spks=spks, cond=cond)
+
+ def solve_euler(self, x, t_span, mu, mask, spks, cond):
+ """
+ Fixed euler solver for ODEs.
+ Args:
+ x (torch.Tensor): random noise torch.Size([1, 80, 621])
+ t_span (torch.Tensor): n_timesteps interpolated
+ shape: (n_timesteps + 1,)
+ mu (torch.Tensor): output of encoder
+ shape: (batch_size, n_feats, mel_timesteps)
+ mask (torch.Tensor): output_mask
+ shape: (batch_size, 1, mel_timesteps)
+ spks (torch.Tensor, optional): speaker ids. Defaults to None.
+ shape: (batch_size, spk_emb_dim)
+ cond: Not used but kept for future purposes
+ """
+ t, _, dt = t_span[0], t_span[-1], t_span[1] - t_span[0]
+
+ # I am storing this because I can later plot it by putting a debugger here and saving it to a file
+ # Or in future might add like a return_all_steps flag
+ sol = []
+
+ cfg_dropout_prob = 0.1
+ cfg_scale = 1.0
+
+ # cfg_dropout_prob = 0.0
+ # cfg_scale = 3.0
+
+ for step in range(1, len(t_span)):
+ # dphi_dt = self.estimator(x, mask, mu, t, spks, cond)
+ # pdb.set_trace()
+ dphi_dt = self.estimator(x, # [bs, 80, 229]
+ t[None], # (bs,)
+ global_embed=spks,
+ input_concat_cond=mu,
+ mask=mask[0], # [bs, 229]
+ cfg_dropout_prob=cfg_dropout_prob, cfg_scale=cfg_scale)
+
+ # Classifier-Free Guidance inference introduced in VoiceBox
+ if self.inference_cfg_rate > 0:
+ # cfg_dphi_dt = self.estimator(
+ # x, mask,
+ # torch.zeros_like(mu), t,
+ # torch.zeros_like(spks) if spks is not None else None,
+ # torch.zeros_like(cond)
+ # )
+ cfg_dphi_dt = self.estimator(x, # [bs, 80, 229]
+ t[None], # (bs,)
+ global_embed=torch.zeros_like(spks) if spks is not None else None,
+ input_concat_cond=torch.zeros_like(mu),
+ mask=mask[0], # [bs, 229]
+ cfg_dropout_prob=cfg_dropout_prob, cfg_scale=cfg_scale)
+
+ dphi_dt = ((1.0 + self.inference_cfg_rate) * dphi_dt -
+ self.inference_cfg_rate * cfg_dphi_dt)
+ x = x + dt * dphi_dt
+ t = t + dt
+ sol.append(x)
+ if step < len(t_span) - 1:
+ dt = t_span[step + 1] - t
+
+ return sol[-1]
+
+ def compute_loss(self, x1, mask, mu, spks=None, cond=None):
+ """Computes diffusion loss
+
+ Args:
+ x1 (torch.Tensor): Target
+ shape: (batch_size, n_feats, mel_timesteps)
+ mask (torch.Tensor): target mask
+ shape: (batch_size, 1, mel_timesteps)
+ mu (torch.Tensor): output of encoder
+ shape: (batch_size, n_feats, mel_timesteps)
+ spks (torch.Tensor, optional): speaker embedding. Defaults to None.
+ shape: (batch_size, spk_emb_dim)
+
+ Returns:
+ loss: conditional flow matching loss
+ y: conditional flow
+ shape: (batch_size, n_feats, mel_timesteps)
+ """
+ b, _, t = mu.shape
+
+ # random timestep
+ t = torch.rand([b, 1, 1], device=mu.device, dtype=mu.dtype)
+ if self.t_scheduler == 'cosine':
+ t = 1 - torch.cos(t * 0.5 * torch.pi)
+ # sample noise p(x_0)
+ z = torch.randn_like(x1)
+
+ y = (1 - (1 - self.sigma_min) * t) * z + t * x1
+ u = x1 - (1 - self.sigma_min) * z
+
+ # during training, we randomly drop condition to trade off mode coverage and sample fidelity
+ if self.training_cfg_rate > 0:
+ cfg_mask = torch.rand(b, device=x1.device) > self.training_cfg_rate
+ mu = mu * cfg_mask.view(-1, 1, 1)
+ spks = spks * cfg_mask.view(-1, 1)
+ cond = cond * cfg_mask.view(-1, 1, 1)
+
+ # pred = self.estimator(y, mask, mu, t.squeeze(), spks, cond)
+ pred = self.estimator(y, # [bs, 80, 229]
+ t.squeeze(1, 2), # (bs,)
+ global_embed=spks,
+ input_concat_cond=mu,
+ mask=mask.squeeze(1), # [bs, 229]
+ cfg_dropout_prob=0.1)
+
+ loss = F.mse_loss(pred * mask, u * mask, reduction="sum") / (torch.sum(mask) * u.shape[1])
+ return loss, y
+
+ # def estimator_trans(self):
+ # pass
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/length_regulator.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/length_regulator.py
new file mode 100644
index 0000000000000000000000000000000000000000..622f29aaccc44d8e8cce23ecab7b086ebb853fde
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/length_regulator.py
@@ -0,0 +1,49 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from typing import Tuple
+import torch.nn as nn
+from torch.nn import functional as F
+from cosyvoice.utils.mask import make_pad_mask
+
+
+class InterpolateRegulator(nn.Module):
+ def __init__(
+ self,
+ channels: int,
+ sampling_ratios: Tuple,
+ out_channels: int = None,
+ groups: int = 1,
+ ):
+ super().__init__()
+ self.sampling_ratios = sampling_ratios
+ out_channels = out_channels or channels
+ model = nn.ModuleList([])
+ if len(sampling_ratios) > 0:
+ for _ in sampling_ratios:
+ module = nn.Conv1d(channels, channels, 3, 1, 1)
+ norm = nn.GroupNorm(groups, channels)
+ act = nn.Mish()
+ model.extend([module, norm, act])
+ model.append(
+ nn.Conv1d(channels, out_channels, 1, 1)
+ )
+ self.model = nn.Sequential(*model)
+
+ def forward(self, x, ylens=None):
+ # x in (B, T, D)
+ mask = (~make_pad_mask(ylens)).to(x).unsqueeze(-1)
+ x = F.interpolate(x.transpose(1, 2).contiguous(), size=ylens.max(), mode='nearest')
+ out = self.model(x).transpose(1, 2).contiguous()
+ olens = ylens
+ return out * mask, olens
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/adp.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/adp.py
new file mode 100644
index 0000000000000000000000000000000000000000..a7ff72026df1c0bed73563d025d314dd2ccd4d19
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/adp.py
@@ -0,0 +1,1591 @@
+# Copied and modified from https://github.com/archinetai/audio-diffusion-pytorch/blob/v0.0.94/audio_diffusion_pytorch/modules.py under MIT License
+# License can be found in LICENSES/LICENSE_ADP.txt
+
+import math
+from inspect import isfunction
+from math import ceil, floor, log, pi, log2
+from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, TypeVar, Union
+from packaging import version
+
+import torch
+import torch.nn as nn
+from einops import rearrange, reduce, repeat
+from einops.layers.torch import Rearrange
+from einops_exts import rearrange_many
+from torch import Tensor, einsum
+from torch.backends.cuda import sdp_kernel
+from torch.nn import functional as F
+from dac.nn.layers import Snake1d
+import pdb
+"""
+Utils
+"""
+
+
+class ConditionedSequential(nn.Module):
+ def __init__(self, *modules):
+ super().__init__()
+ self.module_list = nn.ModuleList(*modules)
+
+ def forward(self, x: Tensor, mapping: Optional[Tensor] = None):
+ for module in self.module_list:
+ x = module(x, mapping)
+ return x
+
+T = TypeVar("T")
+
+def default(val: Optional[T], d: Union[Callable[..., T], T]) -> T:
+ if exists(val):
+ return val
+ return d() if isfunction(d) else d
+
+def exists(val: Optional[T]) -> T:
+ return val is not None
+
+def closest_power_2(x: float) -> int:
+ exponent = log2(x)
+ distance_fn = lambda z: abs(x - 2 ** z) # noqa
+ exponent_closest = min((floor(exponent), ceil(exponent)), key=distance_fn)
+ return 2 ** int(exponent_closest)
+
+def group_dict_by_prefix(prefix: str, d: Dict) -> Tuple[Dict, Dict]:
+ return_dicts: Tuple[Dict, Dict] = ({}, {})
+ for key in d.keys():
+ no_prefix = int(not key.startswith(prefix))
+ return_dicts[no_prefix][key] = d[key]
+ return return_dicts
+
+def groupby(prefix: str, d: Dict, keep_prefix: bool = False) -> Tuple[Dict, Dict]:
+ kwargs_with_prefix, kwargs = group_dict_by_prefix(prefix, d)
+ if keep_prefix:
+ return kwargs_with_prefix, kwargs
+ kwargs_no_prefix = {k[len(prefix) :]: v for k, v in kwargs_with_prefix.items()}
+ return kwargs_no_prefix, kwargs
+
+"""
+Convolutional Blocks
+"""
+import typing as tp
+
+# Copied from https://github.com/facebookresearch/audiocraft/blob/main/audiocraft/modules/conv.py under MIT License
+# License available in LICENSES/LICENSE_META.txt
+
+def get_extra_padding_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int,
+ padding_total: int = 0) -> int:
+ """See `pad_for_conv1d`."""
+ length = x.shape[-1]
+ n_frames = (length - kernel_size + padding_total) / stride + 1
+ ideal_length = (math.ceil(n_frames) - 1) * stride + (kernel_size - padding_total)
+ return ideal_length - length
+
+
+def pad_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int, padding_total: int = 0):
+ """Pad for a convolution to make sure that the last window is full.
+ Extra padding is added at the end. This is required to ensure that we can rebuild
+ an output of the same length, as otherwise, even with padding, some time steps
+ might get removed.
+ For instance, with total padding = 4, kernel size = 4, stride = 2:
+ 0 0 1 2 3 4 5 0 0 # (0s are padding)
+ 1 2 3 # (output frames of a convolution, last 0 is never used)
+ 0 0 1 2 3 4 5 0 # (output of tr. conv., but pos. 5 is going to get removed as padding)
+ 1 2 3 4 # once you removed padding, we are missing one time step !
+ """
+ extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
+ return F.pad(x, (0, extra_padding))
+
+
+def pad1d(x: torch.Tensor, paddings: tp.Tuple[int, int], mode: str = 'constant', value: float = 0.):
+ """Tiny wrapper around F.pad, just to allow for reflect padding on small input.
+ If this is the case, we insert extra 0 padding to the right before the reflection happen.
+ """
+ length = x.shape[-1]
+ padding_left, padding_right = paddings
+ assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
+ if mode == 'reflect':
+ max_pad = max(padding_left, padding_right)
+ extra_pad = 0
+ if length <= max_pad:
+ extra_pad = max_pad - length + 1
+ x = F.pad(x, (0, extra_pad))
+ padded = F.pad(x, paddings, mode, value)
+ end = padded.shape[-1] - extra_pad
+ return padded[..., :end]
+ else:
+ return F.pad(x, paddings, mode, value)
+
+
+def unpad1d(x: torch.Tensor, paddings: tp.Tuple[int, int]):
+ """Remove padding from x, handling properly zero padding. Only for 1d!"""
+ padding_left, padding_right = paddings
+ assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
+ assert (padding_left + padding_right) <= x.shape[-1]
+ end = x.shape[-1] - padding_right
+ return x[..., padding_left: end]
+
+
+class Conv1d(nn.Conv1d):
+ def __init__(self, *args, **kwargs):
+ super().__init__(*args, **kwargs)
+
+ def forward(self, x: Tensor, causal=False) -> Tensor:
+ kernel_size = self.kernel_size[0]
+ stride = self.stride[0]
+ dilation = self.dilation[0]
+ kernel_size = (kernel_size - 1) * dilation + 1 # effective kernel size with dilations
+ padding_total = kernel_size - stride
+ extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
+ if causal:
+ # Left padding for causal
+ x = pad1d(x, (padding_total, extra_padding))
+ else:
+ # Asymmetric padding required for odd strides
+ padding_right = padding_total // 2
+ padding_left = padding_total - padding_right
+ x = pad1d(x, (padding_left, padding_right + extra_padding))
+ return super().forward(x)
+
+class ConvTranspose1d(nn.ConvTranspose1d):
+ def __init__(self, *args, **kwargs):
+ super().__init__(*args, **kwargs)
+
+ def forward(self, x: Tensor, causal=False) -> Tensor:
+ kernel_size = self.kernel_size[0]
+ stride = self.stride[0]
+ padding_total = kernel_size - stride
+
+ y = super().forward(x)
+
+ # We will only trim fixed padding. Extra padding from `pad_for_conv1d` would be
+ # removed at the very end, when keeping only the right length for the output,
+ # as removing it here would require also passing the length at the matching layer
+ # in the encoder.
+ if causal:
+ padding_right = ceil(padding_total)
+ padding_left = padding_total - padding_right
+ y = unpad1d(y, (padding_left, padding_right))
+ else:
+ # Asymmetric padding required for odd strides
+ padding_right = padding_total // 2
+ padding_left = padding_total - padding_right
+ y = unpad1d(y, (padding_left, padding_right))
+ return y
+
+
+def Downsample1d(
+ in_channels: int, out_channels: int, factor: int, kernel_multiplier: int = 2
+) -> nn.Module:
+ assert kernel_multiplier % 2 == 0, "Kernel multiplier must be even"
+
+ return Conv1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=factor * kernel_multiplier + 1,
+ stride=factor
+ )
+
+
+def Upsample1d(
+ in_channels: int, out_channels: int, factor: int, use_nearest: bool = False
+) -> nn.Module:
+
+ if factor == 1:
+ return Conv1d(
+ in_channels=in_channels, out_channels=out_channels, kernel_size=3
+ )
+
+ if use_nearest:
+ return nn.Sequential(
+ nn.Upsample(scale_factor=factor, mode="nearest"),
+ Conv1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=3
+ ),
+ )
+ else:
+ return ConvTranspose1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=factor * 2,
+ stride=factor
+ )
+
+
+class ConvBlock1d(nn.Module):
+ def __init__(
+ self,
+ in_channels: int,
+ out_channels: int,
+ *,
+ kernel_size: int = 3,
+ stride: int = 1,
+ dilation: int = 1,
+ num_groups: int = 8,
+ use_norm: bool = True,
+ use_snake: bool = False
+ ) -> None:
+ super().__init__()
+
+ self.groupnorm = (
+ nn.GroupNorm(num_groups=num_groups, num_channels=in_channels)
+ if use_norm
+ else nn.Identity()
+ )
+
+ if use_snake:
+ self.activation = Snake1d(in_channels)
+ else:
+ self.activation = nn.SiLU()
+
+ self.project = Conv1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=kernel_size,
+ stride=stride,
+ dilation=dilation,
+ )
+
+ def forward(
+ self, x: Tensor, scale_shift: Optional[Tuple[Tensor, Tensor]] = None, causal=False
+ ) -> Tensor:
+ x = self.groupnorm(x)
+ if exists(scale_shift):
+ scale, shift = scale_shift
+ x = x * (scale + 1) + shift
+ x = self.activation(x)
+ return self.project(x, causal=causal)
+
+
+class MappingToScaleShift(nn.Module):
+ def __init__(
+ self,
+ features: int,
+ channels: int,
+ ):
+ super().__init__()
+
+ self.to_scale_shift = nn.Sequential(
+ nn.SiLU(),
+ nn.Linear(in_features=features, out_features=channels * 2),
+ )
+
+ def forward(self, mapping: Tensor) -> Tuple[Tensor, Tensor]:
+ scale_shift = self.to_scale_shift(mapping)
+ scale_shift = rearrange(scale_shift, "b c -> b c 1")
+ scale, shift = scale_shift.chunk(2, dim=1)
+ return scale, shift
+
+
+class ResnetBlock1d(nn.Module):
+ def __init__(
+ self,
+ in_channels: int,
+ out_channels: int,
+ *,
+ kernel_size: int = 3,
+ stride: int = 1,
+ dilation: int = 1,
+ use_norm: bool = True,
+ use_snake: bool = False,
+ num_groups: int = 8,
+ context_mapping_features: Optional[int] = None,
+ ) -> None:
+ super().__init__()
+
+ self.use_mapping = exists(context_mapping_features)
+
+ self.block1 = ConvBlock1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=kernel_size,
+ stride=stride,
+ dilation=dilation,
+ use_norm=use_norm,
+ num_groups=num_groups,
+ use_snake=use_snake
+ )
+
+ if self.use_mapping:
+ assert exists(context_mapping_features)
+ self.to_scale_shift = MappingToScaleShift(
+ features=context_mapping_features, channels=out_channels
+ )
+
+ self.block2 = ConvBlock1d(
+ in_channels=out_channels,
+ out_channels=out_channels,
+ use_norm=use_norm,
+ num_groups=num_groups,
+ use_snake=use_snake
+ )
+
+ self.to_out = (
+ Conv1d(in_channels=in_channels, out_channels=out_channels, kernel_size=1)
+ if in_channels != out_channels
+ else nn.Identity()
+ )
+
+ def forward(self, x: Tensor, mapping: Optional[Tensor] = None, causal=False) -> Tensor:
+ assert_message = "context mapping required if context_mapping_features > 0"
+ assert not (self.use_mapping ^ exists(mapping)), assert_message
+
+ h = self.block1(x, causal=causal)
+
+ scale_shift = None
+ if self.use_mapping:
+ scale_shift = self.to_scale_shift(mapping)
+
+ h = self.block2(h, scale_shift=scale_shift, causal=causal)
+
+ return h + self.to_out(x)
+
+
+class Patcher(nn.Module):
+ def __init__(
+ self,
+ in_channels: int,
+ out_channels: int,
+ patch_size: int,
+ context_mapping_features: Optional[int] = None,
+ use_snake: bool = False,
+ ):
+ super().__init__()
+ assert_message = f"out_channels must be divisible by patch_size ({patch_size})"
+ assert out_channels % patch_size == 0, assert_message
+ self.patch_size = patch_size
+
+ self.block = ResnetBlock1d(
+ in_channels=in_channels,
+ out_channels=out_channels // patch_size,
+ num_groups=1,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+
+ def forward(self, x: Tensor, mapping: Optional[Tensor] = None, causal=False) -> Tensor:
+ x = self.block(x, mapping, causal=causal)
+ x = rearrange(x, "b c (l p) -> b (c p) l", p=self.patch_size)
+ return x
+
+
+class Unpatcher(nn.Module):
+ def __init__(
+ self,
+ in_channels: int,
+ out_channels: int,
+ patch_size: int,
+ context_mapping_features: Optional[int] = None,
+ use_snake: bool = False
+ ):
+ super().__init__()
+ assert_message = f"in_channels must be divisible by patch_size ({patch_size})"
+ assert in_channels % patch_size == 0, assert_message
+ self.patch_size = patch_size
+
+ self.block = ResnetBlock1d(
+ in_channels=in_channels // patch_size,
+ out_channels=out_channels,
+ num_groups=1,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+
+ def forward(self, x: Tensor, mapping: Optional[Tensor] = None, causal=False) -> Tensor:
+ x = rearrange(x, " b (c p) l -> b c (l p) ", p=self.patch_size)
+ x = self.block(x, mapping, causal=causal)
+ return x
+
+
+"""
+Attention Components
+"""
+def FeedForward(features: int, multiplier: int) -> nn.Module:
+ mid_features = features * multiplier
+ return nn.Sequential(
+ nn.Linear(in_features=features, out_features=mid_features),
+ nn.GELU(),
+ nn.Linear(in_features=mid_features, out_features=features),
+ )
+
+def add_mask(sim: Tensor, mask: Tensor) -> Tensor:
+ b, ndim = sim.shape[0], mask.ndim
+ if ndim == 3:
+ mask = rearrange(mask, "b n m -> b 1 n m")
+ if ndim == 2:
+ mask = repeat(mask, "n m -> b 1 n m", b=b)
+ max_neg_value = -torch.finfo(sim.dtype).max
+ sim = sim.masked_fill(~mask, max_neg_value)
+ return sim
+
+def causal_mask(q: Tensor, k: Tensor) -> Tensor:
+ b, i, j, device = q.shape[0], q.shape[-2], k.shape[-2], q.device
+ mask = ~torch.ones((i, j), dtype=torch.bool, device=device).triu(j - i + 1)
+ mask = repeat(mask, "n m -> b n m", b=b)
+ return mask
+
+class AttentionBase(nn.Module):
+ def __init__(
+ self,
+ features: int,
+ *,
+ head_features: int,
+ num_heads: int,
+ out_features: Optional[int] = None,
+ ):
+ super().__init__()
+ self.scale = head_features**-0.5
+ self.num_heads = num_heads
+ mid_features = head_features * num_heads
+ out_features = default(out_features, features)
+
+ self.to_out = nn.Linear(
+ in_features=mid_features, out_features=out_features
+ )
+
+ self.use_flash = torch.cuda.is_available() and version.parse(torch.__version__) >= version.parse('2.0.0')
+
+ if not self.use_flash:
+ return
+
+ device_properties = torch.cuda.get_device_properties(torch.device('cuda'))
+
+ if device_properties.major == 8 and device_properties.minor == 0:
+ # Use flash attention for A100 GPUs
+ self.sdp_kernel_config = (True, False, False)
+ else:
+ # Don't use flash attention for other GPUs
+ self.sdp_kernel_config = (False, True, True)
+
+ def forward(
+ self, q: Tensor, k: Tensor, v: Tensor, mask: Optional[Tensor] = None, is_causal: bool = False
+ ) -> Tensor:
+ # Split heads
+ q, k, v = rearrange_many((q, k, v), "b n (h d) -> b h n d", h=self.num_heads)
+
+ if not self.use_flash:
+ if is_causal and not mask:
+ # Mask out future tokens for causal attention
+ mask = causal_mask(q, k)
+
+ # Compute similarity matrix and add eventual mask
+ sim = einsum("... n d, ... m d -> ... n m", q, k) * self.scale
+ sim = add_mask(sim, mask) if exists(mask) else sim
+
+ # Get attention matrix with softmax
+ attn = sim.softmax(dim=-1, dtype=torch.float32)
+
+ # Compute values
+ out = einsum("... n m, ... m d -> ... n d", attn, v)
+ else:
+ with sdp_kernel(*self.sdp_kernel_config):
+ out = F.scaled_dot_product_attention(q, k, v, attn_mask=mask, is_causal=is_causal)
+
+ out = rearrange(out, "b h n d -> b n (h d)")
+ return self.to_out(out)
+
+class Attention(nn.Module):
+ def __init__(
+ self,
+ features: int,
+ *,
+ head_features: int,
+ num_heads: int,
+ out_features: Optional[int] = None,
+ context_features: Optional[int] = None,
+ causal: bool = False,
+ ):
+ super().__init__()
+ self.context_features = context_features
+ self.causal = causal
+ mid_features = head_features * num_heads
+ context_features = default(context_features, features)
+
+ self.norm = nn.LayerNorm(features)
+ self.norm_context = nn.LayerNorm(context_features)
+ self.to_q = nn.Linear(
+ in_features=features, out_features=mid_features, bias=False
+ )
+ self.to_kv = nn.Linear(
+ in_features=context_features, out_features=mid_features * 2, bias=False
+ )
+ self.attention = AttentionBase(
+ features,
+ num_heads=num_heads,
+ head_features=head_features,
+ out_features=out_features,
+ )
+
+ def forward(
+ self,
+ x: Tensor, # [b, n, c]
+ context: Optional[Tensor] = None, # [b, m, d]
+ context_mask: Optional[Tensor] = None, # [b, m], false is masked,
+ causal: Optional[bool] = False,
+ ) -> Tensor:
+ assert_message = "You must provide a context when using context_features"
+ assert not self.context_features or exists(context), assert_message
+ # Use context if provided
+ context = default(context, x)
+ # Normalize then compute q from input and k,v from context
+ x, context = self.norm(x), self.norm_context(context)
+
+ q, k, v = (self.to_q(x), *torch.chunk(self.to_kv(context), chunks=2, dim=-1))
+
+ if exists(context_mask):
+ # Mask out cross-attention for padding tokens
+ mask = repeat(context_mask, "b m -> b m d", d=v.shape[-1])
+ k, v = k * mask, v * mask
+
+ # Compute and return attention
+ return self.attention(q, k, v, is_causal=self.causal or causal)
+
+
+def FeedForward(features: int, multiplier: int) -> nn.Module:
+ mid_features = features * multiplier
+ return nn.Sequential(
+ nn.Linear(in_features=features, out_features=mid_features),
+ nn.GELU(),
+ nn.Linear(in_features=mid_features, out_features=features),
+ )
+
+"""
+Transformer Blocks
+"""
+
+
+class TransformerBlock(nn.Module):
+ def __init__(
+ self,
+ features: int,
+ num_heads: int,
+ head_features: int,
+ multiplier: int,
+ context_features: Optional[int] = None,
+ ):
+ super().__init__()
+
+ self.use_cross_attention = exists(context_features) and context_features > 0
+
+ self.attention = Attention(
+ features=features,
+ num_heads=num_heads,
+ head_features=head_features
+ )
+
+ if self.use_cross_attention:
+ self.cross_attention = Attention(
+ features=features,
+ num_heads=num_heads,
+ head_features=head_features,
+ context_features=context_features
+ )
+
+ self.feed_forward = FeedForward(features=features, multiplier=multiplier)
+
+ def forward(self, x: Tensor, *, context: Optional[Tensor] = None, context_mask: Optional[Tensor] = None, causal: Optional[bool] = False) -> Tensor:
+ x = self.attention(x, causal=causal) + x
+ if self.use_cross_attention:
+ x = self.cross_attention(x, context=context, context_mask=context_mask) + x
+ x = self.feed_forward(x) + x
+ return x
+
+
+"""
+Transformers
+"""
+
+
+class Transformer1d(nn.Module):
+ def __init__(
+ self,
+ num_layers: int,
+ channels: int,
+ num_heads: int,
+ head_features: int,
+ multiplier: int,
+ context_features: Optional[int] = None,
+ ):
+ super().__init__()
+
+ self.to_in = nn.Sequential(
+ nn.GroupNorm(num_groups=32, num_channels=channels, eps=1e-6, affine=True),
+ Conv1d(
+ in_channels=channels,
+ out_channels=channels,
+ kernel_size=1,
+ ),
+ Rearrange("b c t -> b t c"),
+ )
+
+ self.blocks = nn.ModuleList(
+ [
+ TransformerBlock(
+ features=channels,
+ head_features=head_features,
+ num_heads=num_heads,
+ multiplier=multiplier,
+ context_features=context_features,
+ )
+ for i in range(num_layers)
+ ]
+ )
+
+ self.to_out = nn.Sequential(
+ Rearrange("b t c -> b c t"),
+ Conv1d(
+ in_channels=channels,
+ out_channels=channels,
+ kernel_size=1,
+ ),
+ )
+
+ def forward(self, x: Tensor, *, context: Optional[Tensor] = None, context_mask: Optional[Tensor] = None, causal=False) -> Tensor:
+ x = self.to_in(x)
+ for block in self.blocks:
+ x = block(x, context=context, context_mask=context_mask, causal=causal)
+ x = self.to_out(x)
+ return x
+
+
+"""
+Time Embeddings
+"""
+
+
+class SinusoidalEmbedding(nn.Module):
+ def __init__(self, dim: int):
+ super().__init__()
+ self.dim = dim
+
+ def forward(self, x: Tensor) -> Tensor:
+ device, half_dim = x.device, self.dim // 2
+ emb = torch.tensor(log(10000) / (half_dim - 1), device=device)
+ emb = torch.exp(torch.arange(half_dim, device=device) * -emb)
+ emb = rearrange(x, "i -> i 1") * rearrange(emb, "j -> 1 j")
+ return torch.cat((emb.sin(), emb.cos()), dim=-1)
+
+
+class LearnedPositionalEmbedding(nn.Module):
+ """Used for continuous time"""
+
+ def __init__(self, dim: int):
+ super().__init__()
+ assert (dim % 2) == 0
+ half_dim = dim // 2
+ self.weights = nn.Parameter(torch.randn(half_dim))
+
+ def forward(self, x: Tensor) -> Tensor:
+ x = rearrange(x, "b -> b 1")
+ freqs = x * rearrange(self.weights, "d -> 1 d") * 2 * pi
+ fouriered = torch.cat((freqs.sin(), freqs.cos()), dim=-1)
+ fouriered = torch.cat((x, fouriered), dim=-1)
+ return fouriered
+
+
+def TimePositionalEmbedding(dim: int, out_features: int) -> nn.Module:
+ return nn.Sequential(
+ LearnedPositionalEmbedding(dim),
+ nn.Linear(in_features=dim + 1, out_features=out_features),
+ )
+
+
+"""
+Encoder/Decoder Components
+"""
+
+
+class DownsampleBlock1d(nn.Module):
+ def __init__(
+ self,
+ in_channels: int,
+ out_channels: int,
+ *,
+ factor: int,
+ num_groups: int,
+ num_layers: int,
+ kernel_multiplier: int = 2,
+ use_pre_downsample: bool = True,
+ use_skip: bool = False,
+ use_snake: bool = False,
+ extract_channels: int = 0,
+ context_channels: int = 0,
+ num_transformer_blocks: int = 0,
+ attention_heads: Optional[int] = None,
+ attention_features: Optional[int] = None,
+ attention_multiplier: Optional[int] = None,
+ context_mapping_features: Optional[int] = None,
+ context_embedding_features: Optional[int] = None,
+ ):
+ super().__init__()
+ self.use_pre_downsample = use_pre_downsample
+ self.use_skip = use_skip
+ self.use_transformer = num_transformer_blocks > 0
+ self.use_extract = extract_channels > 0
+ self.use_context = context_channels > 0
+
+ channels = out_channels if use_pre_downsample else in_channels
+
+ self.downsample = Downsample1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ factor=factor,
+ kernel_multiplier=kernel_multiplier,
+ )
+
+ self.blocks = nn.ModuleList(
+ [
+ ResnetBlock1d(
+ in_channels=channels + context_channels if i == 0 else channels,
+ out_channels=channels,
+ num_groups=num_groups,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+ for i in range(num_layers)
+ ]
+ )
+
+ if self.use_transformer:
+ assert (
+ (exists(attention_heads) or exists(attention_features))
+ and exists(attention_multiplier)
+ )
+
+ if attention_features is None and attention_heads is not None:
+ attention_features = channels // attention_heads
+
+ if attention_heads is None and attention_features is not None:
+ attention_heads = channels // attention_features
+
+ self.transformer = Transformer1d(
+ num_layers=num_transformer_blocks,
+ channels=channels,
+ num_heads=attention_heads,
+ head_features=attention_features,
+ multiplier=attention_multiplier,
+ context_features=context_embedding_features
+ )
+
+ if self.use_extract:
+ num_extract_groups = min(num_groups, extract_channels)
+ self.to_extracted = ResnetBlock1d(
+ in_channels=out_channels,
+ out_channels=extract_channels,
+ num_groups=num_extract_groups,
+ use_snake=use_snake
+ )
+
+ def forward(
+ self,
+ x: Tensor,
+ *,
+ mapping: Optional[Tensor] = None,
+ channels: Optional[Tensor] = None,
+ embedding: Optional[Tensor] = None,
+ embedding_mask: Optional[Tensor] = None,
+ causal: Optional[bool] = False
+ ) -> Union[Tuple[Tensor, List[Tensor]], Tensor]:
+
+ if self.use_pre_downsample:
+ x = self.downsample(x)
+
+ if self.use_context and exists(channels):
+ x = torch.cat([x, channels], dim=1)
+
+ skips = []
+ for block in self.blocks:
+ x = block(x, mapping=mapping, causal=causal)
+ skips += [x] if self.use_skip else []
+
+ if self.use_transformer:
+ x = self.transformer(x, context=embedding, context_mask=embedding_mask, causal=causal)
+ skips += [x] if self.use_skip else []
+
+ if not self.use_pre_downsample:
+ x = self.downsample(x)
+
+ if self.use_extract:
+ extracted = self.to_extracted(x)
+ return x, extracted
+
+ return (x, skips) if self.use_skip else x
+
+
+class UpsampleBlock1d(nn.Module):
+ def __init__(
+ self,
+ in_channels: int,
+ out_channels: int,
+ *,
+ factor: int,
+ num_layers: int,
+ num_groups: int,
+ use_nearest: bool = False,
+ use_pre_upsample: bool = False,
+ use_skip: bool = False,
+ use_snake: bool = False,
+ skip_channels: int = 0,
+ use_skip_scale: bool = False,
+ extract_channels: int = 0,
+ num_transformer_blocks: int = 0,
+ attention_heads: Optional[int] = None,
+ attention_features: Optional[int] = None,
+ attention_multiplier: Optional[int] = None,
+ context_mapping_features: Optional[int] = None,
+ context_embedding_features: Optional[int] = None,
+ ):
+ super().__init__()
+
+ self.use_extract = extract_channels > 0
+ self.use_pre_upsample = use_pre_upsample
+ self.use_transformer = num_transformer_blocks > 0
+ self.use_skip = use_skip
+ self.skip_scale = 2 ** -0.5 if use_skip_scale else 1.0
+
+ channels = out_channels if use_pre_upsample else in_channels
+
+ self.blocks = nn.ModuleList(
+ [
+ ResnetBlock1d(
+ in_channels=channels + skip_channels,
+ out_channels=channels,
+ num_groups=num_groups,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+ for _ in range(num_layers)
+ ]
+ )
+
+ if self.use_transformer:
+ assert (
+ (exists(attention_heads) or exists(attention_features))
+ and exists(attention_multiplier)
+ )
+
+ if attention_features is None and attention_heads is not None:
+ attention_features = channels // attention_heads
+
+ if attention_heads is None and attention_features is not None:
+ attention_heads = channels // attention_features
+
+ self.transformer = Transformer1d(
+ num_layers=num_transformer_blocks,
+ channels=channels,
+ num_heads=attention_heads,
+ head_features=attention_features,
+ multiplier=attention_multiplier,
+ context_features=context_embedding_features,
+ )
+
+ self.upsample = Upsample1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ factor=factor,
+ use_nearest=use_nearest,
+ )
+
+ if self.use_extract:
+ num_extract_groups = min(num_groups, extract_channels)
+ self.to_extracted = ResnetBlock1d(
+ in_channels=out_channels,
+ out_channels=extract_channels,
+ num_groups=num_extract_groups,
+ use_snake=use_snake
+ )
+
+ def add_skip(self, x: Tensor, skip: Tensor) -> Tensor:
+ return torch.cat([x, skip * self.skip_scale], dim=1)
+
+ def forward(
+ self,
+ x: Tensor,
+ *,
+ skips: Optional[List[Tensor]] = None,
+ mapping: Optional[Tensor] = None,
+ embedding: Optional[Tensor] = None,
+ embedding_mask: Optional[Tensor] = None,
+ causal: Optional[bool] = False
+ ) -> Union[Tuple[Tensor, Tensor], Tensor]:
+
+ if self.use_pre_upsample:
+ x = self.upsample(x)
+
+ for block in self.blocks:
+ x = self.add_skip(x, skip=skips.pop()) if exists(skips) else x
+ x = block(x, mapping=mapping, causal=causal)
+
+ if self.use_transformer:
+ x = self.transformer(x, context=embedding, context_mask=embedding_mask, causal=causal)
+
+ if not self.use_pre_upsample:
+ x = self.upsample(x)
+
+ if self.use_extract:
+ extracted = self.to_extracted(x)
+ return x, extracted
+
+ return x
+
+
+class BottleneckBlock1d(nn.Module):
+ def __init__(
+ self,
+ channels: int,
+ *,
+ num_groups: int,
+ num_transformer_blocks: int = 0,
+ attention_heads: Optional[int] = None,
+ attention_features: Optional[int] = None,
+ attention_multiplier: Optional[int] = None,
+ context_mapping_features: Optional[int] = None,
+ context_embedding_features: Optional[int] = None,
+ use_snake: bool = False,
+ ):
+ super().__init__()
+ self.use_transformer = num_transformer_blocks > 0
+
+ self.pre_block = ResnetBlock1d(
+ in_channels=channels,
+ out_channels=channels,
+ num_groups=num_groups,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+
+ if self.use_transformer:
+ assert (
+ (exists(attention_heads) or exists(attention_features))
+ and exists(attention_multiplier)
+ )
+
+ if attention_features is None and attention_heads is not None:
+ attention_features = channels // attention_heads
+
+ if attention_heads is None and attention_features is not None:
+ attention_heads = channels // attention_features
+
+ self.transformer = Transformer1d(
+ num_layers=num_transformer_blocks,
+ channels=channels,
+ num_heads=attention_heads,
+ head_features=attention_features,
+ multiplier=attention_multiplier,
+ context_features=context_embedding_features,
+ )
+
+ self.post_block = ResnetBlock1d(
+ in_channels=channels,
+ out_channels=channels,
+ num_groups=num_groups,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+
+ def forward(
+ self,
+ x: Tensor,
+ *,
+ mapping: Optional[Tensor] = None,
+ embedding: Optional[Tensor] = None,
+ embedding_mask: Optional[Tensor] = None,
+ causal: Optional[bool] = False
+ ) -> Tensor:
+ x = self.pre_block(x, mapping=mapping, causal=causal)
+ if self.use_transformer:
+ x = self.transformer(x, context=embedding, context_mask=embedding_mask, causal=causal)
+ x = self.post_block(x, mapping=mapping, causal=causal)
+ return x
+
+
+"""
+UNet
+"""
+
+
+class UNet1d(nn.Module):
+ def __init__(
+ self,
+ in_channels: int,
+ channels: int,
+ multipliers: Sequence[int],
+ factors: Sequence[int],
+ num_blocks: Sequence[int],
+ attentions: Sequence[int],
+ patch_size: int = 1,
+ resnet_groups: int = 8,
+ use_context_time: bool = True,
+ kernel_multiplier_downsample: int = 2,
+ use_nearest_upsample: bool = False,
+ use_skip_scale: bool = True,
+ use_snake: bool = False,
+ use_stft: bool = False,
+ use_stft_context: bool = False,
+ out_channels: Optional[int] = None,
+ context_features: Optional[int] = None,
+ context_features_multiplier: int = 4,
+ context_channels: Optional[Sequence[int]] = None,
+ context_embedding_features: Optional[int] = None,
+ **kwargs,
+ ):
+ super().__init__()
+ out_channels = default(out_channels, in_channels)
+ context_channels = list(default(context_channels, []))
+ num_layers = len(multipliers) - 1
+ use_context_features = exists(context_features)
+ use_context_channels = len(context_channels) > 0
+ context_mapping_features = None
+
+ attention_kwargs, kwargs = groupby("attention_", kwargs, keep_prefix=True)
+
+ self.num_layers = num_layers
+ self.use_context_time = use_context_time
+ self.use_context_features = use_context_features
+ self.use_context_channels = use_context_channels
+ self.use_stft = use_stft
+ self.use_stft_context = use_stft_context
+
+ self.context_features = context_features
+ context_channels_pad_length = num_layers + 1 - len(context_channels)
+ context_channels = context_channels + [0] * context_channels_pad_length
+ self.context_channels = context_channels
+ self.context_embedding_features = context_embedding_features
+
+ if use_context_channels:
+ has_context = [c > 0 for c in context_channels]
+ self.has_context = has_context
+ self.channels_ids = [sum(has_context[:i]) for i in range(len(has_context))]
+
+ assert (
+ len(factors) == num_layers
+ and len(attentions) >= num_layers
+ and len(num_blocks) == num_layers
+ )
+
+ if use_context_time or use_context_features:
+ context_mapping_features = channels * context_features_multiplier
+
+ self.to_mapping = nn.Sequential(
+ nn.Linear(context_mapping_features, context_mapping_features),
+ nn.GELU(),
+ nn.Linear(context_mapping_features, context_mapping_features),
+ nn.GELU(),
+ )
+
+ if use_context_time:
+ assert exists(context_mapping_features)
+ self.to_time = nn.Sequential(
+ TimePositionalEmbedding(
+ dim=channels, out_features=context_mapping_features
+ ),
+ nn.GELU(),
+ )
+
+ if use_context_features:
+ assert exists(context_features) and exists(context_mapping_features)
+ self.to_features = nn.Sequential(
+ nn.Linear(
+ in_features=context_features, out_features=context_mapping_features
+ ),
+ nn.GELU(),
+ )
+
+ if use_stft:
+ stft_kwargs, kwargs = groupby("stft_", kwargs)
+ assert "num_fft" in stft_kwargs, "stft_num_fft required if use_stft=True"
+ stft_channels = (stft_kwargs["num_fft"] // 2 + 1) * 2
+ in_channels *= stft_channels
+ out_channels *= stft_channels
+ context_channels[0] *= stft_channels if use_stft_context else 1
+ assert exists(in_channels) and exists(out_channels)
+ self.stft = STFT(**stft_kwargs)
+
+ assert not kwargs, f"Unknown arguments: {', '.join(list(kwargs.keys()))}"
+
+ self.to_in = Patcher(
+ in_channels=in_channels + context_channels[0],
+ out_channels=channels * multipliers[0],
+ patch_size=patch_size,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+
+ self.downsamples = nn.ModuleList(
+ [
+ DownsampleBlock1d(
+ in_channels=channels * multipliers[i],
+ out_channels=channels * multipliers[i + 1],
+ context_mapping_features=context_mapping_features,
+ context_channels=context_channels[i + 1],
+ context_embedding_features=context_embedding_features,
+ num_layers=num_blocks[i],
+ factor=factors[i],
+ kernel_multiplier=kernel_multiplier_downsample,
+ num_groups=resnet_groups,
+ use_pre_downsample=True,
+ use_skip=True,
+ use_snake=use_snake,
+ num_transformer_blocks=attentions[i],
+ **attention_kwargs,
+ )
+ for i in range(num_layers)
+ ]
+ )
+
+ self.bottleneck = BottleneckBlock1d(
+ channels=channels * multipliers[-1],
+ context_mapping_features=context_mapping_features,
+ context_embedding_features=context_embedding_features,
+ num_groups=resnet_groups,
+ num_transformer_blocks=attentions[-1],
+ use_snake=use_snake,
+ **attention_kwargs,
+ )
+
+ self.upsamples = nn.ModuleList(
+ [
+ UpsampleBlock1d(
+ in_channels=channels * multipliers[i + 1],
+ out_channels=channels * multipliers[i],
+ context_mapping_features=context_mapping_features,
+ context_embedding_features=context_embedding_features,
+ num_layers=num_blocks[i] + (1 if attentions[i] else 0),
+ factor=factors[i],
+ use_nearest=use_nearest_upsample,
+ num_groups=resnet_groups,
+ use_skip_scale=use_skip_scale,
+ use_pre_upsample=False,
+ use_skip=True,
+ use_snake=use_snake,
+ skip_channels=channels * multipliers[i + 1],
+ num_transformer_blocks=attentions[i],
+ **attention_kwargs,
+ )
+ for i in reversed(range(num_layers))
+ ]
+ )
+
+ self.to_out = Unpatcher(
+ in_channels=channels * multipliers[0],
+ out_channels=out_channels,
+ patch_size=patch_size,
+ context_mapping_features=context_mapping_features,
+ use_snake=use_snake
+ )
+
+ def get_channels(
+ self, channels_list: Optional[Sequence[Tensor]] = None, layer: int = 0
+ ) -> Optional[Tensor]:
+ """Gets context channels at `layer` and checks that shape is correct"""
+ use_context_channels = self.use_context_channels and self.has_context[layer]
+ if not use_context_channels:
+ return None
+ assert exists(channels_list), "Missing context"
+ # Get channels index (skipping zero channel contexts)
+ channels_id = self.channels_ids[layer]
+ # Get channels
+ channels = channels_list[channels_id]
+ message = f"Missing context for layer {layer} at index {channels_id}"
+ assert exists(channels), message
+ # Check channels
+ num_channels = self.context_channels[layer]
+ message = f"Expected context with {num_channels} channels at idx {channels_id}"
+ assert channels.shape[1] == num_channels, message
+ # STFT channels if requested
+ channels = self.stft.encode1d(channels) if self.use_stft_context else channels # type: ignore # noqa
+ return channels
+
+ def get_mapping(
+ self, time: Optional[Tensor] = None, features: Optional[Tensor] = None
+ ) -> Optional[Tensor]:
+ """Combines context time features and features into mapping"""
+ items, mapping = [], None
+ # Compute time features
+ if self.use_context_time:
+ assert_message = "use_context_time=True but no time features provided"
+ assert exists(time), assert_message
+ items += [self.to_time(time)]
+ # Compute features
+ if self.use_context_features:
+ assert_message = "context_features exists but no features provided"
+ assert exists(features), assert_message
+ items += [self.to_features(features)]
+ # Compute joint mapping
+ if self.use_context_time or self.use_context_features:
+ mapping = reduce(torch.stack(items), "n b m -> b m", "sum")
+ mapping = self.to_mapping(mapping)
+ return mapping
+
+ def forward(
+ self,
+ x: Tensor,
+ time: Optional[Tensor] = None,
+ *,
+ features: Optional[Tensor] = None,
+ channels_list: Optional[Sequence[Tensor]] = None,
+ embedding: Optional[Tensor] = None,
+ embedding_mask: Optional[Tensor] = None,
+ causal: Optional[bool] = False,
+ ) -> Tensor:
+ channels = self.get_channels(channels_list, layer=0)
+ # Apply stft if required
+ print(x.shape)
+ x = self.stft.encode1d(x) if self.use_stft else x # type: ignore
+ print(x.shape)
+ # Concat context channels at layer 0 if provided
+ x = torch.cat([x, channels], dim=1) if exists(channels) else x
+ print(x.shape)
+ # Compute mapping from time and features
+ mapping = self.get_mapping(time, features)
+ x = self.to_in(x, mapping, causal=causal)
+ print(x.shape)
+ skips_list = [x]
+
+ for i, downsample in enumerate(self.downsamples):
+ channels = self.get_channels(channels_list, layer=i + 1)
+ x, skips = downsample(
+ x, mapping=mapping, channels=channels, embedding=embedding, embedding_mask=embedding_mask, causal=causal
+ )
+ skips_list += [skips]
+
+ x = self.bottleneck(x, mapping=mapping, embedding=embedding, embedding_mask=embedding_mask, causal=causal)
+ for i, upsample in enumerate(self.upsamples):
+ skips = skips_list.pop()
+ x = upsample(x, skips=skips, mapping=mapping, embedding=embedding, embedding_mask=embedding_mask, causal=causal)
+
+ x += skips_list.pop()
+ x = self.to_out(x, mapping, causal=causal)
+ x = self.stft.decode1d(x) if self.use_stft else x
+
+ return x
+
+
+""" Conditioning Modules """
+
+
+class FixedEmbedding(nn.Module):
+ def __init__(self, max_length: int, features: int):
+ super().__init__()
+ self.max_length = max_length
+ self.embedding = nn.Embedding(max_length, features)
+
+ def forward(self, x: Tensor) -> Tensor:
+ batch_size, length, device = *x.shape[0:2], x.device
+ assert_message = "Input sequence length must be <= max_length"
+ assert length <= self.max_length, assert_message
+ position = torch.arange(length, device=device)
+ fixed_embedding = self.embedding(position)
+ fixed_embedding = repeat(fixed_embedding, "n d -> b n d", b=batch_size)
+ return fixed_embedding
+
+
+def rand_bool(shape: Any, proba: float, device: Any = None) -> Tensor:
+ if proba == 1:
+ return torch.ones(shape, device=device, dtype=torch.bool)
+ elif proba == 0:
+ return torch.zeros(shape, device=device, dtype=torch.bool)
+ else:
+ return torch.bernoulli(torch.full(shape, proba, device=device)).to(torch.bool)
+
+
+class UNetCFG1d(UNet1d):
+
+ """UNet1d with Classifier-Free Guidance"""
+
+ def __init__(
+ self,
+ context_embedding_max_length: int,
+ context_embedding_features: int,
+ use_xattn_time: bool = False,
+ **kwargs,
+ ):
+ super().__init__(
+ context_embedding_features=context_embedding_features, **kwargs
+ )
+
+ self.use_xattn_time = use_xattn_time
+
+ if use_xattn_time:
+ assert exists(context_embedding_features)
+ self.to_time_embedding = nn.Sequential(
+ TimePositionalEmbedding(
+ dim=kwargs["channels"], out_features=context_embedding_features
+ ),
+ nn.GELU(),
+ )
+
+ context_embedding_max_length += 1 # Add one for time embedding
+
+ self.fixed_embedding = FixedEmbedding(
+ max_length=context_embedding_max_length, features=context_embedding_features
+ )
+
+ def forward( # type: ignore
+ self,
+ x: Tensor,
+ time: Tensor,
+ *,
+ embedding: Tensor,
+ embedding_mask: Optional[Tensor] = None,
+ embedding_scale: float = 1.0,
+ embedding_mask_proba: float = 0.0,
+ batch_cfg: bool = False,
+ rescale_cfg: bool = False,
+ scale_phi: float = 0.4,
+ negative_embedding: Optional[Tensor] = None,
+ negative_embedding_mask: Optional[Tensor] = None,
+ **kwargs,
+ ) -> Tensor:
+ b, device = embedding.shape[0], embedding.device
+
+ if self.use_xattn_time:
+ embedding = torch.cat([embedding, self.to_time_embedding(time).unsqueeze(1)], dim=1)
+
+ if embedding_mask is not None:
+ embedding_mask = torch.cat([embedding_mask, torch.ones((b, 1), device=device)], dim=1)
+
+ fixed_embedding = self.fixed_embedding(embedding)
+
+ if embedding_mask_proba > 0.0:
+ # Randomly mask embedding
+ batch_mask = rand_bool(
+ shape=(b, 1, 1), proba=embedding_mask_proba, device=device
+ )
+ embedding = torch.where(batch_mask, fixed_embedding, embedding)
+
+ if embedding_scale != 1.0:
+ if batch_cfg:
+ batch_x = torch.cat([x, x], dim=0)
+ batch_time = torch.cat([time, time], dim=0)
+
+ if negative_embedding is not None:
+ if negative_embedding_mask is not None:
+ negative_embedding_mask = negative_embedding_mask.to(torch.bool).unsqueeze(2)
+
+ negative_embedding = torch.where(negative_embedding_mask, negative_embedding, fixed_embedding)
+
+ batch_embed = torch.cat([embedding, negative_embedding], dim=0)
+
+ else:
+ batch_embed = torch.cat([embedding, fixed_embedding], dim=0)
+
+ batch_mask = None
+ if embedding_mask is not None:
+ batch_mask = torch.cat([embedding_mask, embedding_mask], dim=0)
+
+ batch_features = None
+ features = kwargs.pop("features", None)
+ if self.use_context_features:
+ batch_features = torch.cat([features, features], dim=0)
+
+ batch_channels = None
+ channels_list = kwargs.pop("channels_list", None)
+ if self.use_context_channels:
+ batch_channels = []
+ for channels in channels_list:
+ batch_channels += [torch.cat([channels, channels], dim=0)]
+
+ # Compute both normal and fixed embedding outputs
+ batch_out = super().forward(batch_x, batch_time, embedding=batch_embed, embedding_mask=batch_mask, features=batch_features, channels_list=batch_channels, **kwargs)
+ out, out_masked = batch_out.chunk(2, dim=0)
+
+ else:
+ # Compute both normal and fixed embedding outputs
+ out = super().forward(x, time, embedding=embedding, embedding_mask=embedding_mask, **kwargs)
+ out_masked = super().forward(x, time, embedding=fixed_embedding, embedding_mask=embedding_mask, **kwargs)
+
+ out_cfg = out_masked + (out - out_masked) * embedding_scale
+
+ if rescale_cfg:
+
+ out_std = out.std(dim=1, keepdim=True)
+ out_cfg_std = out_cfg.std(dim=1, keepdim=True)
+
+ return scale_phi * (out_cfg * (out_std/out_cfg_std)) + (1-scale_phi) * out_cfg
+
+ else:
+
+ return out_cfg
+
+ else:
+ return super().forward(x, time, embedding=embedding, embedding_mask=embedding_mask, **kwargs)
+
+
+class UNetNCCA1d(UNet1d):
+
+ """UNet1d with Noise Channel Conditioning Augmentation"""
+
+ def __init__(self, context_features: int, **kwargs):
+ super().__init__(context_features=context_features, **kwargs)
+ self.embedder = NumberEmbedder(features=context_features)
+
+ def expand(self, x: Any, shape: Tuple[int, ...]) -> Tensor:
+ x = x if torch.is_tensor(x) else torch.tensor(x)
+ return x.expand(shape)
+
+ def forward( # type: ignore
+ self,
+ x: Tensor,
+ time: Tensor,
+ *,
+ channels_list: Sequence[Tensor],
+ channels_augmentation: Union[
+ bool, Sequence[bool], Sequence[Sequence[bool]], Tensor
+ ] = False,
+ channels_scale: Union[
+ float, Sequence[float], Sequence[Sequence[float]], Tensor
+ ] = 0,
+ **kwargs,
+ ) -> Tensor:
+ b, n = x.shape[0], len(channels_list)
+ channels_augmentation = self.expand(channels_augmentation, shape=(b, n)).to(x)
+ channels_scale = self.expand(channels_scale, shape=(b, n)).to(x)
+
+ # Augmentation (for each channel list item)
+ for i in range(n):
+ scale = channels_scale[:, i] * channels_augmentation[:, i]
+ scale = rearrange(scale, "b -> b 1 1")
+ item = channels_list[i]
+ channels_list[i] = torch.randn_like(item) * scale + item * (1 - scale) # type: ignore # noqa
+
+ # Scale embedding (sum reduction if more than one channel list item)
+ channels_scale_emb = self.embedder(channels_scale)
+ channels_scale_emb = reduce(channels_scale_emb, "b n d -> b d", "sum")
+
+ return super().forward(
+ x=x,
+ time=time,
+ channels_list=channels_list,
+ features=channels_scale_emb,
+ **kwargs,
+ )
+
+
+class UNetAll1d(UNetCFG1d, UNetNCCA1d):
+ def __init__(self, *args, **kwargs):
+ super().__init__(*args, **kwargs)
+
+ def forward(self, *args, **kwargs): # type: ignore
+ return UNetCFG1d.forward(self, *args, **kwargs)
+
+
+def XUNet1d(type: str = "base", **kwargs) -> UNet1d:
+ if type == "base":
+ return UNet1d(**kwargs)
+ elif type == "all":
+ return UNetAll1d(**kwargs)
+ elif type == "cfg":
+ return UNetCFG1d(**kwargs)
+ elif type == "ncca":
+ return UNetNCCA1d(**kwargs)
+ else:
+ raise ValueError(f"Unknown XUNet1d type: {type}")
+
+class NumberEmbedder(nn.Module):
+ def __init__(
+ self,
+ features: int,
+ dim: int = 256,
+ ):
+ super().__init__()
+ self.features = features
+ self.embedding = TimePositionalEmbedding(dim=dim, out_features=features)
+
+ def forward(self, x: Union[List[float], Tensor]) -> Tensor:
+ if not torch.is_tensor(x):
+ device = next(self.embedding.parameters()).device
+ x = torch.tensor(x, device=device)
+ assert isinstance(x, Tensor)
+ shape = x.shape
+ x = rearrange(x, "... -> (...)")
+ embedding = self.embedding(x)
+ x = embedding.view(*shape, self.features)
+ return x # type: ignore
+
+
+"""
+Audio Transforms
+"""
+
+
+class STFT(nn.Module):
+ """Helper for torch stft and istft"""
+
+ def __init__(
+ self,
+ num_fft: int = 1023,
+ hop_length: int = 256,
+ window_length: Optional[int] = None,
+ length: Optional[int] = None,
+ use_complex: bool = False,
+ ):
+ super().__init__()
+ self.num_fft = num_fft
+ self.hop_length = default(hop_length, floor(num_fft // 4))
+ self.window_length = default(window_length, num_fft)
+ self.length = length
+ self.register_buffer("window", torch.hann_window(self.window_length))
+ self.use_complex = use_complex
+
+ def encode(self, wave: Tensor) -> Tuple[Tensor, Tensor]:
+ b = wave.shape[0]
+ wave = rearrange(wave, "b c t -> (b c) t")
+
+ stft = torch.stft(
+ wave,
+ n_fft=self.num_fft,
+ hop_length=self.hop_length,
+ win_length=self.window_length,
+ window=self.window, # type: ignore
+ return_complex=True,
+ normalized=True,
+ )
+
+ if self.use_complex:
+ # Returns real and imaginary
+ stft_a, stft_b = stft.real, stft.imag
+ else:
+ # Returns magnitude and phase matrices
+ magnitude, phase = torch.abs(stft), torch.angle(stft)
+ stft_a, stft_b = magnitude, phase
+
+ return rearrange_many((stft_a, stft_b), "(b c) f l -> b c f l", b=b)
+
+ def decode(self, stft_a: Tensor, stft_b: Tensor) -> Tensor:
+ b, l = stft_a.shape[0], stft_a.shape[-1] # noqa
+ length = closest_power_2(l * self.hop_length)
+
+ stft_a, stft_b = rearrange_many((stft_a, stft_b), "b c f l -> (b c) f l")
+
+ if self.use_complex:
+ real, imag = stft_a, stft_b
+ else:
+ magnitude, phase = stft_a, stft_b
+ real, imag = magnitude * torch.cos(phase), magnitude * torch.sin(phase)
+
+ stft = torch.stack([real, imag], dim=-1)
+
+ wave = torch.istft(
+ stft,
+ n_fft=self.num_fft,
+ hop_length=self.hop_length,
+ win_length=self.window_length,
+ window=self.window, # type: ignore
+ length=default(self.length, length),
+ normalized=True,
+ )
+
+ return rearrange(wave, "(b c) t -> b c t", b=b)
+
+ def encode1d(
+ self, wave: Tensor, stacked: bool = True
+ ) -> Union[Tensor, Tuple[Tensor, Tensor]]:
+ stft_a, stft_b = self.encode(wave)
+ stft_a, stft_b = rearrange_many((stft_a, stft_b), "b c f l -> b (c f) l")
+ return torch.cat((stft_a, stft_b), dim=1) if stacked else (stft_a, stft_b)
+
+ def decode1d(self, stft_pair: Tensor) -> Tensor:
+ f = self.num_fft // 2 + 1
+ stft_a, stft_b = stft_pair.chunk(chunks=2, dim=1)
+ stft_a, stft_b = rearrange_many((stft_a, stft_b), "b (c f) l -> b c f l", f=f)
+ return self.decode(stft_a, stft_b)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/blocks.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/blocks.py
new file mode 100644
index 0000000000000000000000000000000000000000..3c827fd2441e643717d123847236d3d6c003ef4f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/blocks.py
@@ -0,0 +1,339 @@
+from functools import reduce
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from torch.backends.cuda import sdp_kernel
+from packaging import version
+
+from dac.nn.layers import Snake1d
+
+class ResidualBlock(nn.Module):
+ def __init__(self, main, skip=None):
+ super().__init__()
+ self.main = nn.Sequential(*main)
+ self.skip = skip if skip else nn.Identity()
+
+ def forward(self, input):
+ return self.main(input) + self.skip(input)
+
+class ResConvBlock(ResidualBlock):
+ def __init__(self, c_in, c_mid, c_out, is_last=False, kernel_size=5, conv_bias=True, use_snake=False):
+ skip = None if c_in == c_out else nn.Conv1d(c_in, c_out, 1, bias=False)
+ super().__init__([
+ nn.Conv1d(c_in, c_mid, kernel_size, padding=kernel_size//2, bias=conv_bias),
+ nn.GroupNorm(1, c_mid),
+ Snake1d(c_mid) if use_snake else nn.GELU(),
+ nn.Conv1d(c_mid, c_out, kernel_size, padding=kernel_size//2, bias=conv_bias),
+ nn.GroupNorm(1, c_out) if not is_last else nn.Identity(),
+ (Snake1d(c_out) if use_snake else nn.GELU()) if not is_last else nn.Identity(),
+ ], skip)
+
+class SelfAttention1d(nn.Module):
+ def __init__(self, c_in, n_head=1, dropout_rate=0.):
+ super().__init__()
+ assert c_in % n_head == 0
+ self.norm = nn.GroupNorm(1, c_in)
+ self.n_head = n_head
+ self.qkv_proj = nn.Conv1d(c_in, c_in * 3, 1)
+ self.out_proj = nn.Conv1d(c_in, c_in, 1)
+ self.dropout = nn.Dropout(dropout_rate, inplace=True)
+
+ self.use_flash = torch.cuda.is_available() and version.parse(torch.__version__) >= version.parse('2.0.0')
+
+ if not self.use_flash:
+ return
+
+ device_properties = torch.cuda.get_device_properties(torch.device('cuda'))
+
+ if device_properties.major == 8 and device_properties.minor == 0:
+ # Use flash attention for A100 GPUs
+ self.sdp_kernel_config = (True, False, False)
+ else:
+ # Don't use flash attention for other GPUs
+ self.sdp_kernel_config = (False, True, True)
+
+ def forward(self, input):
+ n, c, s = input.shape
+ qkv = self.qkv_proj(self.norm(input))
+ qkv = qkv.view(
+ [n, self.n_head * 3, c // self.n_head, s]).transpose(2, 3)
+ q, k, v = qkv.chunk(3, dim=1)
+ scale = k.shape[3]**-0.25
+
+ if self.use_flash:
+ with sdp_kernel(*self.sdp_kernel_config):
+ y = F.scaled_dot_product_attention(q, k, v, is_causal=False).contiguous().view([n, c, s])
+ else:
+ att = ((q * scale) @ (k.transpose(2, 3) * scale)).softmax(3)
+ y = (att @ v).transpose(2, 3).contiguous().view([n, c, s])
+
+
+ return input + self.dropout(self.out_proj(y))
+
+class SkipBlock(nn.Module):
+ def __init__(self, *main):
+ super().__init__()
+ self.main = nn.Sequential(*main)
+
+ def forward(self, input):
+ return torch.cat([self.main(input), input], dim=1)
+
+class FourierFeatures(nn.Module):
+ def __init__(self, in_features, out_features, std=1.):
+ super().__init__()
+ assert out_features % 2 == 0
+ self.weight = nn.Parameter(torch.randn(
+ [out_features // 2, in_features]) * std)
+
+ def forward(self, input):
+ f = 2 * math.pi * input @ self.weight.T
+ return torch.cat([f.cos(), f.sin()], dim=-1)
+
+def expand_to_planes(input, shape):
+ return input[..., None].repeat([1, 1, shape[2]])
+
+_kernels = {
+ 'linear':
+ [1 / 8, 3 / 8, 3 / 8, 1 / 8],
+ 'cubic':
+ [-0.01171875, -0.03515625, 0.11328125, 0.43359375,
+ 0.43359375, 0.11328125, -0.03515625, -0.01171875],
+ 'lanczos3':
+ [0.003689131001010537, 0.015056144446134567, -0.03399861603975296,
+ -0.066637322306633, 0.13550527393817902, 0.44638532400131226,
+ 0.44638532400131226, 0.13550527393817902, -0.066637322306633,
+ -0.03399861603975296, 0.015056144446134567, 0.003689131001010537]
+}
+
+class Downsample1d(nn.Module):
+ def __init__(self, kernel='linear', pad_mode='reflect', channels_last=False):
+ super().__init__()
+ self.pad_mode = pad_mode
+ kernel_1d = torch.tensor(_kernels[kernel])
+ self.pad = kernel_1d.shape[0] // 2 - 1
+ self.register_buffer('kernel', kernel_1d)
+ self.channels_last = channels_last
+
+ def forward(self, x):
+ if self.channels_last:
+ x = x.permute(0, 2, 1)
+ x = F.pad(x, (self.pad,) * 2, self.pad_mode)
+ weight = x.new_zeros([x.shape[1], x.shape[1], self.kernel.shape[0]])
+ indices = torch.arange(x.shape[1], device=x.device)
+ weight[indices, indices] = self.kernel.to(weight)
+ x = F.conv1d(x, weight, stride=2)
+ if self.channels_last:
+ x = x.permute(0, 2, 1)
+ return x
+
+
+class Upsample1d(nn.Module):
+ def __init__(self, kernel='linear', pad_mode='reflect', channels_last=False):
+ super().__init__()
+ self.pad_mode = pad_mode
+ kernel_1d = torch.tensor(_kernels[kernel]) * 2
+ self.pad = kernel_1d.shape[0] // 2 - 1
+ self.register_buffer('kernel', kernel_1d)
+ self.channels_last = channels_last
+
+ def forward(self, x):
+ if self.channels_last:
+ x = x.permute(0, 2, 1)
+ x = F.pad(x, ((self.pad + 1) // 2,) * 2, self.pad_mode)
+ weight = x.new_zeros([x.shape[1], x.shape[1], self.kernel.shape[0]])
+ indices = torch.arange(x.shape[1], device=x.device)
+ weight[indices, indices] = self.kernel.to(weight)
+ x = F.conv_transpose1d(x, weight, stride=2, padding=self.pad * 2 + 1)
+ if self.channels_last:
+ x = x.permute(0, 2, 1)
+ return x
+
+def Downsample1d_2(
+ in_channels: int, out_channels: int, factor: int, kernel_multiplier: int = 2
+) -> nn.Module:
+ assert kernel_multiplier % 2 == 0, "Kernel multiplier must be even"
+
+ return nn.Conv1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=factor * kernel_multiplier + 1,
+ stride=factor,
+ padding=factor * (kernel_multiplier // 2),
+ )
+
+
+def Upsample1d_2(
+ in_channels: int, out_channels: int, factor: int, use_nearest: bool = False
+) -> nn.Module:
+
+ if factor == 1:
+ return nn.Conv1d(
+ in_channels=in_channels, out_channels=out_channels, kernel_size=3, padding=1
+ )
+
+ if use_nearest:
+ return nn.Sequential(
+ nn.Upsample(scale_factor=factor, mode="nearest"),
+ nn.Conv1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=3,
+ padding=1,
+ ),
+ )
+ else:
+ return nn.ConvTranspose1d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=factor * 2,
+ stride=factor,
+ padding=factor // 2 + factor % 2,
+ output_padding=factor % 2,
+ )
+
+def zero_init(layer):
+ nn.init.zeros_(layer.weight)
+ if layer.bias is not None:
+ nn.init.zeros_(layer.bias)
+ return layer
+
+def rms_norm(x, scale, eps):
+ dtype = reduce(torch.promote_types, (x.dtype, scale.dtype, torch.float32))
+ mean_sq = torch.mean(x.to(dtype)**2, dim=-1, keepdim=True)
+ scale = scale.to(dtype) * torch.rsqrt(mean_sq + eps)
+ return x * scale.to(x.dtype)
+
+#rms_norm = torch.compile(rms_norm)
+
+class AdaRMSNorm(nn.Module):
+ def __init__(self, features, cond_features, eps=1e-6):
+ super().__init__()
+ self.eps = eps
+ self.linear = zero_init(nn.Linear(cond_features, features, bias=False))
+
+ def extra_repr(self):
+ return f"eps={self.eps},"
+
+ def forward(self, x, cond):
+ return rms_norm(x, self.linear(cond)[:, None, :] + 1, self.eps)
+
+def normalize(x, eps=1e-4):
+ dim = list(range(1, x.ndim))
+ n = torch.linalg.vector_norm(x, dim=dim, keepdim=True)
+ alpha = np.sqrt(n.numel() / x.numel())
+ return x / torch.add(eps, n, alpha=alpha)
+
+class ForcedWNConv1d(nn.Module):
+ def __init__(self, in_channels, out_channels, kernel_size=1):
+ super().__init__()
+ self.weight = nn.Parameter(torch.randn([out_channels, in_channels, kernel_size]))
+
+ def forward(self, x):
+ if self.training:
+ with torch.no_grad():
+ self.weight.copy_(normalize(self.weight))
+
+ fan_in = self.weight[0].numel()
+
+ w = normalize(self.weight) / math.sqrt(fan_in)
+
+ return F.conv1d(x, w, padding='same')
+
+# Kernels
+
+use_compile = True
+
+def compile(function, *args, **kwargs):
+ if not use_compile:
+ return function
+ try:
+ return torch.compile(function, *args, **kwargs)
+ except RuntimeError:
+ return function
+
+
+@compile
+def linear_geglu(x, weight, bias=None):
+ x = x @ weight.mT
+ if bias is not None:
+ x = x + bias
+ x, gate = x.chunk(2, dim=-1)
+ return x * F.gelu(gate)
+
+
+@compile
+def rms_norm(x, scale, eps):
+ dtype = reduce(torch.promote_types, (x.dtype, scale.dtype, torch.float32))
+ mean_sq = torch.mean(x.to(dtype)**2, dim=-1, keepdim=True)
+ scale = scale.to(dtype) * torch.rsqrt(mean_sq + eps)
+ return x * scale.to(x.dtype)
+
+# Layers
+
+class LinearGEGLU(nn.Linear):
+ def __init__(self, in_features, out_features, bias=True):
+ super().__init__(in_features, out_features * 2, bias=bias)
+ self.out_features = out_features
+
+ def forward(self, x):
+ return linear_geglu(x, self.weight, self.bias)
+
+
+class RMSNorm(nn.Module):
+ def __init__(self, shape, fix_scale = False, eps=1e-6):
+ super().__init__()
+ self.eps = eps
+
+ if fix_scale:
+ self.register_buffer("scale", torch.ones(shape))
+ else:
+ self.scale = nn.Parameter(torch.ones(shape))
+
+ def extra_repr(self):
+ return f"shape={tuple(self.scale.shape)}, eps={self.eps}"
+
+ def forward(self, x):
+ return rms_norm(x, self.scale, self.eps)
+
+def snake_beta(x, alpha, beta):
+ return x + (1.0 / (beta + 0.000000001)) * pow(torch.sin(x * alpha), 2)
+
+# try:
+# snake_beta = torch.compile(snake_beta)
+# except RuntimeError:
+# pass
+
+# Adapted from https://github.com/NVIDIA/BigVGAN/blob/main/activations.py under MIT license
+# License available in LICENSES/LICENSE_NVIDIA.txt
+class SnakeBeta(nn.Module):
+
+ def __init__(self, in_features, alpha=1.0, alpha_trainable=True, alpha_logscale=True):
+ super(SnakeBeta, self).__init__()
+ self.in_features = in_features
+
+ # initialize alpha
+ self.alpha_logscale = alpha_logscale
+ if self.alpha_logscale: # log scale alphas initialized to zeros
+ self.alpha = nn.Parameter(torch.zeros(in_features) * alpha)
+ self.beta = nn.Parameter(torch.zeros(in_features) * alpha)
+ else: # linear scale alphas initialized to ones
+ self.alpha = nn.Parameter(torch.ones(in_features) * alpha)
+ self.beta = nn.Parameter(torch.ones(in_features) * alpha)
+
+ self.alpha.requires_grad = alpha_trainable
+ self.beta.requires_grad = alpha_trainable
+
+ self.no_div_by_zero = 0.000000001
+
+ def forward(self, x):
+ alpha = self.alpha.unsqueeze(0).unsqueeze(-1) # line up with x to [B, C, T]
+ beta = self.beta.unsqueeze(0).unsqueeze(-1)
+ if self.alpha_logscale:
+ alpha = torch.exp(alpha)
+ beta = torch.exp(beta)
+ x = snake_beta(x, alpha, beta)
+
+ return x
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/dit.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/dit.py
new file mode 100644
index 0000000000000000000000000000000000000000..dcd5efa0f9430ca550b9845b2e8c13ae32534c2c
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/dit.py
@@ -0,0 +1,415 @@
+import typing as tp
+
+import torch
+
+from einops import rearrange
+from torch import nn
+from torch.nn import functional as F
+from x_transformers import ContinuousTransformerWrapper, Encoder
+
+from .blocks import FourierFeatures
+from .transformer import ContinuousTransformer
+from .transformer_use_mask import ContinuousTransformer as ContinuousTransformer_mask
+
+
+class DiffusionTransformer(nn.Module):
+ def __init__(self,
+ io_channels=32,
+ patch_size=1,
+ embed_dim=768,
+ cond_token_dim=0,
+ project_cond_tokens=True,
+ global_cond_dim=0,
+ project_global_cond=True,
+ input_concat_dim=0,
+ prepend_cond_dim=0,
+ depth=12,
+ num_heads=8,
+ transformer_type: tp.Literal["x-transformers", "continuous_transformer"] = "x-transformers",
+ global_cond_type: tp.Literal["prepend", "adaLN"] = "prepend",
+ **kwargs):
+
+ super().__init__()
+
+ self.cond_token_dim = cond_token_dim
+
+ # Timestep embeddings
+ timestep_features_dim = 256
+
+ self.timestep_features = FourierFeatures(1, timestep_features_dim)
+
+ self.to_timestep_embed = nn.Sequential(
+ nn.Linear(timestep_features_dim, embed_dim, bias=True),
+ nn.SiLU(),
+ nn.Linear(embed_dim, embed_dim, bias=True),
+ )
+
+ if cond_token_dim > 0:
+ # Conditioning tokens
+
+ cond_embed_dim = cond_token_dim if not project_cond_tokens else embed_dim
+ self.to_cond_embed = nn.Sequential(
+ nn.Linear(cond_token_dim, cond_embed_dim, bias=False),
+ nn.SiLU(),
+ nn.Linear(cond_embed_dim, cond_embed_dim, bias=False)
+ )
+ else:
+ cond_embed_dim = 0
+ self.to_cond_embed = nn.Identity()
+
+ if global_cond_dim > 0:
+ # Global conditioning
+ global_embed_dim = global_cond_dim if not project_global_cond else embed_dim
+ self.to_global_embed = nn.Sequential(
+ nn.Linear(global_cond_dim, global_embed_dim, bias=False),
+ nn.SiLU(),
+ nn.Linear(global_embed_dim, global_embed_dim, bias=False)
+ )
+
+ if prepend_cond_dim > 0:
+ # Prepend conditioning
+ self.to_prepend_embed = nn.Sequential(
+ nn.Linear(prepend_cond_dim, embed_dim, bias=False),
+ nn.SiLU(),
+ nn.Linear(embed_dim, embed_dim, bias=False)
+ )
+
+ self.input_concat_dim = input_concat_dim
+
+ dim_in = io_channels + self.input_concat_dim
+
+ self.patch_size = patch_size
+
+ # Transformer
+
+ self.transformer_type = transformer_type
+
+ self.global_cond_type = global_cond_type
+
+ if self.transformer_type == "x-transformers":
+ self.transformer = ContinuousTransformerWrapper(
+ dim_in=dim_in * patch_size,
+ dim_out=io_channels * patch_size,
+ max_seq_len=0, # Not relevant without absolute positional embeds
+ attn_layers=Encoder(
+ dim=embed_dim,
+ depth=depth,
+ heads=num_heads,
+ attn_flash=True,
+ cross_attend=cond_token_dim > 0,
+ dim_context=None if cond_embed_dim == 0 else cond_embed_dim,
+ zero_init_branch_output=True,
+ use_abs_pos_emb=False,
+ rotary_pos_emb=True,
+ ff_swish=True,
+ ff_glu=True,
+ **kwargs
+ )
+ )
+
+ elif self.transformer_type == "continuous_transformer":
+
+ global_dim = None
+
+ if self.global_cond_type == "adaLN":
+ # The global conditioning is projected to the embed_dim already at this point
+ global_dim = embed_dim
+
+ self.transformer = ContinuousTransformer(
+ dim=embed_dim,
+ depth=depth,
+ dim_heads=embed_dim // num_heads,
+ dim_in=dim_in * patch_size,
+ dim_out=io_channels * patch_size,
+ cross_attend=cond_token_dim > 0,
+ cond_token_dim=cond_embed_dim,
+ global_cond_dim=global_dim,
+ **kwargs
+ )
+ elif self.transformer_type == "continuous_transformer_with_mask":
+
+ global_dim = None
+
+ if self.global_cond_type == "adaLN":
+ # The global conditioning is projected to the embed_dim already at this point
+ global_dim = embed_dim
+
+ self.transformer = ContinuousTransformer_mask(
+ dim=embed_dim,
+ depth=depth,
+ dim_heads=embed_dim // num_heads,
+ dim_in=dim_in * patch_size,
+ dim_out=io_channels * patch_size,
+ cross_attend=cond_token_dim > 0,
+ cond_token_dim=cond_embed_dim,
+ global_cond_dim=global_dim,
+ **kwargs
+ )
+
+ else:
+ raise ValueError(f"Unknown transformer type: {self.transformer_type}")
+
+ self.preprocess_conv = nn.Conv1d(dim_in, dim_in, 1, bias=False)
+ nn.init.zeros_(self.preprocess_conv.weight)
+ self.postprocess_conv = nn.Conv1d(io_channels, io_channels, 1, bias=False)
+ nn.init.zeros_(self.postprocess_conv.weight)
+
+ def _forward(
+ self,
+ x,
+ t,
+ mask=None,
+ cross_attn_cond=None,
+ cross_attn_cond_mask=None,
+ input_concat_cond=None,
+ global_embed=None,
+ prepend_cond=None,
+ prepend_cond_mask=None,
+ return_info=False,
+ **kwargs):
+ ### 1. 需要重新写过以适应不同长度的con
+ if cross_attn_cond is not None:
+ cross_attn_cond = self.to_cond_embed(cross_attn_cond)
+
+ if global_embed is not None:
+ # Project the global conditioning to the embedding dimension
+ global_embed = self.to_global_embed(global_embed)
+
+ prepend_inputs = None
+ prepend_mask = None
+ prepend_length = 0
+ if prepend_cond is not None:
+ # Project the prepend conditioning to the embedding dimension
+ prepend_cond = self.to_prepend_embed(prepend_cond)
+
+ prepend_inputs = prepend_cond
+ if prepend_cond_mask is not None:
+ prepend_mask = prepend_cond_mask
+
+ if input_concat_cond is not None:
+
+ # Interpolate input_concat_cond to the same length as x
+ if input_concat_cond.shape[2] != x.shape[2]:
+ input_concat_cond = F.interpolate(input_concat_cond, (x.shape[2],), mode='nearest')
+
+ x = torch.cat([x, input_concat_cond], dim=1)
+
+ # Get the batch of timestep embeddings
+ try:
+ timestep_embed = self.to_timestep_embed(self.timestep_features(t[:, None])) # (b, embed_dim)
+ except Exception as e:
+ print("t.shape:", t.shape, "x.shape", x.shape)
+ print("t:", t)
+ raise e
+
+ # Timestep embedding is considered a global embedding. Add to the global conditioning if it exists
+ if global_embed is not None:
+ global_embed = global_embed + timestep_embed
+ else:
+ global_embed = timestep_embed
+
+ # Add the global_embed to the prepend inputs if there is no global conditioning support in the transformer
+ if self.global_cond_type == "prepend":
+ if prepend_inputs is None:
+ # Prepend inputs are just the global embed, and the mask is all ones
+ prepend_inputs = global_embed.unsqueeze(1)
+ prepend_mask = torch.ones((x.shape[0], 1), device=x.device, dtype=torch.bool)
+ else:
+ # Prepend inputs are the prepend conditioning + the global embed
+ prepend_inputs = torch.cat([prepend_inputs, global_embed.unsqueeze(1)], dim=1)
+ prepend_mask = torch.cat([prepend_mask, torch.ones((x.shape[0], 1), device=x.device, dtype=torch.bool)],
+ dim=1)
+
+ prepend_length = prepend_inputs.shape[1]
+
+ x = self.preprocess_conv(x) + x
+
+ x = rearrange(x, "b c t -> b t c")
+
+ extra_args = {}
+
+ if self.global_cond_type == "adaLN":
+ extra_args["global_cond"] = global_embed
+
+ if self.patch_size > 1:
+ x = rearrange(x, "b (t p) c -> b t (c p)", p=self.patch_size)
+
+ if self.transformer_type == "x-transformers":
+ output = self.transformer(x, prepend_embeds=prepend_inputs, context=cross_attn_cond,
+ context_mask=cross_attn_cond_mask, mask=mask, prepend_mask=prepend_mask,
+ **extra_args, **kwargs)
+ elif self.transformer_type in ["continuous_transformer","continuous_transformer_with_mask"] :
+ output = self.transformer(x, prepend_embeds=prepend_inputs, context=cross_attn_cond,
+ context_mask=cross_attn_cond_mask, mask=mask, prepend_mask=prepend_mask,
+ return_info=return_info, **extra_args, **kwargs)
+
+ if return_info:
+ output, info = output
+ elif self.transformer_type == "mm_transformer":
+ output = self.transformer(x, context=cross_attn_cond, mask=mask, context_mask=cross_attn_cond_mask,
+ **extra_args, **kwargs)
+
+ output = rearrange(output, "b t c -> b c t")[:, :, prepend_length:]
+
+ if self.patch_size > 1:
+ output = rearrange(output, "b (c p) t -> b c (t p)", p=self.patch_size)
+
+ output = self.postprocess_conv(output) + output
+
+ if return_info:
+ return output, info
+
+ return output
+
+ def forward(
+ self,
+ x,
+ t,
+ cross_attn_cond=None,
+ cross_attn_cond_mask=None,
+ negative_cross_attn_cond=None,
+ negative_cross_attn_mask=None,
+ input_concat_cond=None,
+ global_embed=None,
+ negative_global_embed=None,
+ prepend_cond=None,
+ prepend_cond_mask=None,
+ cfg_scale=1.0,
+ cfg_dropout_prob=0.0,
+ causal=False,
+ scale_phi=0.0,
+ mask=None,
+ return_info=False,
+ **kwargs):
+
+ assert causal == False, "Causal mode is not supported for DiffusionTransformer"
+
+ if cross_attn_cond_mask is not None:
+ cross_attn_cond_mask = cross_attn_cond_mask.bool()
+
+ cross_attn_cond_mask = None # Temporarily disabling conditioning masks due to kernel issue for flash attention
+
+ if prepend_cond_mask is not None:
+ prepend_cond_mask = prepend_cond_mask.bool()
+
+ # CFG dropout
+ if cfg_dropout_prob > 0.0:
+ if cross_attn_cond is not None:
+ null_embed = torch.zeros_like(cross_attn_cond, device=cross_attn_cond.device)
+ dropout_mask = torch.bernoulli(
+ torch.full((cross_attn_cond.shape[0], 1, 1), cfg_dropout_prob, device=cross_attn_cond.device)).to(
+ torch.bool)
+ cross_attn_cond = torch.where(dropout_mask, null_embed, cross_attn_cond)
+
+ if prepend_cond is not None:
+ null_embed = torch.zeros_like(prepend_cond, device=prepend_cond.device)
+ dropout_mask = torch.bernoulli(
+ torch.full((prepend_cond.shape[0], 1, 1), cfg_dropout_prob, device=prepend_cond.device)).to(
+ torch.bool)
+ prepend_cond = torch.where(dropout_mask, null_embed, prepend_cond)
+
+ if cfg_scale != 1.0 and (cross_attn_cond is not None or prepend_cond is not None):
+ # Classifier-free guidance
+ # Concatenate conditioned and unconditioned inputs on the batch dimension
+ batch_inputs = torch.cat([x, x], dim=0)
+ batch_timestep = torch.cat([t, t], dim=0)
+
+ if global_embed is not None:
+ batch_global_cond = torch.cat([global_embed, global_embed], dim=0)
+ else:
+ batch_global_cond = None
+
+ if input_concat_cond is not None:
+ batch_input_concat_cond = torch.cat([input_concat_cond, input_concat_cond], dim=0)
+ else:
+ batch_input_concat_cond = None
+
+ batch_cond = None
+ batch_cond_masks = None
+
+ # Handle CFG for cross-attention conditioning
+ if cross_attn_cond is not None:
+
+ null_embed = torch.zeros_like(cross_attn_cond, device=cross_attn_cond.device)
+
+ # For negative cross-attention conditioning, replace the null embed with the negative cross-attention conditioning
+ if negative_cross_attn_cond is not None:
+
+ # If there's a negative cross-attention mask, set the masked tokens to the null embed
+ if negative_cross_attn_mask is not None:
+ negative_cross_attn_mask = negative_cross_attn_mask.to(torch.bool).unsqueeze(2)
+
+ negative_cross_attn_cond = torch.where(negative_cross_attn_mask, negative_cross_attn_cond,
+ null_embed)
+
+ batch_cond = torch.cat([cross_attn_cond, negative_cross_attn_cond], dim=0)
+
+ else:
+ batch_cond = torch.cat([cross_attn_cond, null_embed], dim=0)
+
+ if cross_attn_cond_mask is not None:
+ batch_cond_masks = torch.cat([cross_attn_cond_mask, cross_attn_cond_mask], dim=0)
+
+ batch_prepend_cond = None
+ batch_prepend_cond_mask = None
+
+ if prepend_cond is not None:
+
+ null_embed = torch.zeros_like(prepend_cond, device=prepend_cond.device)
+
+ batch_prepend_cond = torch.cat([prepend_cond, null_embed], dim=0)
+
+ if prepend_cond_mask is not None:
+ batch_prepend_cond_mask = torch.cat([prepend_cond_mask, prepend_cond_mask], dim=0)
+
+ if mask is not None:
+ batch_masks = torch.cat([mask, mask], dim=0)
+ else:
+ batch_masks = None
+
+ batch_output = self._forward(
+ batch_inputs,
+ batch_timestep,
+ cross_attn_cond=batch_cond,
+ cross_attn_cond_mask=batch_cond_masks,
+ mask=batch_masks,
+ input_concat_cond=batch_input_concat_cond,
+ global_embed=batch_global_cond,
+ prepend_cond=batch_prepend_cond,
+ prepend_cond_mask=batch_prepend_cond_mask,
+ return_info=return_info,
+ **kwargs)
+
+ if return_info:
+ batch_output, info = batch_output
+
+ cond_output, uncond_output = torch.chunk(batch_output, 2, dim=0)
+ cfg_output = uncond_output + (cond_output - uncond_output) * cfg_scale
+
+ # CFG Rescale
+ if scale_phi != 0.0:
+ cond_out_std = cond_output.std(dim=1, keepdim=True)
+ out_cfg_std = cfg_output.std(dim=1, keepdim=True)
+ output = scale_phi * (cfg_output * (cond_out_std / out_cfg_std)) + (1 - scale_phi) * cfg_output
+ else:
+ output = cfg_output
+
+ if return_info:
+ return output, info
+
+ return output
+
+ else:
+ return self._forward(
+ x,
+ t,
+ cross_attn_cond=cross_attn_cond,
+ cross_attn_cond_mask=cross_attn_cond_mask,
+ input_concat_cond=input_concat_cond,
+ global_embed=global_embed,
+ prepend_cond=prepend_cond,
+ prepend_cond_mask=prepend_cond_mask,
+ mask=mask,
+ return_info=return_info,
+ **kwargs
+ )
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/dit_v2.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/dit_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..b4baad9e5a91561a1c994f2000d75618fa97ba60
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/dit_v2.py
@@ -0,0 +1,307 @@
+import typing as tp
+
+import torch
+
+from einops import rearrange
+from torch import nn
+from torch.nn import functional as F
+from x_transformers import ContinuousTransformerWrapper, Encoder
+
+from .blocks import FourierFeatures
+from .transformer import ContinuousTransformer
+from model.stable import transformer_use_mask
+
+
+class DiffusionTransformerV2(nn.Module):
+ def __init__(self,
+ io_channels=32,
+ patch_size=1,
+ embed_dim=768,
+ cond_token_dim=0,
+ project_cond_tokens=True,
+ global_cond_dim=0,
+ project_global_cond=True,
+ input_concat_dim=0,
+ prepend_cond_dim=0,
+ depth=12,
+ num_heads=8,
+ transformer_type: tp.Literal["x-transformers", "continuous_transformer"] = "x-transformers",
+ global_cond_type: tp.Literal["prepend", "adaLN"] = "prepend",
+ **kwargs):
+
+ super().__init__()
+ d_model = embed_dim
+ n_head = num_heads
+ n_layers = depth
+ encoder_layer = torch.nn.TransformerEncoderLayer(batch_first=True,
+ norm_first=True,
+ d_model=d_model,
+ nhead=n_head)
+ self.transformer = torch.nn.TransformerEncoder(encoder_layer, num_layers=n_layers)
+
+ # ===================================== timestep embedding
+ timestep_features_dim = 256
+ self.timestep_features = FourierFeatures(1, timestep_features_dim)
+ self.to_timestep_embed = nn.Sequential(
+ nn.Linear(timestep_features_dim, embed_dim, bias=True),
+ nn.SiLU(),
+ nn.Linear(embed_dim, embed_dim, bias=True),
+ )
+
+
+ def _forward(
+ self,
+ Xt_btd,
+ t, #(1d)
+ mu_btd,
+ ):
+
+ timestep_embed = self.to_timestep_embed(self.timestep_features(t[:, None])) # (b, embed_dim)
+ cated_input = torch.cat([t,mu,x_t])
+
+ ### 1. 需要重新写过以适应不同长度的con
+ if cross_attn_cond is not None:
+ cross_attn_cond = self.to_cond_embed(cross_attn_cond)
+
+ if global_embed is not None:
+ # Project the global conditioning to the embedding dimension
+ global_embed = self.to_global_embed(global_embed)
+
+ prepend_inputs = None
+ prepend_mask = None
+ prepend_length = 0
+ if prepend_cond is not None:
+ # Project the prepend conditioning to the embedding dimension
+ prepend_cond = self.to_prepend_embed(prepend_cond)
+
+ prepend_inputs = prepend_cond
+ if prepend_cond_mask is not None:
+ prepend_mask = prepend_cond_mask
+
+ if input_concat_cond is not None:
+
+ # Interpolate input_concat_cond to the same length as x
+ if input_concat_cond.shape[2] != x.shape[2]:
+ input_concat_cond = F.interpolate(input_concat_cond, (x.shape[2],), mode='nearest')
+
+ x = torch.cat([x, input_concat_cond], dim=1)
+
+ # Get the batch of timestep embeddings
+ try:
+ timestep_embed = self.to_timestep_embed(self.timestep_features(t[:, None])) # (b, embed_dim)
+ except Exception as e:
+ print("t.shape:", t.shape, "x.shape", x.shape)
+ print("t:", t)
+ raise e
+
+ # Timestep embedding is considered a global embedding. Add to the global conditioning if it exists
+ if global_embed is not None:
+ global_embed = global_embed + timestep_embed
+ else:
+ global_embed = timestep_embed
+
+ # Add the global_embed to the prepend inputs if there is no global conditioning support in the transformer
+ if self.global_cond_type == "prepend":
+ if prepend_inputs is None:
+ # Prepend inputs are just the global embed, and the mask is all ones
+ prepend_inputs = global_embed.unsqueeze(1)
+ prepend_mask = torch.ones((x.shape[0], 1), device=x.device, dtype=torch.bool)
+ else:
+ # Prepend inputs are the prepend conditioning + the global embed
+ prepend_inputs = torch.cat([prepend_inputs, global_embed.unsqueeze(1)], dim=1)
+ prepend_mask = torch.cat([prepend_mask, torch.ones((x.shape[0], 1), device=x.device, dtype=torch.bool)],
+ dim=1)
+
+ prepend_length = prepend_inputs.shape[1]
+
+ x = self.preprocess_conv(x) + x
+
+ x = rearrange(x, "b c t -> b t c")
+
+ extra_args = {}
+
+ if self.global_cond_type == "adaLN":
+ extra_args["global_cond"] = global_embed
+
+ if self.patch_size > 1:
+ x = rearrange(x, "b (t p) c -> b t (c p)", p=self.patch_size)
+
+ if self.transformer_type == "x-transformers":
+ output = self.transformer(x, prepend_embeds=prepend_inputs, context=cross_attn_cond,
+ context_mask=cross_attn_cond_mask, mask=mask, prepend_mask=prepend_mask,
+ **extra_args, **kwargs)
+ elif self.transformer_type in ["continuous_transformer", "continuous_transformer_with_mask"]:
+ output = self.transformer(x, prepend_embeds=prepend_inputs, context=cross_attn_cond,
+ context_mask=cross_attn_cond_mask, mask=mask, prepend_mask=prepend_mask,
+ return_info=return_info, **extra_args, **kwargs)
+
+ if return_info:
+ output, info = output
+ elif self.transformer_type == "mm_transformer":
+ output = self.transformer(x, context=cross_attn_cond, mask=mask, context_mask=cross_attn_cond_mask,
+ **extra_args, **kwargs)
+
+ output = rearrange(output, "b t c -> b c t")[:, :, prepend_length:]
+
+ if self.patch_size > 1:
+ output = rearrange(output, "b (c p) t -> b c (t p)", p=self.patch_size)
+
+ output = self.postprocess_conv(output) + output
+
+ if return_info:
+ return output, info
+
+ return output
+
+ def forward(
+ self,
+ x,
+ t,
+ cross_attn_cond=None,
+ cross_attn_cond_mask=None,
+ negative_cross_attn_cond=None,
+ negative_cross_attn_mask=None,
+ input_concat_cond=None,
+ global_embed=None,
+ negative_global_embed=None,
+ prepend_cond=None,
+ prepend_cond_mask=None,
+ cfg_scale=1.0,
+ cfg_dropout_prob=0.0,
+ causal=False,
+ scale_phi=0.0,
+ mask=None,
+ return_info=False,
+ **kwargs):
+
+ assert causal == False, "Causal mode is not supported for DiffusionTransformer"
+
+ if cross_attn_cond_mask is not None:
+ cross_attn_cond_mask = cross_attn_cond_mask.bool()
+
+ cross_attn_cond_mask = None # Temporarily disabling conditioning masks due to kernel issue for flash attention
+
+ if prepend_cond_mask is not None:
+ prepend_cond_mask = prepend_cond_mask.bool()
+
+ # CFG dropout
+ if cfg_dropout_prob > 0.0:
+ if cross_attn_cond is not None:
+ null_embed = torch.zeros_like(cross_attn_cond, device=cross_attn_cond.device)
+ dropout_mask = torch.bernoulli(
+ torch.full((cross_attn_cond.shape[0], 1, 1), cfg_dropout_prob, device=cross_attn_cond.device)).to(
+ torch.bool)
+ cross_attn_cond = torch.where(dropout_mask, null_embed, cross_attn_cond)
+
+ if prepend_cond is not None:
+ null_embed = torch.zeros_like(prepend_cond, device=prepend_cond.device)
+ dropout_mask = torch.bernoulli(
+ torch.full((prepend_cond.shape[0], 1, 1), cfg_dropout_prob, device=prepend_cond.device)).to(
+ torch.bool)
+ prepend_cond = torch.where(dropout_mask, null_embed, prepend_cond)
+
+ if cfg_scale != 1.0 and (cross_attn_cond is not None or prepend_cond is not None):
+ # Classifier-free guidance
+ # Concatenate conditioned and unconditioned inputs on the batch dimension
+ batch_inputs = torch.cat([x, x], dim=0)
+ batch_timestep = torch.cat([t, t], dim=0)
+
+ if global_embed is not None:
+ batch_global_cond = torch.cat([global_embed, global_embed], dim=0)
+ else:
+ batch_global_cond = None
+
+ if input_concat_cond is not None:
+ batch_input_concat_cond = torch.cat([input_concat_cond, input_concat_cond], dim=0)
+ else:
+ batch_input_concat_cond = None
+
+ batch_cond = None
+ batch_cond_masks = None
+
+ # Handle CFG for cross-attention conditioning
+ if cross_attn_cond is not None:
+
+ null_embed = torch.zeros_like(cross_attn_cond, device=cross_attn_cond.device)
+
+ # For negative cross-attention conditioning, replace the null embed with the negative cross-attention conditioning
+ if negative_cross_attn_cond is not None:
+
+ # If there's a negative cross-attention mask, set the masked tokens to the null embed
+ if negative_cross_attn_mask is not None:
+ negative_cross_attn_mask = negative_cross_attn_mask.to(torch.bool).unsqueeze(2)
+
+ negative_cross_attn_cond = torch.where(negative_cross_attn_mask, negative_cross_attn_cond,
+ null_embed)
+
+ batch_cond = torch.cat([cross_attn_cond, negative_cross_attn_cond], dim=0)
+
+ else:
+ batch_cond = torch.cat([cross_attn_cond, null_embed], dim=0)
+
+ if cross_attn_cond_mask is not None:
+ batch_cond_masks = torch.cat([cross_attn_cond_mask, cross_attn_cond_mask], dim=0)
+
+ batch_prepend_cond = None
+ batch_prepend_cond_mask = None
+
+ if prepend_cond is not None:
+
+ null_embed = torch.zeros_like(prepend_cond, device=prepend_cond.device)
+
+ batch_prepend_cond = torch.cat([prepend_cond, null_embed], dim=0)
+
+ if prepend_cond_mask is not None:
+ batch_prepend_cond_mask = torch.cat([prepend_cond_mask, prepend_cond_mask], dim=0)
+
+ if mask is not None:
+ batch_masks = torch.cat([mask, mask], dim=0)
+ else:
+ batch_masks = None
+
+ batch_output = self._forward(
+ batch_inputs,
+ batch_timestep,
+ cross_attn_cond=batch_cond,
+ cross_attn_cond_mask=batch_cond_masks,
+ mask=batch_masks,
+ input_concat_cond=batch_input_concat_cond,
+ global_embed=batch_global_cond,
+ prepend_cond=batch_prepend_cond,
+ prepend_cond_mask=batch_prepend_cond_mask,
+ return_info=return_info,
+ **kwargs)
+
+ if return_info:
+ batch_output, info = batch_output
+
+ cond_output, uncond_output = torch.chunk(batch_output, 2, dim=0)
+ cfg_output = uncond_output + (cond_output - uncond_output) * cfg_scale
+
+ # CFG Rescale
+ if scale_phi != 0.0:
+ cond_out_std = cond_output.std(dim=1, keepdim=True)
+ out_cfg_std = cfg_output.std(dim=1, keepdim=True)
+ output = scale_phi * (cfg_output * (cond_out_std / out_cfg_std)) + (1 - scale_phi) * cfg_output
+ else:
+ output = cfg_output
+
+ if return_info:
+ return output, info
+
+ return output
+
+ else:
+ return self._forward(
+ x,
+ t,
+ cross_attn_cond=cross_attn_cond,
+ cross_attn_cond_mask=cross_attn_cond_mask,
+ input_concat_cond=input_concat_cond,
+ global_embed=global_embed,
+ prepend_cond=prepend_cond,
+ prepend_cond_mask=prepend_cond_mask,
+ mask=mask,
+ return_info=return_info,
+ **kwargs
+ )
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/sampling.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/sampling.py
new file mode 100644
index 0000000000000000000000000000000000000000..2229e5089e3407a367df2d382ae039ca6364c489
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/sampling.py
@@ -0,0 +1,232 @@
+import torch
+import math
+from tqdm import trange, tqdm
+
+import k_diffusion as K
+
+# Define the noise schedule and sampling loop
+def get_alphas_sigmas(t):
+ """Returns the scaling factors for the clean image (alpha) and for the
+ noise (sigma), given a timestep."""
+ return torch.cos(t * math.pi / 2), torch.sin(t * math.pi / 2)
+
+def alpha_sigma_to_t(alpha, sigma):
+ """Returns a timestep, given the scaling factors for the clean image and for
+ the noise."""
+ return torch.atan2(sigma, alpha) / math.pi * 2
+
+def t_to_alpha_sigma(t):
+ """Returns the scaling factors for the clean image and for the noise, given
+ a timestep."""
+ return torch.cos(t * math.pi / 2), torch.sin(t * math.pi / 2)
+
+
+@torch.no_grad()
+def sample_discrete_euler(model, x, steps, sigma_max=1, **extra_args):
+ """Draws samples from a model given starting noise. Euler method"""
+
+ # Make tensor of ones to broadcast the single t values
+ ts = x.new_ones([x.shape[0]])
+
+ # Create the noise schedule
+ t = torch.linspace(sigma_max, 0, steps + 1)
+
+ #alphas, sigmas = 1-t, t
+
+ for t_curr, t_prev in tqdm(zip(t[:-1], t[1:])):
+ # Broadcast the current timestep to the correct shape
+ t_curr_tensor = t_curr * torch.ones(
+ (x.shape[0],), dtype=x.dtype, device=x.device
+ )
+ dt = t_prev - t_curr # we solve backwards in our formulation
+ x = x + dt * model(x, t_curr_tensor, **extra_args) #.denoise(x, denoiser, t_curr_tensor, cond, uc)
+
+ # If we are on the last timestep, output the denoised image
+ return x
+
+@torch.no_grad()
+def sample(model, x, steps, eta, **extra_args):
+ """Draws samples from a model given starting noise. v-diffusion"""
+ ts = x.new_ones([x.shape[0]])
+
+ # Create the noise schedule
+ t = torch.linspace(1, 0, steps + 1)[:-1]
+
+ alphas, sigmas = get_alphas_sigmas(t)
+
+ # The sampling loop
+ for i in trange(steps):
+
+ # Get the model output (v, the predicted velocity)
+ with torch.cuda.amp.autocast():
+ v = model(x, ts * t[i], **extra_args).float()
+
+ # Predict the noise and the denoised image
+ pred = x * alphas[i] - v * sigmas[i]
+ eps = x * sigmas[i] + v * alphas[i]
+
+ # If we are not on the last timestep, compute the noisy image for the
+ # next timestep.
+ if i < steps - 1:
+ # If eta > 0, adjust the scaling factor for the predicted noise
+ # downward according to the amount of additional noise to add
+ ddim_sigma = eta * (sigmas[i + 1]**2 / sigmas[i]**2).sqrt() * \
+ (1 - alphas[i]**2 / alphas[i + 1]**2).sqrt()
+ adjusted_sigma = (sigmas[i + 1]**2 - ddim_sigma**2).sqrt()
+
+ # Recombine the predicted noise and predicted denoised image in the
+ # correct proportions for the next step
+ x = pred * alphas[i + 1] + eps * adjusted_sigma
+
+ # Add the correct amount of fresh noise
+ if eta:
+ x += torch.randn_like(x) * ddim_sigma
+
+ # If we are on the last timestep, output the denoised image
+ return pred
+
+# Soft mask inpainting is just shrinking hard (binary) mask inpainting
+# Given a float-valued soft mask (values between 0 and 1), get the binary mask for this particular step
+def get_bmask(i, steps, mask):
+ strength = (i+1)/(steps)
+ # convert to binary mask
+ bmask = torch.where(mask<=strength,1,0)
+ return bmask
+
+def make_cond_model_fn(model, cond_fn):
+ def cond_model_fn(x, sigma, **kwargs):
+ with torch.enable_grad():
+ x = x.detach().requires_grad_()
+ denoised = model(x, sigma, **kwargs)
+ cond_grad = cond_fn(x, sigma, denoised=denoised, **kwargs).detach()
+ cond_denoised = denoised.detach() + cond_grad * K.utils.append_dims(sigma**2, x.ndim)
+ return cond_denoised
+ return cond_model_fn
+
+# Uses k-diffusion from https://github.com/crowsonkb/k-diffusion
+# init_data is init_audio as latents (if this is latent diffusion)
+# For sampling, set both init_data and mask to None
+# For variations, set init_data
+# For inpainting, set both init_data & mask
+def sample_k(
+ model_fn,
+ noise,
+ init_data=None,
+ mask=None,
+ steps=100,
+ sampler_type="dpmpp-2m-sde",
+ sigma_min=0.5,
+ sigma_max=50,
+ rho=1.0, device="cuda",
+ callback=None,
+ cond_fn=None,
+ **extra_args
+ ):
+
+ denoiser = K.external.VDenoiser(model_fn)
+
+ if cond_fn is not None:
+ denoiser = make_cond_model_fn(denoiser, cond_fn)
+
+ # Make the list of sigmas. Sigma values are scalars related to the amount of noise each denoising step has
+ sigmas = K.sampling.get_sigmas_polyexponential(steps, sigma_min, sigma_max, rho, device=device)
+ # Scale the initial noise by sigma
+ noise = noise * sigmas[0]
+
+ wrapped_callback = callback
+
+ if mask is None and init_data is not None:
+ # VARIATION (no inpainting)
+ # set the initial latent to the init_data, and noise it with initial sigma
+ x = init_data + noise
+ elif mask is not None and init_data is not None:
+ # INPAINTING
+ bmask = get_bmask(0, steps, mask)
+ # initial noising
+ input_noised = init_data + noise
+ # set the initial latent to a mix of init_data and noise, based on step 0's binary mask
+ x = input_noised * bmask + noise * (1-bmask)
+ # define the inpainting callback function (Note: side effects, it mutates x)
+ # See https://github.com/crowsonkb/k-diffusion/blob/master/k_diffusion/sampling.py#L596C13-L596C105
+ # callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised})
+ # This is called immediately after `denoised = model(x, sigmas[i] * s_in, **extra_args)`
+ def inpainting_callback(args):
+ i = args["i"]
+ x = args["x"]
+ sigma = args["sigma"]
+ #denoised = args["denoised"]
+ # noise the init_data input with this step's appropriate amount of noise
+ input_noised = init_data + torch.randn_like(init_data) * sigma
+ # shrinking hard mask
+ bmask = get_bmask(i, steps, mask)
+ # mix input_noise with x, using binary mask
+ new_x = input_noised * bmask + x * (1-bmask)
+ # mutate x
+ x[:,:,:] = new_x[:,:,:]
+ # wrap together the inpainting callback and the user-submitted callback.
+ if callback is None:
+ wrapped_callback = inpainting_callback
+ else:
+ wrapped_callback = lambda args: (inpainting_callback(args), callback(args))
+ else:
+ # SAMPLING
+ # set the initial latent to noise
+ x = noise
+
+
+ with torch.cuda.amp.autocast():
+ if sampler_type == "k-heun":
+ return K.sampling.sample_heun(denoiser, x, sigmas, disable=False, callback=wrapped_callback, extra_args=extra_args)
+ elif sampler_type == "k-lms":
+ return K.sampling.sample_lms(denoiser, x, sigmas, disable=False, callback=wrapped_callback, extra_args=extra_args)
+ elif sampler_type == "k-dpmpp-2s-ancestral":
+ return K.sampling.sample_dpmpp_2s_ancestral(denoiser, x, sigmas, disable=False, callback=wrapped_callback, extra_args=extra_args)
+ elif sampler_type == "k-dpm-2":
+ return K.sampling.sample_dpm_2(denoiser, x, sigmas, disable=False, callback=wrapped_callback, extra_args=extra_args)
+ elif sampler_type == "k-dpm-fast":
+ return K.sampling.sample_dpm_fast(denoiser, x, sigma_min, sigma_max, steps, disable=False, callback=wrapped_callback, extra_args=extra_args)
+ elif sampler_type == "k-dpm-adaptive":
+ return K.sampling.sample_dpm_adaptive(denoiser, x, sigma_min, sigma_max, rtol=0.01, atol=0.01, disable=False, callback=wrapped_callback, extra_args=extra_args)
+ elif sampler_type == "dpmpp-2m-sde":
+ return K.sampling.sample_dpmpp_2m_sde(denoiser, x, sigmas, disable=False, callback=wrapped_callback, extra_args=extra_args)
+ elif sampler_type == "dpmpp-3m-sde":
+ return K.sampling.sample_dpmpp_3m_sde(denoiser, x, sigmas, disable=False, callback=wrapped_callback, extra_args=extra_args)
+
+# Uses discrete Euler sampling for rectified flow models
+# init_data is init_audio as latents (if this is latent diffusion)
+# For sampling, set both init_data and mask to None
+# For variations, set init_data
+# For inpainting, set both init_data & mask
+def sample_rf(
+ model_fn,
+ noise,
+ init_data=None,
+ steps=100,
+ sigma_max=1,
+ device="cuda",
+ callback=None,
+ cond_fn=None,
+ **extra_args
+ ):
+
+ if sigma_max > 1:
+ sigma_max = 1
+
+ if cond_fn is not None:
+ denoiser = make_cond_model_fn(denoiser, cond_fn)
+
+ wrapped_callback = callback
+
+ if init_data is not None:
+ # VARIATION (no inpainting)
+ # Interpolate the init data and the noise for init audio
+ x = init_data * (1 - sigma_max) + noise * sigma_max
+ else:
+ # SAMPLING
+ # set the initial latent to noise
+ x = noise
+
+ with torch.cuda.amp.autocast():
+ # TODO: Add callback support
+ #return sample_discrete_euler(model_fn, x, steps, sigma_max, callback=wrapped_callback, **extra_args)
+ return sample_discrete_euler(model_fn, x, steps, sigma_max, **extra_args)
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/stable_diffusion.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/stable_diffusion.py
new file mode 100644
index 0000000000000000000000000000000000000000..732ef506c5e95ada6566176d9ffc3ea99a4cb7ab
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/stable_diffusion.py
@@ -0,0 +1,109 @@
+import torch
+from torch.nn import functional as F
+from .dit import DiffusionTransformer
+from .adp import UNet1d
+from .sampling import sample
+import math
+from model.base import BaseModule
+import pdb
+
+target_length = 1536
+
+
+def pad_and_create_mask(matrix, target_length):
+ T = matrix.shape[2]
+ if T > target_length:
+ raise ValueError("The third dimension length %s should not exceed %s" % (T, target_length))
+
+ padding_size = target_length - T
+
+ padded_matrix = F.pad(matrix, (0, padding_size), "constant", 0)
+
+ mask = torch.ones((1, target_length))
+ mask[:, T:] = 0 # Set the padding part to 0
+
+ return padded_matrix.to(matrix.device), mask.to(matrix.device)
+
+
+class Stable_Diffusion(BaseModule):
+ def __init__(self, io_channels, input_concat_dim=None, embed_dim=768, depth=24, num_heads=24,
+ project_cond_tokens=False, transformer_type="continuous_transformer"):
+ super(Stable_Diffusion, self).__init__()
+ self.diffusion = DiffusionTransformer(
+ io_channels=io_channels,
+ input_concat_dim=input_concat_dim,
+ embed_dim=embed_dim,
+ # cond_token_dim=target_length,
+ depth=depth,
+ num_heads=num_heads,
+ project_cond_tokens=project_cond_tokens,
+ transformer_type=transformer_type,
+ )
+ # self.diffusion = UNet1d(
+ # in_channels=80,
+ # channels=256,
+ # resnet_groups=16,
+ # kernel_multiplier_downsample=2,
+ # multipliers=[4, 4, 4, 5, 5],
+ # factors=[1, 2, 2, 4], # 输入长度不一致卷积缩短
+ # num_blocks=[2, 2, 2, 2],
+ # attentions=[1, 3, 3, 3, 3],
+ # attention_heads=16,
+ # attention_multiplier=4,
+ # use_nearest_upsample=False,
+ # use_skip_scale=True,
+ # use_context_time=True
+ # )
+ self.rng = torch.quasirandom.SobolEngine(1, scramble=True)
+
+ @torch.no_grad()
+ def forward(self, mu, mask, n_timesteps):
+ # pdb.set_trace()
+ mask = mask.squeeze(1)
+ noise = torch.randn_like(mu).to(mu.device)
+ # mu_pad, mu_pad_mask = pad_and_create_mask(mu, target_length)
+ # extra_args = {"cross_attn_cond": mu, "cross_attn_cond_mask": mask, "mask": mask}
+ extra_args = {"input_concat_cond": mu, "mask": mask}
+ fakes = sample(self.diffusion, noise, n_timesteps, 0, **extra_args)
+
+ return fakes
+
+ def compute_loss(self, x0, mask, mu):
+
+ # pdb.set_trace()
+ t = self.rng.draw(x0.shape[0])[:, 0].to(x0.device)
+ alphas, sigmas = torch.cos(t * math.pi / 2), torch.sin(t * math.pi / 2)
+
+ alphas = alphas[:, None, None]
+ sigmas = sigmas[:, None, None]
+ noise = torch.randn_like(x0)
+ noised_inputs = x0 * alphas + noise * sigmas
+ targets = noise * alphas - x0 * sigmas
+ mask = mask.squeeze(1)
+ # mu_pad, mu_pad_mask = pad_and_create_mask(mu, target_length)
+ # output = self.diffusion(noised_inputs, t, cross_attn_cond=mu,
+ # cross_attn_cond_mask=mask, mask=mask, cfg_dropout_prob=0.1)
+ # pdb.set_trace()
+ output = self.diffusion(noised_inputs, # [bs, 80, 229]
+ t, # (bs,)
+ input_concat_cond=mu,
+ mask=mask, # [bs, 229]
+ cfg_dropout_prob=0.1)
+
+ return self.mse_loss(output, targets, mask), output
+
+ def mse_loss(self, output, targets, mask):
+
+ mse_loss = F.mse_loss(output, targets, reduction='none')
+
+ if mask.ndim == 2 and mse_loss.ndim == 3:
+ mask = mask.unsqueeze(1)
+
+ if mask.shape[1] != mse_loss.shape[1]:
+ mask = mask.repeat(1, mse_loss.shape[1], 1)
+
+ mse_loss = mse_loss * mask
+
+ mse_loss = mse_loss.mean()
+
+ return mse_loss
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/stable_diffusion_test.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/stable_diffusion_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..b4fb79da70d084ba6571a12fb51f15bb331ea8d7
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/stable_diffusion_test.py
@@ -0,0 +1,104 @@
+import torch
+from torch.nn import functional as F
+from .dit import DiffusionTransformer
+from .adp import UNet1d
+from .sampling import sample
+import math
+from model.base import BaseModule
+import pdb
+
+target_length = 1536
+def pad_and_create_mask(matrix, target_length):
+
+ T = matrix.shape[2]
+ if T > target_length:
+ raise ValueError("The third dimension length %s should not exceed %s"%(T, target_length))
+
+ padding_size = target_length - T
+
+ padded_matrix = F.pad(matrix, (0, padding_size), "constant", 0)
+
+ mask = torch.ones((1, target_length))
+ mask[:, T:] = 0 # Set the padding part to 0
+
+ return padded_matrix.to(matrix.device), mask.to(matrix.device)
+
+
+class Stable_Diffusion(BaseModule):
+ def __init__(self):
+ super(Stable_Diffusion, self).__init__()
+ self.diffusion = DiffusionTransformer(
+ io_channels=80,
+ # input_concat_dim=80,
+ embed_dim=768,
+ # cond_token_dim=target_length,
+ depth=24,
+ num_heads=24,
+ project_cond_tokens=False,
+ transformer_type="continuous_transformer",
+ )
+ # self.diffusion = UNet1d(
+ # in_channels=80,
+ # channels=256,
+ # resnet_groups=16,
+ # kernel_multiplier_downsample=2,
+ # multipliers=[4, 4, 4, 5, 5],
+ # factors=[1, 2, 2, 4], # 输入长度不一致卷积缩短
+ # num_blocks=[2, 2, 2, 2],
+ # attentions=[1, 3, 3, 3, 3],
+ # attention_heads=16,
+ # attention_multiplier=4,
+ # use_nearest_upsample=False,
+ # use_skip_scale=True,
+ # use_context_time=True
+ # )
+ self.rng = torch.quasirandom.SobolEngine(1, scramble=True)
+
+ @torch.no_grad()
+ def forward(self, mu, mask, n_timesteps):
+ # pdb.set_trace()
+ mask = mask.squeeze(1)
+ # noise = torch.randn_like(mu).to(mu.device)
+ # mu_pad, mu_pad_mask = pad_and_create_mask(mu, target_length)
+ # extra_args = {"cross_attn_cond": mu, "cross_attn_cond_mask": mask, "mask": mask}
+ extra_args = {"mask": mask}
+ fakes = sample(self.diffusion, mu, n_timesteps, 0, **extra_args)
+
+ return fakes
+
+
+ def compute_loss(self, x0, mask, mu):
+
+ # pdb.set_trace()
+ t = self.rng.draw(x0.shape[0])[:, 0].to(x0.device)
+ alphas, sigmas = torch.cos(t * math.pi / 2), torch.sin(t * math.pi / 2)
+
+ alphas = alphas[:, None, None]
+ sigmas = sigmas[:, None, None]
+ noise = torch.randn_like(x0)
+ noised_inputs = x0 * alphas + noise * sigmas
+ targets = mu * alphas - x0 * sigmas
+ mask = mask.squeeze(1)
+ # mu_pad, mu_pad_mask = pad_and_create_mask(mu, target_length)
+ # output = self.diffusion(noised_inputs, t, cross_attn_cond=mu,
+ # cross_attn_cond_mask=mask, mask=mask, cfg_dropout_prob=0.1)
+ output = self.diffusion(noised_inputs, t, mask=mask, cfg_dropout_prob=0.1)
+
+ return self.mse_loss(output, targets, mask), output
+
+
+ def mse_loss(self, output, targets, mask):
+
+ mse_loss = F.mse_loss(output, targets, reduction='none')
+
+ if mask.ndim == 2 and mse_loss.ndim == 3:
+ mask = mask.unsqueeze(1)
+
+ if mask.shape[1] != mse_loss.shape[1]:
+ mask = mask.repeat(1, mse_loss.shape[1], 1)
+
+ mse_loss = mse_loss[mask]
+
+ mse_loss = mse_loss.mean()
+
+ return mse_loss
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/transformer.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/transformer.py
new file mode 100644
index 0000000000000000000000000000000000000000..417beeb78dc70d69fcbb323acbc8d9d7f9e22a09
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/transformer.py
@@ -0,0 +1,816 @@
+import pdb
+from functools import reduce, partial
+from packaging import version
+
+from einops import rearrange, repeat
+from einops.layers.torch import Rearrange
+import torch
+import torch.nn.functional as F
+from torch import nn, einsum
+from torch.cuda.amp import autocast
+from typing import Callable, Literal
+
+try:
+ from flash_attn import flash_attn_func, flash_attn_kvpacked_func
+except ImportError as e:
+ print(e)
+ print('flash_attn not installed, disabling Flash Attention')
+ flash_attn_kvpacked_func = None
+ flash_attn_func = None
+
+try:
+ import natten
+except ImportError:
+ natten = None
+
+def checkpoint(function, *args, **kwargs):
+ kwargs.setdefault("use_reentrant", False)
+ return torch.utils.checkpoint.checkpoint(function, *args, **kwargs)
+
+
+# Copied and modified from https://github.com/lucidrains/x-transformers/blob/main/x_transformers/attend.py under MIT License
+# License can be found in LICENSES/LICENSE_XTRANSFORMERS.txt
+
+def create_causal_mask(i, j, device):
+ return torch.ones((i, j), device = device, dtype = torch.bool).triu(j - i + 1)
+
+def or_reduce(masks):
+ head, *body = masks
+ for rest in body:
+ head = head | rest
+ return head
+
+# positional embeddings
+
+class AbsolutePositionalEmbedding(nn.Module):
+ def __init__(self, dim, max_seq_len):
+ super().__init__()
+ self.scale = dim ** -0.5
+ self.max_seq_len = max_seq_len
+ self.emb = nn.Embedding(max_seq_len, dim)
+
+ def forward(self, x, pos = None, seq_start_pos = None):
+ seq_len, device = x.shape[1], x.device
+ assert seq_len <= self.max_seq_len, f'you are passing in a sequence length of {seq_len} but your absolute positional embedding has a max sequence length of {self.max_seq_len}'
+
+ if pos is None:
+ pos = torch.arange(seq_len, device = device)
+
+ if seq_start_pos is not None:
+ pos = (pos - seq_start_pos[..., None]).clamp(min = 0)
+
+ pos_emb = self.emb(pos)
+ pos_emb = pos_emb * self.scale
+ return pos_emb
+
+class ScaledSinusoidalEmbedding(nn.Module):
+ def __init__(self, dim, theta = 10000):
+ super().__init__()
+ assert (dim % 2) == 0, 'dimension must be divisible by 2'
+ self.scale = nn.Parameter(torch.ones(1) * dim ** -0.5)
+
+ half_dim = dim // 2
+ freq_seq = torch.arange(half_dim).float() / half_dim
+ inv_freq = theta ** -freq_seq
+ self.register_buffer('inv_freq', inv_freq, persistent = False)
+
+ def forward(self, x, pos = None, seq_start_pos = None):
+ seq_len, device = x.shape[1], x.device
+
+ if pos is None:
+ pos = torch.arange(seq_len, device = device)
+
+ if seq_start_pos is not None:
+ pos = pos - seq_start_pos[..., None]
+
+ emb = einsum('i, j -> i j', pos, self.inv_freq)
+ emb = torch.cat((emb.sin(), emb.cos()), dim = -1)
+ return emb * self.scale
+
+class RotaryEmbedding(nn.Module):
+ def __init__(
+ self,
+ dim,
+ use_xpos = False,
+ scale_base = 512,
+ interpolation_factor = 1.,
+ base = 10000,
+ base_rescale_factor = 1.
+ ):
+ super().__init__()
+ # proposed by reddit user bloc97, to rescale rotary embeddings to longer sequence length without fine-tuning
+ # has some connection to NTK literature
+ # https://www.reddit.com/r/LocalLLaMA/comments/14lz7j5/ntkaware_scaled_rope_allows_llama_models_to_have/
+ base *= base_rescale_factor ** (dim / (dim - 2))
+
+ inv_freq = 1. / (base ** (torch.arange(0, dim, 2).float() / dim))
+ self.register_buffer('inv_freq', inv_freq)
+
+ assert interpolation_factor >= 1.
+ self.interpolation_factor = interpolation_factor
+
+ if not use_xpos:
+ self.register_buffer('scale', None)
+ return
+
+ scale = (torch.arange(0, dim, 2) + 0.4 * dim) / (1.4 * dim)
+
+ self.scale_base = scale_base
+ self.register_buffer('scale', scale)
+
+ def forward_from_seq_len(self, seq_len):
+ device = self.inv_freq.device
+
+ t = torch.arange(seq_len, device = device)
+ return self.forward(t)
+
+ @autocast(enabled = False)
+ def forward(self, t):
+ device = self.inv_freq.device
+
+ t = t.to(torch.float32)
+
+ t = t / self.interpolation_factor
+
+ freqs = torch.einsum('i , j -> i j', t, self.inv_freq)
+ freqs = torch.cat((freqs, freqs), dim = -1)
+
+ if self.scale is None:
+ return freqs, 1.
+
+ power = (torch.arange(seq_len, device = device) - (seq_len // 2)) / self.scale_base
+ scale = self.scale ** rearrange(power, 'n -> n 1')
+ scale = torch.cat((scale, scale), dim = -1)
+
+ return freqs, scale
+
+def rotate_half(x):
+ x = rearrange(x, '... (j d) -> ... j d', j = 2)
+ x1, x2 = x.unbind(dim = -2)
+ return torch.cat((-x2, x1), dim = -1)
+
+@autocast(enabled = False)
+def apply_rotary_pos_emb(t, freqs, scale = 1):
+ out_dtype = t.dtype
+
+ # cast to float32 if necessary for numerical stability
+ dtype = reduce(torch.promote_types, (t.dtype, freqs.dtype, torch.float32))
+ rot_dim, seq_len = freqs.shape[-1], t.shape[-2]
+ freqs, t = freqs.to(dtype), t.to(dtype)
+ freqs = freqs[-seq_len:, :]
+
+ if t.ndim == 4 and freqs.ndim == 3:
+ freqs = rearrange(freqs, 'b n d -> b 1 n d')
+
+ # partial rotary embeddings, Wang et al. GPT-J
+ t, t_unrotated = t[..., :rot_dim], t[..., rot_dim:]
+ t = (t * freqs.cos() * scale) + (rotate_half(t) * freqs.sin() * scale)
+
+ t, t_unrotated = t.to(out_dtype), t_unrotated.to(out_dtype)
+
+ return torch.cat((t, t_unrotated), dim = -1)
+
+# norms
+class LayerNorm(nn.Module):
+ def __init__(self, dim, bias=False, fix_scale=False):
+ """
+ bias-less layernorm has been shown to be more stable. most newer models have moved towards rmsnorm, also bias-less
+ """
+ super().__init__()
+
+ if fix_scale:
+ self.register_buffer("gamma", torch.ones(dim))
+ else:
+ self.gamma = nn.Parameter(torch.ones(dim))
+
+ if bias:
+ self.beta = nn.Parameter(torch.zeros(dim))
+ else:
+ self.register_buffer("beta", torch.zeros(dim))
+
+
+ def forward(self, x):
+ return F.layer_norm(x, x.shape[-1:], weight=self.gamma, bias=self.beta)
+
+# feedforward
+
+class GLU(nn.Module):
+ def __init__(
+ self,
+ dim_in,
+ dim_out,
+ activation: Callable,
+ use_conv = False,
+ conv_kernel_size = 3,
+ ):
+ super().__init__()
+ self.act = activation
+ self.proj = nn.Linear(dim_in, dim_out * 2) if not use_conv else nn.Conv1d(dim_in, dim_out * 2, conv_kernel_size, padding = (conv_kernel_size // 2))
+ self.use_conv = use_conv
+
+ def forward(self, x):
+ if self.use_conv:
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.proj(x)
+ x = rearrange(x, 'b d n -> b n d')
+ else:
+ x = self.proj(x)
+
+ x, gate = x.chunk(2, dim = -1)
+ return x * self.act(gate)
+
+class FeedForward(nn.Module):
+ def __init__(
+ self,
+ dim,
+ dim_out = None,
+ mult = 4,
+ no_bias = False,
+ glu = True,
+ use_conv = False,
+ conv_kernel_size = 3,
+ zero_init_output = True,
+ ):
+ super().__init__()
+ inner_dim = int(dim * mult)
+
+ # Default to SwiGLU
+
+ activation = nn.SiLU()
+
+ dim_out = dim if dim_out is None else dim_out
+
+ if glu:
+ linear_in = GLU(dim, inner_dim, activation)
+ else:
+ linear_in = nn.Sequential(
+ Rearrange('b n d -> b d n') if use_conv else nn.Identity(),
+ nn.Linear(dim, inner_dim, bias = not no_bias) if not use_conv else nn.Conv1d(dim, inner_dim, conv_kernel_size, padding = (conv_kernel_size // 2), bias = not no_bias),
+ Rearrange('b n d -> b d n') if use_conv else nn.Identity(),
+ activation
+ )
+
+ linear_out = nn.Linear(inner_dim, dim_out, bias = not no_bias) if not use_conv else nn.Conv1d(inner_dim, dim_out, conv_kernel_size, padding = (conv_kernel_size // 2), bias = not no_bias)
+
+ # init last linear layer to 0
+ if zero_init_output:
+ nn.init.zeros_(linear_out.weight)
+ if not no_bias:
+ nn.init.zeros_(linear_out.bias)
+
+
+ self.ff = nn.Sequential(
+ linear_in,
+ Rearrange('b d n -> b n d') if use_conv else nn.Identity(),
+ linear_out,
+ Rearrange('b n d -> b d n') if use_conv else nn.Identity(),
+ )
+
+ def forward(self, x):
+ return self.ff(x)
+
+class Attention(nn.Module):
+ def __init__(
+ self,
+ dim,
+ dim_heads = 64,
+ dim_context = None,
+ causal = False,
+ zero_init_output=True,
+ qk_norm: Literal['l2', 'ln', 'none'] = 'none',
+ natten_kernel_size = None
+ ):
+ super().__init__()
+ self.dim = dim
+ self.dim_heads = dim_heads
+ self.causal = causal
+
+ dim_kv = dim_context if dim_context is not None else dim
+
+ self.num_heads = dim // dim_heads
+ self.kv_heads = dim_kv // dim_heads
+
+ if dim_context is not None:
+ self.to_q = nn.Linear(dim, dim, bias=False)
+ self.to_kv = nn.Linear(dim_kv, dim_kv * 2, bias=False)
+ else:
+ self.to_qkv = nn.Linear(dim, dim * 3, bias=False)
+
+ self.to_out = nn.Linear(dim, dim, bias=False)
+
+ if zero_init_output:
+ nn.init.zeros_(self.to_out.weight)
+
+ self.qk_norm = qk_norm
+
+ if self.qk_norm == "ln":
+ self.q_norm = nn.LayerNorm(dim_heads, elementwise_affine=True, eps=1.0e-6)
+ self.k_norm = nn.LayerNorm(dim_heads, elementwise_affine=True, eps=1.0e-6)
+
+ # Using 1d neighborhood attention
+ self.natten_kernel_size = natten_kernel_size
+ if natten_kernel_size is not None:
+ return
+
+ self.use_pt_flash = torch.cuda.is_available() and version.parse(torch.__version__) >= version.parse('2.0.0')
+
+ self.use_fa_flash = torch.cuda.is_available() and flash_attn_func is not None
+ # pdb.set_trace()
+ self.use_fa_flash = False
+
+ self.sdp_kwargs = dict(
+ enable_flash = True,
+ enable_math = True,
+ enable_mem_efficient = True
+ )
+
+ def flash_attn(
+ self,
+ q,
+ k,
+ v,
+ mask = None,
+ causal = None
+ ):
+ batch, heads, q_len, _, k_len, device = *q.shape, k.shape[-2], q.device
+ kv_heads = k.shape[1]
+ # Recommended for multi-query single-key-value attention by Tri Dao
+ # kv shape torch.Size([1, 512, 64]) -> torch.Size([1, 8, 512, 64])
+
+ if heads != kv_heads:
+ # Repeat interleave kv_heads to match q_heads
+ heads_per_kv_head = heads // kv_heads
+ k, v = map(lambda t: t.repeat_interleave(heads_per_kv_head, dim = 1), (k, v))
+
+ if k.ndim == 3:
+ k = rearrange(k, 'b ... -> b 1 ...').expand_as(q)
+
+ if v.ndim == 3:
+ v = rearrange(v, 'b ... -> b 1 ...').expand_as(q)
+
+ causal = self.causal if causal is None else causal
+
+ if q_len == 1 and causal:
+ causal = False
+
+ if mask is not None:
+ assert mask.ndim == 4
+ mask = mask.expand(batch, heads, q_len, k_len)
+
+ # handle kv cache - this should be bypassable in updated flash attention 2
+
+ if k_len > q_len and causal:
+ causal_mask = self.create_causal_mask(q_len, k_len, device = device)
+ if mask is None:
+ mask = ~causal_mask
+ else:
+ mask = mask & ~causal_mask
+ causal = False
+
+ # manually handle causal mask, if another mask was given
+
+ row_is_entirely_masked = None
+
+ if mask is not None and causal:
+ causal_mask = self.create_causal_mask(q_len, k_len, device = device)
+ mask = mask & ~causal_mask
+
+ # protect against an entire row being masked out
+
+ row_is_entirely_masked = ~mask.any(dim = -1)
+ mask[..., 0] = mask[..., 0] | row_is_entirely_masked
+
+ causal = False
+
+ with torch.backends.cuda.sdp_kernel(**self.sdp_kwargs):
+ out = F.scaled_dot_product_attention(
+ q, k, v,
+ attn_mask = mask,
+ is_causal = causal
+ )
+
+ # for a row that is entirely masked out, should zero out the output of that row token
+
+ if row_is_entirely_masked is not None:
+ out = out.masked_fill(row_is_entirely_masked[..., None], 0.)
+
+ return out
+
+ def forward(
+ self,
+ x,
+ context = None,
+ mask = None,
+ context_mask = None,
+ rotary_pos_emb = None,
+ causal = None
+ ):
+ h, kv_h, has_context = self.num_heads, self.kv_heads, context is not None
+
+ kv_input = context if has_context else x
+
+ if hasattr(self, 'to_q'):
+ # Use separate linear projections for q and k/v
+ q = self.to_q(x)
+ q = rearrange(q, 'b n (h d) -> b h n d', h = h)
+
+ k, v = self.to_kv(kv_input).chunk(2, dim=-1)
+
+ k, v = map(lambda t: rearrange(t, 'b n (h d) -> b h n d', h = kv_h), (k, v))
+ else:
+ # Use fused linear projection
+ q, k, v = self.to_qkv(x).chunk(3, dim=-1)
+ q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b h n d', h = h), (q, k, v))
+
+ # Normalize q and k for cosine sim attention
+ if self.qk_norm == "l2":
+ q = F.normalize(q, dim=-1)
+ k = F.normalize(k, dim=-1)
+ elif self.qk_norm == "ln":
+ q = self.q_norm(q)
+ k = self.k_norm(k)
+
+ if rotary_pos_emb is not None and not has_context:
+ freqs, _ = rotary_pos_emb
+
+ q_dtype = q.dtype
+ k_dtype = k.dtype
+
+ q = q.to(torch.float32)
+ k = k.to(torch.float32)
+ freqs = freqs.to(torch.float32)
+
+ q = apply_rotary_pos_emb(q, freqs)
+ k = apply_rotary_pos_emb(k, freqs)
+
+ q = q.to(q_dtype)
+ k = k.to(k_dtype)
+
+ input_mask = context_mask
+
+ if input_mask is None and not has_context:
+ input_mask = mask
+
+ # determine masking
+ masks = []
+ final_attn_mask = None # The mask that will be applied to the attention matrix, taking all masks into account
+
+ if input_mask is not None:
+ input_mask = rearrange(input_mask, 'b j -> b 1 1 j')
+ masks.append(~input_mask)
+
+ # Other masks will be added here later
+
+ if len(masks) > 0:
+ final_attn_mask = ~or_reduce(masks)
+
+ n, device = q.shape[-2], q.device
+
+ causal = self.causal if causal is None else causal
+
+ if n == 1 and causal:
+ causal = False
+
+ if self.natten_kernel_size is not None:
+ if natten is None:
+ raise ImportError('natten not installed, please install natten to use neighborhood attention')
+
+ dtype_in = q.dtype
+ q, k, v = map(lambda t: t.to(torch.float32), (q, k, v))
+
+ attn = natten.functional.natten1dqk(q, k, kernel_size = self.natten_kernel_size, dilation=1)
+
+ if final_attn_mask is not None:
+ attn = attn.masked_fill(final_attn_mask, -torch.finfo(attn.dtype).max)
+
+ attn = F.softmax(attn, dim=-1, dtype=torch.float32)
+
+ out = natten.functional.natten1dav(attn, v, kernel_size = self.natten_kernel_size, dilation=1).to(dtype_in)
+
+ # Prioritize Flash Attention 2
+ elif self.use_fa_flash:
+ # pdb.set_trace()
+ assert final_attn_mask is None, 'masking not yet supported for Flash Attention 2'
+ # Flash Attention 2 requires FP16 inputs
+ fa_dtype_in = q.dtype
+ q, k, v = map(lambda t: rearrange(t, 'b h n d -> b n h d').to(torch.float16), (q, k, v))
+
+ out = flash_attn_func(q, k, v, causal = causal)
+
+ out = rearrange(out.to(fa_dtype_in), 'b n h d -> b h n d')
+
+ # Fall back to PyTorch implementation
+ elif self.use_pt_flash:
+ out = self.flash_attn(q, k, v, causal = causal, mask = final_attn_mask)
+
+ else:
+ # Fall back to custom implementation
+
+ if h != kv_h:
+ # Repeat interleave kv_heads to match q_heads
+ heads_per_kv_head = h // kv_h
+ k, v = map(lambda t: t.repeat_interleave(heads_per_kv_head, dim = 1), (k, v))
+
+ scale = 1. / (q.shape[-1] ** 0.5)
+
+ kv_einsum_eq = 'b j d' if k.ndim == 3 else 'b h j d'
+
+ dots = einsum(f'b h i d, {kv_einsum_eq} -> b h i j', q, k) * scale
+
+ i, j, dtype = *dots.shape[-2:], dots.dtype
+
+ mask_value = -torch.finfo(dots.dtype).max
+
+ if final_attn_mask is not None:
+ dots = dots.masked_fill(~final_attn_mask, mask_value)
+
+ if causal:
+ causal_mask = self.create_causal_mask(i, j, device = device)
+ dots = dots.masked_fill(causal_mask, mask_value)
+
+ attn = F.softmax(dots, dim=-1, dtype=torch.float32)
+ attn = attn.type(dtype)
+
+ out = einsum(f'b h i j, {kv_einsum_eq} -> b h i d', attn, v)
+
+ # merge heads
+ out = rearrange(out, ' b h n d -> b n (h d)')
+
+ # Communicate between heads
+
+ # with autocast(enabled = False):
+ # out_dtype = out.dtype
+ # out = out.to(torch.float32)
+ # out = self.to_out(out).to(out_dtype)
+ out = self.to_out(out)
+
+ if mask is not None:
+ mask = rearrange(mask, 'b n -> b n 1')
+ out = out.masked_fill(~mask, 0.)
+
+ return out
+
+class ConformerModule(nn.Module):
+ def __init__(
+ self,
+ dim,
+ norm_kwargs = {},
+ ):
+
+ super().__init__()
+
+ self.dim = dim
+
+ self.in_norm = LayerNorm(dim, **norm_kwargs)
+ self.pointwise_conv = nn.Conv1d(dim, dim, kernel_size=1, bias=False)
+ self.glu = GLU(dim, dim, nn.SiLU())
+ self.depthwise_conv = nn.Conv1d(dim, dim, kernel_size=17, groups=dim, padding=8, bias=False)
+ self.mid_norm = LayerNorm(dim, **norm_kwargs) # This is a batch norm in the original but I don't like batch norm
+ self.swish = nn.SiLU()
+ self.pointwise_conv_2 = nn.Conv1d(dim, dim, kernel_size=1, bias=False)
+
+ def forward(self, x):
+ x = self.in_norm(x)
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.pointwise_conv(x)
+ x = rearrange(x, 'b d n -> b n d')
+ x = self.glu(x)
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.depthwise_conv(x)
+ x = rearrange(x, 'b d n -> b n d')
+ x = self.mid_norm(x)
+ x = self.swish(x)
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.pointwise_conv_2(x)
+ x = rearrange(x, 'b d n -> b n d')
+
+ return x
+
+class TransformerBlock(nn.Module):
+ def __init__(
+ self,
+ dim,
+ dim_heads = 64,
+ cross_attend = False,
+ dim_context = None,
+ global_cond_dim = None,
+ causal = False,
+ zero_init_branch_outputs = True,
+ conformer = False,
+ layer_ix = -1,
+ remove_norms = False,
+ attn_kwargs = {},
+ ff_kwargs = {},
+ norm_kwargs = {}
+ ):
+
+ super().__init__()
+ self.dim = dim
+ self.dim_heads = dim_heads
+ self.cross_attend = cross_attend
+ self.dim_context = dim_context
+ self.causal = causal
+
+ self.pre_norm = LayerNorm(dim, **norm_kwargs) if not remove_norms else nn.Identity()
+
+ self.self_attn = Attention(
+ dim,
+ dim_heads = dim_heads,
+ causal = causal,
+ zero_init_output=zero_init_branch_outputs,
+ **attn_kwargs
+ )
+ ### 2. 主要是这边需要修改
+ if cross_attend:
+ self.cross_attend_norm = LayerNorm(dim, **norm_kwargs) if not remove_norms else nn.Identity()
+ self.cross_attn = Attention(
+ dim,
+ dim_heads = dim_heads,
+ dim_context=dim_context,
+ causal = causal,
+ zero_init_output=zero_init_branch_outputs,
+ **attn_kwargs
+ )
+
+ self.ff_norm = LayerNorm(dim, **norm_kwargs) if not remove_norms else nn.Identity()
+ self.ff = FeedForward(dim, zero_init_output=zero_init_branch_outputs, **ff_kwargs)
+
+ self.layer_ix = layer_ix
+
+ self.conformer = ConformerModule(dim, norm_kwargs=norm_kwargs) if conformer else None
+
+ self.global_cond_dim = global_cond_dim
+
+ if global_cond_dim is not None:
+ self.to_scale_shift_gate = nn.Sequential(
+ nn.SiLU(),
+ nn.Linear(global_cond_dim, dim * 6, bias=False)
+ )
+
+ nn.init.zeros_(self.to_scale_shift_gate[1].weight)
+ #nn.init.zeros_(self.to_scale_shift_gate_self[1].bias)
+
+ def forward(
+ self,
+ x,
+ context = None,
+ global_cond=None,
+ mask = None,
+ context_mask = None,
+ rotary_pos_emb = None
+ ):
+ if self.global_cond_dim is not None and self.global_cond_dim > 0 and global_cond is not None:
+
+ scale_self, shift_self, gate_self, scale_ff, shift_ff, gate_ff = self.to_scale_shift_gate(global_cond).unsqueeze(1).chunk(6, dim = -1)
+
+ # self-attention with adaLN
+ residual = x
+ x = self.pre_norm(x)
+ x = x * (1 + scale_self) + shift_self
+ x = self.self_attn(x, mask = mask, rotary_pos_emb = rotary_pos_emb)
+ x = x * torch.sigmoid(1 - gate_self)
+ x = x + residual
+
+ if context is not None:
+ x = x + self.cross_attn(self.cross_attend_norm(x), context = context, context_mask = context_mask)
+
+ if self.conformer is not None:
+ x = x + self.conformer(x)
+
+ # feedforward with adaLN
+ residual = x
+ x = self.ff_norm(x)
+ x = x * (1 + scale_ff) + shift_ff
+ x = self.ff(x)
+ x = x * torch.sigmoid(1 - gate_ff)
+ x = x + residual
+
+ else:
+ x = x + self.self_attn(self.pre_norm(x), mask = mask, rotary_pos_emb = rotary_pos_emb)
+
+ if context is not None:
+ x = x + self.cross_attn(self.cross_attend_norm(x), context = context, context_mask = context_mask)
+
+ if self.conformer is not None:
+ x = x + self.conformer(x)
+
+ x = x + self.ff(self.ff_norm(x))
+
+ return x
+
+class ContinuousTransformer(nn.Module):
+ def __init__(
+ self,
+ dim,
+ depth,
+ *,
+ dim_in = None,
+ dim_out = None,
+ dim_heads = 64,
+ cross_attend=False,
+ cond_token_dim=None,
+ global_cond_dim=None,
+ causal=False,
+ rotary_pos_emb=True,
+ zero_init_branch_outputs=True,
+ conformer=False,
+ use_sinusoidal_emb=False,
+ use_abs_pos_emb=False,
+ abs_pos_emb_max_length=10000,
+ **kwargs
+ ):
+
+ super().__init__()
+
+ self.dim = dim
+ self.depth = depth
+ self.causal = causal
+ self.layers = nn.ModuleList([])
+
+ self.project_in = nn.Linear(dim_in, dim, bias=False) if dim_in is not None else nn.Identity()
+ self.project_out = nn.Linear(dim, dim_out, bias=False) if dim_out is not None else nn.Identity()
+
+ if rotary_pos_emb:
+ self.rotary_pos_emb = RotaryEmbedding(max(dim_heads // 2, 32))
+ else:
+ self.rotary_pos_emb = None
+
+ self.use_sinusoidal_emb = use_sinusoidal_emb
+ if use_sinusoidal_emb:
+ self.pos_emb = ScaledSinusoidalEmbedding(dim)
+
+ self.use_abs_pos_emb = use_abs_pos_emb
+ if use_abs_pos_emb:
+ self.pos_emb = AbsolutePositionalEmbedding(dim, abs_pos_emb_max_length)
+
+ for i in range(depth):
+ self.layers.append(
+ TransformerBlock(
+ dim,
+ dim_heads = dim_heads,
+ cross_attend = cross_attend,
+ dim_context = cond_token_dim,
+ global_cond_dim = global_cond_dim,
+ causal = causal,
+ zero_init_branch_outputs = zero_init_branch_outputs,
+ conformer=conformer,
+ layer_ix=i,
+ **kwargs
+ )
+ )
+
+ def forward(
+ self,
+ x,
+ mask = None,
+ prepend_embeds = None,
+ prepend_mask = None,
+ global_cond = None,
+ return_info = False,
+ **kwargs
+ ):
+ batch, seq, device = *x.shape[:2], x.device
+
+ info = {
+ "hidden_states": [],
+ }
+
+ x = self.project_in(x)
+ if prepend_embeds is not None:
+ prepend_length, prepend_dim = prepend_embeds.shape[1:]
+
+ assert prepend_dim == x.shape[-1], 'prepend dimension must match sequence dimension'
+
+ x = torch.cat((prepend_embeds, x), dim = -2)
+
+ if prepend_mask is not None or mask is not None:
+ mask = mask if mask is not None else torch.ones((batch, seq), device = device, dtype = torch.bool)
+ prepend_mask = prepend_mask if prepend_mask is not None else torch.ones((batch, prepend_length), device = device, dtype = torch.bool)
+
+ mask = torch.cat((prepend_mask, mask), dim = -1)
+
+ # Attention layers
+
+ if self.rotary_pos_emb is not None:
+ rotary_pos_emb = self.rotary_pos_emb.forward_from_seq_len(x.shape[1])
+ else:
+ rotary_pos_emb = None
+
+ if self.use_sinusoidal_emb or self.use_abs_pos_emb:
+ x = x + self.pos_emb(x)
+
+ # Iterate over the transformer layers
+ for layer in self.layers:
+ #x = layer(x, rotary_pos_emb = rotary_pos_emb, global_cond=global_cond, **kwargs)
+ # pdb.set_trace()
+ x = checkpoint(layer, x, mask=mask.bool(),rotary_pos_emb = rotary_pos_emb, global_cond=global_cond, **kwargs)
+
+ if return_info:
+ info["hidden_states"].append(x)
+
+ x = self.project_out(x)
+
+ if return_info:
+ return x, info
+
+ return x
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/transformer_use_mask.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/transformer_use_mask.py
new file mode 100644
index 0000000000000000000000000000000000000000..d22c5704f71d14b1f4446869a7f191383d5c31d3
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/flow/stable/transformer_use_mask.py
@@ -0,0 +1,845 @@
+import pdb
+from functools import reduce, partial
+from packaging import version
+
+from einops import rearrange, repeat
+from einops.layers.torch import Rearrange
+import torch
+import torch.nn.functional as F
+from torch import nn, einsum
+from torch.cuda.amp import autocast
+from typing import Callable, Literal
+
+try:
+ from flash_attn import flash_attn_func, flash_attn_kvpacked_func
+except ImportError as e:
+ print(e)
+ print('flash_attn not installed, disabling Flash Attention')
+ flash_attn_kvpacked_func = None
+ flash_attn_func = None
+
+try:
+ import natten
+except ImportError:
+ natten = None
+
+
+def checkpoint(function, *args, **kwargs):
+ kwargs.setdefault("use_reentrant", False)
+ return torch.utils.checkpoint.checkpoint(function, *args, **kwargs)
+
+
+# Copied and modified from https://github.com/lucidrains/x-transformers/blob/main/x_transformers/attend.py under MIT License
+# License can be found in LICENSES/LICENSE_XTRANSFORMERS.txt
+
+def create_causal_mask(i, j, device):
+ return torch.ones((i, j), device=device, dtype=torch.bool).triu(j - i + 1)
+
+
+def or_reduce(masks):
+ head, *body = masks
+ for rest in body:
+ head = head | rest
+ return head
+
+
+# positional embeddings
+
+class AbsolutePositionalEmbedding(nn.Module):
+ def __init__(self, dim, max_seq_len):
+ super().__init__()
+ self.scale = dim ** -0.5
+ self.max_seq_len = max_seq_len
+ self.emb = nn.Embedding(max_seq_len, dim)
+
+ def forward(self, x, pos=None, seq_start_pos=None):
+ seq_len, device = x.shape[1], x.device
+ assert seq_len <= self.max_seq_len, f'you are passing in a sequence length of {seq_len} but your absolute positional embedding has a max sequence length of {self.max_seq_len}'
+
+ if pos is None:
+ pos = torch.arange(seq_len, device=device)
+
+ if seq_start_pos is not None:
+ pos = (pos - seq_start_pos[..., None]).clamp(min=0)
+
+ pos_emb = self.emb(pos)
+ pos_emb = pos_emb * self.scale
+ return pos_emb
+
+
+class ScaledSinusoidalEmbedding(nn.Module):
+ def __init__(self, dim, theta=10000):
+ super().__init__()
+ assert (dim % 2) == 0, 'dimension must be divisible by 2'
+ self.scale = nn.Parameter(torch.ones(1) * dim ** -0.5)
+
+ half_dim = dim // 2
+ freq_seq = torch.arange(half_dim).float() / half_dim
+ inv_freq = theta ** -freq_seq
+ self.register_buffer('inv_freq', inv_freq, persistent=False)
+
+ def forward(self, x, pos=None, seq_start_pos=None):
+ seq_len, device = x.shape[1], x.device
+
+ if pos is None:
+ pos = torch.arange(seq_len, device=device)
+
+ if seq_start_pos is not None:
+ pos = pos - seq_start_pos[..., None]
+
+ emb = einsum('i, j -> i j', pos, self.inv_freq)
+ emb = torch.cat((emb.sin(), emb.cos()), dim=-1)
+ return emb * self.scale
+
+
+class RotaryEmbedding(nn.Module):
+ def __init__(
+ self,
+ dim,
+ use_xpos=False,
+ scale_base=512,
+ interpolation_factor=1.,
+ base=10000,
+ base_rescale_factor=1.
+ ):
+ super().__init__()
+ # proposed by reddit user bloc97, to rescale rotary embeddings to longer sequence length without fine-tuning
+ # has some connection to NTK literature
+ # https://www.reddit.com/r/LocalLLaMA/comments/14lz7j5/ntkaware_scaled_rope_allows_llama_models_to_have/
+ base *= base_rescale_factor ** (dim / (dim - 2))
+
+ inv_freq = 1. / (base ** (torch.arange(0, dim, 2).float() / dim))
+ self.register_buffer('inv_freq', inv_freq)
+
+ assert interpolation_factor >= 1.
+ self.interpolation_factor = interpolation_factor
+
+ if not use_xpos:
+ self.register_buffer('scale', None)
+ return
+
+ scale = (torch.arange(0, dim, 2) + 0.4 * dim) / (1.4 * dim)
+
+ self.scale_base = scale_base
+ self.register_buffer('scale', scale)
+
+ def forward_from_seq_len(self, seq_len):
+ device = self.inv_freq.device
+
+ t = torch.arange(seq_len, device=device)
+ return self.forward(t)
+
+ @autocast(enabled=False)
+ def forward(self, t):
+ device = self.inv_freq.device
+
+ t = t.to(torch.float32)
+
+ t = t / self.interpolation_factor
+
+ freqs = torch.einsum('i , j -> i j', t, self.inv_freq)
+ freqs = torch.cat((freqs, freqs), dim=-1)
+
+ if self.scale is None:
+ return freqs, 1.
+
+ power = (torch.arange(seq_len, device=device) - (seq_len // 2)) / self.scale_base
+ scale = self.scale ** rearrange(power, 'n -> n 1')
+ scale = torch.cat((scale, scale), dim=-1)
+
+ return freqs, scale
+
+
+def rotate_half(x):
+ x = rearrange(x, '... (j d) -> ... j d', j=2)
+ x1, x2 = x.unbind(dim=-2)
+ return torch.cat((-x2, x1), dim=-1)
+
+
+@autocast(enabled=False)
+def apply_rotary_pos_emb(t, freqs, scale=1):
+ out_dtype = t.dtype
+
+ # cast to float32 if necessary for numerical stability
+ dtype = reduce(torch.promote_types, (t.dtype, freqs.dtype, torch.float32))
+ rot_dim, seq_len = freqs.shape[-1], t.shape[-2]
+ freqs, t = freqs.to(dtype), t.to(dtype)
+ freqs = freqs[-seq_len:, :]
+
+ if t.ndim == 4 and freqs.ndim == 3:
+ freqs = rearrange(freqs, 'b n d -> b 1 n d')
+
+ # partial rotary embeddings, Wang et al. GPT-J
+ t, t_unrotated = t[..., :rot_dim], t[..., rot_dim:]
+ t = (t * freqs.cos() * scale) + (rotate_half(t) * freqs.sin() * scale)
+
+ t, t_unrotated = t.to(out_dtype), t_unrotated.to(out_dtype)
+
+ return torch.cat((t, t_unrotated), dim=-1)
+
+
+# norms
+class LayerNorm(nn.Module):
+ def __init__(self, dim, bias=False, fix_scale=False):
+ """
+ bias-less layernorm has been shown to be more stable. most newer models have moved towards rmsnorm, also bias-less
+ """
+ super().__init__()
+
+ if fix_scale:
+ self.register_buffer("gamma", torch.ones(dim))
+ else:
+ self.gamma = nn.Parameter(torch.ones(dim))
+
+ if bias:
+ self.beta = nn.Parameter(torch.zeros(dim))
+ else:
+ self.register_buffer("beta", torch.zeros(dim))
+
+ def forward(self, x):
+ return F.layer_norm(x, x.shape[-1:], weight=self.gamma, bias=self.beta)
+
+
+# feedforward
+
+class GLU(nn.Module):
+ def __init__(
+ self,
+ dim_in,
+ dim_out,
+ activation: Callable,
+ use_conv=False,
+ conv_kernel_size=3,
+ ):
+ super().__init__()
+ self.act = activation
+ self.proj = nn.Linear(dim_in, dim_out * 2) if not use_conv else nn.Conv1d(dim_in, dim_out * 2, conv_kernel_size,
+ padding=(conv_kernel_size // 2))
+ self.use_conv = use_conv
+
+ def forward(self, x):
+ if self.use_conv:
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.proj(x)
+ x = rearrange(x, 'b d n -> b n d')
+ else:
+ x = self.proj(x)
+
+ x, gate = x.chunk(2, dim=-1)
+ return x * self.act(gate)
+
+
+class FeedForward(nn.Module):
+ def __init__(
+ self,
+ dim,
+ dim_out=None,
+ mult=4,
+ no_bias=False,
+ glu=True,
+ use_conv=False,
+ conv_kernel_size=3,
+ zero_init_output=True,
+ ):
+ super().__init__()
+ inner_dim = int(dim * mult)
+
+ # Default to SwiGLU
+
+ activation = nn.SiLU()
+
+ dim_out = dim if dim_out is None else dim_out
+
+ if glu:
+ linear_in = GLU(dim, inner_dim, activation)
+ else:
+ linear_in = nn.Sequential(
+ Rearrange('b n d -> b d n') if use_conv else nn.Identity(),
+ nn.Linear(dim, inner_dim, bias=not no_bias) if not use_conv else nn.Conv1d(dim, inner_dim,
+ conv_kernel_size, padding=(
+ conv_kernel_size // 2), bias=not no_bias),
+ Rearrange('b n d -> b d n') if use_conv else nn.Identity(),
+ activation
+ )
+
+ linear_out = nn.Linear(inner_dim, dim_out, bias=not no_bias) if not use_conv else nn.Conv1d(inner_dim, dim_out,
+ conv_kernel_size,
+ padding=(
+ conv_kernel_size // 2),
+ bias=not no_bias)
+
+ # init last linear layer to 0
+ if zero_init_output:
+ nn.init.zeros_(linear_out.weight)
+ if not no_bias:
+ nn.init.zeros_(linear_out.bias)
+
+ self.ff = nn.Sequential(
+ linear_in,
+ Rearrange('b d n -> b n d') if use_conv else nn.Identity(),
+ linear_out,
+ Rearrange('b n d -> b d n') if use_conv else nn.Identity(),
+ )
+
+ def forward(self, x):
+ return self.ff(x)
+
+
+class Attention(nn.Module):
+ def __init__(
+ self,
+ dim,
+ dim_heads=64,
+ dim_context=None,
+ causal=False,
+ zero_init_output=True,
+ qk_norm: Literal['l2', 'ln', 'none'] = 'none',
+ natten_kernel_size=None
+ ):
+ super().__init__()
+ self.dim = dim
+ self.dim_heads = dim_heads
+ self.causal = causal
+
+ dim_kv = dim_context if dim_context is not None else dim
+
+ self.num_heads = dim // dim_heads
+ self.kv_heads = dim_kv // dim_heads
+
+ if dim_context is not None:
+ self.to_q = nn.Linear(dim, dim, bias=False)
+ self.to_kv = nn.Linear(dim_kv, dim_kv * 2, bias=False)
+ else:
+ self.to_qkv = nn.Linear(dim, dim * 3, bias=False)
+
+ self.to_out = nn.Linear(dim, dim, bias=False)
+
+ if zero_init_output:
+ nn.init.zeros_(self.to_out.weight)
+
+ self.qk_norm = qk_norm
+
+ if self.qk_norm == "ln":
+ self.q_norm = nn.LayerNorm(dim_heads, elementwise_affine=True, eps=1.0e-6)
+ self.k_norm = nn.LayerNorm(dim_heads, elementwise_affine=True, eps=1.0e-6)
+
+ # Using 1d neighborhood attention
+ self.natten_kernel_size = natten_kernel_size
+ if natten_kernel_size is not None:
+ return
+
+ self.use_pt_flash = torch.cuda.is_available() and version.parse(torch.__version__) >= version.parse('2.0.0')
+
+ self.use_fa_flash = torch.cuda.is_available() and flash_attn_func is not None
+ # pdb.set_trace()
+ self.use_fa_flash = False
+
+ self.sdp_kwargs = dict(
+ enable_flash=True,
+ enable_math=True,
+ enable_mem_efficient=True
+ )
+
+ def flash_attn(
+ self,
+ q,
+ k,
+ v,
+ mask=None,
+ causal=None
+ ):
+ batch, heads, q_len, _, k_len, device = *q.shape, k.shape[-2], q.device
+ kv_heads = k.shape[1]
+ # Recommended for multi-query single-key-value attention by Tri Dao
+ # kv shape torch.Size([1, 512, 64]) -> torch.Size([1, 8, 512, 64])
+
+ if heads != kv_heads:
+ # Repeat interleave kv_heads to match q_heads
+ heads_per_kv_head = heads // kv_heads
+ k, v = map(lambda t: t.repeat_interleave(heads_per_kv_head, dim=1), (k, v))
+
+ if k.ndim == 3:
+ k = rearrange(k, 'b ... -> b 1 ...').expand_as(q)
+
+ if v.ndim == 3:
+ v = rearrange(v, 'b ... -> b 1 ...').expand_as(q)
+
+ causal = self.causal if causal is None else causal
+
+ if q_len == 1 and causal:
+ causal = False
+
+ if mask is not None:
+ assert mask.ndim == 4
+ mask = mask.expand(batch, heads, q_len, k_len)
+
+ assert causal
+ # handle kv cache - this should be bypassable in updated flash attention 2
+ if k_len > q_len and causal:
+ causal_mask = create_causal_mask(q_len, k_len, device=device)
+ if mask is None:
+ mask = ~causal_mask
+ else:
+ mask = mask & ~causal_mask
+ causal = False
+
+ # manually handle causal mask, if another mask was given
+
+ row_is_entirely_masked = None
+
+ if mask is not None and causal:
+ causal_mask = create_causal_mask(q_len, k_len, device=device)
+ mask = mask & ~causal_mask
+
+ # protect against an entire row being masked out
+
+ row_is_entirely_masked = ~mask.any(dim=-1)
+ mask[..., 0] = mask[..., 0] | row_is_entirely_masked
+
+ causal = False
+
+ with torch.backends.cuda.sdp_kernel(**self.sdp_kwargs):
+ out = F.scaled_dot_product_attention(
+ q, k, v,
+ attn_mask=mask,
+ is_causal=causal
+ )
+
+ # for a row that is entirely masked out, should zero out the output of that row token
+
+ if row_is_entirely_masked is not None:
+ out = out.masked_fill(row_is_entirely_masked[..., None], 0.)
+
+ return out
+
+ def forward(
+ self,
+ x,
+ context=None,
+ mask=None,
+ context_mask=None,
+ rotary_pos_emb=None,
+ causal=None
+ ):
+ h, kv_h, has_context = self.num_heads, self.kv_heads, context is not None
+
+ kv_input = context if has_context else x
+
+ if hasattr(self, 'to_q'):
+ # Use separate linear projections for q and k/v
+ q = self.to_q(x)
+ q = rearrange(q, 'b n (h d) -> b h n d', h=h)
+
+ k, v = self.to_kv(kv_input).chunk(2, dim=-1)
+
+ k, v = map(lambda t: rearrange(t, 'b n (h d) -> b h n d', h=kv_h), (k, v))
+ else:
+ # Use fused linear projection
+ q, k, v = self.to_qkv(x).chunk(3, dim=-1)
+ q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b h n d', h=h), (q, k, v))
+
+ # Normalize q and k for cosine sim attention
+ if self.qk_norm == "l2":
+ q = F.normalize(q, dim=-1)
+ k = F.normalize(k, dim=-1)
+ elif self.qk_norm == "ln":
+ q = self.q_norm(q)
+ k = self.k_norm(k)
+
+ if rotary_pos_emb is not None and not has_context:
+ freqs, _ = rotary_pos_emb
+
+ q_dtype = q.dtype
+ k_dtype = k.dtype
+
+ q = q.to(torch.float32)
+ k = k.to(torch.float32)
+ freqs = freqs.to(torch.float32)
+
+ q = apply_rotary_pos_emb(q, freqs)
+ k = apply_rotary_pos_emb(k, freqs)
+
+ q = q.to(q_dtype)
+ k = k.to(k_dtype)
+
+ input_mask = context_mask
+
+ if input_mask is None and not has_context:
+ input_mask = mask
+
+ # determine masking
+ masks = []
+ final_attn_mask = None # The mask that will be applied to the attention matrix, taking all masks into account
+
+ if input_mask is not None:
+ input_mask = rearrange(input_mask, 'b j -> b 1 1 j')
+ masks.append(~input_mask)
+
+ # Other masks will be added here later
+
+ if len(masks) > 0:
+ final_attn_mask = ~or_reduce(masks)
+
+ n, device = q.shape[-2], q.device
+
+ causal = self.causal if causal is None else causal
+
+ if n == 1 and causal:
+ causal = False
+
+ if self.natten_kernel_size is not None:
+ if natten is None:
+ raise ImportError('natten not installed, please install natten to use neighborhood attention')
+
+ dtype_in = q.dtype
+ q, k, v = map(lambda t: t.to(torch.float32), (q, k, v))
+
+ attn = natten.functional.natten1dqk(q, k, kernel_size=self.natten_kernel_size, dilation=1)
+
+ if final_attn_mask is not None:
+ attn = attn.masked_fill(final_attn_mask, -torch.finfo(attn.dtype).max)
+
+ attn = F.softmax(attn, dim=-1, dtype=torch.float32)
+
+ out = natten.functional.natten1dav(attn, v, kernel_size=self.natten_kernel_size, dilation=1).to(dtype_in)
+
+ # Prioritize Flash Attention 2
+ elif self.use_fa_flash:
+ assert final_attn_mask is None, 'masking not yet supported for Flash Attention 2'
+ # Flash Attention 2 requires FP16 inputs
+ fa_dtype_in = q.dtype
+ q, k, v = map(lambda t: rearrange(t, 'b h n d -> b n h d').to(torch.float16), (q, k, v))
+
+ out = flash_attn_func(q, k, v, causal=causal)
+
+ out = rearrange(out.to(fa_dtype_in), 'b n h d -> b h n d')
+
+ # Fall back to PyTorch implementation
+ elif self.use_pt_flash:
+ # causal=False
+ # final_attn_mask:[64, 1, 1, 348]
+ out = self.flash_attn(q, k, v, causal=True, mask=final_attn_mask)
+
+ else:
+ # Fall back to custom implementation
+
+ if h != kv_h:
+ # Repeat interleave kv_heads to match q_heads
+ heads_per_kv_head = h // kv_h
+ k, v = map(lambda t: t.repeat_interleave(heads_per_kv_head, dim=1), (k, v))
+
+ scale = 1. / (q.shape[-1] ** 0.5)
+
+ kv_einsum_eq = 'b j d' if k.ndim == 3 else 'b h j d'
+
+ dots = einsum(f'b h i d, {kv_einsum_eq} -> b h i j', q, k) * scale
+
+ i, j, dtype = *dots.shape[-2:], dots.dtype
+
+ mask_value = -torch.finfo(dots.dtype).max
+
+ if final_attn_mask is not None:
+ dots = dots.masked_fill(~final_attn_mask, mask_value)
+
+ if causal:
+ causal_mask = create_causal_mask(i, j, device=device)
+ dots = dots.masked_fill(causal_mask, mask_value)
+
+ attn = F.softmax(dots, dim=-1, dtype=torch.float32)
+ attn = attn.type(dtype)
+
+ out = einsum(f'b h i j, {kv_einsum_eq} -> b h i d', attn, v)
+
+ # merge heads
+ out = rearrange(out, ' b h n d -> b n (h d)')
+
+ # Communicate between heads
+
+ # with autocast(enabled = False):
+ # out_dtype = out.dtype
+ # out = out.to(torch.float32)
+ # out = self.to_out(out).to(out_dtype)
+ out = self.to_out(out)
+
+ if mask is not None:
+ mask = rearrange(mask, 'b n -> b n 1')
+ out = out.masked_fill(~mask, 0.)
+
+ return out
+
+
+class ConformerModule(nn.Module):
+ def __init__(
+ self,
+ dim,
+ norm_kwargs={},
+ ):
+ super().__init__()
+
+ self.dim = dim
+
+ self.in_norm = LayerNorm(dim, **norm_kwargs)
+ self.pointwise_conv = nn.Conv1d(dim, dim, kernel_size=1, bias=False)
+ self.glu = GLU(dim, dim, nn.SiLU())
+ self.depthwise_conv = nn.Conv1d(dim, dim, kernel_size=17, groups=dim, padding=8, bias=False)
+ self.mid_norm = LayerNorm(dim,
+ **norm_kwargs) # This is a batch norm in the original but I don't like batch norm
+ self.swish = nn.SiLU()
+ self.pointwise_conv_2 = nn.Conv1d(dim, dim, kernel_size=1, bias=False)
+
+ def forward(self, x):
+ x = self.in_norm(x)
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.pointwise_conv(x)
+ x = rearrange(x, 'b d n -> b n d')
+ x = self.glu(x)
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.depthwise_conv(x)
+ x = rearrange(x, 'b d n -> b n d')
+ x = self.mid_norm(x)
+ x = self.swish(x)
+ x = rearrange(x, 'b n d -> b d n')
+ x = self.pointwise_conv_2(x)
+ x = rearrange(x, 'b d n -> b n d')
+
+ return x
+
+
+class TransformerBlock(nn.Module):
+ def __init__(
+ self,
+ dim,
+ dim_heads=64,
+ cross_attend=False,
+ dim_context=None,
+ global_cond_dim=None,
+ causal=False,
+ zero_init_branch_outputs=True,
+ conformer=False,
+ layer_ix=-1,
+ remove_norms=False,
+ attn_kwargs={},
+ ff_kwargs={},
+ norm_kwargs={}
+ ):
+
+ super().__init__()
+ self.dim = dim
+ self.dim_heads = dim_heads
+ self.cross_attend = cross_attend
+ self.dim_context = dim_context
+ self.causal = causal
+
+ self.pre_norm = LayerNorm(dim, **norm_kwargs) if not remove_norms else nn.Identity()
+
+ self.self_attn = Attention(
+ dim,
+ dim_heads=dim_heads,
+ causal=causal,
+ zero_init_output=zero_init_branch_outputs,
+ **attn_kwargs
+ )
+ ### 2. 主要是这边需要修改
+ if cross_attend:
+ self.cross_attend_norm = LayerNorm(dim, **norm_kwargs) if not remove_norms else nn.Identity()
+ self.cross_attn = Attention(
+ dim,
+ dim_heads=dim_heads,
+ dim_context=dim_context,
+ causal=causal,
+ zero_init_output=zero_init_branch_outputs,
+ **attn_kwargs
+ )
+
+ self.ff_norm = LayerNorm(dim, **norm_kwargs) if not remove_norms else nn.Identity()
+ self.ff = FeedForward(dim, zero_init_output=zero_init_branch_outputs, **ff_kwargs)
+
+ self.layer_ix = layer_ix
+
+ self.conformer = ConformerModule(dim, norm_kwargs=norm_kwargs) if conformer else None
+
+ self.global_cond_dim = global_cond_dim
+
+ if global_cond_dim is not None:
+ self.to_scale_shift_gate = nn.Sequential(
+ nn.SiLU(),
+ nn.Linear(global_cond_dim, dim * 6, bias=False)
+ )
+
+ nn.init.zeros_(self.to_scale_shift_gate[1].weight)
+ # nn.init.zeros_(self.to_scale_shift_gate_self[1].bias)
+
+ def forward(
+ self,
+ x,
+ context=None,
+ global_cond=None,
+ mask=None,
+ context_mask=None,
+ rotary_pos_emb=None
+ ):
+ if self.global_cond_dim is not None and self.global_cond_dim > 0 and global_cond is not None:
+
+ scale_self, shift_self, gate_self, scale_ff, shift_ff, gate_ff = self.to_scale_shift_gate(
+ global_cond).unsqueeze(1).chunk(6, dim=-1)
+
+ # self-attention with adaLN
+ residual = x
+ x = self.pre_norm(x)
+ x = x * (1 + scale_self) + shift_self
+ x = self.self_attn(x, mask=mask, rotary_pos_emb=rotary_pos_emb)
+ x = x * torch.sigmoid(1 - gate_self)
+ x = x + residual
+
+ if context is not None:
+ x = x + self.cross_attn(self.cross_attend_norm(x), context=context, context_mask=context_mask)
+
+ if self.conformer is not None:
+ x = x + self.conformer(x)
+
+ # feedforward with adaLN
+ residual = x
+ x = self.ff_norm(x)
+ x = x * (1 + scale_ff) + shift_ff
+ x = self.ff(x)
+ x = x * torch.sigmoid(1 - gate_ff)
+ x = x + residual
+
+ else:
+ x = x + self.self_attn(self.pre_norm(x), mask=mask, rotary_pos_emb=rotary_pos_emb)
+
+ if context is not None:
+ x = x + self.cross_attn(self.cross_attend_norm(x), context=context, context_mask=context_mask)
+
+ if self.conformer is not None:
+ x = x + self.conformer(x)
+
+ x = x + self.ff(self.ff_norm(x))
+
+ return x
+
+
+class ContinuousTransformer(nn.Module):
+ def __init__(
+ self,
+ dim,
+ depth,
+ *,
+ dim_in=None,
+ dim_out=None,
+ dim_heads=64,
+ cross_attend=False,
+ cond_token_dim=None,
+ global_cond_dim=None,
+ causal=False,
+ rotary_pos_emb=True,
+ zero_init_branch_outputs=True,
+ conformer=False,
+ use_sinusoidal_emb=False,
+ use_abs_pos_emb=False,
+ abs_pos_emb_max_length=10000,
+ **kwargs
+ ):
+
+ super().__init__()
+
+ self.dim = dim
+ self.depth = depth
+ self.causal = causal
+ self.layers = nn.ModuleList([])
+
+ self.project_in = nn.Linear(dim_in, dim, bias=False) if dim_in is not None else nn.Identity()
+ self.project_out = nn.Linear(dim, dim_out, bias=False) if dim_out is not None else nn.Identity()
+
+ if rotary_pos_emb:
+ self.rotary_pos_emb = RotaryEmbedding(max(dim_heads // 2, 32))
+ else:
+ self.rotary_pos_emb = None
+
+ self.use_sinusoidal_emb = use_sinusoidal_emb
+ if use_sinusoidal_emb:
+ self.pos_emb = ScaledSinusoidalEmbedding(dim)
+
+ self.use_abs_pos_emb = use_abs_pos_emb
+ if use_abs_pos_emb:
+ self.pos_emb = AbsolutePositionalEmbedding(dim, abs_pos_emb_max_length)
+
+ for i in range(depth):
+ self.layers.append(
+ TransformerBlock(
+ dim,
+ dim_heads=dim_heads,
+ cross_attend=cross_attend,
+ dim_context=cond_token_dim,
+ global_cond_dim=global_cond_dim,
+ causal=causal,
+ zero_init_branch_outputs=zero_init_branch_outputs,
+ conformer=conformer,
+ layer_ix=i,
+ **kwargs
+ )
+ )
+
+ def forward(
+ self,
+ x,
+ mask=None,
+ prepend_embeds=None,
+ prepend_mask=None,
+ global_cond=None,
+ return_info=False,
+ **kwargs
+ ):
+ batch, seq, device = *x.shape[:2], x.device
+
+ info = {
+ "hidden_states": [],
+ }
+
+ x = self.project_in(x)
+ if prepend_embeds is not None:
+ prepend_length, prepend_dim = prepend_embeds.shape[1:]
+
+ assert prepend_dim == x.shape[-1], 'prepend dimension must match sequence dimension'
+
+ x = torch.cat((prepend_embeds, x), dim=-2)
+
+ if prepend_mask is not None or mask is not None:
+ mask = mask if mask is not None else torch.ones((batch, seq), device=device, dtype=torch.bool)
+ prepend_mask = prepend_mask if prepend_mask is not None else torch.ones((batch, prepend_length),
+ device=device, dtype=torch.bool)
+
+ mask = torch.cat((prepend_mask, mask), dim=-1)
+
+ # Attention layers
+
+ if self.rotary_pos_emb is not None:
+ rotary_pos_emb = self.rotary_pos_emb.forward_from_seq_len(x.shape[1])
+ else:
+ rotary_pos_emb = None
+
+ if self.use_sinusoidal_emb or self.use_abs_pos_emb:
+ x = x + self.pos_emb(x)
+
+ # Iterate over the transformer layers
+ mask = self.refine_mask(mask)
+ for layer in self.layers:
+ # x = layer(x, rotary_pos_emb = rotary_pos_emb, global_cond=global_cond, **kwargs)
+ # pdb.set_trace()
+ x = checkpoint(layer, x, mask=mask.bool(), rotary_pos_emb=rotary_pos_emb, global_cond=global_cond, **kwargs)
+
+ if return_info:
+ info["hidden_states"].append(x)
+
+ x = self.project_out(x)
+
+ if return_info:
+ return x, info
+
+ return x
+
+ def refine_mask(self, mask):
+ return mask
+ # pdb.set_trace()
+ # mask = 1 - torch.triu(torch.ones(seq_length, seq_length), diagonal=1)
+ # return mask
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/hifigan/f0_predictor.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/hifigan/f0_predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..36b85f4ed90c3a412cb179f49ccb471132a86550
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/hifigan/f0_predictor.py
@@ -0,0 +1,55 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Kai Hu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import torch
+import torch.nn as nn
+from torch.nn.utils import weight_norm
+
+
+class ConvRNNF0Predictor(nn.Module):
+ def __init__(self,
+ num_class: int = 1,
+ in_channels: int = 80,
+ cond_channels: int = 512
+ ):
+ super().__init__()
+
+ self.num_class = num_class
+ self.condnet = nn.Sequential(
+ weight_norm(
+ nn.Conv1d(in_channels, cond_channels, kernel_size=3, padding=1)
+ ),
+ nn.ELU(),
+ weight_norm(
+ nn.Conv1d(cond_channels, cond_channels, kernel_size=3, padding=1)
+ ),
+ nn.ELU(),
+ weight_norm(
+ nn.Conv1d(cond_channels, cond_channels, kernel_size=3, padding=1)
+ ),
+ nn.ELU(),
+ weight_norm(
+ nn.Conv1d(cond_channels, cond_channels, kernel_size=3, padding=1)
+ ),
+ nn.ELU(),
+ weight_norm(
+ nn.Conv1d(cond_channels, cond_channels, kernel_size=3, padding=1)
+ ),
+ nn.ELU(),
+ )
+ self.classifier = nn.Linear(in_features=cond_channels, out_features=self.num_class)
+
+ def forward(self, x: torch.Tensor) -> torch.Tensor:
+ x = self.condnet(x)
+ x = x.transpose(1, 2)
+ return torch.abs(self.classifier(x).squeeze(-1))
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/hifigan/generator.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/hifigan/generator.py
new file mode 100644
index 0000000000000000000000000000000000000000..a43ac05a7d828c86965d3f56b6798d522689089f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/hifigan/generator.py
@@ -0,0 +1,398 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Kai Hu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""HIFI-GAN"""
+
+import typing as tp
+import numpy as np
+from scipy.signal import get_window
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from torch.nn import Conv1d
+from torch.nn import ConvTranspose1d
+from torch.nn.utils import remove_weight_norm
+from torch.nn.utils import weight_norm
+from torch.distributions.uniform import Uniform
+
+from cosyvoice.transformer.activation import Snake
+from cosyvoice.utils.common import get_padding
+from cosyvoice.utils.common import init_weights
+
+
+"""hifigan based generator implementation.
+
+This code is modified from https://github.com/jik876/hifi-gan
+ ,https://github.com/kan-bayashi/ParallelWaveGAN and
+ https://github.com/NVIDIA/BigVGAN
+
+"""
+
+
+class ResBlock(torch.nn.Module):
+ """Residual block module in HiFiGAN/BigVGAN."""
+ def __init__(
+ self,
+ channels: int = 512,
+ kernel_size: int = 3,
+ dilations: tp.List[int] = [1, 3, 5],
+ ):
+ super(ResBlock, self).__init__()
+ self.convs1 = nn.ModuleList()
+ self.convs2 = nn.ModuleList()
+
+ for dilation in dilations:
+ self.convs1.append(
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=dilation,
+ padding=get_padding(kernel_size, dilation)
+ )
+ )
+ )
+ self.convs2.append(
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=1,
+ padding=get_padding(kernel_size, 1)
+ )
+ )
+ )
+ self.convs1.apply(init_weights)
+ self.convs2.apply(init_weights)
+ self.activations1 = nn.ModuleList([
+ Snake(channels, alpha_logscale=False)
+ for _ in range(len(self.convs1))
+ ])
+ self.activations2 = nn.ModuleList([
+ Snake(channels, alpha_logscale=False)
+ for _ in range(len(self.convs2))
+ ])
+
+ def forward(self, x: torch.Tensor) -> torch.Tensor:
+ for idx in range(len(self.convs1)):
+ xt = self.activations1[idx](x)
+ xt = self.convs1[idx](xt)
+ xt = self.activations2[idx](xt)
+ xt = self.convs2[idx](xt)
+ x = xt + x
+ return x
+
+ def remove_weight_norm(self):
+ for idx in range(len(self.convs1)):
+ remove_weight_norm(self.convs1[idx])
+ remove_weight_norm(self.convs2[idx])
+
+
+class SineGen(torch.nn.Module):
+ """ Definition of sine generator
+ SineGen(samp_rate, harmonic_num = 0,
+ sine_amp = 0.1, noise_std = 0.003,
+ voiced_threshold = 0,
+ flag_for_pulse=False)
+ samp_rate: sampling rate in Hz
+ harmonic_num: number of harmonic overtones (default 0)
+ sine_amp: amplitude of sine-wavefrom (default 0.1)
+ noise_std: std of Gaussian noise (default 0.003)
+ voiced_thoreshold: F0 threshold for U/V classification (default 0)
+ flag_for_pulse: this SinGen is used inside PulseGen (default False)
+ Note: when flag_for_pulse is True, the first time step of a voiced
+ segment is always sin(np.pi) or cos(0)
+ """
+
+ def __init__(self, samp_rate, harmonic_num=0,
+ sine_amp=0.1, noise_std=0.003,
+ voiced_threshold=0):
+ super(SineGen, self).__init__()
+ self.sine_amp = sine_amp
+ self.noise_std = noise_std
+ self.harmonic_num = harmonic_num
+ self.sampling_rate = samp_rate
+ self.voiced_threshold = voiced_threshold
+
+ def _f02uv(self, f0):
+ # generate uv signal
+ uv = (f0 > self.voiced_threshold).type(torch.float32)
+ return uv
+
+ @torch.no_grad()
+ def forward(self, f0):
+ """
+ :param f0: [B, 1, sample_len], Hz
+ :return: [B, 1, sample_len]
+ """
+
+ F_mat = torch.zeros((f0.size(0), self.harmonic_num + 1, f0.size(-1))).to(f0.device)
+ for i in range(self.harmonic_num + 1):
+ F_mat[:, i: i + 1, :] = f0 * (i + 1) / self.sampling_rate
+
+ theta_mat = 2 * np.pi * (torch.cumsum(F_mat, dim=-1) % 1)
+ u_dist = Uniform(low=-np.pi, high=np.pi)
+ phase_vec = u_dist.sample(sample_shape=(f0.size(0), self.harmonic_num + 1, 1)).to(F_mat.device)
+ phase_vec[:, 0, :] = 0
+
+ # generate sine waveforms
+ sine_waves = self.sine_amp * torch.sin(theta_mat + phase_vec)
+
+ # generate uv signal
+ uv = self._f02uv(f0)
+
+ # noise: for unvoiced should be similar to sine_amp
+ # std = self.sine_amp/3 -> max value ~ self.sine_amp
+ # . for voiced regions is self.noise_std
+ noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+ noise = noise_amp * torch.randn_like(sine_waves)
+
+ # first: set the unvoiced part to 0 by uv
+ # then: additive noise
+ sine_waves = sine_waves * uv + noise
+ return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+ """ SourceModule for hn-nsf
+ SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+ add_noise_std=0.003, voiced_threshod=0)
+ sampling_rate: sampling_rate in Hz
+ harmonic_num: number of harmonic above F0 (default: 0)
+ sine_amp: amplitude of sine source signal (default: 0.1)
+ add_noise_std: std of additive Gaussian noise (default: 0.003)
+ note that amplitude of noise in unvoiced is decided
+ by sine_amp
+ voiced_threshold: threhold to set U/V given F0 (default: 0)
+ Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+ F0_sampled (batchsize, length, 1)
+ Sine_source (batchsize, length, 1)
+ noise_source (batchsize, length 1)
+ uv (batchsize, length, 1)
+ """
+
+ def __init__(self, sampling_rate, upsample_scale, harmonic_num=0, sine_amp=0.1,
+ add_noise_std=0.003, voiced_threshod=0):
+ super(SourceModuleHnNSF, self).__init__()
+
+ self.sine_amp = sine_amp
+ self.noise_std = add_noise_std
+
+ # to produce sine waveforms
+ self.l_sin_gen = SineGen(sampling_rate, harmonic_num,
+ sine_amp, add_noise_std, voiced_threshod)
+
+ # to merge source harmonics into a single excitation
+ self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+ self.l_tanh = torch.nn.Tanh()
+
+ def forward(self, x):
+ """
+ Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+ F0_sampled (batchsize, length, 1)
+ Sine_source (batchsize, length, 1)
+ noise_source (batchsize, length 1)
+ """
+ # source for harmonic branch
+ with torch.no_grad():
+ sine_wavs, uv, _ = self.l_sin_gen(x.transpose(1, 2))
+ sine_wavs = sine_wavs.transpose(1, 2)
+ uv = uv.transpose(1, 2)
+ sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+
+ # source for noise branch, in the same shape as uv
+ noise = torch.randn_like(uv) * self.sine_amp / 3
+ return sine_merge, noise, uv
+
+
+class HiFTGenerator(nn.Module):
+ """
+ HiFTNet Generator: Neural Source Filter + ISTFTNet
+ https://arxiv.org/abs/2309.09493
+ """
+ def __init__(
+ self,
+ in_channels: int = 80,
+ base_channels: int = 512,
+ nb_harmonics: int = 8,
+ sampling_rate: int = 22050,
+ nsf_alpha: float = 0.1,
+ nsf_sigma: float = 0.003,
+ nsf_voiced_threshold: float = 10,
+ upsample_rates: tp.List[int] = [8, 8],
+ upsample_kernel_sizes: tp.List[int] = [16, 16],
+ istft_params: tp.Dict[str, int] = {"n_fft": 16, "hop_len": 4},
+ resblock_kernel_sizes: tp.List[int] = [3, 7, 11],
+ resblock_dilation_sizes: tp.List[tp.List[int]] = [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+ source_resblock_kernel_sizes: tp.List[int] = [7, 11],
+ source_resblock_dilation_sizes: tp.List[tp.List[int]] = [[1, 3, 5], [1, 3, 5]],
+ lrelu_slope: float = 0.1,
+ audio_limit: float = 0.99,
+ f0_predictor: torch.nn.Module = None,
+ ):
+ super(HiFTGenerator, self).__init__()
+
+ self.out_channels = 1
+ self.nb_harmonics = nb_harmonics
+ self.sampling_rate = sampling_rate
+ self.istft_params = istft_params
+ self.lrelu_slope = lrelu_slope
+ self.audio_limit = audio_limit
+
+ self.num_kernels = len(resblock_kernel_sizes)
+ self.num_upsamples = len(upsample_rates)
+ self.m_source = SourceModuleHnNSF(
+ sampling_rate=sampling_rate,
+ upsample_scale=np.prod(upsample_rates) * istft_params["hop_len"],
+ harmonic_num=nb_harmonics,
+ sine_amp=nsf_alpha,
+ add_noise_std=nsf_sigma,
+ voiced_threshod=nsf_voiced_threshold)
+ self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates) * istft_params["hop_len"])
+
+ self.conv_pre = weight_norm(
+ Conv1d(in_channels, base_channels, 7, 1, padding=3)
+ )
+
+ # Up
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+ self.ups.append(
+ weight_norm(
+ ConvTranspose1d(
+ base_channels // (2**i),
+ base_channels // (2**(i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ )
+
+ # Down
+ self.source_downs = nn.ModuleList()
+ self.source_resblocks = nn.ModuleList()
+ downsample_rates = [1] + upsample_rates[::-1][:-1]
+ downsample_cum_rates = np.cumprod(downsample_rates)
+ for i, (u, k, d) in enumerate(zip(downsample_cum_rates[::-1], source_resblock_kernel_sizes, source_resblock_dilation_sizes)):
+ if u == 1:
+ self.source_downs.append(
+ Conv1d(istft_params["n_fft"] + 2, base_channels // (2 ** (i + 1)), 1, 1)
+ )
+ else:
+ self.source_downs.append(
+ Conv1d(istft_params["n_fft"] + 2, base_channels // (2 ** (i + 1)), u * 2, u, padding=(u // 2))
+ )
+
+ self.source_resblocks.append(
+ ResBlock(base_channels // (2 ** (i + 1)), k, d)
+ )
+
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = base_channels // (2**(i + 1))
+ for _, (k, d) in enumerate(zip(resblock_kernel_sizes, resblock_dilation_sizes)):
+ self.resblocks.append(ResBlock(ch, k, d))
+
+ self.conv_post = weight_norm(Conv1d(ch, istft_params["n_fft"] + 2, 7, 1, padding=3))
+ self.ups.apply(init_weights)
+ self.conv_post.apply(init_weights)
+ self.reflection_pad = nn.ReflectionPad1d((1, 0))
+ self.stft_window = torch.from_numpy(get_window("hann", istft_params["n_fft"], fftbins=True).astype(np.float32))
+ self.f0_predictor = f0_predictor
+
+ def _f02source(self, f0: torch.Tensor) -> torch.Tensor:
+ f0 = self.f0_upsamp(f0[:, None]).transpose(1, 2) # bs,n,t
+
+ har_source, _, _ = self.m_source(f0)
+ return har_source.transpose(1, 2)
+
+ def _stft(self, x):
+ spec = torch.stft(
+ x,
+ self.istft_params["n_fft"], self.istft_params["hop_len"], self.istft_params["n_fft"], window=self.stft_window.to(x.device),
+ return_complex=True)
+ spec = torch.view_as_real(spec) # [B, F, TT, 2]
+ return spec[..., 0], spec[..., 1]
+
+ def _istft(self, magnitude, phase):
+ magnitude = torch.clip(magnitude, max=1e2)
+ real = magnitude * torch.cos(phase)
+ img = magnitude * torch.sin(phase)
+ inverse_transform = torch.istft(torch.complex(real, img), self.istft_params["n_fft"], self.istft_params["hop_len"],
+ self.istft_params["n_fft"], window=self.stft_window.to(magnitude.device))
+ return inverse_transform
+
+ def forward(self, x: torch.Tensor, cache_source: torch.Tensor = torch.zeros(1, 1, 0)) -> torch.Tensor:
+ f0 = self.f0_predictor(x)
+ s = self._f02source(f0)
+
+ # use cache_source to avoid glitch
+ if cache_source.shape[2] != 0:
+ s[:, :, :cache_source.shape[2]] = cache_source
+
+ s_stft_real, s_stft_imag = self._stft(s.squeeze(1))
+ s_stft = torch.cat([s_stft_real, s_stft_imag], dim=1)
+
+ x = self.conv_pre(x)
+ for i in range(self.num_upsamples):
+ x = F.leaky_relu(x, self.lrelu_slope)
+ x = self.ups[i](x)
+
+ if i == self.num_upsamples - 1:
+ x = self.reflection_pad(x)
+
+ # fusion
+ si = self.source_downs[i](s_stft)
+ si = self.source_resblocks[i](si)
+ x = x + si
+
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+
+ x = F.leaky_relu(x)
+ x = self.conv_post(x)
+ magnitude = torch.exp(x[:, :self.istft_params["n_fft"] // 2 + 1, :])
+ phase = torch.sin(x[:, self.istft_params["n_fft"] // 2 + 1:, :]) # actually, sin is redundancy
+
+ x = self._istft(magnitude, phase)
+ x = torch.clamp(x, -self.audio_limit, self.audio_limit)
+ return x, s
+
+ def remove_weight_norm(self):
+ print('Removing weight norm...')
+ for l in self.ups:
+ remove_weight_norm(l)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+ remove_weight_norm(self.conv_pre)
+ remove_weight_norm(self.conv_post)
+ self.source_module.remove_weight_norm()
+ for l in self.source_downs:
+ remove_weight_norm(l)
+ for l in self.source_resblocks:
+ l.remove_weight_norm()
+
+ @torch.inference_mode()
+ def inference(self, mel: torch.Tensor, cache_source: torch.Tensor = torch.zeros(1, 1, 0)) -> torch.Tensor:
+ return self.forward(x=mel, cache_source=cache_source)
\ No newline at end of file
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/llm/llm.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/llm/llm.py
new file mode 100644
index 0000000000000000000000000000000000000000..3b418c5d1017c6f8412418dd8d1c1b7790947241
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/llm/llm.py
@@ -0,0 +1,206 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from typing import Dict, Optional, Union
+import torch
+from torch import nn
+import torch.nn.functional as F
+from torch.nn.utils.rnn import pad_sequence, unpad_sequence
+from cosyvoice.utils.common import IGNORE_ID
+from cosyvoice.transformer.label_smoothing_loss import LabelSmoothingLoss
+from cosyvoice.utils.common import th_accuracy
+
+
+class TransformerLM(torch.nn.Module):
+ def __init__(
+ self,
+ text_encoder_input_size: int,
+ llm_input_size: int,
+ llm_output_size: int,
+ text_token_size: int,
+ speech_token_size: int,
+ text_encoder: torch.nn.Module,
+ llm: torch.nn.Module,
+ length_normalized_loss: bool = True,
+ lsm_weight: float = 0.0,
+ spk_embed_dim: int = 192,
+ ):
+ super().__init__()
+ self.llm_input_size = llm_input_size
+ self.speech_token_size = speech_token_size
+ # 1. build text token inputs related modules
+ self.text_embedding = torch.nn.Embedding(text_token_size, text_encoder_input_size)
+ self.text_encoder = text_encoder
+ self.text_encoder_affine_layer = nn.Linear(
+ self.text_encoder.output_size(),
+ llm_input_size
+ )
+
+ # 2. build speech token language model related modules
+ self.sos_eos = 0
+ self.task_id = 1
+ self.llm_embedding = torch.nn.Embedding(2, llm_input_size)
+ self.llm = llm
+ self.llm_decoder = nn.Linear(llm_output_size, speech_token_size + 1)
+ self.criterion_ce = LabelSmoothingLoss(
+ size=speech_token_size + 1,
+ padding_idx=IGNORE_ID,
+ smoothing=lsm_weight,
+ normalize_length=length_normalized_loss,
+ )
+
+ # 3. [Optional] build speech token related modules
+ self.speech_embedding = torch.nn.Embedding(speech_token_size, llm_input_size)
+ self.spk_embed_affine_layer = torch.nn.Linear(spk_embed_dim, llm_input_size)
+
+ def encode(
+ self,
+ text: torch.Tensor,
+ text_lengths: torch.Tensor,
+ ):
+ encoder_out, encoder_mask = self.text_encoder(text, text_lengths, decoding_chunk_size=1, num_decoding_left_chunks=-1)
+ encoder_out_lens = encoder_mask.squeeze(1).sum(1)
+ encoder_out = self.text_encoder_affine_layer(encoder_out)
+ return encoder_out, encoder_out_lens
+
+ def pad_unpad_sequence(self, sos_eos_emb, embedding, text_token, text_token_len, task_id_emb, speech_token, speech_token_len):
+ text_token = unpad_sequence(text_token, text_token_len.cpu(), batch_first=True)
+ speech_token = unpad_sequence(speech_token, speech_token_len.cpu(), batch_first=True)
+ lm_input = [torch.concat([sos_eos_emb.squeeze(dim=0), embedding[i], text_token[i], task_id_emb.squeeze(dim=0), speech_token[i]], dim=0) for i in range(len(text_token))]
+ lm_input_len = torch.tensor([i.size(0) for i in lm_input], dtype=torch.int32)
+ lm_input = pad_sequence(lm_input, batch_first=True, padding_value=IGNORE_ID)
+ return lm_input, lm_input_len
+
+ def forward(
+ self,
+ batch: dict,
+ device: torch.device,
+ ) -> Dict[str, Optional[torch.Tensor]]:
+ """
+ Args:
+ text: (B, L, D)
+ text_lengths: (B,)
+ audio: (B, T, N) or (B, T)
+ audio_lengths: (B,)
+ """
+ text_token = batch['text_token'].to(device)
+ text_token_len = batch['text_token_len'].to(device)
+ speech_token = batch['speech_token'].to(device)
+ speech_token_len = batch['speech_token_len'].to(device)
+ embedding = batch['embedding'].to(device)
+
+ # 1. prepare llm_target
+ lm_target = [torch.tensor([IGNORE_ID] * (2 + text_token_len[i]) + speech_token[i, :speech_token_len[i]].tolist() + [self.speech_token_size]) for i in range(text_token.size(0))]
+ lm_target = pad_sequence(lm_target, batch_first=True, padding_value=IGNORE_ID).to(device)
+
+ # 1. encode text_token
+ text_token = self.text_embedding(text_token)
+ text_token, text_token_len = self.encode(text_token, text_token_len)
+
+ # 2. embedding projection
+ embedding = F.normalize(embedding, dim=1)
+ embedding = self.spk_embed_affine_layer(embedding)
+ embedding = embedding.unsqueeze(1)
+
+ # 3. eos and task_id
+ sos_eos_emb = self.llm_embedding.weight[self.sos_eos].reshape(1, 1, -1)
+ task_id_emb = self.llm_embedding.weight[self.task_id].reshape(1, 1, -1)
+
+ # 4. encode speech_token
+ speech_token = self.speech_embedding(speech_token)
+
+ # 5. unpad and pad
+ lm_input, lm_input_len = self.pad_unpad_sequence(sos_eos_emb, embedding, text_token, text_token_len, task_id_emb, speech_token, speech_token_len)
+
+ # 6. run lm forward
+ lm_output, lm_output_mask = self.llm(lm_input, lm_input_len.to(device))
+ logits = self.llm_decoder(lm_output)
+ loss = self.criterion_ce(logits, lm_target)
+ acc = th_accuracy(logits.view(-1, self.speech_token_size + 1), lm_target, ignore_label=IGNORE_ID)
+ return {'loss': loss, 'acc': acc}
+
+ def sampling_ids(
+ self,
+ weighted_scores: torch.Tensor,
+ sampling: Union[bool, int, float] = True,
+ beam_size: int = 1,
+ ignore_eos: bool = True,
+ ):
+ while True:
+ prob, indices = weighted_scores.softmax(dim=-1).topk(sampling)
+ top_ids = prob.multinomial(beam_size, replacement=True)
+ top_ids = indices[top_ids]
+ if (not ignore_eos) or (self.speech_token_size not in top_ids):
+ break
+ return top_ids
+
+ @torch.inference_mode()
+ def inference(
+ self,
+ text: torch.Tensor,
+ text_len: torch.Tensor,
+ prompt_text: torch.Tensor,
+ prompt_text_len: torch.Tensor,
+ prompt_speech_token: torch.Tensor,
+ prompt_speech_token_len: torch.Tensor,
+ embedding: torch.Tensor,
+ beam_size: int = 1,
+ sampling: int = 25,
+ max_token_text_ratio: float = 20,
+ min_token_text_ratio: float = 2,
+ ) -> torch.Tensor:
+ device = text.device
+ text = torch.concat([prompt_text, text], dim=1)
+ text_len += prompt_text_len
+ text = self.text_embedding(text)
+
+ # 1. encode text
+ text, text_len = self.encode(text, text_len)
+
+ # 2. encode embedding
+ if embedding.shape[0] != 0:
+ embedding = F.normalize(embedding, dim=1)
+ embedding = self.spk_embed_affine_layer(embedding)
+ embedding = embedding.unsqueeze(dim=1)
+ else:
+ embedding = torch.zeros(1, 0, self.llm_input_size).to(device)
+
+ # 3. concat llm_input
+ sos_eos_emb = self.llm_embedding.weight[self.sos_eos].reshape(1, 1, -1)
+ task_id_emb = self.llm_embedding.weight[self.task_id].reshape(1, 1, -1)
+ if prompt_speech_token_len != 0:
+ prompt_speech_token_emb = self.speech_embedding(prompt_speech_token)
+ else:
+ prompt_speech_token_emb = torch.zeros(1, 0, self.llm_input_size).to(device)
+ lm_input = torch.concat([sos_eos_emb, embedding, text, task_id_emb, prompt_speech_token_emb], dim=1)
+
+ # 4. cal min/max_length
+ min_len = int((text_len - prompt_text_len) * min_token_text_ratio)
+ max_len = int((text_len - prompt_text_len) * max_token_text_ratio)
+
+ # 5. step by step decode
+ out_tokens = []
+ offset = 0
+ att_cache, cnn_cache = torch.zeros((0, 0, 0, 0), device=lm_input.device), torch.zeros((0, 0, 0, 0), device=lm_input.device)
+ for i in range(max_len):
+ y_pred, att_cache, cnn_cache = self.llm.forward_chunk(lm_input, offset=0, required_cache_size=-1, att_cache=att_cache, cnn_cache=cnn_cache,
+ att_mask=torch.tril(torch.ones((1, lm_input.shape[1], lm_input.shape[1]), device=lm_input.device)).to(torch.bool))
+ logp = self.llm_decoder(y_pred[:, -1]).log_softmax(dim=-1)
+ top_ids = self.sampling_ids(logp.squeeze(dim=0), sampling, beam_size, ignore_eos=True if i < min_len else False).item()
+ if top_ids == self.speech_token_size:
+ break
+ out_tokens.append(top_ids)
+ offset += lm_input.size(1)
+ lm_input = self.speech_embedding.weight[top_ids].reshape(1, 1, -1)
+
+ return torch.tensor([out_tokens], dtype=torch.int64, device=device)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/activation.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/activation.py
new file mode 100644
index 0000000000000000000000000000000000000000..8cea54816385d3b6585ccc2417bc71630d578177
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/activation.py
@@ -0,0 +1,84 @@
+# Copyright (c) 2020 Johns Hopkins University (Shinji Watanabe)
+# 2020 Northwestern Polytechnical University (Pengcheng Guo)
+# 2020 Mobvoi Inc (Binbin Zhang)
+# 2024 Alibaba Inc (Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Swish() activation function for Conformer."""
+
+import torch
+from torch import nn, sin, pow
+from torch.nn import Parameter
+
+
+class Swish(torch.nn.Module):
+ """Construct an Swish object."""
+
+ def forward(self, x: torch.Tensor) -> torch.Tensor:
+ """Return Swish activation function."""
+ return x * torch.sigmoid(x)
+
+
+# Implementation adapted from https://github.com/EdwardDixon/snake under the MIT license.
+# LICENSE is in incl_licenses directory.
+class Snake(nn.Module):
+ '''
+ Implementation of a sine-based periodic activation function
+ Shape:
+ - Input: (B, C, T)
+ - Output: (B, C, T), same shape as the input
+ Parameters:
+ - alpha - trainable parameter
+ References:
+ - This activation function is from this paper by Liu Ziyin, Tilman Hartwig, Masahito Ueda:
+ https://arxiv.org/abs/2006.08195
+ Examples:
+ >>> a1 = snake(256)
+ >>> x = torch.randn(256)
+ >>> x = a1(x)
+ '''
+ def __init__(self, in_features, alpha=1.0, alpha_trainable=True, alpha_logscale=False):
+ '''
+ Initialization.
+ INPUT:
+ - in_features: shape of the input
+ - alpha: trainable parameter
+ alpha is initialized to 1 by default, higher values = higher-frequency.
+ alpha will be trained along with the rest of your model.
+ '''
+ super(Snake, self).__init__()
+ self.in_features = in_features
+
+ # initialize alpha
+ self.alpha_logscale = alpha_logscale
+ if self.alpha_logscale: # log scale alphas initialized to zeros
+ self.alpha = Parameter(torch.zeros(in_features) * alpha)
+ else: # linear scale alphas initialized to ones
+ self.alpha = Parameter(torch.ones(in_features) * alpha)
+
+ self.alpha.requires_grad = alpha_trainable
+
+ self.no_div_by_zero = 0.000000001
+
+ def forward(self, x):
+ '''
+ Forward pass of the function.
+ Applies the function to the input elementwise.
+ Snake ∶= x + 1/a * sin^2 (xa)
+ '''
+ alpha = self.alpha.unsqueeze(0).unsqueeze(-1) # line up with x to [B, C, T]
+ if self.alpha_logscale:
+ alpha = torch.exp(alpha)
+ x = x + (1.0 / (alpha + self.no_div_by_zero)) * pow(sin(x * alpha), 2)
+
+ return x
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/attention.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/attention.py
new file mode 100644
index 0000000000000000000000000000000000000000..b9aaa62d1ec0954e9a168b42bc66702e41591aed
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/attention.py
@@ -0,0 +1,612 @@
+# Copyright (c) 2019 Shigeki Karita
+# 2020 Mobvoi Inc (Binbin Zhang)
+# 2022 Xingchen Song (sxc19@mails.tsinghua.edu.cn)
+# 2024 Alibaba Inc (Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Multi-Head Attention layer definition."""
+
+import math
+from typing import Tuple
+
+import torch
+from torch import nn
+
+
+class MultiHeadedAttention(nn.Module):
+ """Multi-Head Attention layer.
+
+ Args:
+ n_head (int): The number of heads.
+ n_feat (int): The number of features.
+ dropout_rate (float): Dropout rate.
+
+ """
+
+ def __init__(self,
+ n_head: int,
+ n_feat: int,
+ dropout_rate: float,
+ key_bias: bool = True):
+ """Construct an MultiHeadedAttention object."""
+ super().__init__()
+ assert n_feat % n_head == 0
+ # We assume d_v always equals d_k
+ self.d_k = n_feat // n_head
+ self.h = n_head
+ self.linear_q = nn.Linear(n_feat, n_feat)
+ self.linear_k = nn.Linear(n_feat, n_feat, bias=key_bias)
+ self.linear_v = nn.Linear(n_feat, n_feat)
+ self.linear_out = nn.Linear(n_feat, n_feat)
+ self.dropout = nn.Dropout(p=dropout_rate)
+
+ def forward_qkv(
+ self, query: torch.Tensor, key: torch.Tensor, value: torch.Tensor
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Transform query, key and value.
+
+ Args:
+ query (torch.Tensor): Query tensor (#batch, time1, size).
+ key (torch.Tensor): Key tensor (#batch, time2, size).
+ value (torch.Tensor): Value tensor (#batch, time2, size).
+
+ Returns:
+ torch.Tensor: Transformed query tensor, size
+ (#batch, n_head, time1, d_k).
+ torch.Tensor: Transformed key tensor, size
+ (#batch, n_head, time2, d_k).
+ torch.Tensor: Transformed value tensor, size
+ (#batch, n_head, time2, d_k).
+
+ """
+ n_batch = query.size(0)
+ q = self.linear_q(query).view(n_batch, -1, self.h, self.d_k)
+ k = self.linear_k(key).view(n_batch, -1, self.h, self.d_k)
+ v = self.linear_v(value).view(n_batch, -1, self.h, self.d_k)
+ q = q.transpose(1, 2) # (batch, head, time1, d_k)
+ k = k.transpose(1, 2) # (batch, head, time2, d_k)
+ v = v.transpose(1, 2) # (batch, head, time2, d_k)
+
+ return q, k, v
+
+ def forward_attention(
+ self,
+ value: torch.Tensor,
+ scores: torch.Tensor,
+ mask: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool)
+ ) -> torch.Tensor:
+ """Compute attention context vector.
+
+ Args:
+ value (torch.Tensor): Transformed value, size
+ (#batch, n_head, time2, d_k).
+ scores (torch.Tensor): Attention score, size
+ (#batch, n_head, time1, time2).
+ mask (torch.Tensor): Mask, size (#batch, 1, time2) or
+ (#batch, time1, time2), (0, 0, 0) means fake mask.
+
+ Returns:
+ torch.Tensor: Transformed value (#batch, time1, d_model)
+ weighted by the attention score (#batch, time1, time2).
+
+ """
+ n_batch = value.size(0)
+ # NOTE(xcsong): When will `if mask.size(2) > 0` be True?
+ # 1. onnx(16/4) [WHY? Because we feed real cache & real mask for the
+ # 1st chunk to ease the onnx export.]
+ # 2. pytorch training
+ if mask.size(2) > 0: # time2 > 0
+ mask = mask.unsqueeze(1).eq(0) # (batch, 1, *, time2)
+ # For last chunk, time2 might be larger than scores.size(-1)
+ mask = mask[:, :, :, :scores.size(-1)] # (batch, 1, *, time2)
+ scores = scores.masked_fill(mask, -float('inf'))
+ attn = torch.softmax(scores, dim=-1).masked_fill(
+ mask, 0.0) # (batch, head, time1, time2)
+ # NOTE(xcsong): When will `if mask.size(2) > 0` be False?
+ # 1. onnx(16/-1, -1/-1, 16/0)
+ # 2. jit (16/-1, -1/-1, 16/0, 16/4)
+ else:
+ attn = torch.softmax(scores, dim=-1) # (batch, head, time1, time2)
+
+ p_attn = self.dropout(attn)
+ x = torch.matmul(p_attn, value) # (batch, head, time1, d_k)
+ x = (x.transpose(1, 2).contiguous().view(n_batch, -1,
+ self.h * self.d_k)
+ ) # (batch, time1, d_model)
+
+ return self.linear_out(x) # (batch, time1, d_model)
+
+ def forward(
+ self,
+ query: torch.Tensor,
+ key: torch.Tensor,
+ value: torch.Tensor,
+ mask: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+ pos_emb: torch.Tensor = torch.empty(0),
+ cache: torch.Tensor = torch.zeros((0, 0, 0, 0))
+ ) -> Tuple[torch.Tensor, torch.Tensor]:
+ """Compute scaled dot product attention.
+
+ Args:
+ query (torch.Tensor): Query tensor (#batch, time1, size).
+ key (torch.Tensor): Key tensor (#batch, time2, size).
+ value (torch.Tensor): Value tensor (#batch, time2, size).
+ mask (torch.Tensor): Mask tensor (#batch, 1, time2) or
+ (#batch, time1, time2).
+ 1.When applying cross attention between decoder and encoder,
+ the batch padding mask for input is in (#batch, 1, T) shape.
+ 2.When applying self attention of encoder,
+ the mask is in (#batch, T, T) shape.
+ 3.When applying self attention of decoder,
+ the mask is in (#batch, L, L) shape.
+ 4.If the different position in decoder see different block
+ of the encoder, such as Mocha, the passed in mask could be
+ in (#batch, L, T) shape. But there is no such case in current
+ CosyVoice.
+ cache (torch.Tensor): Cache tensor (1, head, cache_t, d_k * 2),
+ where `cache_t == chunk_size * num_decoding_left_chunks`
+ and `head * d_k == size`
+
+
+ Returns:
+ torch.Tensor: Output tensor (#batch, time1, d_model).
+ torch.Tensor: Cache tensor (1, head, cache_t + time1, d_k * 2)
+ where `cache_t == chunk_size * num_decoding_left_chunks`
+ and `head * d_k == size`
+
+ """
+ q, k, v = self.forward_qkv(query, key, value)
+
+ # NOTE(xcsong):
+ # when export onnx model, for 1st chunk, we feed
+ # cache(1, head, 0, d_k * 2) (16/-1, -1/-1, 16/0 mode)
+ # or cache(1, head, real_cache_t, d_k * 2) (16/4 mode).
+ # In all modes, `if cache.size(0) > 0` will alwayse be `True`
+ # and we will always do splitting and
+ # concatnation(this will simplify onnx export). Note that
+ # it's OK to concat & split zero-shaped tensors(see code below).
+ # when export jit model, for 1st chunk, we always feed
+ # cache(0, 0, 0, 0) since jit supports dynamic if-branch.
+ # >>> a = torch.ones((1, 2, 0, 4))
+ # >>> b = torch.ones((1, 2, 3, 4))
+ # >>> c = torch.cat((a, b), dim=2)
+ # >>> torch.equal(b, c) # True
+ # >>> d = torch.split(a, 2, dim=-1)
+ # >>> torch.equal(d[0], d[1]) # True
+ if cache.size(0) > 0:
+ key_cache, value_cache = torch.split(cache,
+ cache.size(-1) // 2,
+ dim=-1)
+ k = torch.cat([key_cache, k], dim=2)
+ v = torch.cat([value_cache, v], dim=2)
+ # NOTE(xcsong): We do cache slicing in encoder.forward_chunk, since it's
+ # non-trivial to calculate `next_cache_start` here.
+ new_cache = torch.cat((k, v), dim=-1)
+
+ scores = torch.matmul(q, k.transpose(-2, -1)) / math.sqrt(self.d_k)
+ return self.forward_attention(v, scores, mask), new_cache
+
+
+class RelPositionMultiHeadedAttention(MultiHeadedAttention):
+ """Multi-Head Attention layer with relative position encoding.
+ Paper: https://arxiv.org/abs/1901.02860
+ Args:
+ n_head (int): The number of heads.
+ n_feat (int): The number of features.
+ dropout_rate (float): Dropout rate.
+ """
+
+ def __init__(self,
+ n_head: int,
+ n_feat: int,
+ dropout_rate: float,
+ key_bias: bool = True):
+ """Construct an RelPositionMultiHeadedAttention object."""
+ super().__init__(n_head, n_feat, dropout_rate, key_bias)
+ # linear transformation for positional encoding
+ self.linear_pos = nn.Linear(n_feat, n_feat, bias=False)
+ # these two learnable bias are used in matrix c and matrix d
+ # as described in https://arxiv.org/abs/1901.02860 Section 3.3
+ self.pos_bias_u = nn.Parameter(torch.Tensor(self.h, self.d_k))
+ self.pos_bias_v = nn.Parameter(torch.Tensor(self.h, self.d_k))
+ torch.nn.init.xavier_uniform_(self.pos_bias_u)
+ torch.nn.init.xavier_uniform_(self.pos_bias_v)
+
+ def rel_shift(self, x):
+ """Compute relative positional encoding.
+
+ Args:
+ x (torch.Tensor): Input tensor (batch, head, time1, 2*time1-1).
+ time1 means the length of query vector.
+
+ Returns:
+ torch.Tensor: Output tensor.
+
+ """
+ zero_pad = torch.zeros((*x.size()[:3], 1), device=x.device, dtype=x.dtype)
+ x_padded = torch.cat([zero_pad, x], dim=-1)
+
+ x_padded = x_padded.view(*x.size()[:2], x.size(3) + 1, x.size(2))
+ x = x_padded[:, :, 1:].view_as(x)[
+ :, :, :, : x.size(-1) // 2 + 1
+ ] # only keep the positions from 0 to time2
+ return x
+
+ def forward(
+ self,
+ query: torch.Tensor,
+ key: torch.Tensor,
+ value: torch.Tensor,
+ mask: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+ pos_emb: torch.Tensor = torch.empty(0),
+ cache: torch.Tensor = torch.zeros((0, 0, 0, 0))
+ ) -> Tuple[torch.Tensor, torch.Tensor]:
+ """Compute 'Scaled Dot Product Attention' with rel. positional encoding.
+ Args:
+ query (torch.Tensor): Query tensor (#batch, time1, size).
+ key (torch.Tensor): Key tensor (#batch, time2, size).
+ value (torch.Tensor): Value tensor (#batch, time2, size).
+ mask (torch.Tensor): Mask tensor (#batch, 1, time2) or
+ (#batch, time1, time2), (0, 0, 0) means fake mask.
+ pos_emb (torch.Tensor): Positional embedding tensor
+ (#batch, time2, size).
+ cache (torch.Tensor): Cache tensor (1, head, cache_t, d_k * 2),
+ where `cache_t == chunk_size * num_decoding_left_chunks`
+ and `head * d_k == size`
+ Returns:
+ torch.Tensor: Output tensor (#batch, time1, d_model).
+ torch.Tensor: Cache tensor (1, head, cache_t + time1, d_k * 2)
+ where `cache_t == chunk_size * num_decoding_left_chunks`
+ and `head * d_k == size`
+ """
+ q, k, v = self.forward_qkv(query, key, value)
+ q = q.transpose(1, 2) # (batch, time1, head, d_k)
+
+ # NOTE(xcsong):
+ # when export onnx model, for 1st chunk, we feed
+ # cache(1, head, 0, d_k * 2) (16/-1, -1/-1, 16/0 mode)
+ # or cache(1, head, real_cache_t, d_k * 2) (16/4 mode).
+ # In all modes, `if cache.size(0) > 0` will alwayse be `True`
+ # and we will always do splitting and
+ # concatnation(this will simplify onnx export). Note that
+ # it's OK to concat & split zero-shaped tensors(see code below).
+ # when export jit model, for 1st chunk, we always feed
+ # cache(0, 0, 0, 0) since jit supports dynamic if-branch.
+ # >>> a = torch.ones((1, 2, 0, 4))
+ # >>> b = torch.ones((1, 2, 3, 4))
+ # >>> c = torch.cat((a, b), dim=2)
+ # >>> torch.equal(b, c) # True
+ # >>> d = torch.split(a, 2, dim=-1)
+ # >>> torch.equal(d[0], d[1]) # True
+ if cache.size(0) > 0:
+ key_cache, value_cache = torch.split(cache,
+ cache.size(-1) // 2,
+ dim=-1)
+ k = torch.cat([key_cache, k], dim=2)
+ v = torch.cat([value_cache, v], dim=2)
+ # NOTE(xcsong): We do cache slicing in encoder.forward_chunk, since it's
+ # non-trivial to calculate `next_cache_start` here.
+ new_cache = torch.cat((k, v), dim=-1)
+
+ n_batch_pos = pos_emb.size(0)
+ p = self.linear_pos(pos_emb).view(n_batch_pos, -1, self.h, self.d_k)
+ p = p.transpose(1, 2) # (batch, head, time1, d_k)
+
+ # (batch, head, time1, d_k)
+ q_with_bias_u = (q + self.pos_bias_u).transpose(1, 2)
+ # (batch, head, time1, d_k)
+ q_with_bias_v = (q + self.pos_bias_v).transpose(1, 2)
+
+ # compute attention score
+ # first compute matrix a and matrix c
+ # as described in https://arxiv.org/abs/1901.02860 Section 3.3
+ # (batch, head, time1, time2)
+ matrix_ac = torch.matmul(q_with_bias_u, k.transpose(-2, -1))
+
+ # compute matrix b and matrix d
+ # (batch, head, time1, time2)
+ matrix_bd = torch.matmul(q_with_bias_v, p.transpose(-2, -1))
+ # NOTE(Xiang Lyu): Keep rel_shift since espnet rel_pos_emb is used
+ if matrix_ac.shape != matrix_bd.shape:
+ matrix_bd = self.rel_shift(matrix_bd)
+
+ scores = (matrix_ac + matrix_bd) / math.sqrt(
+ self.d_k) # (batch, head, time1, time2)
+
+ return self.forward_attention(v, scores, mask), new_cache
+
+
+
+
+# class BlockRelPositionMultiHeadedAttention(MultiHeadedAttention):
+# """Multi-Head Attention layer with relative position encoding.
+# Paper: https://arxiv.org/abs/1901.02860
+# Args:
+# n_head (int): The number of heads.
+# n_feat (int): The number of features.
+# dropout_rate (float): Dropout rate.
+# """
+
+# def __init__(self,
+# n_head: int,
+# n_feat: int,
+# dropout_rate: float,
+# key_bias: bool = True,
+# block_size=25):
+# """Construct an RelPositionMultiHeadedAttention object."""
+# super().__init__(n_head, n_feat, dropout_rate, key_bias)
+# # linear transformation for positional encoding
+# self.linear_pos = nn.Linear(n_feat, n_feat, bias=False)
+# # these two learnable bias are used in matrix c and matrix d
+# # as described in https://arxiv.org/abs/1901.02860 Section 3.3
+# self.pos_bias_u = nn.Parameter(torch.Tensor(self.h, self.d_k))
+# self.pos_bias_v = nn.Parameter(torch.Tensor(self.h, self.d_k))
+# torch.nn.init.xavier_uniform_(self.pos_bias_u)
+# torch.nn.init.xavier_uniform_(self.pos_bias_v)
+# self.block_size=block_size
+
+# def rel_shift(self, x):
+# """Compute relative positional encoding.
+
+# Args:
+# x (torch.Tensor): Input tensor (batch, head, time1, 2*time1-1).
+# time1 means the length of query vector.
+
+# Returns:
+# torch.Tensor: Output tensor.
+
+# """
+# zero_pad = torch.zeros((*x.size()[:3], 1), device=x.device, dtype=x.dtype)
+# x_padded = torch.cat([zero_pad, x], dim=-1)
+
+# x_padded = x_padded.view(*x.size()[:2], x.size(3) + 1, x.size(2))
+# x = x_padded[:, :, 1:].view_as(x)[
+# :, :, :, : x.size(-1) // 2 + 1
+# ] # only keep the positions from 0 to time2
+# return x
+
+# def forward(
+# self,
+# query: torch.Tensor,
+# key: torch.Tensor,
+# value: torch.Tensor,
+# mask: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+# pos_emb: torch.Tensor = torch.empty(0),
+# cache: torch.Tensor = torch.zeros((0, 0, 0, 0))
+# ) -> Tuple[torch.Tensor, torch.Tensor]:
+# """Compute 'Scaled Dot Product Attention' with rel. positional encoding.
+# Args:
+# query (torch.Tensor): Query tensor (#batch, time1, size).
+# key (torch.Tensor): Key tensor (#batch, time2, size).
+# value (torch.Tensor): Value tensor (#batch, time2, size).
+# mask (torch.Tensor): Mask tensor (#batch, 1, time2) or
+# (#batch, time1, time2), (0, 0, 0) means fake mask.
+# pos_emb (torch.Tensor): Positional embedding tensor
+# (#batch, time2, size).
+# cache (torch.Tensor): Cache tensor (1, head, cache_t, d_k * 2),
+# where `cache_t == chunk_size * num_decoding_left_chunks`
+# and `head * d_k == size`
+# Returns:
+# torch.Tensor: Output tensor (#batch, time1, d_model).
+# torch.Tensor: Cache tensor (1, head, cache_t + time1, d_k * 2)
+# where `cache_t == chunk_size * num_decoding_left_chunks`
+# and `head * d_k == size`
+# """
+# q, k, v = self.forward_qkv(query, key, value)
+# q = q.transpose(1, 2) # (batch, time1, head, d_k)
+
+# # NOTE(xcsong):
+# # when export onnx model, for 1st chunk, we feed
+# # cache(1, head, 0, d_k * 2) (16/-1, -1/-1, 16/0 mode)
+# # or cache(1, head, real_cache_t, d_k * 2) (16/4 mode).
+# # In all modes, `if cache.size(0) > 0` will alwayse be `True`
+# # and we will always do splitting and
+# # concatnation(this will simplify onnx export). Note that
+# # it's OK to concat & split zero-shaped tensors(see code below).
+# # when export jit model, for 1st chunk, we always feed
+# # cache(0, 0, 0, 0) since jit supports dynamic if-branch.
+# # >>> a = torch.ones((1, 2, 0, 4))
+# # >>> b = torch.ones((1, 2, 3, 4))
+# # >>> c = torch.cat((a, b), dim=2)
+# # >>> torch.equal(b, c) # True
+# # >>> d = torch.split(a, 2, dim=-1)
+# # >>> torch.equal(d[0], d[1]) # True
+# if cache.size(0) > 0:
+# key_cache, value_cache = torch.split(cache,
+# cache.size(-1) // 2,
+# dim=-1)
+# k = torch.cat([key_cache, k], dim=2)
+# v = torch.cat([value_cache, v], dim=2)
+# # NOTE(xcsong): We do cache slicing in encoder.forward_chunk, since it's
+# # non-trivial to calculate `next_cache_start` here.
+# new_cache = torch.cat((k, v), dim=-1)
+
+# n_batch_pos = pos_emb.size(0)
+# p = self.linear_pos(pos_emb).view(n_batch_pos, -1, self.h, self.d_k)
+# p = p.transpose(1, 2) # (batch, head, time1, d_k)
+
+# # (batch, head, time1, d_k)
+# q_with_bias_u = (q + self.pos_bias_u).transpose(1, 2)
+# # (batch, head, time1, d_k)
+# q_with_bias_v = (q + self.pos_bias_v).transpose(1, 2)
+
+# # compute attention score
+# # first compute matrix a and matrix c
+# # as described in https://arxiv.org/abs/1901.02860 Section 3.3
+# # (batch, head, time1, time2)
+
+# # Compute matrix ac and bd
+# matrix_ac = torch.matmul(q_with_bias_u, k.transpose(-2, -1)) # (batch, head, time1, time2)
+# matrix_bd = torch.matmul(q_with_bias_v, p.transpose(-2, -1)) # (batch, head, time1, time2)
+
+# batch_size, num_heads, seq_len, _ = matrix_ac.shape
+
+# # Create block causal mask
+# block_mask = torch.triu(torch.ones(seq_len, seq_len), diagonal=self.block_size).to(matrix_ac.device).bool()
+# # mask = mask.masked_fill(mask == 1, float('-inf')) # mask upper triangular matrix beyond block
+
+# # Apply relative shift if necessary
+# if matrix_ac.shape != matrix_bd.shape:
+# matrix_bd = self.rel_shift(matrix_bd)
+
+# # Combine ac and bd and apply the block causal mask
+# scores = (matrix_ac + matrix_bd) / math.sqrt(self.d_k) # (batch, head, time1, time2)
+# scores = scores.masked_fill(block_mask.unsqueeze(0).unsqueeze(0), float('-inf')) # apply the block mask
+
+# # Forward attention
+# return self.forward_attention(v, scores, mask), new_cache
+
+
+
+from cosyvoice.utils import block_mask_util
+class BlockRelPositionMultiHeadedAttention(MultiHeadedAttention):
+ """Multi-Head Attention layer with relative position encoding.
+ Paper: https://arxiv.org/abs/1901.02860
+ Args:
+ n_head (int): The number of heads.
+ n_feat (int): The number of features.
+ dropout_rate (float): Dropout rate.
+ """
+
+ def __init__(self,
+ n_head: int,
+ n_feat: int,
+ dropout_rate: float,
+ key_bias: bool = True, block_size=25):
+ """Construct an RelPositionMultiHeadedAttention object."""
+ super().__init__(n_head, n_feat, dropout_rate, key_bias)
+ # linear transformation for positional encoding
+ self.linear_pos = nn.Linear(n_feat, n_feat, bias=False)
+ # these two learnable bias are used in matrix c and matrix d
+ # as described in https://arxiv.org/abs/1901.02860 Section 3.3
+ self.pos_bias_u = nn.Parameter(torch.Tensor(self.h, self.d_k))
+ self.pos_bias_v = nn.Parameter(torch.Tensor(self.h, self.d_k))
+ torch.nn.init.xavier_uniform_(self.pos_bias_u)
+ torch.nn.init.xavier_uniform_(self.pos_bias_v)
+ self.block_size = block_size
+
+ def rel_shift(self, x: torch.Tensor) -> torch.Tensor:
+ """Compute relative positional encoding.
+
+ Args:
+ x (torch.Tensor): Input tensor (batch, head, time1, 2*time1-1).
+ time1 means the length of query vector.
+
+ Returns:
+ torch.Tensor: Output tensor.
+
+ """
+ zero_pad = torch.zeros((x.size()[0], x.size()[1], x.size()[2], 1),
+ device=x.device,
+ dtype=x.dtype)
+ x_padded = torch.cat([zero_pad, x], dim=-1)
+
+ x_padded = x_padded.view(x.size()[0],
+ x.size()[1],
+ x.size(3) + 1, x.size(2))
+ x = x_padded[:, :, 1:].view_as(x)[
+ :, :, :, : x.size(-1) // 2 + 1
+ ] # only keep the positions from 0 to time2
+ return x
+
+ def forward(
+ self,
+ query: torch.Tensor,
+ key: torch.Tensor,
+ value: torch.Tensor,
+ mask: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+ pos_emb: torch.Tensor = torch.empty(0),
+ cache: torch.Tensor = torch.zeros((0, 0, 0, 0))
+ ) -> Tuple[torch.Tensor, torch.Tensor]:
+ """Compute 'Scaled Dot Product Attention' with rel. positional encoding.
+ Args:
+ query (torch.Tensor): Query tensor (#batch, time1, size).
+ key (torch.Tensor): Key tensor (#batch, time2, size).
+ value (torch.Tensor): Value tensor (#batch, time2, size).
+ mask (torch.Tensor): Mask tensor (#batch, 1, time2) or
+ (#batch, time1, time2), (0, 0, 0) means fake mask.
+ pos_emb (torch.Tensor): Positional embedding tensor
+ (#batch, time2, size).
+ cache (torch.Tensor): Cache tensor (1, head, cache_t, d_k * 2),
+ where `cache_t == chunk_size * num_decoding_left_chunks`
+ and `head * d_k == size`
+ Returns:
+ torch.Tensor: Output tensor (#batch, time1, d_model).
+ torch.Tensor: Cache tensor (1, head, cache_t + time1, d_k * 2)
+ where `cache_t == chunk_size * num_decoding_left_chunks`
+ and `head * d_k == size`
+ """
+ q, k, v = self.forward_qkv(query, key, value)
+ q = q.transpose(1, 2) # (batch, time1, head, d_k)
+
+ # 0代表被mask的位置
+ bs, time_len, _ = query.shape
+ # mask = torch.tril(torch.ones(time_len, time_len).to(mask), diagonal=0).int()
+ # block_size = self.block_size
+ # mask[:, 0:block_size] = 1
+ block_mask = block_mask_util.create_grid_mask(time_len,self.block_size,fill_triangle=True).to(query).int()
+ block_mask = block_mask[None].repeat(bs, 1, 1)
+ mask=mask*block_mask
+
+ # NOTE(xcsong):
+ # when export onnx model, for 1st chunk, we feed
+ # cache(1, head, 0, d_k * 2) (16/-1, -1/-1, 16/0 mode)
+ # or cache(1, head, real_cache_t, d_k * 2) (16/4 mode).
+ # In all modes, `if cache.size(0) > 0` will alwayse be `True`
+ # and we will always do splitting and
+ # concatnation(this will simplify onnx export). Note that
+ # it's OK to concat & split zero-shaped tensors(see code below).
+ # when export jit model, for 1st chunk, we always feed
+ # cache(0, 0, 0, 0) since jit supports dynamic if-branch.
+ # >>> a = torch.ones((1, 2, 0, 4))
+ # >>> b = torch.ones((1, 2, 3, 4))
+ # >>> c = torch.cat((a, b), dim=2)
+ # >>> torch.equal(b, c) # True
+ # >>> d = torch.split(a, 2, dim=-1)
+ # >>> torch.equal(d[0], d[1]) # True
+ if cache.size(0) > 0:
+ key_cache, value_cache = torch.split(cache,
+ cache.size(-1) // 2,
+ dim=-1)
+ k = torch.cat([key_cache, k], dim=2)
+ v = torch.cat([value_cache, v], dim=2)
+ # NOTE(xcsong): We do cache slicing in encoder.forward_chunk, since it's
+ # non-trivial to calculate `next_cache_start` here.
+ new_cache = torch.cat((k, v), dim=-1)
+
+ n_batch_pos = pos_emb.size(0)
+ p = self.linear_pos(pos_emb).view(n_batch_pos, -1, self.h, self.d_k)
+ p = p.transpose(1, 2) # (batch, head, time1, d_k)
+
+ # (batch, head, time1, d_k)
+ q_with_bias_u = (q + self.pos_bias_u).transpose(1, 2)
+ # (batch, head, time1, d_k)
+ q_with_bias_v = (q + self.pos_bias_v).transpose(1, 2)
+
+ # compute attention score
+ # first compute matrix a and matrix c
+ # as described in https://arxiv.org/abs/1901.02860 Section 3.3
+ # (batch, head, time1, time2)
+ matrix_ac = torch.matmul(q_with_bias_u, k.transpose(-2, -1))
+
+ # compute matrix b and matrix d
+ # (batch, head, time1, time2)
+ matrix_bd = torch.matmul(q_with_bias_v, p.transpose(-2, -1))
+ # NOTE(Xiang Lyu): Keep rel_shift since espnet rel_pos_emb is used
+ if matrix_ac.shape != matrix_bd.shape:
+ matrix_bd = self.rel_shift(matrix_bd)
+
+ scores = (matrix_ac + matrix_bd) / math.sqrt(
+ self.d_k) # (batch, head, time1, time2)
+
+ return self.forward_attention(v, scores, mask), new_cache
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/convolution.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/convolution.py
new file mode 100644
index 0000000000000000000000000000000000000000..4d5d96149154776000991a681a666fbe55e562fe
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/convolution.py
@@ -0,0 +1,145 @@
+# Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang, Di Wu)
+# 2024 Alibaba Inc (Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+"""ConvolutionModule definition."""
+
+from typing import Tuple
+
+import torch
+from torch import nn
+
+
+class ConvolutionModule(nn.Module):
+ """ConvolutionModule in Conformer model."""
+
+ def __init__(self,
+ channels: int,
+ kernel_size: int = 15,
+ activation: nn.Module = nn.ReLU(),
+ norm: str = "batch_norm",
+ causal: bool = False,
+ bias: bool = True):
+ """Construct an ConvolutionModule object.
+ Args:
+ channels (int): The number of channels of conv layers.
+ kernel_size (int): Kernel size of conv layers.
+ causal (int): Whether use causal convolution or not
+ """
+ super().__init__()
+
+ self.pointwise_conv1 = nn.Conv1d(
+ channels,
+ 2 * channels,
+ kernel_size=1,
+ stride=1,
+ padding=0,
+ bias=bias,
+ )
+ # self.lorder is used to distinguish if it's a causal convolution,
+ # if self.lorder > 0: it's a causal convolution, the input will be
+ # padded with self.lorder frames on the left in forward.
+ # else: it's a symmetrical convolution
+ if causal:
+ padding = 0
+ self.lorder = kernel_size - 1
+ else:
+ # kernel_size should be an odd number for none causal convolution
+ assert (kernel_size - 1) % 2 == 0
+ padding = (kernel_size - 1) // 2
+ self.lorder = 0
+ self.depthwise_conv = nn.Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ stride=1,
+ padding=padding,
+ groups=channels,
+ bias=bias,
+ )
+
+ assert norm in ['batch_norm', 'layer_norm']
+ if norm == "batch_norm":
+ self.use_layer_norm = False
+ self.norm = nn.BatchNorm1d(channels)
+ else:
+ self.use_layer_norm = True
+ self.norm = nn.LayerNorm(channels)
+
+ self.pointwise_conv2 = nn.Conv1d(
+ channels,
+ channels,
+ kernel_size=1,
+ stride=1,
+ padding=0,
+ bias=bias,
+ )
+ self.activation = activation
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ mask_pad: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+ cache: torch.Tensor = torch.zeros((0, 0, 0)),
+ ) -> Tuple[torch.Tensor, torch.Tensor]:
+ """Compute convolution module.
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, channels).
+ mask_pad (torch.Tensor): used for batch padding (#batch, 1, time),
+ (0, 0, 0) means fake mask.
+ cache (torch.Tensor): left context cache, it is only
+ used in causal convolution (#batch, channels, cache_t),
+ (0, 0, 0) meas fake cache.
+ Returns:
+ torch.Tensor: Output tensor (#batch, time, channels).
+ """
+ # exchange the temporal dimension and the feature dimension
+ x = x.transpose(1, 2) # (#batch, channels, time)
+
+ # mask batch padding
+ if mask_pad.size(2) > 0: # time > 0
+ x.masked_fill_(~mask_pad, 0.0)
+
+ if self.lorder > 0:
+ if cache.size(2) == 0: # cache_t == 0
+ x = nn.functional.pad(x, (self.lorder, 0), 'constant', 0.0)
+ else:
+ assert cache.size(0) == x.size(0) # equal batch
+ assert cache.size(1) == x.size(1) # equal channel
+ x = torch.cat((cache, x), dim=2)
+ assert (x.size(2) > self.lorder)
+ new_cache = x[:, :, -self.lorder:]
+ else:
+ # It's better we just return None if no cache is required,
+ # However, for JIT export, here we just fake one tensor instead of
+ # None.
+ new_cache = torch.zeros((0, 0, 0), dtype=x.dtype, device=x.device)
+
+ # GLU mechanism
+ x = self.pointwise_conv1(x) # (batch, 2*channel, dim)
+ x = nn.functional.glu(x, dim=1) # (batch, channel, dim)
+
+ # 1D Depthwise Conv
+ x = self.depthwise_conv(x)
+ if self.use_layer_norm:
+ x = x.transpose(1, 2)
+ x = self.activation(self.norm(x))
+ if self.use_layer_norm:
+ x = x.transpose(1, 2)
+ x = self.pointwise_conv2(x)
+ # mask batch padding
+ if mask_pad.size(2) > 0: # time > 0
+ x.masked_fill_(~mask_pad, 0.0)
+
+ return x.transpose(1, 2), new_cache
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/decoder.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/decoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..961c875eab519f7a9e8a6e56720dc878b7852372
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/decoder.py
@@ -0,0 +1,396 @@
+# Copyright (c) 2021 Mobvoi Inc. (authors: Binbin Zhang, Di Wu)
+# 2024 Alibaba Inc (Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+"""Decoder definition."""
+from typing import Tuple, List, Optional
+
+import torch
+import torch.utils.checkpoint as ckpt
+import logging
+
+from cosyvoice.transformer.decoder_layer import DecoderLayer
+from cosyvoice.transformer.positionwise_feed_forward import PositionwiseFeedForward
+from cosyvoice.utils.class_utils import (
+ COSYVOICE_EMB_CLASSES,
+ COSYVOICE_ATTENTION_CLASSES,
+ COSYVOICE_ACTIVATION_CLASSES,
+)
+from cosyvoice.utils.mask import (subsequent_mask, make_pad_mask)
+
+
+class TransformerDecoder(torch.nn.Module):
+ """Base class of Transfomer decoder module.
+ Args:
+ vocab_size: output dim
+ encoder_output_size: dimension of attention
+ attention_heads: the number of heads of multi head attention
+ linear_units: the hidden units number of position-wise feedforward
+ num_blocks: the number of decoder blocks
+ dropout_rate: dropout rate
+ self_attention_dropout_rate: dropout rate for attention
+ input_layer: input layer type
+ use_output_layer: whether to use output layer
+ pos_enc_class: PositionalEncoding or ScaledPositionalEncoding
+ normalize_before:
+ True: use layer_norm before each sub-block of a layer.
+ False: use layer_norm after each sub-block of a layer.
+ src_attention: if false, encoder-decoder cross attention is not
+ applied, such as CIF model
+ key_bias: whether use bias in attention.linear_k, False for whisper models.
+ gradient_checkpointing: rerunning a forward-pass segment for each
+ checkpointed segment during backward.
+ tie_word_embedding: Tie or clone module weights depending of whether we are
+ using TorchScript or not
+ """
+
+ def __init__(
+ self,
+ vocab_size: int,
+ encoder_output_size: int,
+ attention_heads: int = 4,
+ linear_units: int = 2048,
+ num_blocks: int = 6,
+ dropout_rate: float = 0.1,
+ positional_dropout_rate: float = 0.1,
+ self_attention_dropout_rate: float = 0.0,
+ src_attention_dropout_rate: float = 0.0,
+ input_layer: str = "embed",
+ use_output_layer: bool = True,
+ normalize_before: bool = True,
+ src_attention: bool = True,
+ key_bias: bool = True,
+ activation_type: str = "relu",
+ gradient_checkpointing: bool = False,
+ tie_word_embedding: bool = False,
+ ):
+ super().__init__()
+ attention_dim = encoder_output_size
+ activation = COSYVOICE_ACTIVATION_CLASSES[activation_type]()
+
+ self.embed = torch.nn.Sequential(
+ torch.nn.Identity() if input_layer == "no_pos" else
+ torch.nn.Embedding(vocab_size, attention_dim),
+ COSYVOICE_EMB_CLASSES[input_layer](attention_dim,
+ positional_dropout_rate),
+ )
+
+ self.normalize_before = normalize_before
+ self.after_norm = torch.nn.LayerNorm(attention_dim, eps=1e-5)
+ self.use_output_layer = use_output_layer
+ if use_output_layer:
+ self.output_layer = torch.nn.Linear(attention_dim, vocab_size)
+ else:
+ self.output_layer = torch.nn.Identity()
+ self.num_blocks = num_blocks
+ self.decoders = torch.nn.ModuleList([
+ DecoderLayer(
+ attention_dim,
+ COSYVOICE_ATTENTION_CLASSES["selfattn"](
+ attention_heads, attention_dim,
+ self_attention_dropout_rate, key_bias),
+ COSYVOICE_ATTENTION_CLASSES["selfattn"](
+ attention_heads, attention_dim, src_attention_dropout_rate,
+ key_bias) if src_attention else None,
+ PositionwiseFeedForward(attention_dim, linear_units,
+ dropout_rate, activation),
+ dropout_rate,
+ normalize_before,
+ ) for _ in range(self.num_blocks)
+ ])
+
+ self.gradient_checkpointing = gradient_checkpointing
+ self.tie_word_embedding = tie_word_embedding
+
+ def forward(
+ self,
+ memory: torch.Tensor,
+ memory_mask: torch.Tensor,
+ ys_in_pad: torch.Tensor,
+ ys_in_lens: torch.Tensor,
+ r_ys_in_pad: torch.Tensor = torch.empty(0),
+ reverse_weight: float = 0.0,
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Forward decoder.
+ Args:
+ memory: encoded memory, float32 (batch, maxlen_in, feat)
+ memory_mask: encoder memory mask, (batch, 1, maxlen_in)
+ ys_in_pad: padded input token ids, int64 (batch, maxlen_out)
+ ys_in_lens: input lengths of this batch (batch)
+ r_ys_in_pad: not used in transformer decoder, in order to unify api
+ with bidirectional decoder
+ reverse_weight: not used in transformer decoder, in order to unify
+ api with bidirectional decode
+ Returns:
+ (tuple): tuple containing:
+ x: decoded token score before softmax (batch, maxlen_out,
+ vocab_size) if use_output_layer is True,
+ torch.tensor(0.0), in order to unify api with bidirectional decoder
+ olens: (batch, )
+ NOTE(xcsong):
+ We pass the `__call__` method of the modules instead of `forward` to the
+ checkpointing API because `__call__` attaches all the hooks of the module.
+ https://discuss.pytorch.org/t/any-different-between-model-input-and-model-forward-input/3690/2
+ """
+ tgt = ys_in_pad
+ maxlen = tgt.size(1)
+ # tgt_mask: (B, 1, L)
+ tgt_mask = ~make_pad_mask(ys_in_lens, maxlen).unsqueeze(1)
+ tgt_mask = tgt_mask.to(tgt.device)
+ # m: (1, L, L)
+ m = subsequent_mask(tgt_mask.size(-1),
+ device=tgt_mask.device).unsqueeze(0)
+ # tgt_mask: (B, L, L)
+ tgt_mask = tgt_mask & m
+ x, _ = self.embed(tgt)
+ if self.gradient_checkpointing and self.training:
+ x = self.forward_layers_checkpointed(x, tgt_mask, memory,
+ memory_mask)
+ else:
+ x = self.forward_layers(x, tgt_mask, memory, memory_mask)
+ if self.normalize_before:
+ x = self.after_norm(x)
+ if self.use_output_layer:
+ x = self.output_layer(x)
+ olens = tgt_mask.sum(1)
+ return x, torch.tensor(0.0), olens
+
+ def forward_layers(self, x: torch.Tensor, tgt_mask: torch.Tensor,
+ memory: torch.Tensor,
+ memory_mask: torch.Tensor) -> torch.Tensor:
+ for layer in self.decoders:
+ x, tgt_mask, memory, memory_mask = layer(x, tgt_mask, memory,
+ memory_mask)
+ return x
+
+ @torch.jit.ignore(drop=True)
+ def forward_layers_checkpointed(self, x: torch.Tensor,
+ tgt_mask: torch.Tensor,
+ memory: torch.Tensor,
+ memory_mask: torch.Tensor) -> torch.Tensor:
+ for layer in self.decoders:
+ x, tgt_mask, memory, memory_mask = ckpt.checkpoint(
+ layer.__call__, x, tgt_mask, memory, memory_mask)
+ return x
+
+ def forward_one_step(
+ self,
+ memory: torch.Tensor,
+ memory_mask: torch.Tensor,
+ tgt: torch.Tensor,
+ tgt_mask: torch.Tensor,
+ cache: Optional[List[torch.Tensor]] = None,
+ ) -> Tuple[torch.Tensor, List[torch.Tensor]]:
+ """Forward one step.
+ This is only used for decoding.
+ Args:
+ memory: encoded memory, float32 (batch, maxlen_in, feat)
+ memory_mask: encoded memory mask, (batch, 1, maxlen_in)
+ tgt: input token ids, int64 (batch, maxlen_out)
+ tgt_mask: input token mask, (batch, maxlen_out)
+ dtype=torch.uint8 in PyTorch 1.2-
+ dtype=torch.bool in PyTorch 1.2+ (include 1.2)
+ cache: cached output list of (batch, max_time_out-1, size)
+ Returns:
+ y, cache: NN output value and cache per `self.decoders`.
+ y.shape` is (batch, maxlen_out, token)
+ """
+ x, _ = self.embed(tgt)
+ new_cache = []
+ for i, decoder in enumerate(self.decoders):
+ if cache is None:
+ c = None
+ else:
+ c = cache[i]
+ x, tgt_mask, memory, memory_mask = decoder(x,
+ tgt_mask,
+ memory,
+ memory_mask,
+ cache=c)
+ new_cache.append(x)
+ if self.normalize_before:
+ y = self.after_norm(x[:, -1])
+ else:
+ y = x[:, -1]
+ if self.use_output_layer:
+ y = torch.log_softmax(self.output_layer(y), dim=-1)
+ return y, new_cache
+
+ def tie_or_clone_weights(self, jit_mode: bool = True):
+ """Tie or clone module weights (between word_emb and output_layer)
+ depending of whether we are using TorchScript or not"""
+ if not self.use_output_layer:
+ return
+ if jit_mode:
+ logging.info("clone emb.weight to output.weight")
+ self.output_layer.weight = torch.nn.Parameter(
+ self.embed[0].weight.clone())
+ else:
+ logging.info("tie emb.weight with output.weight")
+ self.output_layer.weight = self.embed[0].weight
+
+ if getattr(self.output_layer, "bias", None) is not None:
+ self.output_layer.bias.data = torch.nn.functional.pad(
+ self.output_layer.bias.data,
+ (
+ 0,
+ self.output_layer.weight.shape[0] -
+ self.output_layer.bias.shape[0],
+ ),
+ "constant",
+ 0,
+ )
+
+
+class BiTransformerDecoder(torch.nn.Module):
+ """Base class of Transfomer decoder module.
+ Args:
+ vocab_size: output dim
+ encoder_output_size: dimension of attention
+ attention_heads: the number of heads of multi head attention
+ linear_units: the hidden units number of position-wise feedforward
+ num_blocks: the number of decoder blocks
+ r_num_blocks: the number of right to left decoder blocks
+ dropout_rate: dropout rate
+ self_attention_dropout_rate: dropout rate for attention
+ input_layer: input layer type
+ use_output_layer: whether to use output layer
+ pos_enc_class: PositionalEncoding or ScaledPositionalEncoding
+ normalize_before:
+ True: use layer_norm before each sub-block of a layer.
+ False: use layer_norm after each sub-block of a layer.
+ key_bias: whether use bias in attention.linear_k, False for whisper models.
+ """
+
+ def __init__(
+ self,
+ vocab_size: int,
+ encoder_output_size: int,
+ attention_heads: int = 4,
+ linear_units: int = 2048,
+ num_blocks: int = 6,
+ r_num_blocks: int = 0,
+ dropout_rate: float = 0.1,
+ positional_dropout_rate: float = 0.1,
+ self_attention_dropout_rate: float = 0.0,
+ src_attention_dropout_rate: float = 0.0,
+ input_layer: str = "embed",
+ use_output_layer: bool = True,
+ normalize_before: bool = True,
+ key_bias: bool = True,
+ gradient_checkpointing: bool = False,
+ tie_word_embedding: bool = False,
+ ):
+
+ super().__init__()
+ self.tie_word_embedding = tie_word_embedding
+ self.left_decoder = TransformerDecoder(
+ vocab_size,
+ encoder_output_size,
+ attention_heads,
+ linear_units,
+ num_blocks,
+ dropout_rate,
+ positional_dropout_rate,
+ self_attention_dropout_rate,
+ src_attention_dropout_rate,
+ input_layer,
+ use_output_layer,
+ normalize_before,
+ key_bias=key_bias,
+ gradient_checkpointing=gradient_checkpointing,
+ tie_word_embedding=tie_word_embedding)
+
+ self.right_decoder = TransformerDecoder(
+ vocab_size,
+ encoder_output_size,
+ attention_heads,
+ linear_units,
+ r_num_blocks,
+ dropout_rate,
+ positional_dropout_rate,
+ self_attention_dropout_rate,
+ src_attention_dropout_rate,
+ input_layer,
+ use_output_layer,
+ normalize_before,
+ key_bias=key_bias,
+ gradient_checkpointing=gradient_checkpointing,
+ tie_word_embedding=tie_word_embedding)
+
+ def forward(
+ self,
+ memory: torch.Tensor,
+ memory_mask: torch.Tensor,
+ ys_in_pad: torch.Tensor,
+ ys_in_lens: torch.Tensor,
+ r_ys_in_pad: torch.Tensor,
+ reverse_weight: float = 0.0,
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Forward decoder.
+ Args:
+ memory: encoded memory, float32 (batch, maxlen_in, feat)
+ memory_mask: encoder memory mask, (batch, 1, maxlen_in)
+ ys_in_pad: padded input token ids, int64 (batch, maxlen_out)
+ ys_in_lens: input lengths of this batch (batch)
+ r_ys_in_pad: padded input token ids, int64 (batch, maxlen_out),
+ used for right to left decoder
+ reverse_weight: used for right to left decoder
+ Returns:
+ (tuple): tuple containing:
+ x: decoded token score before softmax (batch, maxlen_out,
+ vocab_size) if use_output_layer is True,
+ r_x: x: decoded token score (right to left decoder)
+ before softmax (batch, maxlen_out, vocab_size)
+ if use_output_layer is True,
+ olens: (batch, )
+ """
+ l_x, _, olens = self.left_decoder(memory, memory_mask, ys_in_pad,
+ ys_in_lens)
+ r_x = torch.tensor(0.0)
+ if reverse_weight > 0.0:
+ r_x, _, olens = self.right_decoder(memory, memory_mask,
+ r_ys_in_pad, ys_in_lens)
+ return l_x, r_x, olens
+
+ def forward_one_step(
+ self,
+ memory: torch.Tensor,
+ memory_mask: torch.Tensor,
+ tgt: torch.Tensor,
+ tgt_mask: torch.Tensor,
+ cache: Optional[List[torch.Tensor]] = None,
+ ) -> Tuple[torch.Tensor, List[torch.Tensor]]:
+ """Forward one step.
+ This is only used for decoding.
+ Args:
+ memory: encoded memory, float32 (batch, maxlen_in, feat)
+ memory_mask: encoded memory mask, (batch, 1, maxlen_in)
+ tgt: input token ids, int64 (batch, maxlen_out)
+ tgt_mask: input token mask, (batch, maxlen_out)
+ dtype=torch.uint8 in PyTorch 1.2-
+ dtype=torch.bool in PyTorch 1.2+ (include 1.2)
+ cache: cached output list of (batch, max_time_out-1, size)
+ Returns:
+ y, cache: NN output value and cache per `self.decoders`.
+ y.shape` is (batch, maxlen_out, token)
+ """
+ return self.left_decoder.forward_one_step(memory, memory_mask, tgt,
+ tgt_mask, cache)
+
+ def tie_or_clone_weights(self, jit_mode: bool = True):
+ """Tie or clone module weights (between word_emb and output_layer)
+ depending of whether we are using TorchScript or not"""
+ self.left_decoder.tie_or_clone_weights(jit_mode)
+ self.right_decoder.tie_or_clone_weights(jit_mode)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/decoder_layer.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/decoder_layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..91c7c5d7fb2a8e79cea7705646e5381016f73466
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/decoder_layer.py
@@ -0,0 +1,132 @@
+# Copyright (c) 2019 Shigeki Karita
+# 2020 Mobvoi Inc (Binbin Zhang)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Decoder self-attention layer definition."""
+from typing import Optional, Tuple
+
+import torch
+from torch import nn
+
+
+class DecoderLayer(nn.Module):
+ """Single decoder layer module.
+
+ Args:
+ size (int): Input dimension.
+ self_attn (torch.nn.Module): Self-attention module instance.
+ `MultiHeadedAttention` instance can be used as the argument.
+ src_attn (torch.nn.Module): Inter-attention module instance.
+ `MultiHeadedAttention` instance can be used as the argument.
+ If `None` is passed, Inter-attention is not used, such as
+ CIF, GPT, and other decoder only model.
+ feed_forward (torch.nn.Module): Feed-forward module instance.
+ `PositionwiseFeedForward` instance can be used as the argument.
+ dropout_rate (float): Dropout rate.
+ normalize_before (bool):
+ True: use layer_norm before each sub-block.
+ False: to use layer_norm after each sub-block.
+ """
+
+ def __init__(
+ self,
+ size: int,
+ self_attn: nn.Module,
+ src_attn: Optional[nn.Module],
+ feed_forward: nn.Module,
+ dropout_rate: float,
+ normalize_before: bool = True,
+ ):
+ """Construct an DecoderLayer object."""
+ super().__init__()
+ self.size = size
+ self.self_attn = self_attn
+ self.src_attn = src_attn
+ self.feed_forward = feed_forward
+ self.norm1 = nn.LayerNorm(size, eps=1e-5)
+ self.norm2 = nn.LayerNorm(size, eps=1e-5)
+ self.norm3 = nn.LayerNorm(size, eps=1e-5)
+ self.dropout = nn.Dropout(dropout_rate)
+ self.normalize_before = normalize_before
+
+ def forward(
+ self,
+ tgt: torch.Tensor,
+ tgt_mask: torch.Tensor,
+ memory: torch.Tensor,
+ memory_mask: torch.Tensor,
+ cache: Optional[torch.Tensor] = None
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Compute decoded features.
+
+ Args:
+ tgt (torch.Tensor): Input tensor (#batch, maxlen_out, size).
+ tgt_mask (torch.Tensor): Mask for input tensor
+ (#batch, maxlen_out).
+ memory (torch.Tensor): Encoded memory
+ (#batch, maxlen_in, size).
+ memory_mask (torch.Tensor): Encoded memory mask
+ (#batch, maxlen_in).
+ cache (torch.Tensor): cached tensors.
+ (#batch, maxlen_out - 1, size).
+
+ Returns:
+ torch.Tensor: Output tensor (#batch, maxlen_out, size).
+ torch.Tensor: Mask for output tensor (#batch, maxlen_out).
+ torch.Tensor: Encoded memory (#batch, maxlen_in, size).
+ torch.Tensor: Encoded memory mask (#batch, maxlen_in).
+
+ """
+ residual = tgt
+ if self.normalize_before:
+ tgt = self.norm1(tgt)
+
+ if cache is None:
+ tgt_q = tgt
+ tgt_q_mask = tgt_mask
+ else:
+ # compute only the last frame query keeping dim: max_time_out -> 1
+ assert cache.shape == (
+ tgt.shape[0],
+ tgt.shape[1] - 1,
+ self.size,
+ ), "{cache.shape} == {(tgt.shape[0], tgt.shape[1] - 1, self.size)}"
+ tgt_q = tgt[:, -1:, :]
+ residual = residual[:, -1:, :]
+ tgt_q_mask = tgt_mask[:, -1:, :]
+
+ x = residual + self.dropout(
+ self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)[0])
+ if not self.normalize_before:
+ x = self.norm1(x)
+
+ if self.src_attn is not None:
+ residual = x
+ if self.normalize_before:
+ x = self.norm2(x)
+ x = residual + self.dropout(
+ self.src_attn(x, memory, memory, memory_mask)[0])
+ if not self.normalize_before:
+ x = self.norm2(x)
+
+ residual = x
+ if self.normalize_before:
+ x = self.norm3(x)
+ x = residual + self.dropout(self.feed_forward(x))
+ if not self.normalize_before:
+ x = self.norm3(x)
+
+ if cache is not None:
+ x = torch.cat([cache, x], dim=1)
+
+ return x, tgt_mask, memory, memory_mask
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/embedding.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/embedding.py
new file mode 100644
index 0000000000000000000000000000000000000000..46130a503f72f103e09d3392077ed352368ce54f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/embedding.py
@@ -0,0 +1,293 @@
+# Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang, Di Wu)
+# 2024 Alibaba Inc (Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+"""Positonal Encoding Module."""
+
+import math
+from typing import Tuple, Union
+
+import torch
+import torch.nn.functional as F
+import numpy as np
+
+
+class PositionalEncoding(torch.nn.Module):
+ """Positional encoding.
+
+ :param int d_model: embedding dim
+ :param float dropout_rate: dropout rate
+ :param int max_len: maximum input length
+
+ PE(pos, 2i) = sin(pos/(10000^(2i/dmodel)))
+ PE(pos, 2i+1) = cos(pos/(10000^(2i/dmodel)))
+ """
+
+ def __init__(self,
+ d_model: int,
+ dropout_rate: float,
+ max_len: int = 5000,
+ reverse: bool = False):
+ """Construct an PositionalEncoding object."""
+ super().__init__()
+ self.d_model = d_model
+ self.xscale = math.sqrt(self.d_model)
+ self.dropout = torch.nn.Dropout(p=dropout_rate)
+ self.max_len = max_len
+
+ self.pe = torch.zeros(self.max_len, self.d_model)
+ position = torch.arange(0, self.max_len,
+ dtype=torch.float32).unsqueeze(1)
+ div_term = torch.exp(
+ torch.arange(0, self.d_model, 2, dtype=torch.float32) *
+ -(math.log(10000.0) / self.d_model))
+ self.pe[:, 0::2] = torch.sin(position * div_term)
+ self.pe[:, 1::2] = torch.cos(position * div_term)
+ self.pe = self.pe.unsqueeze(0)
+
+ def forward(self,
+ x: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0) \
+ -> Tuple[torch.Tensor, torch.Tensor]:
+ """Add positional encoding.
+
+ Args:
+ x (torch.Tensor): Input. Its shape is (batch, time, ...)
+ offset (int, torch.tensor): position offset
+
+ Returns:
+ torch.Tensor: Encoded tensor. Its shape is (batch, time, ...)
+ torch.Tensor: for compatibility to RelPositionalEncoding
+ """
+
+ self.pe = self.pe.to(x.device)
+ pos_emb = self.position_encoding(offset, x.size(1), False)
+ x = x * self.xscale + pos_emb
+ return self.dropout(x), self.dropout(pos_emb)
+
+ def position_encoding(self,
+ offset: Union[int, torch.Tensor],
+ size: int,
+ apply_dropout: bool = True) -> torch.Tensor:
+ """ For getting encoding in a streaming fashion
+
+ Attention!!!!!
+ we apply dropout only once at the whole utterance level in a none
+ streaming way, but will call this function several times with
+ increasing input size in a streaming scenario, so the dropout will
+ be applied several times.
+
+ Args:
+ offset (int or torch.tensor): start offset
+ size (int): required size of position encoding
+
+ Returns:
+ torch.Tensor: Corresponding encoding
+ """
+ # How to subscript a Union type:
+ # https://github.com/pytorch/pytorch/issues/69434
+ if isinstance(offset, int):
+ assert offset + size <= self.max_len
+ pos_emb = self.pe[:, offset:offset + size]
+ elif isinstance(offset, torch.Tensor) and offset.dim() == 0: # scalar
+ assert offset + size <= self.max_len
+ pos_emb = self.pe[:, offset:offset + size]
+ else: # for batched streaming decoding on GPU
+ assert torch.max(offset) + size <= self.max_len
+ index = offset.unsqueeze(1) + \
+ torch.arange(0, size).to(offset.device) # B X T
+ flag = index > 0
+ # remove negative offset
+ index = index * flag
+ pos_emb = F.embedding(index, self.pe[0]) # B X T X d_model
+
+ if apply_dropout:
+ pos_emb = self.dropout(pos_emb)
+ return pos_emb
+
+
+class RelPositionalEncoding(PositionalEncoding):
+ """Relative positional encoding module.
+ See : Appendix B in https://arxiv.org/abs/1901.02860
+ Args:
+ d_model (int): Embedding dimension.
+ dropout_rate (float): Dropout rate.
+ max_len (int): Maximum input length.
+ """
+
+ def __init__(self, d_model: int, dropout_rate: float, max_len: int = 5000):
+ """Initialize class."""
+ super().__init__(d_model, dropout_rate, max_len, reverse=True)
+
+ def forward(self,
+ x: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0) \
+ -> Tuple[torch.Tensor, torch.Tensor]:
+ """Compute positional encoding.
+ Args:
+ x (torch.Tensor): Input tensor (batch, time, `*`).
+ Returns:
+ torch.Tensor: Encoded tensor (batch, time, `*`).
+ torch.Tensor: Positional embedding tensor (1, time, `*`).
+ """
+ self.pe = self.pe.to(x.device)
+ x = x * self.xscale
+ pos_emb = self.position_encoding(offset, x.size(1), False)
+ return self.dropout(x), self.dropout(pos_emb)
+
+
+class WhisperPositionalEncoding(PositionalEncoding):
+ """ Sinusoids position encoding used in openai-whisper.encoder
+ """
+
+ def __init__(self, d_model: int, dropout_rate: float, max_len: int = 1500):
+ super().__init__(d_model, dropout_rate, max_len)
+ self.xscale = 1.0
+ log_timescale_increment = np.log(10000) / (d_model // 2 - 1)
+ inv_timescales = torch.exp(-log_timescale_increment *
+ torch.arange(d_model // 2))
+ scaled_time = torch.arange(max_len)[:, np.newaxis] * \
+ inv_timescales[np.newaxis, :]
+ pe = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], dim=1)
+ delattr(self, "pe")
+ self.register_buffer("pe", pe.unsqueeze(0))
+
+
+class LearnablePositionalEncoding(PositionalEncoding):
+ """ Learnable position encoding used in openai-whisper.decoder
+ """
+
+ def __init__(self, d_model: int, dropout_rate: float, max_len: int = 448):
+ super().__init__(d_model, dropout_rate, max_len)
+ # NOTE(xcsong): overwrite self.pe & self.xscale
+ self.pe = torch.nn.Parameter(torch.empty(1, max_len, d_model))
+ self.xscale = 1.0
+
+
+class NoPositionalEncoding(torch.nn.Module):
+ """ No position encoding
+ """
+
+ def __init__(self, d_model: int, dropout_rate: float):
+ super().__init__()
+ self.d_model = d_model
+ self.dropout = torch.nn.Dropout(p=dropout_rate)
+
+ def forward(self,
+ x: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0) \
+ -> Tuple[torch.Tensor, torch.Tensor]:
+ """ Just return zero vector for interface compatibility
+ """
+ pos_emb = torch.zeros(1, x.size(1), self.d_model).to(x.device)
+ return self.dropout(x), pos_emb
+
+ def position_encoding(self, offset: Union[int, torch.Tensor],
+ size: int) -> torch.Tensor:
+ return torch.zeros(1, size, self.d_model)
+
+
+class EspnetRelPositionalEncoding(torch.nn.Module):
+ """Relative positional encoding module (new implementation).
+
+ Details can be found in https://github.com/espnet/espnet/pull/2816.
+
+ See : Appendix B in https://arxiv.org/abs/1901.02860
+
+ Args:
+ d_model (int): Embedding dimension.
+ dropout_rate (float): Dropout rate.
+ max_len (int): Maximum input length.
+
+ """
+
+ def __init__(self, d_model, dropout_rate, max_len=5000):
+ """Construct an PositionalEncoding object."""
+ super(EspnetRelPositionalEncoding, self).__init__()
+ self.d_model = d_model
+ self.xscale = math.sqrt(self.d_model)
+ self.dropout = torch.nn.Dropout(p=dropout_rate)
+ self.pe = None
+ self.extend_pe(torch.tensor(0.0).expand(1, max_len))
+
+ def extend_pe(self, x):
+ """Reset the positional encodings."""
+ if self.pe is not None:
+ # self.pe contains both positive and negative parts
+ # the length of self.pe is 2 * input_len - 1
+ if self.pe.size(1) >= x.size(1) * 2 - 1:
+ if self.pe.dtype != x.dtype or self.pe.device != x.device:
+ self.pe = self.pe.to(dtype=x.dtype, device=x.device)
+ return
+ # Suppose `i` means to the position of query vecotr and `j` means the
+ # position of key vector. We use position relative positions when keys
+ # are to the left (i>j) and negative relative positions otherwise (i torch.Tensor:
+ """ For getting encoding in a streaming fashion
+
+ Attention!!!!!
+ we apply dropout only once at the whole utterance level in a none
+ streaming way, but will call this function several times with
+ increasing input size in a streaming scenario, so the dropout will
+ be applied several times.
+
+ Args:
+ offset (int or torch.tensor): start offset
+ size (int): required size of position encoding
+
+ Returns:
+ torch.Tensor: Corresponding encoding
+ """
+ pos_emb = self.pe[
+ :,
+ self.pe.size(1) // 2 - size + 1 : self.pe.size(1) // 2 + size,
+ ]
+ return pos_emb
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/encoder.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..f5e98c683bd2e76b51fda7acdca355348d072d58
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/encoder.py
@@ -0,0 +1,567 @@
+# Copyright (c) 2021 Mobvoi Inc (Binbin Zhang, Di Wu)
+# 2022 Xingchen Song (sxc19@mails.tsinghua.edu.cn)
+# 2024 Alibaba Inc (Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+"""Encoder definition."""
+from typing import Tuple
+
+import torch
+import torch.utils.checkpoint as ckpt
+
+from cosyvoice.transformer.convolution import ConvolutionModule
+from cosyvoice.transformer.encoder_layer import TransformerEncoderLayer
+from cosyvoice.transformer.encoder_layer import ConformerEncoderLayer
+from cosyvoice.transformer.positionwise_feed_forward import PositionwiseFeedForward
+from cosyvoice.utils.class_utils import (
+ COSYVOICE_EMB_CLASSES,
+ COSYVOICE_SUBSAMPLE_CLASSES,
+ COSYVOICE_ATTENTION_CLASSES,
+ COSYVOICE_ACTIVATION_CLASSES,
+)
+from cosyvoice.utils.mask import make_pad_mask
+from cosyvoice.utils.mask import add_optional_chunk_mask
+
+
+class BaseEncoder(torch.nn.Module):
+
+ def __init__(
+ self,
+ input_size: int,
+ output_size: int = 256,
+ attention_heads: int = 4,
+ linear_units: int = 2048,
+ num_blocks: int = 6,
+ dropout_rate: float = 0.1,
+ positional_dropout_rate: float = 0.1,
+ attention_dropout_rate: float = 0.0,
+ input_layer: str = "conv2d",
+ pos_enc_layer_type: str = "abs_pos",
+ normalize_before: bool = True,
+ static_chunk_size: int = 0,
+ use_dynamic_chunk: bool = False,
+ global_cmvn: torch.nn.Module = None,
+ use_dynamic_left_chunk: bool = False,
+ gradient_checkpointing: bool = False,
+ ):
+ """
+ Args:
+ input_size (int): input dim
+ output_size (int): dimension of attention
+ attention_heads (int): the number of heads of multi head attention
+ linear_units (int): the hidden units number of position-wise feed
+ forward
+ num_blocks (int): the number of decoder blocks
+ dropout_rate (float): dropout rate
+ attention_dropout_rate (float): dropout rate in attention
+ positional_dropout_rate (float): dropout rate after adding
+ positional encoding
+ input_layer (str): input layer type.
+ optional [linear, conv2d, conv2d6, conv2d8]
+ pos_enc_layer_type (str): Encoder positional encoding layer type.
+ opitonal [abs_pos, scaled_abs_pos, rel_pos, no_pos]
+ normalize_before (bool):
+ True: use layer_norm before each sub-block of a layer.
+ False: use layer_norm after each sub-block of a layer.
+ static_chunk_size (int): chunk size for static chunk training and
+ decoding
+ use_dynamic_chunk (bool): whether use dynamic chunk size for
+ training or not, You can only use fixed chunk(chunk_size > 0)
+ or dyanmic chunk size(use_dynamic_chunk = True)
+ global_cmvn (Optional[torch.nn.Module]): Optional GlobalCMVN module
+ use_dynamic_left_chunk (bool): whether use dynamic left chunk in
+ dynamic chunk training
+ key_bias: whether use bias in attention.linear_k, False for whisper models.
+ gradient_checkpointing: rerunning a forward-pass segment for each
+ checkpointed segment during backward.
+ """
+ super().__init__()
+ self._output_size = output_size
+
+ self.global_cmvn = global_cmvn
+ self.embed = COSYVOICE_SUBSAMPLE_CLASSES[input_layer](
+ input_size,
+ output_size,
+ dropout_rate,
+ COSYVOICE_EMB_CLASSES[pos_enc_layer_type](output_size,
+ positional_dropout_rate),
+ )
+
+ self.normalize_before = normalize_before
+ self.after_norm = torch.nn.LayerNorm(output_size, eps=1e-5)
+ self.static_chunk_size = static_chunk_size
+ self.use_dynamic_chunk = use_dynamic_chunk
+ self.use_dynamic_left_chunk = use_dynamic_left_chunk
+ self.gradient_checkpointing = gradient_checkpointing
+
+ def output_size(self) -> int:
+ return self._output_size
+
+ def forward(
+ self,
+ xs: torch.Tensor,
+ xs_lens: torch.Tensor,
+ decoding_chunk_size: int = 0,
+ num_decoding_left_chunks: int = -1,
+ ) -> Tuple[torch.Tensor, torch.Tensor]:
+ """Embed positions in tensor.
+
+ Args:
+ xs: padded input tensor (B, T, D)
+ xs_lens: input length (B)
+ decoding_chunk_size: decoding chunk size for dynamic chunk
+ 0: default for training, use random dynamic chunk.
+ <0: for decoding, use full chunk.
+ >0: for decoding, use fixed chunk size as set.
+ num_decoding_left_chunks: number of left chunks, this is for decoding,
+ the chunk size is decoding_chunk_size.
+ >=0: use num_decoding_left_chunks
+ <0: use all left chunks
+ Returns:
+ encoder output tensor xs, and subsampled masks
+ xs: padded output tensor (B, T' ~= T/subsample_rate, D)
+ masks: torch.Tensor batch padding mask after subsample
+ (B, 1, T' ~= T/subsample_rate)
+ NOTE(xcsong):
+ We pass the `__call__` method of the modules instead of `forward` to the
+ checkpointing API because `__call__` attaches all the hooks of the module.
+ https://discuss.pytorch.org/t/any-different-between-model-input-and-model-forward-input/3690/2
+ """
+ T = xs.size(1)
+ masks = ~make_pad_mask(xs_lens, T).unsqueeze(1) # (B, 1, T)
+ if self.global_cmvn is not None:
+ xs = self.global_cmvn(xs)
+ xs, pos_emb, masks = self.embed(xs, masks)
+ mask_pad = masks # (B, 1, T/subsample_rate)
+ chunk_masks = add_optional_chunk_mask(xs, masks,
+ self.use_dynamic_chunk,
+ self.use_dynamic_left_chunk,
+ decoding_chunk_size,
+ self.static_chunk_size,
+ num_decoding_left_chunks)
+ if self.gradient_checkpointing and self.training:
+ xs = self.forward_layers_checkpointed(xs, chunk_masks, pos_emb,
+ mask_pad)
+ else:
+ xs = self.forward_layers(xs, chunk_masks, pos_emb, mask_pad)
+ if self.normalize_before:
+ xs = self.after_norm(xs)
+ # Here we assume the mask is not changed in encoder layers, so just
+ # return the masks before encoder layers, and the masks will be used
+ # for cross attention with decoder later
+ return xs, masks
+
+ def forward_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,
+ pos_emb: torch.Tensor,
+ mask_pad: torch.Tensor) -> torch.Tensor:
+ for layer in self.encoders:
+ xs, chunk_masks, _, _ = layer(xs, chunk_masks, pos_emb, mask_pad)
+ return xs
+
+ @torch.jit.ignore(drop=True)
+ def forward_layers_checkpointed(self, xs: torch.Tensor,
+ chunk_masks: torch.Tensor,
+ pos_emb: torch.Tensor,
+ mask_pad: torch.Tensor) -> torch.Tensor:
+ for layer in self.encoders:
+ xs, chunk_masks, _, _ = ckpt.checkpoint(layer.__call__, xs,
+ chunk_masks, pos_emb,
+ mask_pad)
+ return xs
+
+ def forward_chunk(
+ self,
+ xs: torch.Tensor,
+ offset: int,
+ required_cache_size: int,
+ att_cache: torch.Tensor = torch.zeros(0, 0, 0, 0),
+ cnn_cache: torch.Tensor = torch.zeros(0, 0, 0, 0),
+ att_mask: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """ Forward just one chunk
+
+ Args:
+ xs (torch.Tensor): chunk input, with shape (b=1, time, mel-dim),
+ where `time == (chunk_size - 1) * subsample_rate + \
+ subsample.right_context + 1`
+ offset (int): current offset in encoder output time stamp
+ required_cache_size (int): cache size required for next chunk
+ compuation
+ >=0: actual cache size
+ <0: means all history cache is required
+ att_cache (torch.Tensor): cache tensor for KEY & VALUE in
+ transformer/conformer attention, with shape
+ (elayers, head, cache_t1, d_k * 2), where
+ `head * d_k == hidden-dim` and
+ `cache_t1 == chunk_size * num_decoding_left_chunks`.
+ cnn_cache (torch.Tensor): cache tensor for cnn_module in conformer,
+ (elayers, b=1, hidden-dim, cache_t2), where
+ `cache_t2 == cnn.lorder - 1`
+
+ Returns:
+ torch.Tensor: output of current input xs,
+ with shape (b=1, chunk_size, hidden-dim).
+ torch.Tensor: new attention cache required for next chunk, with
+ dynamic shape (elayers, head, ?, d_k * 2)
+ depending on required_cache_size.
+ torch.Tensor: new conformer cnn cache required for next chunk, with
+ same shape as the original cnn_cache.
+
+ """
+ assert xs.size(0) == 1
+ # tmp_masks is just for interface compatibility
+ tmp_masks = torch.ones(1,
+ xs.size(1),
+ device=xs.device,
+ dtype=torch.bool)
+ tmp_masks = tmp_masks.unsqueeze(1)
+ if self.global_cmvn is not None:
+ xs = self.global_cmvn(xs)
+ # NOTE(xcsong): Before embed, shape(xs) is (b=1, time, mel-dim)
+ xs, pos_emb, _ = self.embed(xs, tmp_masks, offset)
+ # NOTE(xcsong): After embed, shape(xs) is (b=1, chunk_size, hidden-dim)
+ elayers, cache_t1 = att_cache.size(0), att_cache.size(2)
+ chunk_size = xs.size(1)
+ attention_key_size = cache_t1 + chunk_size
+ pos_emb = self.embed.position_encoding(offset=offset - cache_t1,
+ size=attention_key_size)
+ if required_cache_size < 0:
+ next_cache_start = 0
+ elif required_cache_size == 0:
+ next_cache_start = attention_key_size
+ else:
+ next_cache_start = max(attention_key_size - required_cache_size, 0)
+ r_att_cache = []
+ r_cnn_cache = []
+ for i, layer in enumerate(self.encoders):
+ # NOTE(xcsong): Before layer.forward
+ # shape(att_cache[i:i + 1]) is (1, head, cache_t1, d_k * 2),
+ # shape(cnn_cache[i]) is (b=1, hidden-dim, cache_t2)
+ xs, _, new_att_cache, new_cnn_cache = layer(
+ xs,
+ att_mask,
+ pos_emb,
+ att_cache=att_cache[i:i + 1] if elayers > 0 else att_cache,
+ cnn_cache=cnn_cache[i] if cnn_cache.size(0) > 0 else cnn_cache)
+ # NOTE(xcsong): After layer.forward
+ # shape(new_att_cache) is (1, head, attention_key_size, d_k * 2),
+ # shape(new_cnn_cache) is (b=1, hidden-dim, cache_t2)
+ r_att_cache.append(new_att_cache[:, :, next_cache_start:, :])
+ r_cnn_cache.append(new_cnn_cache.unsqueeze(0))
+ if self.normalize_before:
+ xs = self.after_norm(xs)
+
+ # NOTE(xcsong): shape(r_att_cache) is (elayers, head, ?, d_k * 2),
+ # ? may be larger than cache_t1, it depends on required_cache_size
+ r_att_cache = torch.cat(r_att_cache, dim=0)
+ # NOTE(xcsong): shape(r_cnn_cache) is (e, b=1, hidden-dim, cache_t2)
+ r_cnn_cache = torch.cat(r_cnn_cache, dim=0)
+
+ return (xs, r_att_cache, r_cnn_cache)
+
+ def forward_chunk_by_chunk(
+ self,
+ xs: torch.Tensor,
+ decoding_chunk_size: int,
+ num_decoding_left_chunks: int = -1,
+ ) -> Tuple[torch.Tensor, torch.Tensor]:
+ """ Forward input chunk by chunk with chunk_size like a streaming
+ fashion
+
+ Here we should pay special attention to computation cache in the
+ streaming style forward chunk by chunk. Three things should be taken
+ into account for computation in the current network:
+ 1. transformer/conformer encoder layers output cache
+ 2. convolution in conformer
+ 3. convolution in subsampling
+
+ However, we don't implement subsampling cache for:
+ 1. We can control subsampling module to output the right result by
+ overlapping input instead of cache left context, even though it
+ wastes some computation, but subsampling only takes a very
+ small fraction of computation in the whole model.
+ 2. Typically, there are several covolution layers with subsampling
+ in subsampling module, it is tricky and complicated to do cache
+ with different convolution layers with different subsampling
+ rate.
+ 3. Currently, nn.Sequential is used to stack all the convolution
+ layers in subsampling, we need to rewrite it to make it work
+ with cache, which is not prefered.
+ Args:
+ xs (torch.Tensor): (1, max_len, dim)
+ chunk_size (int): decoding chunk size
+ """
+ assert decoding_chunk_size > 0
+ # The model is trained by static or dynamic chunk
+ assert self.static_chunk_size > 0 or self.use_dynamic_chunk
+ subsampling = self.embed.subsampling_rate
+ context = self.embed.right_context + 1 # Add current frame
+ stride = subsampling * decoding_chunk_size
+ decoding_window = (decoding_chunk_size - 1) * subsampling + context
+ num_frames = xs.size(1)
+ att_cache: torch.Tensor = torch.zeros((0, 0, 0, 0), device=xs.device)
+ cnn_cache: torch.Tensor = torch.zeros((0, 0, 0, 0), device=xs.device)
+ outputs = []
+ offset = 0
+ required_cache_size = decoding_chunk_size * num_decoding_left_chunks
+
+ # Feed forward overlap input step by step
+ for cur in range(0, num_frames - context + 1, stride):
+ end = min(cur + decoding_window, num_frames)
+ chunk_xs = xs[:, cur:end, :]
+ (y, att_cache,
+ cnn_cache) = self.forward_chunk(chunk_xs, offset,
+ required_cache_size, att_cache,
+ cnn_cache)
+ outputs.append(y)
+ offset += y.size(1)
+ ys = torch.cat(outputs, 1)
+ masks = torch.ones((1, 1, ys.size(1)),
+ device=ys.device,
+ dtype=torch.bool)
+ return ys, masks
+
+
+class TransformerEncoder(BaseEncoder):
+ """Transformer encoder module."""
+
+ def __init__(
+ self,
+ input_size: int,
+ output_size: int = 256,
+ attention_heads: int = 4,
+ linear_units: int = 2048,
+ num_blocks: int = 6,
+ dropout_rate: float = 0.1,
+ positional_dropout_rate: float = 0.1,
+ attention_dropout_rate: float = 0.0,
+ input_layer: str = "conv2d",
+ pos_enc_layer_type: str = "abs_pos",
+ normalize_before: bool = True,
+ static_chunk_size: int = 0,
+ use_dynamic_chunk: bool = False,
+ global_cmvn: torch.nn.Module = None,
+ use_dynamic_left_chunk: bool = False,
+ key_bias: bool = True,
+ selfattention_layer_type: str = "selfattn",
+ activation_type: str = "relu",
+ gradient_checkpointing: bool = False,
+ ):
+ """ Construct TransformerEncoder
+
+ See Encoder for the meaning of each parameter.
+ """
+ super().__init__(input_size, output_size, attention_heads,
+ linear_units, num_blocks, dropout_rate,
+ positional_dropout_rate, attention_dropout_rate,
+ input_layer, pos_enc_layer_type, normalize_before,
+ static_chunk_size, use_dynamic_chunk, global_cmvn,
+ use_dynamic_left_chunk, gradient_checkpointing)
+ activation = COSYVOICE_ACTIVATION_CLASSES[activation_type]()
+ self.encoders = torch.nn.ModuleList([
+ TransformerEncoderLayer(
+ output_size,
+ COSYVOICE_ATTENTION_CLASSES[selfattention_layer_type](attention_heads,
+ output_size,
+ attention_dropout_rate,
+ key_bias),
+ PositionwiseFeedForward(output_size, linear_units,
+ dropout_rate, activation),
+ dropout_rate, normalize_before) for _ in range(num_blocks)
+ ])
+
+
+class ConformerEncoder(BaseEncoder):
+ """Conformer encoder module."""
+
+ def __init__(
+ self,
+ input_size: int,
+ output_size: int = 256,
+ attention_heads: int = 4,
+ linear_units: int = 2048,
+ num_blocks: int = 6,
+ dropout_rate: float = 0.1,
+ positional_dropout_rate: float = 0.1,
+ attention_dropout_rate: float = 0.0,
+ input_layer: str = "conv2d",
+ pos_enc_layer_type: str = "rel_pos",
+ normalize_before: bool = True,
+ static_chunk_size: int = 0,
+ use_dynamic_chunk: bool = False,
+ global_cmvn: torch.nn.Module = None,
+ use_dynamic_left_chunk: bool = False,
+ positionwise_conv_kernel_size: int = 1,
+ macaron_style: bool = True,
+ selfattention_layer_type: str = "rel_selfattn",
+ activation_type: str = "swish",
+ use_cnn_module: bool = True,
+ cnn_module_kernel: int = 15,
+ causal: bool = False,
+ cnn_module_norm: str = "batch_norm",
+ key_bias: bool = True,
+ gradient_checkpointing: bool = False,
+ ):
+ """Construct ConformerEncoder
+
+ Args:
+ input_size to use_dynamic_chunk, see in BaseEncoder
+ positionwise_conv_kernel_size (int): Kernel size of positionwise
+ conv1d layer.
+ macaron_style (bool): Whether to use macaron style for
+ positionwise layer.
+ selfattention_layer_type (str): Encoder attention layer type,
+ the parameter has no effect now, it's just for configure
+ compatibility.
+ activation_type (str): Encoder activation function type.
+ use_cnn_module (bool): Whether to use convolution module.
+ cnn_module_kernel (int): Kernel size of convolution module.
+ causal (bool): whether to use causal convolution or not.
+ key_bias: whether use bias in attention.linear_k, False for whisper models.
+ """
+ super().__init__(input_size, output_size, attention_heads,
+ linear_units, num_blocks, dropout_rate,
+ positional_dropout_rate, attention_dropout_rate,
+ input_layer, pos_enc_layer_type, normalize_before,
+ static_chunk_size, use_dynamic_chunk, global_cmvn,
+ use_dynamic_left_chunk, gradient_checkpointing)
+ activation = COSYVOICE_ACTIVATION_CLASSES[activation_type]()
+
+ # self-attention module definition
+ encoder_selfattn_layer_args = (
+ attention_heads,
+ output_size,
+ attention_dropout_rate,
+ key_bias,
+ )
+ # feed-forward module definition
+ positionwise_layer_args = (
+ output_size,
+ linear_units,
+ dropout_rate,
+ activation,
+ )
+ # convolution module definition
+ convolution_layer_args = (output_size, cnn_module_kernel, activation,
+ cnn_module_norm, causal)
+
+ self.encoders = torch.nn.ModuleList([
+ ConformerEncoderLayer(
+ output_size,
+ COSYVOICE_ATTENTION_CLASSES[selfattention_layer_type](
+ *encoder_selfattn_layer_args),
+ PositionwiseFeedForward(*positionwise_layer_args),
+ PositionwiseFeedForward(
+ *positionwise_layer_args) if macaron_style else None,
+ ConvolutionModule(
+ *convolution_layer_args) if use_cnn_module else None,
+ dropout_rate,
+ normalize_before,
+ ) for _ in range(num_blocks)
+ ])
+
+
+
+
+class BlockConformerEncoder(BaseEncoder):
+ """Conformer encoder module."""
+
+ def __init__(
+ self,
+ input_size: int,
+ output_size: int = 256,
+ attention_heads: int = 4,
+ linear_units: int = 2048,
+ num_blocks: int = 6,
+ dropout_rate: float = 0.1,
+ positional_dropout_rate: float = 0.1,
+ attention_dropout_rate: float = 0.0,
+ input_layer: str = "conv2d",
+ pos_enc_layer_type: str = "rel_pos",
+ normalize_before: bool = True,
+ static_chunk_size: int = 0,
+ use_dynamic_chunk: bool = False,
+ global_cmvn: torch.nn.Module = None,
+ use_dynamic_left_chunk: bool = False,
+ positionwise_conv_kernel_size: int = 1,
+ macaron_style: bool = True,
+ selfattention_layer_type: str = "rel_selfattn",
+ activation_type: str = "swish",
+ use_cnn_module: bool = True,
+ cnn_module_kernel: int = 15,
+ causal: bool = False,
+ cnn_module_norm: str = "batch_norm",
+ key_bias: bool = True,
+ gradient_checkpointing: bool = False,
+ block_size=25,
+ ):
+ """Construct ConformerEncoder
+
+ Args:
+ input_size to use_dynamic_chunk, see in BaseEncoder
+ positionwise_conv_kernel_size (int): Kernel size of positionwise
+ conv1d layer.
+ macaron_style (bool): Whether to use macaron style for
+ positionwise layer.
+ selfattention_layer_type (str): Encoder attention layer type,
+ the parameter has no effect now, it's just for configure
+ compatibility.
+ activation_type (str): Encoder activation function type.
+ use_cnn_module (bool): Whether to use convolution module.
+ cnn_module_kernel (int): Kernel size of convolution module.
+ causal (bool): whether to use causal convolution or not.
+ key_bias: whether use bias in attention.linear_k, False for whisper models.
+ """
+ super().__init__(input_size, output_size, attention_heads,
+ linear_units, num_blocks, dropout_rate,
+ positional_dropout_rate, attention_dropout_rate,
+ input_layer, pos_enc_layer_type, normalize_before,
+ static_chunk_size, use_dynamic_chunk, global_cmvn,
+ use_dynamic_left_chunk, gradient_checkpointing)
+ activation = COSYVOICE_ACTIVATION_CLASSES[activation_type]()
+
+ # self-attention module definition
+ encoder_selfattn_layer_args = (
+ attention_heads,
+ output_size,
+ attention_dropout_rate,
+ key_bias,
+ block_size,
+ )
+ # feed-forward module definition
+ positionwise_layer_args = (
+ output_size,
+ linear_units,
+ dropout_rate,
+ activation,
+ )
+ # convolution module definition
+ convolution_layer_args = (output_size, cnn_module_kernel, activation,
+ cnn_module_norm, causal)
+
+ self.encoders = torch.nn.ModuleList([
+ ConformerEncoderLayer(
+ output_size,
+ COSYVOICE_ATTENTION_CLASSES[selfattention_layer_type](
+ *encoder_selfattn_layer_args),
+ PositionwiseFeedForward(*positionwise_layer_args),
+ PositionwiseFeedForward(
+ *positionwise_layer_args) if macaron_style else None,
+ ConvolutionModule(
+ *convolution_layer_args) if use_cnn_module else None,
+ dropout_rate,
+ normalize_before,
+ ) for _ in range(num_blocks)
+ ])
+ self.block_size=block_size
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/encoder_layer.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/encoder_layer.py
new file mode 100644
index 0000000000000000000000000000000000000000..dfd758bc1cc7780aa4f6a322a264c879b74a6cfe
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/encoder_layer.py
@@ -0,0 +1,236 @@
+# Copyright (c) 2021 Mobvoi Inc (Binbin Zhang, Di Wu)
+# 2022 Xingchen Song (sxc19@mails.tsinghua.edu.cn)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+"""Encoder self-attention layer definition."""
+
+from typing import Optional, Tuple
+
+import torch
+from torch import nn
+
+
+class TransformerEncoderLayer(nn.Module):
+ """Encoder layer module.
+
+ Args:
+ size (int): Input dimension.
+ self_attn (torch.nn.Module): Self-attention module instance.
+ `MultiHeadedAttention` or `RelPositionMultiHeadedAttention`
+ instance can be used as the argument.
+ feed_forward (torch.nn.Module): Feed-forward module instance.
+ `PositionwiseFeedForward`, instance can be used as the argument.
+ dropout_rate (float): Dropout rate.
+ normalize_before (bool):
+ True: use layer_norm before each sub-block.
+ False: to use layer_norm after each sub-block.
+ """
+
+ def __init__(
+ self,
+ size: int,
+ self_attn: torch.nn.Module,
+ feed_forward: torch.nn.Module,
+ dropout_rate: float,
+ normalize_before: bool = True,
+ ):
+ """Construct an EncoderLayer object."""
+ super().__init__()
+ self.self_attn = self_attn
+ self.feed_forward = feed_forward
+ self.norm1 = nn.LayerNorm(size, eps=1e-5)
+ self.norm2 = nn.LayerNorm(size, eps=1e-5)
+ self.dropout = nn.Dropout(dropout_rate)
+ self.size = size
+ self.normalize_before = normalize_before
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ mask: torch.Tensor,
+ pos_emb: torch.Tensor,
+ mask_pad: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+ att_cache: torch.Tensor = torch.zeros((0, 0, 0, 0)),
+ cnn_cache: torch.Tensor = torch.zeros((0, 0, 0, 0)),
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Compute encoded features.
+
+ Args:
+ x (torch.Tensor): (#batch, time, size)
+ mask (torch.Tensor): Mask tensor for the input (#batch, time，time),
+ (0, 0, 0) means fake mask.
+ pos_emb (torch.Tensor): just for interface compatibility
+ to ConformerEncoderLayer
+ mask_pad (torch.Tensor): does not used in transformer layer,
+ just for unified api with conformer.
+ att_cache (torch.Tensor): Cache tensor of the KEY & VALUE
+ (#batch=1, head, cache_t1, d_k * 2), head * d_k == size.
+ cnn_cache (torch.Tensor): Convolution cache in conformer layer
+ (#batch=1, size, cache_t2), not used here, it's for interface
+ compatibility to ConformerEncoderLayer.
+ Returns:
+ torch.Tensor: Output tensor (#batch, time, size).
+ torch.Tensor: Mask tensor (#batch, time, time).
+ torch.Tensor: att_cache tensor,
+ (#batch=1, head, cache_t1 + time, d_k * 2).
+ torch.Tensor: cnn_cahce tensor (#batch=1, size, cache_t2).
+
+ """
+ residual = x
+ if self.normalize_before:
+ x = self.norm1(x)
+ x_att, new_att_cache = self.self_attn(x, x, x, mask, pos_emb=pos_emb, cache=att_cache)
+ x = residual + self.dropout(x_att)
+ if not self.normalize_before:
+ x = self.norm1(x)
+
+ residual = x
+ if self.normalize_before:
+ x = self.norm2(x)
+ x = residual + self.dropout(self.feed_forward(x))
+ if not self.normalize_before:
+ x = self.norm2(x)
+
+ fake_cnn_cache = torch.zeros((0, 0, 0), dtype=x.dtype, device=x.device)
+ return x, mask, new_att_cache, fake_cnn_cache
+
+
+class ConformerEncoderLayer(nn.Module):
+ """Encoder layer module.
+ Args:
+ size (int): Input dimension.
+ self_attn (torch.nn.Module): Self-attention module instance.
+ `MultiHeadedAttention` or `RelPositionMultiHeadedAttention`
+ instance can be used as the argument.
+ feed_forward (torch.nn.Module): Feed-forward module instance.
+ `PositionwiseFeedForward` instance can be used as the argument.
+ feed_forward_macaron (torch.nn.Module): Additional feed-forward module
+ instance.
+ `PositionwiseFeedForward` instance can be used as the argument.
+ conv_module (torch.nn.Module): Convolution module instance.
+ `ConvlutionModule` instance can be used as the argument.
+ dropout_rate (float): Dropout rate.
+ normalize_before (bool):
+ True: use layer_norm before each sub-block.
+ False: use layer_norm after each sub-block.
+ """
+
+ def __init__(
+ self,
+ size: int,
+ self_attn: torch.nn.Module,
+ feed_forward: Optional[nn.Module] = None,
+ feed_forward_macaron: Optional[nn.Module] = None,
+ conv_module: Optional[nn.Module] = None,
+ dropout_rate: float = 0.1,
+ normalize_before: bool = True,
+ ):
+ """Construct an EncoderLayer object."""
+ super().__init__()
+ self.self_attn = self_attn
+ self.feed_forward = feed_forward
+ self.feed_forward_macaron = feed_forward_macaron
+ self.conv_module = conv_module
+ self.norm_ff = nn.LayerNorm(size, eps=1e-5) # for the FNN module
+ self.norm_mha = nn.LayerNorm(size, eps=1e-5) # for the MHA module
+ if feed_forward_macaron is not None:
+ self.norm_ff_macaron = nn.LayerNorm(size, eps=1e-5)
+ self.ff_scale = 0.5
+ else:
+ self.ff_scale = 1.0
+ if self.conv_module is not None:
+ self.norm_conv = nn.LayerNorm(size, eps=1e-5) # for the CNN module
+ self.norm_final = nn.LayerNorm(
+ size, eps=1e-5) # for the final output of the block
+ self.dropout = nn.Dropout(dropout_rate)
+ self.size = size
+ self.normalize_before = normalize_before
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ mask: torch.Tensor,
+ pos_emb: torch.Tensor,
+ mask_pad: torch.Tensor = torch.ones((0, 0, 0), dtype=torch.bool),
+ att_cache: torch.Tensor = torch.zeros((0, 0, 0, 0)),
+ cnn_cache: torch.Tensor = torch.zeros((0, 0, 0, 0)),
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Compute encoded features.
+
+ Args:
+ x (torch.Tensor): (#batch, time, size)
+ mask (torch.Tensor): Mask tensor for the input (#batch, time，time),
+ (0, 0, 0) means fake mask.
+ pos_emb (torch.Tensor): positional encoding, must not be None
+ for ConformerEncoderLayer.
+ mask_pad (torch.Tensor): batch padding mask used for conv module.
+ (#batch, 1，time), (0, 0, 0) means fake mask.
+ att_cache (torch.Tensor): Cache tensor of the KEY & VALUE
+ (#batch=1, head, cache_t1, d_k * 2), head * d_k == size.
+ cnn_cache (torch.Tensor): Convolution cache in conformer layer
+ (#batch=1, size, cache_t2)
+ Returns:
+ torch.Tensor: Output tensor (#batch, time, size).
+ torch.Tensor: Mask tensor (#batch, time, time).
+ torch.Tensor: att_cache tensor,
+ (#batch=1, head, cache_t1 + time, d_k * 2).
+ torch.Tensor: cnn_cahce tensor (#batch, size, cache_t2).
+ """
+
+ # whether to use macaron style
+ if self.feed_forward_macaron is not None:
+ residual = x
+ if self.normalize_before:
+ x = self.norm_ff_macaron(x)
+ x = residual + self.ff_scale * self.dropout(
+ self.feed_forward_macaron(x))
+ if not self.normalize_before:
+ x = self.norm_ff_macaron(x)
+
+ # multi-headed self-attention module
+ residual = x
+ if self.normalize_before:
+ x = self.norm_mha(x)
+ x_att, new_att_cache = self.self_attn(x, x, x, mask, pos_emb,
+ att_cache)
+ x = residual + self.dropout(x_att)
+ if not self.normalize_before:
+ x = self.norm_mha(x)
+
+ # convolution module
+ # Fake new cnn cache here, and then change it in conv_module
+ new_cnn_cache = torch.zeros((0, 0, 0), dtype=x.dtype, device=x.device)
+ if self.conv_module is not None:
+ residual = x
+ if self.normalize_before:
+ x = self.norm_conv(x)
+ x, new_cnn_cache = self.conv_module(x, mask_pad, cnn_cache)
+ x = residual + self.dropout(x)
+
+ if not self.normalize_before:
+ x = self.norm_conv(x)
+
+ # feed forward module
+ residual = x
+ if self.normalize_before:
+ x = self.norm_ff(x)
+
+ x = residual + self.ff_scale * self.dropout(self.feed_forward(x))
+ if not self.normalize_before:
+ x = self.norm_ff(x)
+
+ if self.conv_module is not None:
+ x = self.norm_final(x)
+
+ return x, mask, new_att_cache, new_cnn_cache
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/label_smoothing_loss.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/label_smoothing_loss.py
new file mode 100644
index 0000000000000000000000000000000000000000..feacabf09609ee6eb047c89ce18d372256c72c71
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/label_smoothing_loss.py
@@ -0,0 +1,96 @@
+# Copyright (c) 2019 Shigeki Karita
+# 2020 Mobvoi Inc (Binbin Zhang)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Label smoothing module."""
+
+import torch
+from torch import nn
+
+
+class LabelSmoothingLoss(nn.Module):
+ """Label-smoothing loss.
+
+ In a standard CE loss, the label's data distribution is:
+ [0,1,2] ->
+ [
+ [1.0, 0.0, 0.0],
+ [0.0, 1.0, 0.0],
+ [0.0, 0.0, 1.0],
+ ]
+
+ In the smoothing version CE Loss,some probabilities
+ are taken from the true label prob (1.0) and are divided
+ among other labels.
+
+ e.g.
+ smoothing=0.1
+ [0,1,2] ->
+ [
+ [0.9, 0.05, 0.05],
+ [0.05, 0.9, 0.05],
+ [0.05, 0.05, 0.9],
+ ]
+
+ Args:
+ size (int): the number of class
+ padding_idx (int): padding class id which will be ignored for loss
+ smoothing (float): smoothing rate (0.0 means the conventional CE)
+ normalize_length (bool):
+ normalize loss by sequence length if True
+ normalize loss by batch size if False
+ """
+
+ def __init__(self,
+ size: int,
+ padding_idx: int,
+ smoothing: float,
+ normalize_length: bool = False):
+ """Construct an LabelSmoothingLoss object."""
+ super(LabelSmoothingLoss, self).__init__()
+ self.criterion = nn.KLDivLoss(reduction="none")
+ self.padding_idx = padding_idx
+ self.confidence = 1.0 - smoothing
+ self.smoothing = smoothing
+ self.size = size
+ self.normalize_length = normalize_length
+
+ def forward(self, x: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
+ """Compute loss between x and target.
+
+ The model outputs and data labels tensors are flatten to
+ (batch*seqlen, class) shape and a mask is applied to the
+ padding part which should not be calculated for loss.
+
+ Args:
+ x (torch.Tensor): prediction (batch, seqlen, class)
+ target (torch.Tensor):
+ target signal masked with self.padding_id (batch, seqlen)
+ Returns:
+ loss (torch.Tensor) : The KL loss, scalar float value
+ """
+ assert x.size(2) == self.size
+ batch_size = x.size(0)
+ x = x.view(-1, self.size)
+ target = target.view(-1)
+ # use zeros_like instead of torch.no_grad() for true_dist,
+ # since no_grad() can not be exported by JIT
+ true_dist = torch.zeros_like(x)
+ true_dist.fill_(self.smoothing / (self.size - 1))
+ ignore = target == self.padding_idx # (B,)
+ total = len(target) - ignore.sum().item()
+ target = target.masked_fill(ignore, 0) # avoid -1 index
+ true_dist.scatter_(1, target.unsqueeze(1), self.confidence)
+ kl = self.criterion(torch.log_softmax(x, dim=1), true_dist)
+ denom = total if self.normalize_length else batch_size
+ return kl.masked_fill(ignore.unsqueeze(1), 0).sum() / denom
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/positionwise_feed_forward.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/positionwise_feed_forward.py
new file mode 100644
index 0000000000000000000000000000000000000000..b7a2cf6e7315e3a5ed2794423daff0a59cc5b208
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/positionwise_feed_forward.py
@@ -0,0 +1,115 @@
+# Copyright (c) 2019 Shigeki Karita
+# 2020 Mobvoi Inc (Binbin Zhang)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Positionwise feed forward layer definition."""
+
+import torch
+
+
+class PositionwiseFeedForward(torch.nn.Module):
+ """Positionwise feed forward layer.
+
+ FeedForward are appied on each position of the sequence.
+ The output dim is same with the input dim.
+
+ Args:
+ idim (int): Input dimenstion.
+ hidden_units (int): The number of hidden units.
+ dropout_rate (float): Dropout rate.
+ activation (torch.nn.Module): Activation function
+ """
+
+ def __init__(
+ self,
+ idim: int,
+ hidden_units: int,
+ dropout_rate: float,
+ activation: torch.nn.Module = torch.nn.ReLU(),
+ ):
+ """Construct a PositionwiseFeedForward object."""
+ super(PositionwiseFeedForward, self).__init__()
+ self.w_1 = torch.nn.Linear(idim, hidden_units)
+ self.activation = activation
+ self.dropout = torch.nn.Dropout(dropout_rate)
+ self.w_2 = torch.nn.Linear(hidden_units, idim)
+
+ def forward(self, xs: torch.Tensor) -> torch.Tensor:
+ """Forward function.
+
+ Args:
+ xs: input tensor (B, L, D)
+ Returns:
+ output tensor, (B, L, D)
+ """
+ return self.w_2(self.dropout(self.activation(self.w_1(xs))))
+
+
+class MoEFFNLayer(torch.nn.Module):
+ """
+ Mixture of expert with Positionwise feed forward layer
+ See also figure 1 in https://arxiv.org/pdf/2305.15663.pdf
+ The output dim is same with the input dim.
+
+ Modified from https://github.com/Lightning-AI/lit-gpt/pull/823
+ https://github.com/mistralai/mistral-src/blob/b46d6/moe_one_file_ref.py#L203-L219
+ Args:
+ n_expert: number of expert.
+ n_expert_per_token: The actual number of experts used for each frame
+ idim (int): Input dimenstion.
+ hidden_units (int): The number of hidden units.
+ dropout_rate (float): Dropout rate.
+ activation (torch.nn.Module): Activation function
+ """
+
+ def __init__(
+ self,
+ n_expert: int,
+ n_expert_per_token: int,
+ idim: int,
+ hidden_units: int,
+ dropout_rate: float,
+ activation: torch.nn.Module = torch.nn.ReLU(),
+ ):
+ super(MoEFFNLayer, self).__init__()
+ self.gate = torch.nn.Linear(idim, n_expert, bias=False)
+ self.experts = torch.nn.ModuleList(
+ PositionwiseFeedForward(idim, hidden_units, dropout_rate,
+ activation) for _ in range(n_expert))
+ self.n_expert_per_token = n_expert_per_token
+
+ def forward(self, xs: torch.Tensor) -> torch.Tensor:
+ """Foward function.
+ Args:
+ xs: input tensor (B, L, D)
+ Returns:
+ output tensor, (B, L, D)
+
+ """
+ B, L, D = xs.size(
+ ) # batch size, sequence length, embedding dimension (idim)
+ xs = xs.view(-1, D) # (B*L, D)
+ router = self.gate(xs) # (B*L, n_expert)
+ logits, indices = torch.topk(
+ router, self.n_expert_per_token
+ ) # probs:(B*L, n_expert), indices: (B*L, n_expert)
+ weights = torch.nn.functional.softmax(
+ logits, dim=1,
+ dtype=torch.float).to(dtype=xs.dtype) # (B*L, n_expert_per_token)
+ output = torch.zeros_like(xs) # (B*L, D)
+ for i, expert in enumerate(self.experts):
+ mask = indices == i
+ batch_idx, ith_expert = torch.where(mask)
+ output[batch_idx] += weights[batch_idx, ith_expert, None] * expert(
+ xs[batch_idx])
+ return output.view(B, L, D)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/subsampling.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/subsampling.py
new file mode 100644
index 0000000000000000000000000000000000000000..e17c2e324e3afb24e1b619effe29cef07c9c5b3a
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/transformer/subsampling.py
@@ -0,0 +1,383 @@
+# Copyright (c) 2021 Mobvoi Inc (Binbin Zhang, Di Wu)
+# 2024 Alibaba Inc (Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+"""Subsampling layer definition."""
+
+from typing import Tuple, Union
+
+import torch
+
+
+class BaseSubsampling(torch.nn.Module):
+
+ def __init__(self):
+ super().__init__()
+ self.right_context = 0
+ self.subsampling_rate = 1
+
+ def position_encoding(self, offset: Union[int, torch.Tensor],
+ size: int) -> torch.Tensor:
+ return self.pos_enc.position_encoding(offset, size)
+
+
+class EmbedinigNoSubsampling(BaseSubsampling):
+ """Embedding input without subsampling
+ """
+
+ def __init__(self, idim: int, odim: int, dropout_rate: float,
+ pos_enc_class: torch.nn.Module):
+ super().__init__()
+ self.embed = torch.nn.Embedding(idim, odim)
+ self.pos_enc = pos_enc_class
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ x_mask: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Input x.
+
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, idim).
+ x_mask (torch.Tensor): Input mask (#batch, 1, time).
+
+ Returns:
+ torch.Tensor: linear input tensor (#batch, time', odim),
+ where time' = time .
+ torch.Tensor: linear input mask (#batch, 1, time'),
+ where time' = time .
+
+ """
+ x = self.embed(x)
+ x, pos_emb = self.pos_enc(x, offset)
+ return x, pos_emb, x_mask
+
+
+class LinearNoSubsampling(BaseSubsampling):
+ """Linear transform the input without subsampling
+
+ Args:
+ idim (int): Input dimension.
+ odim (int): Output dimension.
+ dropout_rate (float): Dropout rate.
+
+ """
+
+ def __init__(self, idim: int, odim: int, dropout_rate: float,
+ pos_enc_class: torch.nn.Module):
+ """Construct an linear object."""
+ super().__init__()
+ self.out = torch.nn.Sequential(
+ torch.nn.Linear(idim, odim),
+ torch.nn.LayerNorm(odim, eps=1e-5),
+ torch.nn.Dropout(dropout_rate),
+ )
+ self.pos_enc = pos_enc_class
+ self.right_context = 0
+ self.subsampling_rate = 1
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ x_mask: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Input x.
+
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, idim).
+ x_mask (torch.Tensor): Input mask (#batch, 1, time).
+
+ Returns:
+ torch.Tensor: linear input tensor (#batch, time', odim),
+ where time' = time .
+ torch.Tensor: linear input mask (#batch, 1, time'),
+ where time' = time .
+
+ """
+ x = self.out(x)
+ x, pos_emb = self.pos_enc(x, offset)
+ return x, pos_emb, x_mask
+
+
+class Conv1dSubsampling2(BaseSubsampling):
+ """Convolutional 1D subsampling (to 1/2 length).
+ It is designed for Whisper, ref:
+ https://github.com/openai/whisper/blob/main/whisper/model.py
+
+ Args:
+ idim (int): Input dimension.
+ odim (int): Output dimension.
+ dropout_rate (float): Dropout rate.
+
+ """
+
+ def __init__(self, idim: int, odim: int, dropout_rate: float,
+ pos_enc_class: torch.nn.Module):
+ """Construct an Conv1dSubsampling2 object."""
+ super().__init__()
+ self.conv = torch.nn.Sequential(
+ torch.nn.Conv1d(idim, odim, kernel_size=3, padding=1),
+ torch.nn.GELU(),
+ torch.nn.Conv1d(odim, odim, kernel_size=3, stride=2, padding=1),
+ torch.nn.GELU(),
+ )
+ self.pos_enc = pos_enc_class
+ # The right context for every conv layer is computed by:
+ # (kernel_size - 1) * frame_rate_of_this_layer
+ self.subsampling_rate = 2
+ # 4 = (3 - 1) * 1 + (3 - 1) * 1
+ self.right_context = 4
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ x_mask: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Subsample x.
+
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, idim).
+ x_mask (torch.Tensor): Input mask (#batch, 1, time).
+
+ Returns:
+ torch.Tensor: Subsampled tensor (#batch, time', odim),
+ where time' = time // 2.
+ torch.Tensor: Subsampled mask (#batch, 1, time'),
+ where time' = time // 2.
+ torch.Tensor: positional encoding
+
+ """
+ time = x.size(1)
+ x = x.transpose(1, 2) # (b, f, t)
+ x = self.conv(x)
+ x = x.transpose(1, 2) # (b, t, f)
+ x, pos_emb = self.pos_enc(x, offset)
+ return x, pos_emb, x_mask[:, :, (time + 1) % 2::2]
+
+
+class Conv2dSubsampling4(BaseSubsampling):
+ """Convolutional 2D subsampling (to 1/4 length).
+
+ Args:
+ idim (int): Input dimension.
+ odim (int): Output dimension.
+ dropout_rate (float): Dropout rate.
+
+ """
+
+ def __init__(self, idim: int, odim: int, dropout_rate: float,
+ pos_enc_class: torch.nn.Module):
+ """Construct an Conv2dSubsampling4 object."""
+ super().__init__()
+ self.conv = torch.nn.Sequential(
+ torch.nn.Conv2d(1, odim, 3, 2),
+ torch.nn.ReLU(),
+ torch.nn.Conv2d(odim, odim, 3, 2),
+ torch.nn.ReLU(),
+ )
+ self.out = torch.nn.Sequential(
+ torch.nn.Linear(odim * (((idim - 1) // 2 - 1) // 2), odim))
+ self.pos_enc = pos_enc_class
+ # The right context for every conv layer is computed by:
+ # (kernel_size - 1) * frame_rate_of_this_layer
+ self.subsampling_rate = 4
+ # 6 = (3 - 1) * 1 + (3 - 1) * 2
+ self.right_context = 6
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ x_mask: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Subsample x.
+
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, idim).
+ x_mask (torch.Tensor): Input mask (#batch, 1, time).
+
+ Returns:
+ torch.Tensor: Subsampled tensor (#batch, time', odim),
+ where time' = time // 4.
+ torch.Tensor: Subsampled mask (#batch, 1, time'),
+ where time' = time // 4.
+ torch.Tensor: positional encoding
+
+ """
+ x = x.unsqueeze(1) # (b, c=1, t, f)
+ x = self.conv(x)
+ b, c, t, f = x.size()
+ x = self.out(x.transpose(1, 2).contiguous().view(b, t, c * f))
+ x, pos_emb = self.pos_enc(x, offset)
+ return x, pos_emb, x_mask[:, :, 2::2][:, :, 2::2]
+
+
+class Conv2dSubsampling6(BaseSubsampling):
+ """Convolutional 2D subsampling (to 1/6 length).
+ Args:
+ idim (int): Input dimension.
+ odim (int): Output dimension.
+ dropout_rate (float): Dropout rate.
+ pos_enc (torch.nn.Module): Custom position encoding layer.
+ """
+
+ def __init__(self, idim: int, odim: int, dropout_rate: float,
+ pos_enc_class: torch.nn.Module):
+ """Construct an Conv2dSubsampling6 object."""
+ super().__init__()
+ self.conv = torch.nn.Sequential(
+ torch.nn.Conv2d(1, odim, 3, 2),
+ torch.nn.ReLU(),
+ torch.nn.Conv2d(odim, odim, 5, 3),
+ torch.nn.ReLU(),
+ )
+ self.linear = torch.nn.Linear(odim * (((idim - 1) // 2 - 2) // 3),
+ odim)
+ self.pos_enc = pos_enc_class
+ # 10 = (3 - 1) * 1 + (5 - 1) * 2
+ self.subsampling_rate = 6
+ self.right_context = 10
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ x_mask: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Subsample x.
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, idim).
+ x_mask (torch.Tensor): Input mask (#batch, 1, time).
+
+ Returns:
+ torch.Tensor: Subsampled tensor (#batch, time', odim),
+ where time' = time // 6.
+ torch.Tensor: Subsampled mask (#batch, 1, time'),
+ where time' = time // 6.
+ torch.Tensor: positional encoding
+ """
+ x = x.unsqueeze(1) # (b, c, t, f)
+ x = self.conv(x)
+ b, c, t, f = x.size()
+ x = self.linear(x.transpose(1, 2).contiguous().view(b, t, c * f))
+ x, pos_emb = self.pos_enc(x, offset)
+ return x, pos_emb, x_mask[:, :, 2::2][:, :, 4::3]
+
+
+class Conv2dSubsampling8(BaseSubsampling):
+ """Convolutional 2D subsampling (to 1/8 length).
+
+ Args:
+ idim (int): Input dimension.
+ odim (int): Output dimension.
+ dropout_rate (float): Dropout rate.
+
+ """
+
+ def __init__(self, idim: int, odim: int, dropout_rate: float,
+ pos_enc_class: torch.nn.Module):
+ """Construct an Conv2dSubsampling8 object."""
+ super().__init__()
+ self.conv = torch.nn.Sequential(
+ torch.nn.Conv2d(1, odim, 3, 2),
+ torch.nn.ReLU(),
+ torch.nn.Conv2d(odim, odim, 3, 2),
+ torch.nn.ReLU(),
+ torch.nn.Conv2d(odim, odim, 3, 2),
+ torch.nn.ReLU(),
+ )
+ self.linear = torch.nn.Linear(
+ odim * ((((idim - 1) // 2 - 1) // 2 - 1) // 2), odim)
+ self.pos_enc = pos_enc_class
+ self.subsampling_rate = 8
+ # 14 = (3 - 1) * 1 + (3 - 1) * 2 + (3 - 1) * 4
+ self.right_context = 14
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ x_mask: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Subsample x.
+
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, idim).
+ x_mask (torch.Tensor): Input mask (#batch, 1, time).
+
+ Returns:
+ torch.Tensor: Subsampled tensor (#batch, time', odim),
+ where time' = time // 8.
+ torch.Tensor: Subsampled mask (#batch, 1, time'),
+ where time' = time // 8.
+ torch.Tensor: positional encoding
+ """
+ x = x.unsqueeze(1) # (b, c, t, f)
+ x = self.conv(x)
+ b, c, t, f = x.size()
+ x = self.linear(x.transpose(1, 2).contiguous().view(b, t, c * f))
+ x, pos_emb = self.pos_enc(x, offset)
+ return x, pos_emb, x_mask[:, :, 2::2][:, :, 2::2][:, :, 2::2]
+
+
+class LegacyLinearNoSubsampling(BaseSubsampling):
+ """Linear transform the input without subsampling
+
+ Args:
+ idim (int): Input dimension.
+ odim (int): Output dimension.
+ dropout_rate (float): Dropout rate.
+
+ """
+
+ def __init__(self, idim: int, odim: int, dropout_rate: float,
+ pos_enc_class: torch.nn.Module):
+ """Construct an linear object."""
+ super().__init__()
+ self.out = torch.nn.Sequential(
+ torch.nn.Linear(idim, odim),
+ torch.nn.LayerNorm(odim, eps=1e-5),
+ torch.nn.Dropout(dropout_rate),
+ torch.nn.ReLU(),
+ )
+ self.pos_enc = pos_enc_class
+ self.right_context = 0
+ self.subsampling_rate = 1
+
+ def forward(
+ self,
+ x: torch.Tensor,
+ x_mask: torch.Tensor,
+ offset: Union[int, torch.Tensor] = 0
+ ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+ """Input x.
+
+ Args:
+ x (torch.Tensor): Input tensor (#batch, time, idim).
+ x_mask (torch.Tensor): Input mask (#batch, 1, time).
+
+ Returns:
+ torch.Tensor: linear input tensor (#batch, time', odim),
+ where time' = time .
+ torch.Tensor: linear input mask (#batch, 1, time'),
+ where time' = time .
+
+ """
+ x = self.out(x)
+ x, pos_emb = self.pos_enc(x, offset)
+ return x, pos_emb, x_mask
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/block_mask_util.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/block_mask_util.py
new file mode 100644
index 0000000000000000000000000000000000000000..58e22b051e2ed91fbe51f3287ae09ac31fee65da
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/block_mask_util.py
@@ -0,0 +1,34 @@
+import torch
+
+
+def create_grid_mask(seq_length, trunck_length, fill_triangle):
+ assert seq_length > 0
+
+ # 先不考虑seen_length创建一个grid mask：
+ if fill_triangle:
+ mask = 1 - torch.triu(torch.ones(seq_length, seq_length), diagonal=1)
+ # 下三角与主对角线都为1
+ else:
+ mask = torch.zeros(seq_length, seq_length)
+
+ for i in range(seq_length):
+ trunck_idx = i // trunck_length
+ trunck_start = trunck_idx * trunck_length
+ trunck_end = trunck_length + trunck_start
+ mask[i][trunck_start:trunck_end] = 1
+
+ return mask
+
+
+if __name__ == "__main__":
+ mask = create_grid_mask(seq_length=8, trunck_length=3, fill_triangle=True).int()
+ print(mask)
+# tensor([[1, 1, 1, 0, 0, 0, 0, 0],
+# [1, 1, 1, 0, 0, 0, 0, 0],
+# [1, 1, 1, 0, 0, 0, 0, 0],
+# [1, 1, 1, 1, 1, 1, 0, 0],
+# [1, 1, 1, 1, 1, 1, 0, 0],
+# [1, 1, 1, 1, 1, 1, 0, 0],
+# [1, 1, 1, 1, 1, 1, 1, 1],
+# [1, 1, 1, 1, 1, 1, 1, 1]]
+
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/class_utils.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/class_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..f2250c792cbf5f2cdf2705500fcdd22c5615a133
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/class_utils.py
@@ -0,0 +1,72 @@
+# Copyright [2023-11-28]
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import torch
+
+from cosyvoice.transformer.activation import Swish
+from cosyvoice.transformer.subsampling import (
+ LinearNoSubsampling,
+ EmbedinigNoSubsampling,
+ Conv1dSubsampling2,
+ Conv2dSubsampling4,
+ Conv2dSubsampling6,
+ Conv2dSubsampling8,
+)
+from cosyvoice.transformer.embedding import (PositionalEncoding,
+ RelPositionalEncoding,
+ WhisperPositionalEncoding,
+ LearnablePositionalEncoding,
+ NoPositionalEncoding)
+from cosyvoice.transformer.attention import (MultiHeadedAttention,
+ RelPositionMultiHeadedAttention,
+ BlockRelPositionMultiHeadedAttention)
+from cosyvoice.transformer.embedding import EspnetRelPositionalEncoding
+from cosyvoice.transformer.subsampling import LegacyLinearNoSubsampling
+
+
+COSYVOICE_ACTIVATION_CLASSES = {
+ "hardtanh": torch.nn.Hardtanh,
+ "tanh": torch.nn.Tanh,
+ "relu": torch.nn.ReLU,
+ "selu": torch.nn.SELU,
+ "swish": getattr(torch.nn, "SiLU", Swish),
+ "gelu": torch.nn.GELU,
+}
+
+COSYVOICE_SUBSAMPLE_CLASSES = {
+ "linear": LinearNoSubsampling,
+ "linear_legacy": LegacyLinearNoSubsampling,
+ "embed": EmbedinigNoSubsampling,
+ "conv1d2": Conv1dSubsampling2,
+ "conv2d": Conv2dSubsampling4,
+ "conv2d6": Conv2dSubsampling6,
+ "conv2d8": Conv2dSubsampling8,
+ 'paraformer_dummy': torch.nn.Identity
+}
+
+COSYVOICE_EMB_CLASSES = {
+ "embed": PositionalEncoding,
+ "abs_pos": PositionalEncoding,
+ "rel_pos": RelPositionalEncoding,
+ "rel_pos_espnet": EspnetRelPositionalEncoding,
+ "no_pos": NoPositionalEncoding,
+ "abs_pos_whisper": WhisperPositionalEncoding,
+ "embed_learnable_pe": LearnablePositionalEncoding,
+}
+
+COSYVOICE_ATTENTION_CLASSES = {
+ "selfattn": MultiHeadedAttention,
+ "rel_selfattn": RelPositionMultiHeadedAttention,
+ "block_rel_selfattn": BlockRelPositionMultiHeadedAttention,
+}
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/common.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/common.py
new file mode 100644
index 0000000000000000000000000000000000000000..6ec5e178359031e42c64090eede8aabfdf067afa
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/common.py
@@ -0,0 +1,103 @@
+# Copyright (c) 2020 Mobvoi Inc (Binbin Zhang)
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+"""Unility functions for Transformer."""
+
+from typing import List
+
+import torch
+
+IGNORE_ID = -1
+
+
+def pad_list(xs: List[torch.Tensor], pad_value: int):
+ """Perform padding for the list of tensors.
+
+ Args:
+ xs (List): List of Tensors [(T_1, `*`), (T_2, `*`), ..., (T_B, `*`)].
+ pad_value (float): Value for padding.
+
+ Returns:
+ Tensor: Padded tensor (B, Tmax, `*`).
+
+ Examples:
+ >>> x = [torch.ones(4), torch.ones(2), torch.ones(1)]
+ >>> x
+ [tensor([1., 1., 1., 1.]), tensor([1., 1.]), tensor([1.])]
+ >>> pad_list(x, 0)
+ tensor([[1., 1., 1., 1.],
+ [1., 1., 0., 0.],
+ [1., 0., 0., 0.]])
+
+ """
+ max_len = max([len(item) for item in xs])
+ batchs = len(xs)
+ ndim = xs[0].ndim
+ if ndim == 1:
+ pad_res = torch.zeros(batchs,
+ max_len,
+ dtype=xs[0].dtype,
+ device=xs[0].device)
+ elif ndim == 2:
+ pad_res = torch.zeros(batchs,
+ max_len,
+ xs[0].shape[1],
+ dtype=xs[0].dtype,
+ device=xs[0].device)
+ elif ndim == 3:
+ pad_res = torch.zeros(batchs,
+ max_len,
+ xs[0].shape[1],
+ xs[0].shape[2],
+ dtype=xs[0].dtype,
+ device=xs[0].device)
+ else:
+ raise ValueError(f"Unsupported ndim: {ndim}")
+ pad_res.fill_(pad_value)
+ for i in range(batchs):
+ pad_res[i, :len(xs[i])] = xs[i]
+ return pad_res
+
+
+def th_accuracy(pad_outputs: torch.Tensor, pad_targets: torch.Tensor,
+ ignore_label: int) -> torch.Tensor:
+ """Calculate accuracy.
+
+ Args:
+ pad_outputs (Tensor): Prediction tensors (B * Lmax, D).
+ pad_targets (LongTensor): Target label tensors (B, Lmax).
+ ignore_label (int): Ignore label id.
+
+ Returns:
+ torch.Tensor: Accuracy value (0.0 - 1.0).
+
+ """
+ pad_pred = pad_outputs.view(pad_targets.size(0), pad_targets.size(1),
+ pad_outputs.size(1)).argmax(2)
+ mask = pad_targets != ignore_label
+ numerator = torch.sum(
+ pad_pred.masked_select(mask) == pad_targets.masked_select(mask))
+ denominator = torch.sum(mask)
+ return (numerator / denominator).detach()
+
+
+def get_padding(kernel_size, dilation=1):
+ return int((kernel_size * dilation - dilation) / 2)
+
+
+def init_weights(m, mean=0.0, std=0.01):
+ classname = m.__class__.__name__
+ if classname.find("Conv") != -1:
+ m.weight.data.normal_(mean, std)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/executor.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/executor.py
new file mode 100644
index 0000000000000000000000000000000000000000..5d9159411eab228fb36b46d5c728f3989ce5e920
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/executor.py
@@ -0,0 +1,132 @@
+# Copyright (c) 2020 Mobvoi Inc (Binbin Zhang)
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+from contextlib import nullcontext
+import os
+
+import torch
+import torch.distributed as dist
+import tqdm
+
+from cosyvoice.utils.train_utils import update_parameter_and_lr, log_per_step, log_per_save, batch_forward, batch_backward, save_model, cosyvoice_join
+
+
+class Executor:
+
+ def __init__(self):
+ self.step = 0
+ self.epoch = 0
+ self.rank = int(os.environ.get('RANK', 0))
+ self.device = torch.device('cuda:{}'.format(self.rank))
+
+ def train_one_epoc(self, model, optimizer, scheduler, train_data_loader, cv_data_loader, writer, info_dict, group_join):
+ ''' Train one epoch
+ '''
+
+ lr = optimizer.param_groups[0]['lr']
+ logging.info('Epoch {} TRAIN info lr {} rank {}'.format(self.epoch, lr, self.rank))
+ logging.info('using accumulate grad, new batch size is {} times'
+ ' larger than before'.format(info_dict['accum_grad']))
+ # A context manager to be used in conjunction with an instance of
+ # torch.nn.parallel.DistributedDataParallel to be able to train
+ # with uneven inputs across participating processes.
+ model.train()
+ model_context = model.join if info_dict['train_engine'] == 'torch_ddp' else nullcontext
+ with model_context():
+ for batch_idx, batch_dict in tqdm.tqdm(enumerate(train_data_loader)):
+ # print("======== forword ========")
+ info_dict["tag"] = "TRAIN"
+ info_dict["step"] = self.step
+ info_dict["epoch"] = self.epoch
+ info_dict["batch_idx"] = batch_idx
+ if cosyvoice_join(group_join, info_dict):
+ break
+ # import pdb
+ # pdb.set_trace()
+ # Disable gradient synchronizations across DDP processes.
+ # Within this context, gradients will be accumulated on module
+ # variables, which will later be synchronized.
+ if info_dict['train_engine'] == 'torch_ddp' and (batch_idx + 1) % info_dict["accum_grad"] != 0:
+ context = model.no_sync
+ # Used for single gpu training and DDP gradient synchronization
+ # processes.
+ else:
+ context = nullcontext
+
+ new_batch_dict={
+ # "utts":batch_dict["utts"],
+ "speech_token":batch_dict["speech_token"],
+ "speech_token_len":batch_dict["speech_token_len"],
+ "speech_feat":batch_dict["speech_feat"],
+ "speech_feat_len":batch_dict["speech_feat_len"],
+ "embedding":batch_dict["embedding"],
+ # "embedding":torch.zeros((batch_dict["speech_feat"].size(0),192),device=batch_dict["speech_feat"].device)
+ }
+
+ with context():
+ info_dict = batch_forward(model, new_batch_dict, info_dict)
+ info_dict = batch_backward(model, info_dict)
+
+ info_dict = update_parameter_and_lr(model, optimizer, scheduler, info_dict)
+ log_per_step(writer, info_dict)
+ # NOTE specify save_per_step in cosyvoice.yaml if you want to enable step save
+ if info_dict['save_per_step'] > 0 and (self.step + 1) % info_dict['save_per_step'] == 0 and (batch_idx + 1) % info_dict["accum_grad"] == 0:
+ dist.barrier()
+ # try:
+ # dist.barrier()
+ # except RuntimeError as e:
+ # logging.info('except RuntimeError as e: {}'.format(e))
+ self.cv(model, cv_data_loader, writer, info_dict, on_batch_end=False)
+ model.train()
+ if (batch_idx + 1) % info_dict["accum_grad"] == 0:
+ self.step += 1
+ dist.barrier()
+ # try:
+ # dist.barrier()
+ # except RuntimeError as e:
+ # logging.info('except RuntimeError as e: {}'.format(e))
+ self.cv(model, cv_data_loader, writer, info_dict, on_batch_end=True)
+
+ @torch.inference_mode()
+ def cv(self, model, cv_data_loader, writer, info_dict, on_batch_end=True):
+ ''' Cross validation on
+ '''
+ logging.info('Epoch {} Step {} on_batch_end {} CV rank {}'.format(self.epoch, self.step + 1, on_batch_end, self.rank))
+ model.eval()
+ total_num_utts, total_loss_dict = 0, {} # avoid division by 0
+ for batch_idx, batch_dict in enumerate(cv_data_loader):
+ info_dict["tag"] = "CV"
+ info_dict["step"] = self.step
+ info_dict["epoch"] = self.epoch
+ info_dict["batch_idx"] = batch_idx
+
+ # num_utts = len(batch_dict["utts"])
+ num_utts=batch_dict["speech_token"].size(0)
+ total_num_utts += num_utts
+
+ info_dict = batch_forward(model, batch_dict, info_dict)
+
+ for k, v in info_dict['loss_dict'].items():
+ if k not in total_loss_dict:
+ total_loss_dict[k] = []
+ total_loss_dict[k].append(v.item() * num_utts)
+ log_per_step(None, info_dict)
+ for k, v in total_loss_dict.items():
+ total_loss_dict[k] = sum(v) / total_num_utts
+ info_dict['loss_dict'] = total_loss_dict
+ log_per_save(writer, info_dict)
+ model_name = 'epoch_{}_whole'.format(self.epoch) if on_batch_end else 'epoch_{}_step_{}'.format(self.epoch, self.step + 1)
+ save_model(model, model_name, info_dict)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/file_utils.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/file_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4179e109da4073ca9be75767c3f59d2ee68a5cf
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/file_utils.py
@@ -0,0 +1,53 @@
+# Copyright (c) 2021 Mobvoi Inc. (authors: Binbin Zhang)
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import torchaudio
+
+
+def read_lists(list_file):
+ lists = []
+ with open(list_file, 'r', encoding='utf8') as fin:
+ for line in fin:
+ lists.append(line.strip())
+ return lists
+
+def read_json_lists(list_file):
+ lists = read_lists(list_file)
+ results = {}
+ for fn in lists:
+ with open(fn, 'r', encoding='utf8') as fin:
+ results.update(json.load(fin))
+ return results
+
+def load_wav(wav, target_sr):
+ speech, sample_rate = torchaudio.load(wav)
+ speech = speech.mean(dim=0, keepdim=True)
+ if sample_rate != target_sr:
+ assert sample_rate > target_sr, 'wav sample rate {} must be greater than {}'.format(sample_rate, target_sr)
+ speech = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=target_sr)(speech)
+ return speech
+
+def speed_change(waveform, sample_rate, speed_factor: str):
+ effects = [
+ ["tempo", speed_factor], # speed_factor
+ ["rate", f"{sample_rate}"]
+ ]
+ augmented_waveform, new_sample_rate = torchaudio.sox_effects.apply_effects_tensor(
+ waveform,
+ sample_rate,
+ effects
+ )
+ return augmented_waveform, new_sample_rate
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/frontend_utils.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/frontend_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..59489a7a6fdb442b1134baac3e5eef0211130954
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/frontend_utils.py
@@ -0,0 +1,125 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import re
+chinese_char_pattern = re.compile(r'[\u4e00-\u9fff]+')
+
+# whether contain chinese character
+def contains_chinese(text):
+ return bool(chinese_char_pattern.search(text))
+
+
+# replace special symbol
+def replace_corner_mark(text):
+ text = text.replace('²', '平方')
+ text = text.replace('³', '立方')
+ return text
+
+
+# remove meaningless symbol
+def remove_bracket(text):
+ text = text.replace('（', '').replace('）', '')
+ text = text.replace('【', '').replace('】', '')
+ text = text.replace('`', '').replace('`', '')
+ text = text.replace("——", " ")
+ return text
+
+
+# spell Arabic numerals
+def spell_out_number(text: str, inflect_parser):
+ new_text = []
+ st = None
+ for i, c in enumerate(text):
+ if not c.isdigit():
+ if st is not None:
+ num_str = inflect_parser.number_to_words(text[st: i])
+ new_text.append(num_str)
+ st = None
+ new_text.append(c)
+ else:
+ if st is None:
+ st = i
+ if st is not None and st < len(text):
+ num_str = inflect_parser.number_to_words(text[st:])
+ new_text.append(num_str)
+ return ''.join(new_text)
+
+
+# split paragrah logic：
+# 1. per sentence max len token_max_n, min len token_min_n, merge if last sentence len less than merge_len
+# 2. cal sentence len according to lang
+# 3. split sentence according to puncatation
+def split_paragraph(text: str, tokenize, lang="zh", token_max_n=80, token_min_n=60, merge_len=20, comma_split=False):
+ def calc_utt_length(_text: str):
+ if lang == "zh":
+ return len(_text)
+ else:
+ return len(tokenize(_text))
+
+ def should_merge(_text: str):
+ if lang == "zh":
+ return len(_text) < merge_len
+ else:
+ return len(tokenize(_text)) < merge_len
+
+ if lang == "zh":
+ pounc = ['。', '？', '！', '；', '：', '、', '.', '?', '!', ';']
+ else:
+ pounc = ['.', '?', '!', ';', ':']
+ if comma_split:
+ pounc.extend(['，', ','])
+ st = 0
+ utts = []
+ for i, c in enumerate(text):
+ if c in pounc:
+ if len(text[st: i]) > 0:
+ utts.append(text[st: i] + c)
+ if i + 1 < len(text) and text[i + 1] in ['"', '”']:
+ tmp = utts.pop(-1)
+ utts.append(tmp + text[i + 1])
+ st = i + 2
+ else:
+ st = i + 1
+ if len(utts) == 0:
+ if lang == "zh":
+ utts.append(text + '。')
+ else:
+ utts.append(text + '.')
+ final_utts = []
+ cur_utt = ""
+ for utt in utts:
+ if calc_utt_length(cur_utt + utt) > token_max_n and calc_utt_length(cur_utt) > token_min_n:
+ final_utts.append(cur_utt)
+ cur_utt = ""
+ cur_utt = cur_utt + utt
+ if len(cur_utt) > 0:
+ if should_merge(cur_utt) and len(final_utts) != 0:
+ final_utts[-1] = final_utts[-1] + cur_utt
+ else:
+ final_utts.append(cur_utt)
+
+ return final_utts
+
+
+# remove blank between chinese character
+def replace_blank(text: str):
+ out_str = []
+ for i, c in enumerate(text):
+ if c == " ":
+ if ((text[i + 1].isascii() and text[i + 1] != " ") and
+ (text[i - 1].isascii() and text[i - 1] != " ")):
+ out_str.append(c)
+ else:
+ out_str.append(c)
+ return "".join(out_str)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/mask.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/mask.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b460bbd5adb4bd61d643ace71400a14fe314236
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/mask.py
@@ -0,0 +1,227 @@
+# Copyright (c) 2019 Shigeki Karita
+# 2020 Mobvoi Inc (Binbin Zhang)
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+'''
+def subsequent_mask(
+ size: int,
+ device: torch.device = torch.device("cpu"),
+) -> torch.Tensor:
+ """Create mask for subsequent steps (size, size).
+
+ This mask is used only in decoder which works in an auto-regressive mode.
+ This means the current step could only do attention with its left steps.
+
+ In encoder, fully attention is used when streaming is not necessary and
+ the sequence is not long. In this case, no attention mask is needed.
+
+ When streaming is need, chunk-based attention is used in encoder. See
+ subsequent_chunk_mask for the chunk-based attention mask.
+
+ Args:
+ size (int): size of mask
+ str device (str): "cpu" or "cuda" or torch.Tensor.device
+ dtype (torch.device): result dtype
+
+ Returns:
+ torch.Tensor: mask
+
+ Examples:
+ >>> subsequent_mask(3)
+ [[1, 0, 0],
+ [1, 1, 0],
+ [1, 1, 1]]
+ """
+ ret = torch.ones(size, size, device=device, dtype=torch.bool)
+ return torch.tril(ret)
+'''
+
+
+def subsequent_mask(
+ size: int,
+ device: torch.device = torch.device("cpu"),
+) -> torch.Tensor:
+ """Create mask for subsequent steps (size, size).
+
+ This mask is used only in decoder which works in an auto-regressive mode.
+ This means the current step could only do attention with its left steps.
+
+ In encoder, fully attention is used when streaming is not necessary and
+ the sequence is not long. In this case, no attention mask is needed.
+
+ When streaming is need, chunk-based attention is used in encoder. See
+ subsequent_chunk_mask for the chunk-based attention mask.
+
+ Args:
+ size (int): size of mask
+ str device (str): "cpu" or "cuda" or torch.Tensor.device
+ dtype (torch.device): result dtype
+
+ Returns:
+ torch.Tensor: mask
+
+ Examples:
+ >>> subsequent_mask(3)
+ [[1, 0, 0],
+ [1, 1, 0],
+ [1, 1, 1]]
+ """
+ arange = torch.arange(size, device=device)
+ mask = arange.expand(size, size)
+ arange = arange.unsqueeze(-1)
+ mask = mask <= arange
+ return mask
+
+
+def subsequent_chunk_mask(
+ size: int,
+ chunk_size: int,
+ num_left_chunks: int = -1,
+ device: torch.device = torch.device("cpu"),
+) -> torch.Tensor:
+ """Create mask for subsequent steps (size, size) with chunk size,
+ this is for streaming encoder
+
+ Args:
+ size (int): size of mask
+ chunk_size (int): size of chunk
+ num_left_chunks (int): number of left chunks
+ <0: use full chunk
+ >=0: use num_left_chunks
+ device (torch.device): "cpu" or "cuda" or torch.Tensor.device
+
+ Returns:
+ torch.Tensor: mask
+
+ Examples:
+ >>> subsequent_chunk_mask(4, 2)
+ [[1, 1, 0, 0],
+ [1, 1, 0, 0],
+ [1, 1, 1, 1],
+ [1, 1, 1, 1]]
+ """
+ ret = torch.zeros(size, size, device=device, dtype=torch.bool)
+ for i in range(size):
+ if num_left_chunks < 0:
+ start = 0
+ else:
+ start = max((i // chunk_size - num_left_chunks) * chunk_size, 0)
+ ending = min((i // chunk_size + 1) * chunk_size, size)
+ ret[i, start:ending] = True
+ return ret
+
+
+def add_optional_chunk_mask(xs: torch.Tensor,
+ masks: torch.Tensor,
+ use_dynamic_chunk: bool,
+ use_dynamic_left_chunk: bool,
+ decoding_chunk_size: int,
+ static_chunk_size: int,
+ num_decoding_left_chunks: int,
+ enable_full_context: bool = True):
+ """ Apply optional mask for encoder.
+
+ Args:
+ xs (torch.Tensor): padded input, (B, L, D), L for max length
+ mask (torch.Tensor): mask for xs, (B, 1, L)
+ use_dynamic_chunk (bool): whether to use dynamic chunk or not
+ use_dynamic_left_chunk (bool): whether to use dynamic left chunk for
+ training.
+ decoding_chunk_size (int): decoding chunk size for dynamic chunk, it's
+ 0: default for training, use random dynamic chunk.
+ <0: for decoding, use full chunk.
+ >0: for decoding, use fixed chunk size as set.
+ static_chunk_size (int): chunk size for static chunk training/decoding
+ if it's greater than 0, if use_dynamic_chunk is true,
+ this parameter will be ignored
+ num_decoding_left_chunks: number of left chunks, this is for decoding,
+ the chunk size is decoding_chunk_size.
+ >=0: use num_decoding_left_chunks
+ <0: use all left chunks
+ enable_full_context (bool):
+ True: chunk size is either [1, 25] or full context(max_len)
+ False: chunk size ~ U[1, 25]
+
+ Returns:
+ torch.Tensor: chunk mask of the input xs.
+ """
+ # Whether to use chunk mask or not
+ if use_dynamic_chunk:
+ max_len = xs.size(1)
+ if decoding_chunk_size < 0:
+ chunk_size = max_len
+ num_left_chunks = -1
+ elif decoding_chunk_size > 0:
+ chunk_size = decoding_chunk_size
+ num_left_chunks = num_decoding_left_chunks
+ else:
+ # chunk size is either [1, 25] or full context(max_len).
+ # Since we use 4 times subsampling and allow up to 1s(100 frames)
+ # delay, the maximum frame is 100 / 4 = 25.
+ chunk_size = torch.randint(1, max_len, (1, )).item()
+ num_left_chunks = -1
+ if chunk_size > max_len // 2 and enable_full_context:
+ chunk_size = max_len
+ else:
+ chunk_size = chunk_size % 25 + 1
+ if use_dynamic_left_chunk:
+ max_left_chunks = (max_len - 1) // chunk_size
+ num_left_chunks = torch.randint(0, max_left_chunks,
+ (1, )).item()
+ chunk_masks = subsequent_chunk_mask(xs.size(1), chunk_size,
+ num_left_chunks,
+ xs.device) # (L, L)
+ chunk_masks = chunk_masks.unsqueeze(0) # (1, L, L)
+ chunk_masks = masks & chunk_masks # (B, L, L)
+ elif static_chunk_size > 0:
+ num_left_chunks = num_decoding_left_chunks
+ chunk_masks = subsequent_chunk_mask(xs.size(1), static_chunk_size,
+ num_left_chunks,
+ xs.device) # (L, L)
+ chunk_masks = chunk_masks.unsqueeze(0) # (1, L, L)
+ chunk_masks = masks & chunk_masks # (B, L, L)
+ else:
+ chunk_masks = masks
+ return chunk_masks
+
+
+def make_pad_mask(lengths: torch.Tensor, max_len: int = 0) -> torch.Tensor:
+ """Make mask tensor containing indices of padded part.
+
+ See description of make_non_pad_mask.
+
+ Args:
+ lengths (torch.Tensor): Batch of lengths (B,).
+ Returns:
+ torch.Tensor: Mask tensor containing indices of padded part.
+
+ Examples:
+ >>> lengths = [5, 3, 2]
+ >>> make_pad_mask(lengths)
+ masks = [[0, 0, 0, 0 ,0],
+ [0, 0, 0, 1, 1],
+ [0, 0, 1, 1, 1]]
+ """
+ batch_size = lengths.size(0)
+ max_len = max_len if max_len > 0 else lengths.max().item()
+ seq_range = torch.arange(0,
+ max_len,
+ dtype=torch.int64,
+ device=lengths.device)
+ seq_range_expand = seq_range.unsqueeze(0).expand(batch_size, max_len)
+ seq_length_expand = lengths.unsqueeze(-1)
+ mask = seq_range_expand >= seq_length_expand
+ return mask
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/scheduler.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/scheduler.py
new file mode 100644
index 0000000000000000000000000000000000000000..fbf4803f81bd7a3cee4af7bd8b6af2d3b46304d7
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/scheduler.py
@@ -0,0 +1,739 @@
+# Copyright (c) 2020 Mobvoi Inc (Binbin Zhang)
+# 2022 Ximalaya Inc (Yuguang Yang)
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# Modified from ESPnet(https://github.com/espnet/espnet)
+# NeMo(https://github.com/NVIDIA/NeMo)
+
+from typing import Union
+
+import math
+import warnings
+import torch
+from torch.optim.lr_scheduler import _LRScheduler
+
+
+class WarmupLR(_LRScheduler):
+ """The WarmupLR scheduler
+
+ This scheduler is almost same as NoamLR Scheduler except for following
+ difference:
+
+ NoamLR:
+ lr = optimizer.lr * model_size ** -0.5
+ * min(step ** -0.5, step * warmup_step ** -1.5)
+ WarmupLR:
+ lr = optimizer.lr * warmup_step ** 0.5
+ * min(step ** -0.5, step * warmup_step ** -1.5)
+
+ Note that the maximum lr equals to optimizer.lr in this scheduler.
+
+ """
+
+ def __init__(
+ self,
+ optimizer: torch.optim.Optimizer,
+ warmup_steps: Union[int, float] = 25000,
+ last_epoch: int = -1,
+ ):
+ self.warmup_steps = warmup_steps
+
+ # __init__() must be invoked before setting field
+ # because step() is also invoked in __init__()
+ super().__init__(optimizer, last_epoch)
+
+ def __repr__(self):
+ return f"{self.__class__.__name__}(warmup_steps={self.warmup_steps})"
+
+ def get_lr(self):
+ step_num = self.last_epoch + 1
+ if self.warmup_steps == 0:
+ return [lr * step_num**-0.5 for lr in self.base_lrs]
+ else:
+ return [
+ lr * self.warmup_steps**0.5 *
+ min(step_num**-0.5, step_num * self.warmup_steps**-1.5)
+ for lr in self.base_lrs
+ ]
+
+ def set_step(self, step: int):
+ self.last_epoch = step
+
+
+class WarmupPolicy(_LRScheduler):
+ """Adds warmup kwargs and warmup logic to lr policy.
+ All arguments should be passed as kwargs for clarity,
+ Args:
+ warmup_steps: Number of training steps in warmup stage
+ warmup_ratio: Ratio of warmup steps to total steps
+ max_steps: Total number of steps while training or `None` for
+ infinite training
+ """
+
+ def __init__(self,
+ optimizer,
+ *,
+ warmup_steps=None,
+ warmup_ratio=None,
+ max_steps=None,
+ min_lr=0.0,
+ last_epoch=-1):
+ assert not (warmup_steps is not None and warmup_ratio is not None),\
+ "Either use particular number of step or ratio"
+ assert warmup_ratio is None or max_steps is not None, \
+ "If there is a ratio, there should be a total steps"
+
+ # It is necessary to assign all attributes *before* __init__,
+ # as class is wrapped by an inner class.
+ self.max_steps = max_steps
+ if warmup_steps is not None:
+ self.warmup_steps = warmup_steps
+ elif warmup_ratio is not None:
+ self.warmup_steps = int(warmup_ratio * max_steps)
+ else:
+ self.warmup_steps = 0
+
+ self.min_lr = min_lr
+ super().__init__(optimizer, last_epoch)
+
+ def get_lr(self):
+ if not self._get_lr_called_within_step:
+ warnings.warn(
+ "To get the last learning rate computed "
+ "by the scheduler, please use `get_last_lr()`.",
+ UserWarning,
+ stacklevel=2)
+
+ step = self.last_epoch
+
+ if step <= self.warmup_steps and self.warmup_steps > 0:
+ return self._get_warmup_lr(step)
+
+ if step > self.max_steps:
+ return [self.min_lr for _ in self.base_lrs]
+
+ return self._get_lr(step)
+
+ def _get_warmup_lr(self, step):
+ lr_val = (step + 1) / (self.warmup_steps + 1)
+ return [initial_lr * lr_val for initial_lr in self.base_lrs]
+
+ def _get_lr(self, step):
+ """Simple const lr policy"""
+ return self.base_lrs
+
+
+class SquareRootConstantPolicy(_LRScheduler):
+ """Adds warmup kwargs and warmup logic to lr policy.
+ All arguments should be passed as kwargs for clarity,
+ Args:
+ warmup_steps: Number of training steps in warmup stage
+ warmup_ratio: Ratio of warmup steps to total steps
+ max_steps: Total number of steps while training or `None` for
+ infinite training
+ """
+
+ def __init__(self,
+ optimizer,
+ *,
+ constant_steps=None,
+ constant_ratio=None,
+ max_steps=None,
+ min_lr=0.0,
+ last_epoch=-1):
+ assert not (constant_steps is not None
+ and constant_ratio is not None), \
+ "Either use particular number of step or ratio"
+ assert constant_ratio is None or max_steps is not None, \
+ "If there is a ratio, there should be a total steps"
+
+ # It is necessary to assign all attributes *before* __init__,
+ # as class is wrapped by an inner class.
+ self.max_steps = max_steps
+ if constant_steps is not None:
+ self.constant_steps = constant_steps
+ elif constant_ratio is not None:
+ self.constant_steps = int(constant_ratio * max_steps)
+ else:
+ self.constant_steps = 0
+
+ self.constant_lr = 1 / (constant_steps**0.5)
+ self.min_lr = min_lr
+ super().__init__(optimizer, last_epoch)
+
+ def get_lr(self):
+ if not self._get_lr_called_within_step:
+ warnings.warn(
+ "To get the last learning rate computed "
+ "by the scheduler, please use `get_last_lr()`.",
+ UserWarning,
+ stacklevel=2)
+
+ step = self.last_epoch
+
+ if step <= self.constant_steps:
+ return [self.constant_lr for _ in self.base_lrs]
+
+ if step > self.max_steps:
+ return [self.min_lr for _ in self.base_lrs]
+
+ return self._get_lr(step)
+
+ def _get_lr(self, step):
+ """Simple const lr policy"""
+ return self.base_lrs
+
+
+class WarmupHoldPolicy(WarmupPolicy):
+ """Variant of WarmupPolicy which maintains high
+ learning rate for a defined number of steps.
+ All arguments should be passed as kwargs for clarity,
+ Args:
+ warmup_steps: Number of training steps in warmup stage
+ warmup_ratio: Ratio of warmup steps to total steps
+ hold_steps: Number of training steps to
+ hold the learning rate after warm up
+ hold_ratio: Ratio of hold steps to total steps
+ max_steps: Total number of steps while training or `None` for
+ infinite training
+ """
+
+ def __init__(
+ self,
+ optimizer,
+ *,
+ warmup_steps=None,
+ warmup_ratio=None,
+ hold_steps=None,
+ hold_ratio=None,
+ max_steps=None,
+ min_lr=0.0,
+ last_epoch=-1,
+ ):
+ assert not (hold_steps is not None and hold_ratio is not None), \
+ "Either use particular number of step or ratio"
+ assert hold_ratio is None or max_steps is not None, \
+ "If there is a ratio, there should be a total steps"
+
+ self.min_lr = min_lr
+ self._last_warmup_lr = 0.0
+
+ # Necessary to duplicate as class attributes are hidden in inner class
+ self.max_steps = max_steps
+ if warmup_steps is not None:
+ self.warmup_steps = warmup_steps
+ elif warmup_ratio is not None:
+ self.warmup_steps = int(warmup_ratio * max_steps)
+ else:
+ self.warmup_steps = 0
+
+ if hold_steps is not None:
+ self.hold_steps = hold_steps + self.warmup_steps
+ elif hold_ratio is not None:
+ self.hold_steps = int(hold_ratio * max_steps) + self.warmup_steps
+ else:
+ self.hold_steps = 0
+
+ super().__init__(
+ optimizer,
+ warmup_steps=warmup_steps,
+ warmup_ratio=warmup_ratio,
+ max_steps=max_steps,
+ last_epoch=last_epoch,
+ min_lr=min_lr,
+ )
+
+ def get_lr(self):
+ if not self._get_lr_called_within_step:
+ warnings.warn(
+ "To get the last learning rate computed by the scheduler,"
+ " "
+ "please use `get_last_lr()`.",
+ UserWarning,
+ stacklevel=2)
+
+ step = self.last_epoch
+
+ # Warmup phase
+ if step <= self.warmup_steps and self.warmup_steps > 0:
+ return self._get_warmup_lr(step)
+
+ # Hold phase
+ if (step >= self.warmup_steps) and (step < self.hold_steps):
+ return self.base_lrs
+
+ if step > self.max_steps:
+ return [self.min_lr for _ in self.base_lrs]
+
+ return self._get_lr(step)
+
+
+class WarmupAnnealHoldPolicy(_LRScheduler):
+ """Adds warmup kwargs and warmup logic to lr policy.
+ All arguments should be passed as kwargs for clarity,
+ Args:
+ warmup_steps: Number of training steps in warmup stage
+ warmup_ratio: Ratio of warmup steps to total steps
+ max_steps: Total number of steps while training or `None` for
+ infinite training
+ min_lr: Minimum lr to hold the learning rate after decay at.
+ constant_steps: Number of steps to keep lr constant at.
+ constant_ratio: Ratio of steps to keep lr constant.
+ """
+
+ def __init__(
+ self,
+ optimizer,
+ *,
+ warmup_steps=None,
+ warmup_ratio=None,
+ constant_steps=None,
+ constant_ratio=None,
+ max_steps=None,
+ min_lr=0.0,
+ last_epoch=-1,
+ ):
+ assert not (warmup_steps is not None
+ and warmup_ratio is not None), \
+ "Either use particular number of step or ratio"
+ assert not (constant_steps is not None
+ and constant_ratio is not None), \
+ "Either use constant_steps or constant_ratio"
+ assert warmup_ratio is None or max_steps is not None, \
+ "If there is a ratio, there should be a total steps"
+
+ # It is necessary to assign all attributes *before* __init__,
+ # as class is wrapped by an inner class.
+ self.max_steps = max_steps
+
+ if warmup_steps is not None:
+ self.warmup_steps = warmup_steps
+ elif warmup_ratio is not None:
+ self.warmup_steps = int(warmup_ratio * max_steps)
+ else:
+ self.warmup_steps = 0
+
+ if constant_steps is not None:
+ self.constant_steps = constant_steps
+ elif constant_ratio is not None:
+ self.constant_steps = int(constant_ratio * max_steps)
+ else:
+ self.constant_steps = 0
+
+ self.decay_steps = max_steps - (self.constant_steps +
+ self.warmup_steps)
+
+ self.min_lr = min_lr
+ super().__init__(optimizer, last_epoch)
+
+ def get_lr(self):
+ if not self._get_lr_called_within_step:
+ warnings.warn(
+ "To get the last learning rate computed "
+ "by the scheduler, please use `get_last_lr()`.",
+ UserWarning,
+ stacklevel=2)
+
+ step = self.last_epoch
+
+ # Warmup steps
+ if self.warmup_steps > 0 and step <= self.warmup_steps:
+ return self._get_warmup_lr(step)
+
+ # Constant steps after warmup and decay
+ if self.constant_steps > 0 and (
+ self.warmup_steps + self.decay_steps) < step <= self.max_steps:
+ return self._get_constant_lr(step)
+
+ # Min lr after max steps of updates
+ if step > self.max_steps:
+ return [self.min_lr for _ in self.base_lrs]
+
+ return self._get_lr(step)
+
+ def _get_warmup_lr(self, step):
+ lr_val = (step + 1) / (self.warmup_steps + 1)
+ return [initial_lr * lr_val for initial_lr in self.base_lrs]
+
+ def _get_constant_lr(self, step):
+ return [self.min_lr for _ in self.base_lrs]
+
+ def _get_lr(self, step):
+ """Simple const lr policy"""
+ return self.base_lrs
+
+
+def _squareroot_annealing(initial_lr, step, max_steps, min_lr):
+ mult = ((max_steps - step) / max_steps)**0.5
+ out_lr = initial_lr * mult
+ out_lr = max(out_lr, min_lr)
+ return out_lr
+
+
+def _square_annealing(initial_lr, step, max_steps, min_lr):
+ mult = ((max_steps - step) / max_steps)**2
+ out_lr = initial_lr * mult
+ out_lr = max(out_lr, min_lr)
+ return out_lr
+
+
+def _cosine_annealing(initial_lr, step, max_steps, min_lr):
+ mult = 0.5 * (1 + math.cos(math.pi * step / max_steps))
+ out_lr = (initial_lr - min_lr) * mult + min_lr
+ return out_lr
+
+
+def _linear_warmup_with_cosine_annealing(max_lr, warmup_steps, step,
+ decay_steps, min_lr):
+ assert max_lr > min_lr
+ # Use linear warmup for the initial part.
+ if warmup_steps > 0 and step <= warmup_steps:
+ return max_lr * float(step) / float(warmup_steps)
+
+ # For any steps larger than `decay_steps`, use `min_lr`.
+ if step > warmup_steps + decay_steps:
+ return min_lr
+
+ # If we are done with the warmup period, use the decay style.
+ num_steps_ = step - warmup_steps
+ decay_steps_ = decay_steps
+ decay_ratio = float(num_steps_) / float(decay_steps_)
+ assert decay_ratio >= 0.0
+ assert decay_ratio <= 1.0
+ delta_lr = max_lr - min_lr
+
+ coeff = 0.5 * (math.cos(math.pi * decay_ratio) + 1.0)
+
+ return min_lr + coeff * delta_lr
+
+
+def _poly_decay(initial_lr, step, decay_steps, power, min_lr, cycle):
+ if cycle:
+ multiplier = 1.0 if step == 0 else math.ceil(step / decay_steps)
+ decay_steps *= multiplier
+ else:
+ step = min(step, decay_steps)
+ p = step / decay_steps
+ lr = (initial_lr - min_lr) * math.pow(1.0 - p, power)
+ lr += min_lr
+ return lr
+
+
+def _noam_hold_annealing(initial_lr, step, warmup_steps, hold_steps,
+ decay_rate, min_lr):
+ # hold_steps = total number of steps
+ # to hold the LR, not the warmup + hold steps.
+ T_warmup_decay = max(1, warmup_steps**decay_rate)
+ T_hold_decay = max(1, (step - hold_steps)**decay_rate)
+ lr = (initial_lr * T_warmup_decay) / T_hold_decay
+ lr = max(lr, min_lr)
+ return lr
+
+
+class SquareAnnealing(WarmupPolicy):
+
+ def __init__(self,
+ optimizer,
+ *,
+ max_steps,
+ min_lr=1e-5,
+ last_epoch=-1,
+ **kwargs):
+ super().__init__(optimizer=optimizer,
+ max_steps=max_steps,
+ last_epoch=last_epoch,
+ min_lr=min_lr,
+ **kwargs)
+
+ def _get_lr(self, step):
+ new_lrs = [
+ _square_annealing(
+ initial_lr=initial_lr,
+ step=step - self.warmup_steps,
+ max_steps=self.max_steps - self.warmup_steps,
+ min_lr=self.min_lr,
+ ) for initial_lr in self.base_lrs
+ ]
+ return new_lrs
+
+
+class SquareRootAnnealing(WarmupPolicy):
+
+ def __init__(self,
+ optimizer,
+ *,
+ max_steps,
+ min_lr=0,
+ last_epoch=-1,
+ **kwargs):
+ super().__init__(optimizer=optimizer,
+ max_steps=max_steps,
+ last_epoch=last_epoch,
+ min_lr=min_lr,
+ **kwargs)
+
+ def _get_lr(self, step):
+ new_lrs = [
+ _squareroot_annealing(initial_lr=initial_lr,
+ step=step,
+ max_steps=self.max_steps,
+ min_lr=self.min_lr)
+ for initial_lr in self.base_lrs
+ ]
+ return new_lrs
+
+
+class CosineAnnealing(WarmupAnnealHoldPolicy):
+
+ def __init__(self,
+ optimizer,
+ *,
+ max_steps,
+ min_lr=0,
+ last_epoch=-1,
+ **kwargs):
+ super().__init__(optimizer=optimizer,
+ max_steps=max_steps,
+ last_epoch=last_epoch,
+ min_lr=min_lr,
+ **kwargs)
+
+ def _get_lr(self, step):
+ for initial_lr in self.base_lrs:
+ if initial_lr < self.min_lr:
+ raise ValueError(
+ f"{self} received an initial learning rate "
+ f"that was lower than the minimum learning rate.")
+
+ if self.constant_steps is None or self.constant_steps == 0:
+ new_lrs = [
+ _cosine_annealing(
+ initial_lr=initial_lr,
+ step=step - self.warmup_steps,
+ max_steps=self.max_steps - self.warmup_steps,
+ min_lr=self.min_lr,
+ ) for initial_lr in self.base_lrs
+ ]
+ else:
+ new_lrs = self._get_linear_warmup_with_cosine_annealing_lr(step)
+ return new_lrs
+
+ def _get_warmup_lr(self, step):
+ if self.constant_steps is None or self.constant_steps == 0:
+ return super()._get_warmup_lr(step)
+ else:
+ # Use linear warmup for the initial part.
+ return self._get_linear_warmup_with_cosine_annealing_lr(step)
+
+ def _get_constant_lr(self, step):
+ # Only called when `constant_steps` > 0.
+ return self._get_linear_warmup_with_cosine_annealing_lr(step)
+
+ def _get_linear_warmup_with_cosine_annealing_lr(self, step):
+ # Cosine Schedule for Megatron LM,
+ # slightly different warmup schedule + constant LR at the end.
+ new_lrs = [
+ _linear_warmup_with_cosine_annealing(
+ max_lr=self.base_lrs[0],
+ warmup_steps=self.warmup_steps,
+ step=step,
+ decay_steps=self.decay_steps,
+ min_lr=self.min_lr,
+ ) for _ in self.base_lrs
+ ]
+ return new_lrs
+
+
+class NoamAnnealing(_LRScheduler):
+
+ def __init__(self,
+ optimizer,
+ *,
+ d_model,
+ warmup_steps=None,
+ warmup_ratio=None,
+ max_steps=None,
+ min_lr=0.0,
+ last_epoch=-1):
+ self._normalize = d_model**(-0.5)
+ assert not (warmup_steps is not None
+ and warmup_ratio is not None), \
+ "Either use particular number of step or ratio"
+ assert warmup_ratio is None or max_steps is not None, \
+ "If there is a ratio, there should be a total steps"
+
+ # It is necessary to assign all attributes *before* __init__,
+ # as class is wrapped by an inner class.
+ self.max_steps = max_steps
+ if warmup_steps is not None:
+ self.warmup_steps = warmup_steps
+ elif warmup_ratio is not None:
+ self.warmup_steps = int(warmup_ratio * max_steps)
+ else:
+ self.warmup_steps = 0
+
+ self.min_lr = min_lr
+ super().__init__(optimizer, last_epoch)
+
+ def get_lr(self):
+ if not self._get_lr_called_within_step:
+ warnings.warn(
+ "To get the last learning rate computed "
+ "by the scheduler, please use `get_last_lr()`.",
+ UserWarning,
+ stacklevel=2)
+
+ step = max(1, self.last_epoch)
+
+ for initial_lr in self.base_lrs:
+ if initial_lr < self.min_lr:
+ raise ValueError(
+ f"{self} received an initial learning rate "
+ f"that was lower than the minimum learning rate.")
+
+ new_lrs = [
+ self._noam_annealing(initial_lr=initial_lr, step=step)
+ for initial_lr in self.base_lrs
+ ]
+ return new_lrs
+
+ def _noam_annealing(self, initial_lr, step):
+ if self.warmup_steps > 0:
+ mult = self._normalize * min(step**(-0.5),
+ step * (self.warmup_steps**(-1.5)))
+ else:
+ mult = self._normalize * step**(-0.5)
+
+ out_lr = initial_lr * mult
+ if step > self.warmup_steps:
+ out_lr = max(out_lr, self.min_lr)
+ return out_lr
+
+
+class NoamHoldAnnealing(WarmupHoldPolicy):
+
+ def __init__(self,
+ optimizer,
+ *,
+ max_steps,
+ decay_rate=0.5,
+ min_lr=0.0,
+ last_epoch=-1,
+ **kwargs):
+ """
+ From Nemo:
+ Implementation of the Noam Hold Annealing policy
+ from the SqueezeFormer paper.
+
+ Unlike NoamAnnealing, the peak learning rate
+ can be explicitly set for this scheduler.
+ The schedule first performs linear warmup,
+ then holds the peak LR, then decays with some schedule for
+ the remainder of the steps.
+ Therefore the min-lr is still dependent
+ on the hyper parameters selected.
+
+ It's schedule is determined by three factors-
+
+ Warmup Steps: Initial stage, where linear warmup
+ occurs uptil the peak LR is reached. Unlike NoamAnnealing,
+ the peak LR is explicitly stated here instead of a scaling factor.
+
+ Hold Steps: Intermediate stage, where the peak LR
+ is maintained for some number of steps. In this region,
+ the high peak LR allows the model to converge faster
+ if training is stable. However the high LR
+ may also cause instability during training.
+ Should usually be a significant fraction of training
+ steps (around 30-40% of the entire training steps).
+
+ Decay Steps: Final stage, where the LR rapidly decays
+ with some scaling rate (set by decay rate).
+ To attain Noam decay, use 0.5,
+ for Squeezeformer recommended decay, use 1.0.
+ The fast decay after prolonged high LR during
+ hold phase allows for rapid convergence.
+
+ References:
+ - [Squeezeformer:
+ An Efficient Transformer for Automatic Speech Recognition]
+ (https://arxiv.org/abs/2206.00888)
+
+ Args:
+ optimizer: Pytorch compatible Optimizer object.
+ warmup_steps: Number of training steps in warmup stage
+ warmup_ratio: Ratio of warmup steps to total steps
+ hold_steps: Number of training steps to
+ hold the learning rate after warm up
+ hold_ratio: Ratio of hold steps to total steps
+ max_steps: Total number of steps while training or `None` for
+ infinite training
+ decay_rate: Float value describing the polynomial decay
+ after the hold period. Default value
+ of 0.5 corresponds to Noam decay.
+ min_lr: Minimum learning rate.
+ """
+ self.decay_rate = decay_rate
+ super().__init__(optimizer=optimizer,
+ max_steps=max_steps,
+ last_epoch=last_epoch,
+ min_lr=min_lr,
+ **kwargs)
+
+ def _get_lr(self, step):
+ if self.warmup_steps is None or self.warmup_steps == 0:
+ raise ValueError(
+ "Noam scheduler cannot be used without warmup steps")
+
+ if self.hold_steps > 0:
+ hold_steps = self.hold_steps - self.warmup_steps
+ else:
+ hold_steps = 0
+
+ new_lrs = [
+ _noam_hold_annealing(
+ initial_lr,
+ step=step,
+ warmup_steps=self.warmup_steps,
+ hold_steps=hold_steps,
+ decay_rate=self.decay_rate,
+ min_lr=self.min_lr,
+ ) for initial_lr in self.base_lrs
+ ]
+ return new_lrs
+
+ def set_step(self, step: int):
+ self.last_epoch = step
+
+
+class ConstantLR(_LRScheduler):
+ """The ConstantLR scheduler
+
+ This scheduler keeps a constant lr
+
+ """
+
+ def __init__(
+ self,
+ optimizer: torch.optim.Optimizer,
+ ):
+ # __init__() must be invoked before setting field
+ # because step() is also invoked in __init__()
+ super().__init__(optimizer)
+
+ def get_lr(self):
+ return self.base_lrs
+
+ def set_step(self, step: int):
+ self.last_epoch = step
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/train_utils.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/train_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..020005d001e1c386c84398981dfcc039b41fa89b
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/cosyvoice/utils/train_utils.py
@@ -0,0 +1,289 @@
+# Copyright (c) 2021 Mobvoi Inc. (authors: Binbin Zhang)
+# 2023 Horizon Inc. (authors: Xingchen Song)
+# 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from contextlib import nullcontext
+import logging
+import os
+import torch
+import json
+import re
+import datetime
+import yaml
+
+# import deepspeed
+import torch.optim as optim
+import torch.distributed as dist
+
+from torch.utils.tensorboard import SummaryWriter
+from torch.utils.data import DataLoader
+from torch.nn.utils import clip_grad_norm_
+
+# from deepspeed.runtime.zero.stage_1_and_2 import estimate_zero2_model_states_mem_needs_all_live
+
+from cosyvoice.dataset.dataset import Dataset
+from cosyvoice.utils.scheduler import WarmupLR, NoamHoldAnnealing, ConstantLR
+
+
+def init_distributed(args):
+ world_size = int(os.environ.get('WORLD_SIZE', 1))
+ local_rank = int(os.environ.get('LOCAL_RANK', 0))
+ rank = int(os.environ.get('RANK', 0))
+ logging.info('training on multiple gpus, this gpu {}'.format(local_rank) +
+ ', rank {}, world_size {}'.format(rank, world_size))
+ if args.train_engine == 'torch_ddp':
+ torch.cuda.set_device(local_rank)
+ dist.init_process_group(args.dist_backend)
+ else:
+ deepspeed.init_distributed(dist_backend=args.dist_backend)
+ return world_size, local_rank, rank
+
+
+def init_dataset_and_dataloader(args, configs):
+ train_dataset = Dataset(args.train_data, data_pipeline=configs['data_pipeline'], mode='train', shuffle=True, partition=True)
+ cv_dataset = Dataset(args.cv_data, data_pipeline=configs['data_pipeline'], mode='train', shuffle=False, partition=False)
+
+ # do not use persistent_workers=True, as whisper tokenizer opens tiktoken file each time when the for loop starts
+ train_data_loader = DataLoader(train_dataset,
+ batch_size=None,
+ pin_memory=args.pin_memory,
+ num_workers=args.num_workers,
+ prefetch_factor=args.prefetch)
+ cv_data_loader = DataLoader(cv_dataset,
+ batch_size=None,
+ pin_memory=args.pin_memory,
+ num_workers=args.num_workers,
+ prefetch_factor=args.prefetch)
+ return train_dataset, cv_dataset, train_data_loader, cv_data_loader
+
+
+
+def check_modify_and_save_config(args, configs):
+ if args.train_engine == "torch_ddp":
+ configs['train_conf']["dtype"] = 'fp32'
+ else:
+ with open(args.deepspeed_config, 'r') as fin:
+ ds_configs = json.load(fin)
+ if "fp16" in ds_configs and ds_configs["fp16"]["enabled"]:
+ configs['train_conf']["dtype"] = "fp16"
+ elif "bf16" in ds_configs and ds_configs["bf16"]["enabled"]:
+ configs['train_conf']["dtype"] = "bf16"
+ else:
+ configs['train_conf']["dtype"] = "fp32"
+ assert ds_configs["train_micro_batch_size_per_gpu"] == 1
+ # if use deepspeed, override ddp config
+ configs['train_conf']['save_per_step'] = int(configs['train_conf']['save_per_step'] * configs['train_conf']['accum_grad'] / ds_configs["gradient_accumulation_steps"])
+ configs['train_conf']['accum_grad'] = ds_configs["gradient_accumulation_steps"]
+ configs['train_conf']['grad_clip'] = ds_configs["gradient_clipping"]
+ configs['train_conf']['log_interval'] = ds_configs["steps_per_print"]
+ return configs
+
+
+def wrap_cuda_model(args, model):
+ local_world_size = int(os.environ.get('LOCAL_WORLD_SIZE', 1))
+ world_size = int(os.environ.get('WORLD_SIZE', 1))
+ if args.train_engine == "torch_ddp": # native pytorch ddp
+ assert (torch.cuda.is_available())
+ model.cuda()
+ model = torch.nn.parallel.DistributedDataParallel(model, find_unused_parameters=True)
+ else:
+ if int(os.environ.get('RANK', 0)) == 0:
+ logging.info("Estimating model states memory needs (zero2)...")
+ estimate_zero2_model_states_mem_needs_all_live(
+ model,
+ num_gpus_per_node=local_world_size,
+ num_nodes=world_size // local_world_size)
+ return model
+
+
+def init_optimizer_and_scheduler(args, configs, model):
+ if configs['train_conf']['optim'] == 'adam':
+ optimizer = optim.Adam(model.parameters(), **configs['train_conf']['optim_conf'])
+ elif configs['train_conf']['optim'] == 'adamw':
+ optimizer = optim.AdamW(model.parameters(), **configs['train_conf']['optim_conf'])
+ else:
+ raise ValueError("unknown optimizer: " + configs['train_conf'])
+
+ if configs['train_conf']['scheduler'] == 'warmuplr':
+ scheduler_type = WarmupLR
+ scheduler = WarmupLR(optimizer, **configs['train_conf']['scheduler_conf'])
+ elif configs['train_conf']['scheduler'] == 'NoamHoldAnnealing':
+ scheduler_type = NoamHoldAnnealing
+ scheduler = NoamHoldAnnealing(optimizer, **configs['train_conf']['scheduler_conf'])
+ elif configs['train_conf']['scheduler'] == 'constantlr':
+ scheduler_type = ConstantLR
+ scheduler = ConstantLR(optimizer)
+ else:
+ raise ValueError("unknown scheduler: " + configs['train_conf'])
+
+ # use deepspeed optimizer for speedup
+ if args.train_engine == "deepspeed":
+ def scheduler(opt):
+ return scheduler_type(opt, **configs['train_conf']['scheduler_conf'])
+ model, optimizer, _, scheduler = deepspeed.initialize(
+ args=args,
+ model=model,
+ optimizer=None,
+ lr_scheduler=scheduler,
+ model_parameters=model.parameters())
+
+ return model, optimizer, scheduler
+
+
+def init_summarywriter(args):
+ writer = None
+ if int(os.environ.get('RANK', 0)) == 0:
+ os.makedirs(args.model_dir, exist_ok=True)
+ writer = SummaryWriter(args.tensorboard_dir)
+ return writer
+
+
+def save_model(model, model_name, info_dict):
+ rank = int(os.environ.get('RANK', 0))
+ model_dir = info_dict["model_dir"]
+ save_model_path = os.path.join(model_dir, '{}.pt'.format(model_name))
+
+ if info_dict["train_engine"] == "torch_ddp":
+ if rank == 0:
+ torch.save(model.module.state_dict(), save_model_path)
+ else:
+ with torch.no_grad():
+ model.save_checkpoint(save_dir=model_dir,
+ tag=model_name,
+ client_state=info_dict)
+ if rank == 0:
+ info_path = re.sub('.pt$', '.yaml', save_model_path)
+ info_dict['save_time'] = datetime.datetime.now().strftime('%d/%m/%Y %H:%M:%S')
+ with open(info_path, 'w') as fout:
+ data = yaml.dump(info_dict)
+ fout.write(data)
+ logging.info('[Rank {}] Checkpoint: save to checkpoint {}'.format(rank, save_model_path))
+
+
+def cosyvoice_join(group_join, info_dict):
+ world_size = int(os.environ.get('WORLD_SIZE', 1))
+ local_rank = int(os.environ.get('LOCAL_RANK', 0))
+ rank = int(os.environ.get('RANK', 0))
+
+ if info_dict["batch_idx"] != 0:
+ # we try to join all rank in both ddp and deepspeed mode, in case different rank has different lr
+ try:
+ dist.monitored_barrier(group=group_join,
+ timeout=group_join.options._timeout)
+ return False
+ except RuntimeError as e:
+ logging.info("Detected uneven workload distribution: {}\n".format(e) +
+ "Break current worker to manually join all workers, " +
+ "world_size {}, current rank {}, current local_rank {}\n".
+ format(world_size, rank, local_rank))
+ return True
+ else:
+ return False
+
+
+def batch_forward(model, batch, info_dict):
+ device = int(os.environ.get('LOCAL_RANK', 0))
+
+ dtype = info_dict["dtype"]
+ if dtype == "fp16":
+ dtype = torch.float16
+ elif dtype == "bf16":
+ dtype = torch.bfloat16
+ else: # fp32
+ dtype = torch.float32
+
+ if info_dict['train_engine'] == 'torch_ddp':
+ autocast = nullcontext()
+ else:
+ autocast = torch.cuda.amp.autocast(enabled=True, dtype=dtype, cache_enabled=False)
+
+ with autocast:
+ info_dict['loss_dict'] = model(batch, device)
+ return info_dict
+
+
+def batch_backward(model, info_dict):
+ if info_dict["train_engine"] == "deepspeed":
+ scaled_loss = model.backward(info_dict['loss_dict']['loss'])
+ else:
+ scaled_loss = info_dict['loss_dict']['loss'] / info_dict['accum_grad']
+ scaled_loss.backward()
+
+ info_dict['loss_dict']['loss'] = scaled_loss
+ return info_dict
+
+
+def update_parameter_and_lr(model, optimizer, scheduler, info_dict):
+ grad_norm = 0.0
+ if info_dict['train_engine'] == "deepspeed":
+ info_dict["is_gradient_accumulation_boundary"] = model.is_gradient_accumulation_boundary()
+ model.step()
+ grad_norm = model.get_global_grad_norm()
+ elif (info_dict['batch_idx'] + 1) % info_dict["accum_grad"] == 0:
+ grad_norm = clip_grad_norm_(model.parameters(), info_dict['grad_clip'])
+ if torch.isfinite(grad_norm):
+ optimizer.step()
+ optimizer.zero_grad()
+ scheduler.step()
+ info_dict["lr"] = optimizer.param_groups[0]['lr']
+ info_dict["grad_norm"] = grad_norm
+ return info_dict
+
+
+def log_per_step(writer, info_dict):
+ tag = info_dict["tag"]
+ epoch = info_dict.get('epoch', 0)
+ step = info_dict["step"]
+ batch_idx = info_dict["batch_idx"]
+ loss_dict = info_dict['loss_dict']
+ rank = int(os.environ.get('RANK', 0))
+
+ # only rank 0 write to tensorboard to avoid multi-process write
+ if writer is not None:
+ if (info_dict['train_engine'] == 'deepspeed' and info_dict['is_gradient_accumulation_boundary'] is True) or \
+ (info_dict['train_engine'] == 'torch_ddp' and (info_dict['batch_idx'] + 1) % info_dict['accum_grad'] == 0):
+ for k in ['epoch', 'lr', 'grad_norm']:
+ writer.add_scalar('{}/{}'.format(tag, k), info_dict[k], step + 1)
+ for k, v in loss_dict.items():
+ writer.add_scalar('{}/{}'.format(tag, k), v, step + 1)
+
+ # TRAIN & CV, Shell log (stdout)
+ if (info_dict['batch_idx'] + 1) % info_dict['log_interval'] == 0:
+ log_str = '{} Batch {}/{} '.format(tag, epoch, batch_idx + 1)
+ for name, value in loss_dict.items():
+ log_str += '{} {:.6f} '.format(name, value)
+ if tag == "TRAIN":
+ log_str += 'lr {:.8f} grad_norm {:.6f}'.format(
+ info_dict["lr"], info_dict['grad_norm'])
+ log_str += ' rank {}'.format(rank)
+ logging.debug(log_str)
+
+
+def log_per_save(writer, info_dict):
+ tag = info_dict["tag"]
+ epoch = info_dict["epoch"]
+ step = info_dict["step"]
+ loss_dict = info_dict["loss_dict"]
+ lr = info_dict['lr']
+ rank = int(os.environ.get('RANK', 0))
+ logging.info(
+ 'Epoch {} Step {} CV info lr {} {} rank {}'.format(
+ epoch, step + 1, lr, rank, ' '.join(['{}_{}'.format(k, v) for k, v in loss_dict.items()])))
+
+ if writer is not None:
+ for k in ['epoch', 'lr']:
+ writer.add_scalar('{}/{}'.format(tag, k), info_dict[k], step + 1)
+ for k, v in loss_dict.items():
+ writer.add_scalar('{}/{}'.format(tag, k), v, step + 1)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/flow_inference.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/flow_inference.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebee05a936c6b6ce76f5ec9a6d6e26ecb847bcd9
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/flow_inference.py
@@ -0,0 +1,142 @@
+import torch
+import torchaudio
+import numpy as np
+import re
+from hyperpyyaml import load_hyperpyyaml
+import uuid
+from collections import defaultdict
+
+
+def fade_in_out(fade_in_mel, fade_out_mel, window):
+ device = fade_in_mel.device
+ fade_in_mel, fade_out_mel = fade_in_mel.cpu(), fade_out_mel.cpu()
+ mel_overlap_len = int(window.shape[0] / 2)
+ fade_in_mel[..., :mel_overlap_len] = fade_in_mel[..., :mel_overlap_len] * window[:mel_overlap_len] + \
+ fade_out_mel[..., -mel_overlap_len:] * window[mel_overlap_len:]
+ return fade_in_mel.to(device)
+
+
+class AudioDecoder:
+ def __init__(self, config_path, flow_ckpt_path, hift_ckpt_path, device="cuda"):
+ self.device = device
+
+ with open(config_path, 'r') as f:
+ self.scratch_configs = load_hyperpyyaml(f)
+
+ # Load models
+ self.flow = self.scratch_configs['flow']
+ self.flow.load_state_dict(torch.load(flow_ckpt_path, map_location=self.device))
+ self.hift = self.scratch_configs['hift']
+ self.hift.load_state_dict(torch.load(hift_ckpt_path, map_location=self.device))
+
+ # Move models to the appropriate device
+ self.flow.to(self.device)
+ self.hift.to(self.device)
+ self.mel_overlap_dict = defaultdict(lambda: None)
+ self.hift_cache_dict = defaultdict(lambda: None)
+ self.token_min_hop_len = 2 * self.flow.input_frame_rate
+ self.token_max_hop_len = 4 * self.flow.input_frame_rate
+ self.token_overlap_len = 5
+ self.mel_overlap_len = int(self.token_overlap_len / self.flow.input_frame_rate * 22050 / 256)
+ self.mel_window = np.hamming(2 * self.mel_overlap_len)
+ # hift cache
+ self.mel_cache_len = 1
+ self.source_cache_len = int(self.mel_cache_len * 256)
+ # speech fade in out
+ self.speech_window = np.hamming(2 * self.source_cache_len)
+
+ def token2wav(self, token, uuid, prompt_token=torch.zeros(1, 0, dtype=torch.int32),
+ prompt_feat=torch.zeros(1, 0, 80), embedding=torch.zeros(1, 192), finalize=False):
+ tts_mel = self.flow.inference(token=token.to(self.device),
+ token_len=torch.tensor([token.shape[1]], dtype=torch.int32).to(self.device),
+ prompt_token=prompt_token.to(self.device),
+ prompt_token_len=torch.tensor([prompt_token.shape[1]], dtype=torch.int32).to(
+ self.device),
+ prompt_feat=prompt_feat.to(self.device),
+ prompt_feat_len=torch.tensor([prompt_feat.shape[1]], dtype=torch.int32).to(
+ self.device),
+ embedding=embedding.to(self.device))
+
+ # mel overlap fade in out
+ if self.mel_overlap_dict[uuid] is not None:
+ tts_mel = fade_in_out(tts_mel, self.mel_overlap_dict[uuid], self.mel_window)
+ # append hift cache
+ if self.hift_cache_dict[uuid] is not None:
+ hift_cache_mel, hift_cache_source = self.hift_cache_dict[uuid]['mel'], self.hift_cache_dict[uuid]['source']
+ tts_mel = torch.concat([hift_cache_mel, tts_mel], dim=2)
+
+ else:
+ hift_cache_source = torch.zeros(1, 1, 0)
+ # _tts_mel=tts_mel.contiguous()
+ # keep overlap mel and hift cache
+ if finalize is False:
+ self.mel_overlap_dict[uuid] = tts_mel[:, :, -self.mel_overlap_len:]
+ tts_mel = tts_mel[:, :, :-self.mel_overlap_len]
+ tts_speech, tts_source = self.hift.inference(mel=tts_mel, cache_source=hift_cache_source)
+
+ self.hift_cache_dict[uuid] = {'mel': tts_mel[:, :, -self.mel_cache_len:],
+ 'source': tts_source[:, :, -self.source_cache_len:],
+ 'speech': tts_speech[:, -self.source_cache_len:]}
+ # if self.hift_cache_dict[uuid] is not None:
+ # tts_speech = fade_in_out(tts_speech, self.hift_cache_dict[uuid]['speech'], self.speech_window)
+ tts_speech = tts_speech[:, :-self.source_cache_len]
+
+ else:
+ tts_speech, tts_source = self.hift.inference(mel=tts_mel, cache_source=hift_cache_source)
+ del self.hift_cache_dict[uuid]
+ del self.mel_overlap_dict[uuid]
+ # if uuid in self.hift_cache_dict.keys() and self.hift_cache_dict[uuid] is not None:
+ # tts_speech = fade_in_out(tts_speech, self.hift_cache_dict[uuid]['speech'], self.speech_window)
+ return tts_speech, tts_mel
+
+ def offline_inference(self, token):
+ this_uuid = str(uuid.uuid1())
+ tts_speech, tts_mel = self.token2wav(token, uuid=this_uuid, finalize=True)
+ return tts_speech.cpu()
+
+ def stream_inference(self, token):
+ token.to(self.device)
+ this_uuid = str(uuid.uuid1())
+
+ # Prepare other necessary input tensors
+ llm_embedding = torch.zeros(1, 192).to(self.device)
+ prompt_speech_feat = torch.zeros(1, 0, 80).to(self.device)
+ flow_prompt_speech_token = torch.zeros(1, 0, dtype=torch.int32).to(self.device)
+
+ tts_speechs = []
+ tts_mels = []
+
+ block_size = self.flow.encoder.block_size
+ prev_mel = None
+
+ for idx in range(0, token.size(1), block_size):
+ # if idx>block_size: break
+ tts_token = token[:, idx:idx + block_size]
+
+ print(tts_token.size())
+
+ if prev_mel is not None:
+ prompt_speech_feat = torch.cat(tts_mels, dim=-1).transpose(1, 2)
+ flow_prompt_speech_token = token[:, :idx]
+
+ if idx + block_size >= token.size(-1):
+ is_finalize = True
+ else:
+ is_finalize = False
+
+ tts_speech, tts_mel = self.token2wav(tts_token, uuid=this_uuid,
+ prompt_token=flow_prompt_speech_token.to(self.device),
+ prompt_feat=prompt_speech_feat.to(self.device), finalize=is_finalize)
+
+ prev_mel = tts_mel
+ prev_speech = tts_speech
+ print(tts_mel.size())
+
+ tts_speechs.append(tts_speech)
+ tts_mels.append(tts_mel)
+
+ # Convert Mel spectrogram to audio using HiFi-GAN
+ tts_speech = torch.cat(tts_speechs, dim=-1).cpu()
+
+ return tts_speech.cpu()
+
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/model_server.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/model_server.py
new file mode 100644
index 0000000000000000000000000000000000000000..bbbc75ecc36be64a2876c9d0db27590da9afc646
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/model_server.py
@@ -0,0 +1,144 @@
+"""
+A model worker with transformers libs executes the model.
+
+Run BF16 inference with:
+
+python model_server.py --host localhost --model-path THUDM/glm-4-voice-9b --port 10000 --dtype bfloat16 --device cuda:0
+
+Run Int4 inference with:
+
+python model_server.py --host localhost --model-path THUDM/glm-4-voice-9b --port 10000 --dtype int4 --device cuda:0
+
+"""
+import argparse
+import json
+
+from fastapi import FastAPI, Request
+from fastapi.responses import StreamingResponse
+from transformers import AutoModel, AutoTokenizer, BitsAndBytesConfig
+from transformers.generation.streamers import BaseStreamer
+import torch
+import uvicorn
+
+from threading import Thread
+from queue import Queue
+
+
+class TokenStreamer(BaseStreamer):
+ def __init__(self, skip_prompt: bool = False, timeout=None):
+ self.skip_prompt = skip_prompt
+
+ # variables used in the streaming process
+ self.token_queue = Queue()
+ self.stop_signal = None
+ self.next_tokens_are_prompt = True
+ self.timeout = timeout
+
+ def put(self, value):
+ if len(value.shape) > 1 and value.shape[0] > 1:
+ raise ValueError("TextStreamer only supports batch size 1")
+ elif len(value.shape) > 1:
+ value = value[0]
+
+ if self.skip_prompt and self.next_tokens_are_prompt:
+ self.next_tokens_are_prompt = False
+ return
+
+ for token in value.tolist():
+ self.token_queue.put(token)
+
+ def end(self):
+ self.token_queue.put(self.stop_signal)
+
+ def __iter__(self):
+ return self
+
+ def __next__(self):
+ value = self.token_queue.get(timeout=self.timeout)
+ if value == self.stop_signal:
+ raise StopIteration()
+ else:
+ return value
+
+
+class ModelWorker:
+ def __init__(self, model_path, dtype="bfloat16", device='cuda'):
+ self.device = device
+ self.bnb_config = BitsAndBytesConfig(
+ load_in_4bit=True,
+ bnb_4bit_use_double_quant=True,
+ bnb_4bit_quant_type="nf4",
+ bnb_4bit_compute_dtype=torch.bfloat16
+ ) if dtype == "int4" else None
+
+ self.glm_model = AutoModel.from_pretrained(
+ model_path,
+ trust_remote_code=True,
+ quantization_config=self.bnb_config if self.bnb_config else None,
+ device_map={"": 0}
+ ).eval()
+ self.glm_tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+
+ @torch.inference_mode()
+ def generate_stream(self, params):
+ tokenizer, model = self.glm_tokenizer, self.glm_model
+
+ prompt = params["prompt"]
+
+ temperature = float(params.get("temperature", 1.0))
+ top_p = float(params.get("top_p", 1.0))
+ max_new_tokens = int(params.get("max_new_tokens", 256))
+
+ inputs = tokenizer([prompt], return_tensors="pt")
+ inputs = inputs.to(self.device)
+ streamer = TokenStreamer(skip_prompt=True)
+ thread = Thread(
+ target=model.generate,
+ kwargs=dict(
+ **inputs,
+ max_new_tokens=int(max_new_tokens),
+ temperature=float(temperature),
+ top_p=float(top_p),
+ streamer=streamer
+ )
+ )
+ thread.start()
+ for token_id in streamer:
+ yield (json.dumps({"token_id": token_id, "error_code": 0}) + "\n").encode()
+
+ def generate_stream_gate(self, params):
+ try:
+ for x in self.generate_stream(params):
+ yield x
+ except Exception as e:
+ print("Caught Unknown Error", e)
+ ret = {
+ "text": "Server Error",
+ "error_code": 1,
+ }
+ yield (json.dumps(ret) + "\n").encode()
+
+
+app = FastAPI()
+
+
+@app.post("/generate_stream")
+async def generate_stream(request: Request):
+ params = await request.json()
+
+ generator = worker.generate_stream_gate(params)
+ return StreamingResponse(generator)
+
+
+if __name__ == "__main__":
+ parser = argparse.ArgumentParser()
+
+ parser.add_argument("--host", type=str, default="localhost")
+ parser.add_argument("--dtype", type=str, default="bfloat16")
+ parser.add_argument("--device", type=str, default="cuda:0")
+ parser.add_argument("--port", type=int, default=10000)
+ parser.add_argument("--model-path", type=str, default="THUDM/glm-4-voice-9b")
+ args = parser.parse_args()
+
+ worker = ModelWorker(args.model_path, args.dtype, args.device)
+ uvicorn.run(app, host=args.host, port=args.port, log_level="info")
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/requirements.txt b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..12e69ee84794c421b1941139f18456798d953fb0
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/requirements.txt
@@ -0,0 +1,36 @@
+conformer==0.3.2
+deepspeed==0.14.2; sys_platform == 'linux'
+diffusers==0.27.2
+fastapi==0.115.3
+fastapi-cli==0.0.4
+gdown==5.1.0
+gradio==5.3.0
+grpcio==1.57.0
+grpcio-tools==1.57.0
+huggingface_hub==0.25.2
+hydra-core==1.3.2
+HyperPyYAML==1.2.2
+inflect==7.3.1
+librosa==0.10.2
+lightning==2.2.4
+matplotlib==3.7.5
+modelscope==1.15.0
+networkx==3.1
+numpy==1.24.4
+omegaconf==2.3.0
+onnxruntime-gpu==1.16.0; sys_platform == 'linux'
+onnxruntime==1.16.0; sys_platform == 'darwin' or sys_platform == 'windows'
+openai-whisper==20231117
+protobuf==4.25
+pydantic==2.7.0
+rich==13.7.1
+Requests==2.32.3
+safetensors==0.4.5
+soundfile==0.12.1
+tensorboard==2.14.0
+transformers==4.44.1
+uvicorn==0.32.0
+wget==3.2
+WeTextProcessing==1.0.3
+torch==2.3.0
+torchaudio==2.3.0
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/__init__.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/configuration_whisper.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/configuration_whisper.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ee76eeae2921fa2c8665a926f957e238807c32e
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/configuration_whisper.py
@@ -0,0 +1,37 @@
+from transformers import WhisperConfig
+
+
+class WhisperVQConfig(WhisperConfig):
+ def __init__(self,
+ pooling_kernel_size=None,
+ pooling_type="max",
+ pooling_position=0,
+ quantize_vocab_size=None,
+ quantize_position=16,
+ quantize_commit_coefficient=0.25,
+ quantize_loss_scale=1.0,
+ quantize_ema_decay=None,
+ quantize_restart_interval=None,
+ quantize_encoder_only=False,
+ quantize_causal_encoder=False,
+ quantize_causal_block_size=None,
+ skip_language_detection=False,
+ encoder_causal_attention=False,
+ encoder_causal_convolution=False,
+ **kwargs):
+ self.pooling_kernel_size = pooling_kernel_size
+ self.pooling_type = pooling_type
+ self.pooling_position = pooling_position
+ self.quantize_vocab_size = quantize_vocab_size
+ self.quantize_position = quantize_position
+ self.quantize_commit_coefficient = quantize_commit_coefficient
+ self.quantize_loss_scale = quantize_loss_scale
+ self.quantize_ema_decay = quantize_ema_decay
+ self.quantize_restart_interval = quantize_restart_interval
+ self.quantize_encoder_only = quantize_encoder_only
+ self.quantize_causal_encoder = quantize_causal_encoder
+ self.quantize_causal_block_size = quantize_causal_block_size
+ self.skip_language_detection = skip_language_detection
+ self.encoder_causal_attention = encoder_causal_attention
+ self.encoder_causal_convolution = encoder_causal_convolution
+ super().__init__(**kwargs)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/generation_whisper.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/generation_whisper.py
new file mode 100644
index 0000000000000000000000000000000000000000..7141ba72f7d7e7928318378f06d675607692f267
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/generation_whisper.py
@@ -0,0 +1,1828 @@
+# coding=utf-8
+# Copyright 2024 The HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import copy
+import math
+import warnings
+import zlib
+from typing import Callable, Iterator, List, Optional, Tuple, Union
+
+import numpy as np
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from transformers.cache_utils import EncoderDecoderCache
+
+from transformers.generation.configuration_utils import GenerationConfig
+from transformers.generation.logits_process import (
+ LogitsProcessorList,
+ SuppressTokensAtBeginLogitsProcessor,
+ SuppressTokensLogitsProcessor,
+ WhisperNoSpeechDetection,
+ WhisperTimeStampLogitsProcessor,
+)
+from transformers.generation.stopping_criteria import StoppingCriteriaList
+from transformers.modeling_outputs import BaseModelOutput
+from transformers.utils import logging
+from transformers.models.whisper.tokenization_whisper import TASK_IDS, TO_LANGUAGE_CODE
+
+
+logger = logging.get_logger(__name__)
+
+
+def _median_filter(inputs: torch.Tensor, filter_width: int) -> torch.Tensor:
+ """
+ Applies a median filter of width `filter_width` along the last dimension of the input.
+
+ The `inputs` tensor is assumed to be 3- or 4-dimensional.
+ """
+ if filter_width <= 0 or filter_width % 2 != 1:
+ raise ValueError("`filter_width` should be an odd number")
+
+ pad_width = filter_width // 2
+ if inputs.shape[-1] <= pad_width:
+ return inputs
+
+ # Pad the left and right edges.
+ inputs = nn.functional.pad(inputs, (pad_width, pad_width, 0, 0), mode="reflect")
+
+ # sort() is faster than torch.median (https://github.com/pytorch/pytorch/issues/51450)
+ result = inputs.unfold(-1, filter_width, 1).sort()[0][..., pad_width]
+ return result
+
+
+def _dynamic_time_warping(matrix: np.ndarray):
+ """
+ Measures similarity between two temporal sequences: the input audio and the output tokens. Used to generate
+ token-level timestamps.
+ """
+ output_length, input_length = matrix.shape
+ cost = np.ones((output_length + 1, input_length + 1), dtype=np.float32) * np.inf
+ trace = -np.ones((output_length + 1, input_length + 1), dtype=np.float32)
+
+ cost[0, 0] = 0
+ for j in range(1, input_length + 1):
+ for i in range(1, output_length + 1):
+ c0 = cost[i - 1, j - 1]
+ c1 = cost[i - 1, j]
+ c2 = cost[i, j - 1]
+
+ if c0 < c1 and c0 < c2:
+ c, t = c0, 0
+ elif c1 < c0 and c1 < c2:
+ c, t = c1, 1
+ else:
+ c, t = c2, 2
+
+ cost[i, j] = matrix[i - 1, j - 1] + c
+ trace[i, j] = t
+
+ # backtrace
+ i = trace.shape[0] - 1
+ j = trace.shape[1] - 1
+ trace[0, :] = 2
+ trace[:, 0] = 1
+
+ text_indices = []
+ time_indices = []
+ while i > 0 or j > 0:
+ text_indices.append(i - 1)
+ time_indices.append(j - 1)
+ if trace[i, j] == 0:
+ i -= 1
+ j -= 1
+ elif trace[i, j] == 1:
+ i -= 1
+ elif trace[i, j] == 2:
+ j -= 1
+ else:
+ raise RuntimeError(
+ f"Internal error in dynamic time warping. Unexpected trace[{i}, {j}]. Please file a bug report."
+ )
+
+ text_indices = np.array(text_indices)[::-1]
+ time_indices = np.array(time_indices)[::-1]
+ return text_indices, time_indices
+
+
+def _get_attr_from_logit_processors(logits_processor, logit_processor_class, attribute_name):
+ if logits_processor is not None:
+ logit_processor = next((cls for cls in logits_processor if isinstance(cls, logit_processor_class)), None)
+ if logit_processor:
+ return getattr(logit_processor, attribute_name, None)
+ return None
+
+
+def _pad_to_max_length(
+ current_segments,
+ pad_token_id,
+ device,
+ padding_side="right",
+ padding="longest",
+ bos_token_tensor=None,
+ cut_off_length=None,
+):
+ max_total_length = 0
+ sequences = []
+
+ if padding_side not in ["right", "left"]:
+ raise ValueError(f"`padding_side` must be either 'right' or 'left', not {padding_side}")
+
+ if padding not in ["longest", "max_length"]:
+ raise ValueError(f"`padding` must be either 'longest' or 'max_length', not {padding}")
+ elif padding == "max_length" and cut_off_length is None:
+ raise ValueError("`cut_off_length` must be specified when `padding='max_length'`")
+
+ for current_segment_list in current_segments:
+ if current_segment_list is not None and len([d["tokens"] for d in current_segment_list]) > 0:
+ sequence = torch.cat([d["tokens"] for d in current_segment_list], dim=-1)
+
+ if cut_off_length is not None:
+ sequence = sequence[-cut_off_length:]
+
+ if bos_token_tensor is not None:
+ sequence = torch.cat([bos_token_tensor, sequence])
+
+ sequences.append(sequence)
+ max_total_length = max(max_total_length, len(sequences[-1]))
+ elif bos_token_tensor is not None:
+ sequences.append(bos_token_tensor)
+ else:
+ sequences.append(torch.tensor([], device=device))
+
+ max_total_length = cut_off_length + 1 if padding == "max_length" else max_total_length
+ for i in range(len(current_segments)):
+ pad_length = max_total_length - len(sequences[i])
+ pad = (0, pad_length) if padding_side == "right" else (pad_length, 0)
+ sequences[i] = F.pad(sequences[i], pad=pad, value=pad_token_id)
+
+ sequences = torch.stack(sequences, dim=0)
+ return sequences
+
+
+class WhisperGenerationMixin:
+ def _extract_token_timestamps(self, generate_outputs, alignment_heads, time_precision=0.02, num_frames=None):
+ """
+ Calculates token-level timestamps using the encoder-decoder cross-attentions and dynamic time-warping (DTW) to
+ map each output token to a position in the input audio. If `num_frames` is specified, the encoder-decoder
+ cross-attentions will be cropped before applying DTW.
+
+ Returns:
+ tensor containing the timestamps in seconds for each predicted token
+ """
+ # Create a list with `decoder_layers` elements, each a tensor of shape
+ # (batch size, attention_heads, output length, input length).
+ cross_attentions = []
+ for i in range(self.config.decoder_layers):
+ cross_attentions.append(torch.cat([x[i] for x in generate_outputs.cross_attentions], dim=2))
+
+ # Select specific cross-attention layers and heads. This is a tensor
+ # of shape (batch size, num selected, output length, input length).
+ weights = torch.stack([cross_attentions[l][:, h] for l, h in alignment_heads])
+ weights = weights.permute([1, 0, 2, 3])
+
+ weight_length = None
+
+ if "beam_indices" in generate_outputs:
+ # If beam search has been used, the output sequences may have been generated for more timesteps than their sequence_lengths
+ # since the beam search strategy chooses the most probable sequences at the end of the search.
+ # In that case, the cross_attentions weights are too long and we have to make sure that they have the right output_length
+ weight_length = (generate_outputs.beam_indices != -1).sum(-1).max()
+ weights = weights[:, :, :weight_length]
+
+ # If beam index is still -1, it means that the associated token id is EOS
+ # We need to replace the index with 0 since index_select gives an error if any of the indexes is -1.
+ beam_indices = generate_outputs.beam_indices[:, :weight_length]
+ beam_indices = beam_indices.masked_fill(beam_indices == -1, 0)
+
+ # Select the cross attention from the right beam for each output sequences
+ weights = torch.stack(
+ [
+ torch.index_select(weights[:, :, i, :], dim=0, index=beam_indices[:, i])
+ for i in range(beam_indices.shape[1])
+ ],
+ dim=2,
+ )
+
+ # make sure timestamps are as long as weights
+ input_length = weight_length or cross_attentions[0].shape[2]
+ timestamps = torch.zeros_like(generate_outputs.sequences, dtype=torch.float32)[:, : input_length + 1]
+ batch_size = timestamps.shape[0]
+
+ if num_frames is not None:
+ # two cases:
+ # 1. num_frames is the same for each sample -> compute the DTW matrix for each sample in parallel
+ # 2. num_frames is different, compute the DTW matrix for each sample sequentially
+
+ # we're using np.unique because num_frames can be int/list/tuple
+ if isinstance(num_frames, int):
+ weights = weights[..., : num_frames // 2]
+
+ elif isinstance(num_frames, (list, tuple, np.ndarray)) and len(np.unique(num_frames)) == 1:
+ weights = weights[..., : num_frames[0] // 2]
+
+ elif isinstance(num_frames, (torch.Tensor)) and len(torch.unique(num_frames)) == 1:
+ weights = weights[..., : num_frames[0] // 2]
+
+ else:
+ # num_frames is of shape (batch_size,) whereas batch_size is truely batch_size*num_return_sequences
+ repeat_time = batch_size if isinstance(num_frames, int) else batch_size // len(num_frames)
+ num_frames = np.repeat(num_frames, repeat_time)
+
+ if num_frames is None or isinstance(num_frames, int):
+ # Normalize and smoothen the weights.
+ std = torch.std(weights, dim=-2, keepdim=True, unbiased=False)
+ mean = torch.mean(weights, dim=-2, keepdim=True)
+ weights = (weights - mean) / std
+ weights = _median_filter(weights, self.config.median_filter_width)
+
+ # Average the different cross-attention heads.
+ weights = weights.mean(dim=1)
+
+ # Perform dynamic time warping on each element of the batch.
+ for batch_idx in range(batch_size):
+ if num_frames is not None and isinstance(num_frames, (tuple, list, np.ndarray, torch.Tensor)):
+ matrix = weights[batch_idx, ..., : num_frames[batch_idx] // 2]
+
+ # Normalize and smoothen the weights.
+ std = torch.std(matrix, dim=-2, keepdim=True, unbiased=False)
+ mean = torch.mean(matrix, dim=-2, keepdim=True)
+ matrix = (matrix - mean) / std
+ matrix = _median_filter(matrix, self.config.median_filter_width)
+
+ # Average the different cross-attention heads.
+ matrix = matrix.mean(dim=0)
+ else:
+ matrix = weights[batch_idx]
+
+ text_indices, time_indices = _dynamic_time_warping(-matrix.cpu().double().numpy())
+ jumps = np.pad(np.diff(text_indices), (1, 0), constant_values=1).astype(bool)
+ jump_times = time_indices[jumps] * time_precision
+ timestamps[batch_idx, 1:] = torch.tensor(jump_times)
+
+ return timestamps
+
+ def generate(
+ self,
+ input_features: Optional[torch.Tensor] = None,
+ generation_config: Optional[GenerationConfig] = None,
+ logits_processor: Optional[LogitsProcessorList] = None,
+ stopping_criteria: Optional[StoppingCriteriaList] = None,
+ prefix_allowed_tokens_fn: Optional[Callable[[int, torch.Tensor], List[int]]] = None,
+ synced_gpus: bool = False,
+ return_timestamps: Optional[bool] = None,
+ task: Optional[str] = None,
+ language: Optional[Union[str, List[str]]] = None,
+ is_multilingual: Optional[bool] = None,
+ prompt_ids: Optional[torch.Tensor] = None,
+ prompt_condition_type: Optional[str] = None, # first-segment, all-segments
+ condition_on_prev_tokens: Optional[bool] = None,
+ temperature: Optional[Union[float, Tuple[float, ...]]] = None,
+ compression_ratio_threshold: Optional[float] = None,
+ logprob_threshold: Optional[float] = None,
+ no_speech_threshold: Optional[float] = None,
+ num_segment_frames: Optional[int] = None,
+ attention_mask: Optional[torch.Tensor] = None,
+ time_precision: float = 0.02,
+ return_token_timestamps: Optional[bool] = None,
+ return_segments: bool = False,
+ return_dict_in_generate: Optional[bool] = None,
+ **kwargs,
+ ):
+ """
+ Transcribes or translates log-mel input features to a sequence of auto-regressively generated token ids.
+
+
+
+ Most generation-controlling parameters are set in `generation_config` which, if not passed, will be set to the
+ model's default generation configuration. You can override any `generation_config` by passing the corresponding
+ parameters to generate(), e.g. `.generate(inputs, num_beams=4, do_sample=True)`.
+
+ For an overview of generation strategies and code examples, check out the [following
+ guide](./generation_strategies).
+
+
+
+ Parameters:
+ input_features (`torch.Tensor` of shape `(batch_size, feature_size, sequence_length)`, *optional*):
+ Float values of log-mel features extracted from the raw speech waveform. The raw speech waveform can be obtained by
+ loading a `.flac` or `.wav` audio file into an array of type `List[float]` or a `numpy.ndarray`, *e.g.* via
+ the soundfile library (`pip install soundfile`). To prepare the array into `input_features`, the
+ [`AutoFeatureExtractor`] should be used for extracting the mel features, padding and conversion into a
+ tensor of type `torch.FloatTensor`. See [`~WhisperFeatureExtractor.__call__`] for details.
+ generation_config (`~generation.GenerationConfig`, *optional*):
+ The generation configuration to be used as base parametrization for the generation call. `**kwargs`
+ passed to generate matching the attributes of `generation_config` will override them. If
+ `generation_config` is not provided, the default will be used, which had the following loading
+ priority: 1) from the `generation_config.json` model file, if it exists; 2) from the model
+ configuration. Please note that unspecified parameters will inherit [`~generation.GenerationConfig`]'s
+ default values, whose documentation should be checked to parameterize generation.
+ logits_processor (`LogitsProcessorList`, *optional*):
+ Custom logits processors that complement the default logits processors built from arguments and
+ generation config. If a logit processor is passed that is already created with the arguments or a
+ generation config an error is thrown. This feature is intended for advanced users.
+ stopping_criteria (`StoppingCriteriaList`, *optional*):
+ Custom stopping criteria that complement the default stopping criteria built from arguments and a
+ generation config. If a stopping criteria is passed that is already created with the arguments or a
+ generation config an error is thrown. This feature is intended for advanced users.
+ prefix_allowed_tokens_fn (`Callable[[int, torch.Tensor], List[int]]`, *optional*):
+ If provided, this function constraints the beam search to allowed tokens only at each step. If not
+ provided no constraint is applied. This function takes 2 arguments: the batch ID `batch_id` and
+ `input_ids`. It has to return a list with the allowed tokens for the next generation step conditioned
+ on the batch ID `batch_id` and the previously generated tokens `inputs_ids`. This argument is useful
+ for constrained generation conditioned on the prefix, as described in [Autoregressive Entity
+ Retrieval](https://arxiv.org/abs/2010.00904).
+ synced_gpus (`bool`, *optional*, defaults to `False`):
+ Whether to continue running the while loop until max_length (needed for ZeRO stage 3)
+ return_timestamps (`bool`, *optional*):
+ Whether to return the timestamps with the text. This enables the `WhisperTimestampsLogitsProcessor`.
+ task (`str`, *optional*):
+ Task to use for generation, either "translate" or "transcribe". The `model.config.forced_decoder_ids`
+ will be updated accordingly.
+ language (`str` or list of `str`, *optional*):
+ Language token to use for generation, can be either in the form of `<|en|>`, `en` or `english`. For
+ batched generation, a list of language tokens can be passed. You can find all the possible language
+ tokens in the `model.generation_config.lang_to_id` dictionary.
+ is_multilingual (`bool`, *optional*):
+ Whether or not the model is multilingual.
+ prompt_ids (`torch.Tensor`, *optional*):
+ Rank-1 tensor of token IDs created by passing text to [`~WhisperProcessor.get_prompt_ids`] that is
+ provided as a prompt to each chunk. This can be used to provide or "prompt-engineer" a context for
+ transcription, e.g. custom vocabularies or proper nouns to make it more likely to predict those words
+ correctly. It cannot be used in conjunction with `decoder_start_token_id` as it overwrites this value.
+ prompt_condition_type (`str`, *optional*):
+ Only relevant for long-form transcription. Condition type of `prompt_ids`. 'first-segment' means only the first segment is conditioned on `prompt_ids`. 'all-segments' means each segment is conditioned on `prompt_ids`. Make sure to enable `condition_on_prev_tokens` for 'all-segments'.
+ Defaults to 'first-segment'. For short-term transcription only 'first-segment' is possible.
+ condition_on_prev_tokens (`bool`, *optional*):
+ Only relevant for long-form transcription. Whether to condition each segment on the previous segment.
+ As shown in the [the Whisper paper](https://cdn.openai.com/papers/whisper.pdf), this can help to improve
+ performance.
+ temperature (`float` or list of `float`, *optional*):
+ The temperature to be used for generation. Passing a single `float` value and `do_sample=True` activates
+ generation using sampling. For long-form transcription, temperature fallback can be activated by passing
+ a list of float values such as (0.0, 0.2, 0.4, 0.6, 0.8, 1.0). As shown in the [the Whisper paper](https://cdn.openai.com/papers/whisper.pdf), this can help to improve
+ performance.
+ compression_ratio_threshold (`float`, *optional*):
+ Only relevant for long-form transcription. If defined, the zlib compression rate of each segment will be computed. If the compression rate of
+ a segment is higher than `compression_ratio_threshold`, temperature fallback is activated: the generated segment is discarded and the generation is
+ repeated using a higher temperature. The intuition behind this feature is that segments with very high compression rates
+ suffer from a lot of repetition. The unwanted repetition can be reduced by injecting more randomness by increasing the temperature. If `compression_ratio_threshold` is defined
+ make sure that `temperature` is a list of values. A common value for `compression_ratio_threshold` is 1.35.
+ As shown in the [the Whisper paper](https://cdn.openai.com/papers/whisper.pdf), this can help to improve
+ performance.
+ logprob_threshold (`float`, *optional*):
+ Only relevant for long-form transcription. If defined, the average log-probability of each segment will be computed. If the log-probability of
+ a given segment is lower than `logprob_threshold`, temperature fallback is activated: the generated segment is discarded and the generation is
+ repeated using a higher temperature. The intuition behind this feature is that segments of low log-probability
+ can be improved by injecting more randomness by increasing the temperature. If `logprob_threshold` is defined
+ make sure that `temperature` is a list of values. A common value for `logprob_threshold` is -1.0.
+ As shown in the [the Whisper paper](https://cdn.openai.com/papers/whisper.pdf), this can help to improve
+ performance.
+ no_speech_threshold (`float`, *optional*):
+ Only relevant for long-form transcription. If defined, the "no-speech" token combined with the `logprob_threshold`
+ is used to determine whether a segment contains only silence. In this case, the transcription for this segment
+ is skipped.
+ As shown in the [the Whisper paper](https://cdn.openai.com/papers/whisper.pdf), this can help to improve
+ performance.
+ num_segment_frames (`int`, *optional*):
+ The number of frames a single segment is made of. If not defined, `num_segment_frames` defaults to the model's stride
+ times the maximum input length.
+ attention_mask (`torch.Tensor`, *optional*):
+ `attention_mask` needs to be passed when doing long-form transcription using a batch size > 1.
+ time_precision (`int`, *optional*, defaults to 0.02):
+ The duration of output token in seconds. *E.g.* 0.02 means that a generated token on average accounts
+ for 20 ms.
+ return_token_timestamps (`bool`, *optional*):
+ Whether to return token-level timestamps with the text. This can be used with or without the
+ `return_timestamps` option. To get word-level timestamps, use the tokenizer to group the tokens into
+ words.
+ return_segments (`bool`, *optional*, defaults to `False`):
+ Whether to additionally return a list of all segments. Note that this option can only be enabled
+ when doing long-form transcription.
+ return_dict_in_generate (`bool`, *optional*, defaults to `False`):
+ Whether or not to return a [`~utils.ModelOutput`] instead of just returning the generated tokens.
+ Note that when doing long-form transcription, `return_dict_in_generate` can only be enabled when
+ `return_segments` is set True. In this case the generation outputs of each segment is added to each
+ segment.
+ kwargs (`Dict[str, Any]`, *optional*):
+ Ad hoc parametrization of `generate_config` and/or additional model-specific kwargs that will be
+ forwarded to the `forward` function of the model. If the model is an encoder-decoder model, encoder
+ specific kwargs should not be prefixed and decoder specific kwargs should be prefixed with *decoder_*.
+
+ Return:
+ [`~utils.ModelOutput`] or `torch.LongTensor` or `Dict[str, Any]`: A [`~utils.ModelOutput`] (if `return_dict_in_generate=True`
+ or when `config.return_dict_in_generate=True`) or a `torch.FloatTensor` or a dict of segments when `return_segments=True`.
+
+ If the passed input is > 30 seconds / > 3000 mel input features and `return_segments=True` then a dictionary of generated sequence ids, called `sequences` and a list of each generated segment is returned.
+
+ else if the passed input is <= 30 seconds / >= 3000 mel input features, the possible [`~utils.ModelOutput`] types are:
+
+ - [`~generation.GenerateEncoderDecoderOutput`],
+ - [`~generation.GenerateBeamEncoderDecoderOutput`]
+
+ else only the generated output sequence ids are returned.
+
+ Example:
+
+ - *Longform transcription*: To transcribe or translate audios longer than 30 seconds, process the audio files without truncation and pass all mel features at once to generate.
+
+ ```python
+ >>> import torch
+ >>> from transformers import AutoProcessor, WhisperForConditionalGeneration
+ >>> from datasets import load_dataset, Audio
+
+ >>> processor = AutoProcessor.from_pretrained("openai/whisper-tiny.en")
+ >>> model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
+ >>> model.cuda() # doctest: +IGNORE_RESULT
+
+ >>> # load audios > 30 seconds
+ >>> ds = load_dataset("distil-whisper/meanwhile", "default")["test"]
+ >>> # resample to 16kHz
+ >>> ds = ds.cast_column("audio", Audio(sampling_rate=16000))
+ >>> # take first 8 audios and retrieve array
+ >>> audio = ds[:8]["audio"]
+ >>> audio = [x["array"] for x in audio]
+
+ >>> # make sure to NOT truncate the input audio, to return the `attention_mask` and to pad to the longest audio
+ >>> inputs = processor(audio, return_tensors="pt", truncation=False, padding="longest", return_attention_mask=True, sampling_rate=16_000)
+ >>> inputs = inputs.to("cuda", torch.float32)
+
+ >>> # transcribe audio to ids
+ >>> generated_ids = model.generate(**inputs)
+
+ >>> transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)
+ >>> transcription[0]
+ " Folks, if you watch the show, you know, I spent a lot of time right over there. Patiently and astutely scrutinizing the boxwood and mahogany chest set of the day's biggest stories developing the central headline pawns, definitely maneuvering an oso topical night to F6, fainting a classic Sicilian, nade door variation on the news, all the while seeing eight moves deep and patiently marshalling the latest press releases into a fisher's shows in Lip Nitsky attack that culminates in the elegant lethal slow-played, all-passant checkmate that is my nightly monologue. But sometimes, sometimes, folks, I. CHEERING AND APPLAUSE Sometimes I startle away, cubside down in the monkey bars of a condemned playground on a super fun site. Get all hept up on goofballs. Rummage that were discarded tag bag of defective toys. Yank out a fist bowl of disembodied doll limbs, toss them on a stained kid's place mat from a defunct dennies. set up a table inside a rusty cargo container down by the Wharf and challenged toothless drifters to the godless bughouse blitz of tournament that is my segment. Meanwhile."
+ ```
+
+ - *Shortform transcription*: If passed mel input features are < 30 seconds, the whole audio will be transcribed with a single call to generate.
+
+ ```python
+ >>> import torch
+ >>> from transformers import AutoProcessor, WhisperForConditionalGeneration
+ >>> from datasets import load_dataset
+
+ >>> processor = AutoProcessor.from_pretrained("openai/whisper-tiny.en")
+ >>> model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
+
+ >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
+
+ >>> inputs = processor(ds[0]["audio"]["array"], return_tensors="pt")
+ >>> input_features = inputs.input_features
+
+ >>> generated_ids = model.generate(inputs=input_features)
+
+ >>> transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+ >>> transcription
+ ' Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel.'
+ ```
+
+ """
+ # 0. deprecate old inputs
+ if "inputs" in kwargs:
+ input_features = kwargs.pop("inputs")
+ warnings.warn(
+ "The input name `inputs` is deprecated. Please make sure to use `input_features` instead.",
+ FutureWarning,
+ )
+
+ # 1. prepare generation config
+ generation_config, kwargs = self._prepare_generation_config(generation_config, **kwargs)
+
+ # 2. set global generate variables
+ input_stride = self.model.encoder.conv1.stride[0] * self.model.encoder.conv2.stride[0]
+ num_segment_frames = input_stride * self.config.max_source_positions
+ batch_size, total_input_frames = self._retrieve_total_input_frames(
+ input_features=input_features, input_stride=input_stride, kwargs=kwargs
+ )
+ is_shortform = total_input_frames <= num_segment_frames
+
+ # 3. Make sure generation config is correctly set
+ # Make sure the generation config is correctly set depending on whether timestamps are to be returned or not
+ return_dict_in_generate = self._set_return_outputs(
+ return_dict_in_generate=return_dict_in_generate,
+ return_token_timestamps=return_token_timestamps,
+ logprob_threshold=logprob_threshold,
+ generation_config=generation_config,
+ )
+ timestamp_begin = self._set_return_timestamps(
+ return_timestamps=return_timestamps, is_shortform=is_shortform, generation_config=generation_config
+ )
+ self._set_language_and_task(
+ language=language, task=task, is_multilingual=is_multilingual, generation_config=generation_config
+ )
+ self._set_num_frames(
+ return_token_timestamps=return_token_timestamps, generation_config=generation_config, kwargs=kwargs
+ )
+ self._set_thresholds_and_condition(
+ generation_config=generation_config,
+ logprob_threshold=logprob_threshold,
+ compression_ratio_threshold=compression_ratio_threshold,
+ no_speech_threshold=no_speech_threshold,
+ condition_on_prev_tokens=condition_on_prev_tokens,
+ )
+ self._set_prompt_condition_type(
+ generation_config=generation_config,
+ prompt_condition_type=prompt_condition_type,
+ )
+
+ kwargs["attention_mask"] = attention_mask
+ # pass self.config for backward compatibility
+ init_tokens = self._retrieve_init_tokens(
+ input_features,
+ batch_size=batch_size,
+ generation_config=generation_config,
+ config=self.config,
+ num_segment_frames=num_segment_frames,
+ kwargs=kwargs,
+ )
+ # passing `decoder_input_ids` is deprecated - the only exception is for assisted generation
+ # where the input ids are handled explicitly by the generate method
+ self._check_decoder_input_ids(kwargs=kwargs)
+
+ # 3. Retrieve logits processors
+ device = kwargs["encoder_outputs"][0].device if "encoder_outputs" in kwargs else input_features.device
+ begin_index = init_tokens.shape[1]
+ logits_processor = self._retrieve_logit_processors(
+ generation_config=generation_config,
+ logits_processor=logits_processor,
+ begin_index=begin_index, # begin index is index of first generated decoder token
+ num_beams=kwargs.get("num_beams", 1),
+ device=device,
+ )
+
+ # 4 Set and retrieve global generation variables
+ self._set_condition_on_prev_tokens(
+ condition_on_prev_tokens=condition_on_prev_tokens, generation_config=generation_config
+ )
+
+ temperatures = [temperature] if not isinstance(temperature, (list, tuple)) else temperature
+ temperature = temperatures[0]
+
+ max_frames, seek = self._retrieve_max_frames_and_seek(
+ batch_size=batch_size,
+ attention_mask=attention_mask,
+ total_input_frames=total_input_frames,
+ is_shortform=is_shortform,
+ )
+
+ # 5 Prepare running variables, list for generation
+ num_return_sequences = generation_config.num_return_sequences
+ (
+ batch_idx_map,
+ cur_bsz,
+ input_features,
+ seek,
+ max_frames,
+ init_tokens,
+ do_condition_on_prev_tokens,
+ ) = self._expand_variables_for_generation(
+ input_features=input_features,
+ seek=seek,
+ max_frames=max_frames,
+ init_tokens=init_tokens,
+ batch_size=batch_size,
+ condition_on_prev_tokens=condition_on_prev_tokens,
+ generation_config=generation_config,
+ )
+
+ current_segments = self._prepare_segments(
+ prompt_ids=prompt_ids,
+ batch_size=cur_bsz,
+ generation_config=generation_config,
+ )
+
+ # 6 Transcribe audio until we reach the end of all input audios
+ while (seek < max_frames).any():
+ # 6.1 NOTE: When in longform transcription mode and batch size > 1 we need to dynamically reduce the batch size during the loop
+ # in case one audio finished earlier than another one. Thus, we need to keep a table of "previous-index-2-current-index" in order
+ # to know which original audio is being decoded
+ # Set updated index map, duration of previously decoded chunks and number of max frames of current decoding chunk
+ input_features, cur_bsz, batch_idx_map = self._maybe_reduce_batch(
+ input_features=input_features,
+ seek=seek,
+ max_frames=max_frames,
+ cur_bsz=cur_bsz,
+ batch_idx_map=batch_idx_map,
+ )
+ time_offset = seek * time_precision / input_stride
+ seek_num_frames = (max_frames - seek).clamp(max=num_segment_frames)
+
+ # 6.2 cut out next 30s segment from input features
+ segment_input = self._get_input_segment(
+ input_features=input_features,
+ seek=seek,
+ seek_num_frames=seek_num_frames,
+ num_segment_frames=num_segment_frames,
+ cur_bsz=cur_bsz,
+ batch_idx_map=batch_idx_map,
+ )
+
+ # 6.3 prepare decoder input ids
+ suppress_tokens = _get_attr_from_logit_processors(
+ logits_processor, SuppressTokensLogitsProcessor, "suppress_tokens"
+ )
+
+ decoder_input_ids, kwargs = self._prepare_decoder_input_ids(
+ cur_bsz=cur_bsz,
+ init_tokens=init_tokens,
+ current_segments=current_segments,
+ batch_idx_map=batch_idx_map,
+ do_condition_on_prev_tokens=do_condition_on_prev_tokens,
+ prompt_ids=prompt_ids,
+ generation_config=generation_config,
+ config=self.config,
+ device=init_tokens.device,
+ suppress_tokens=suppress_tokens,
+ kwargs=kwargs,
+ )
+
+ # 6.4 set max new tokens or max length
+ self._set_max_new_tokens_and_length(
+ config=self.config,
+ decoder_input_ids=decoder_input_ids,
+ generation_config=generation_config,
+ )
+
+ # 6.5 Set current `begin_index` for all logit processors
+ if logits_processor is not None:
+ for proc in logits_processor:
+ if hasattr(proc, "set_begin_index"):
+ proc.set_begin_index(decoder_input_ids.shape[-1])
+
+ # 6.6 Run generate with fallback
+ (
+ seek_sequences,
+ seek_outputs,
+ should_skip,
+ do_condition_on_prev_tokens,
+ model_output_type,
+ ) = self.generate_with_fallback(
+ segment_input=segment_input,
+ decoder_input_ids=decoder_input_ids,
+ cur_bsz=cur_bsz,
+ batch_idx_map=batch_idx_map,
+ seek=seek,
+ num_segment_frames=num_segment_frames,
+ max_frames=max_frames,
+ temperatures=temperatures,
+ generation_config=generation_config,
+ logits_processor=logits_processor,
+ stopping_criteria=stopping_criteria,
+ prefix_allowed_tokens_fn=prefix_allowed_tokens_fn,
+ synced_gpus=synced_gpus,
+ return_token_timestamps=return_token_timestamps,
+ do_condition_on_prev_tokens=do_condition_on_prev_tokens,
+ is_shortform=is_shortform,
+ batch_size=batch_size,
+ kwargs=kwargs,
+ )
+
+ # 6.7 In every generated sequence, split by timestamp tokens and extract segments
+ for i, seek_sequence in enumerate(seek_sequences):
+ prev_i = batch_idx_map[i]
+
+ if should_skip[i]:
+ seek[prev_i] += seek_num_frames[prev_i]
+ continue
+
+ segments, segment_offset = self._retrieve_segment(
+ seek_sequence=seek_sequence,
+ seek_outputs=seek_outputs,
+ time_offset=time_offset,
+ timestamp_begin=timestamp_begin,
+ seek_num_frames=seek_num_frames,
+ time_precision=time_precision,
+ input_stride=input_stride,
+ prev_idx=prev_i,
+ idx=i,
+ return_token_timestamps=return_token_timestamps,
+ )
+
+ current_segments[prev_i] += segments
+
+ if is_shortform:
+ seek[prev_i] += max_frames[i]
+ else:
+ seek[prev_i] += segment_offset
+
+ # 7. Once all segments are added to the list of all segments, called `current_segments`, we extract the predicted
+ # output tokens from the list of dicts. If we use batch size > 1, we make sure to pad the output
+ final_segments = (
+ [x[1:] for x in current_segments]
+ if (prompt_ids is not None and generation_config.prompt_condition_type == "first-segment")
+ else current_segments
+ )
+
+ sequences = _pad_to_max_length(
+ final_segments, generation_config.pad_token_id, device=self.device, padding_side="right"
+ )
+
+ # 8. If we return all segments, the predicted output sequences are put under `"sequences"`.
+ if return_segments:
+ return {"sequences": sequences, "segments": final_segments}
+
+ if is_shortform:
+ # add eos token:
+ if generation_config.max_new_tokens is None and generation_config.max_length is None:
+ eos_tokens = torch.full((sequences.shape[0], 1), generation_config.eos_token_id)
+ sequences = torch.cat([sequences, eos_tokens], dim=-1)
+
+ if return_token_timestamps:
+ outputs = {}
+ outputs["sequences"] = sequences
+ outputs["token_timestamps"] = torch.stack([d["token_timestamps"] for d in seek_outputs], dim=0)
+ else:
+ outputs = sequences
+
+ if return_dict_in_generate and generation_config.return_dict_in_generate:
+ dict_outputs = self._stack_split_outputs(seek_outputs, model_output_type, sequences.device, kwargs)
+
+ if num_return_sequences > 1:
+ if hasattr(dict_outputs, "encoder_attentions") and dict_outputs.encoder_attentions is not None:
+ dict_outputs.encoder_attentions = tuple(
+ dict_outputs.encoder_attentions[i][::num_return_sequences]
+ for i in range(len(dict_outputs.encoder_attentions))
+ )
+ if (
+ hasattr(dict_outputs, "encoder_hidden_states")
+ and dict_outputs.encoder_hidden_states is not None
+ ):
+ dict_outputs.encoder_hidden_states = tuple(
+ dict_outputs.encoder_hidden_states[i][::num_return_sequences]
+ for i in range(len(dict_outputs.encoder_hidden_states))
+ )
+ if return_token_timestamps:
+ dict_outputs["token_timestamps"] = outputs["token_timestamps"]
+ return dict_outputs
+
+ return outputs
+
+ return sequences
+
+ def generate_with_fallback(
+ self,
+ segment_input,
+ decoder_input_ids,
+ cur_bsz,
+ batch_idx_map,
+ seek,
+ num_segment_frames,
+ max_frames,
+ temperatures,
+ generation_config,
+ logits_processor,
+ stopping_criteria,
+ prefix_allowed_tokens_fn,
+ synced_gpus,
+ return_token_timestamps,
+ do_condition_on_prev_tokens,
+ is_shortform,
+ batch_size,
+ kwargs,
+ ):
+ kwargs = copy.copy(kwargs)
+
+ # 6.6 Batch generate current chunk
+ seek_sequence_list = [None for _ in range(cur_bsz)]
+ seek_outputs_list = [None for _ in range(cur_bsz)]
+ needs_fallback = [False for _ in range(cur_bsz)]
+ should_skip = [False for _ in range(cur_bsz)]
+ fallback_index_map = list(range(cur_bsz))
+ if generation_config.no_speech_threshold is not None:
+ self._setup_no_speech_detection(logits_processor, segment_input, decoder_input_ids, kwargs)
+
+ for fallback_idx, temperature in enumerate(temperatures):
+ generation_config.do_sample = temperature is not None and temperature > 0.0
+ generation_config.temperature = temperature if generation_config.do_sample else 1.0
+ if generation_config.do_sample:
+ generation_config.num_beams = 1
+
+ generate_kwargs = copy.copy(kwargs)
+ for key in ["do_sample", "temperature", "num_beams"]:
+ if key in generate_kwargs:
+ del generate_kwargs[key]
+
+ cur_bsz = decoder_input_ids.shape[0]
+ if generation_config.cache_implementation == "static" and cur_bsz < batch_size:
+ segment_input = F.pad(segment_input, (0, 0, 0, 0, 0, batch_size - cur_bsz), value=0)
+ decoder_input_ids = F.pad(
+ decoder_input_ids, (0, 0, 0, batch_size - cur_bsz), value=generation_config.pad_token_id
+ )
+ if generate_kwargs.get("decoder_attention_mask") is not None:
+ generate_kwargs["decoder_attention_mask"] = F.pad(
+ generate_kwargs["decoder_attention_mask"], (0, 0, 0, batch_size - cur_bsz), value=True
+ )
+ if generate_kwargs.get("encoder_outputs") is not None:
+ generate_kwargs["encoder_outputs"] = F.pad(
+ generate_kwargs["encoder_outputs"], (0, 0, 0, 0, 0, batch_size - cur_bsz), value=0
+ )
+
+ seek_outputs = super().generate(
+ segment_input,
+ generation_config=generation_config,
+ logits_processor=logits_processor,
+ stopping_criteria=stopping_criteria,
+ prefix_allowed_tokens_fn=prefix_allowed_tokens_fn,
+ synced_gpus=synced_gpus,
+ decoder_input_ids=decoder_input_ids,
+ **generate_kwargs,
+ )
+
+ model_output_type = type(seek_outputs)
+
+ # post-process sequence tokens and outputs to be in list form
+ seek_sequences, seek_outputs = self._postprocess_outputs(
+ seek_outputs=seek_outputs,
+ decoder_input_ids=decoder_input_ids,
+ return_token_timestamps=return_token_timestamps,
+ generation_config=generation_config,
+ is_shortform=is_shortform,
+ )
+
+ if cur_bsz < batch_size:
+ seek_sequences = seek_sequences[:cur_bsz]
+ seek_outputs = seek_outputs[:cur_bsz]
+
+ # 6.7 Extract cut sequences from every sequence and check if fallback should be applied
+ # Loop over each decoded audio individually as each decoding can be of a different length
+ new_fallback_index_map = []
+ new_segment_input = []
+ new_decoder_input_ids = []
+ new_decoder_attention_mask = []
+
+ for i, seek_sequence in enumerate(seek_sequences):
+ # make sure we cut a predicted EOS token if we are not finished with the generation yet
+ prev_i = batch_idx_map[fallback_index_map[i]]
+ is_not_final = (seek[prev_i] + num_segment_frames) < max_frames[prev_i]
+
+ # remove eos token id
+ if is_not_final and seek_sequence[-1] == generation_config.eos_token_id:
+ seek_sequence = seek_sequence[:-1]
+ if return_token_timestamps and not is_shortform:
+ seek_outputs[i]["token_timestamps"] = seek_outputs[i]["token_timestamps"][:-1]
+
+ # remove all padding tokens
+ if seek_sequence[-1] == generation_config.pad_token_id:
+ num_paddings = (seek_sequence == generation_config.pad_token_id).sum()
+ seek_sequence = seek_sequence[:-num_paddings]
+ if return_token_timestamps and not is_shortform:
+ seek_outputs[i]["token_timestamps"] = seek_outputs[i]["token_timestamps"][:-num_paddings]
+
+ # check which sequences in batch need fallback & which should be skipped
+ needs_fallback[i], should_skip[i] = self._need_fallback(
+ seek_sequence,
+ seek_outputs,
+ i,
+ logits_processor,
+ generation_config,
+ self.config.vocab_size,
+ temperature,
+ )
+
+ seek_sequence_list[fallback_index_map[i]] = seek_sequence
+ seek_outputs_list[fallback_index_map[i]] = seek_outputs[i]
+ is_low_temperature = temperature is None or temperature < 0.5
+ do_condition_on_prev_tokens[fallback_index_map[i]] = (
+ generation_config.condition_on_prev_tokens and is_low_temperature
+ )
+
+ if needs_fallback[i]:
+ new_fallback_index_map.append(fallback_index_map[i])
+ new_segment_input.append(segment_input[i])
+ new_decoder_input_ids.append(decoder_input_ids[i])
+ if "decoder_attention_mask" in kwargs:
+ new_decoder_attention_mask.append(kwargs["decoder_attention_mask"][i])
+
+ fallback_index_map = new_fallback_index_map
+
+ # if no sequence needs to be run with temperature fallback, we're finished
+ if len(fallback_index_map) == 0 or fallback_idx == len(temperatures) - 1:
+ seek_sequences = seek_sequence_list
+ seek_outputs = seek_outputs_list
+ break
+
+ # if we're still in the loop, make sure that decoder_input_ids and segment inputs are tensors
+ decoder_input_ids = torch.stack(new_decoder_input_ids)
+ segment_input = torch.stack(new_segment_input)
+ if "decoder_attention_mask" in kwargs:
+ kwargs["decoder_attention_mask"] = torch.stack(new_decoder_attention_mask)
+
+ return seek_sequences, seek_outputs, should_skip, do_condition_on_prev_tokens, model_output_type
+
+ @staticmethod
+ def _prepare_segments(prompt_ids, batch_size, generation_config):
+ if prompt_ids is not None and generation_config.prompt_condition_type == "first-segment":
+ prev_sot_token_id = getattr(generation_config, "prev_sot_token_id", None)
+ prompt_ids = prompt_ids[1:] if prompt_ids[0] == prev_sot_token_id else prompt_ids
+ current_segments = [[{"tokens": prompt_ids}] for _ in range(batch_size)]
+ else:
+ current_segments = [[] for _ in range(batch_size)]
+
+ return current_segments
+
+ def _postprocess_outputs(
+ self, seek_outputs, decoder_input_ids, return_token_timestamps, generation_config, is_shortform
+ ):
+ # remove all previously passed decoder input ids
+ start_idx = decoder_input_ids.shape[-1] if not is_shortform else torch.tensor(0)
+
+ if isinstance(seek_outputs, torch.Tensor):
+ seek_outputs = seek_outputs[:, start_idx:]
+ return seek_outputs, seek_outputs
+
+ if return_token_timestamps and hasattr(generation_config, "alignment_heads"):
+ num_frames = getattr(generation_config, "num_frames", None)
+ seek_outputs["token_timestamps"] = self._extract_token_timestamps(
+ seek_outputs, generation_config.alignment_heads, num_frames=num_frames
+ )
+ seek_outputs["token_timestamps"] = seek_outputs["token_timestamps"][:, start_idx:]
+
+ seek_outputs["sequences"] = seek_outputs["sequences"][:, start_idx:]
+
+ def split_by_batch_index(values, key, batch_idx, is_shortform):
+ if key in ["scores", "encoder_attentions", "encoder_hidden_states", "logits"]:
+ return [v[batch_idx].cpu() for v in values]
+ if key in ["decoder_attentions", "decoder_hidden_states", "cross_attentions"]:
+ return tuple(tuple(w[batch_idx][None].cpu() for w in v) for v in values)
+ elif key == "past_key_values":
+ if not is_shortform:
+ # we don't save `past_key_values` as this is too costly for longform
+ return None
+ elif isinstance(values, EncoderDecoderCache):
+ all_past_key_values = []
+ for layer_idx in range(self.config.decoder_layers):
+ layer_past_key_values = []
+ for cache_cls in [values.self_attention_cache, values.cross_attention_cache]:
+ for v in [cache_cls.key_cache, cache_cls.value_cache]:
+ layer_past_key_values.append(v[layer_idx][batch_idx][None].cpu())
+ all_past_key_values.append(tuple(layer_past_key_values))
+ return tuple(all_past_key_values)
+ else:
+ all_past_key_values = []
+ for v in range(len(values)):
+ layer_past_key_values = []
+ for w in values[v]:
+ layer_past_key_values.append(w[batch_idx][None].cpu())
+ all_past_key_values.append(tuple(layer_past_key_values))
+ return tuple(all_past_key_values)
+
+ return values[batch_idx].cpu()
+
+ sequence_tokens = seek_outputs["sequences"]
+ seek_outputs = [
+ {k: split_by_batch_index(v, k, i, is_shortform) for k, v in seek_outputs.items()}
+ for i in range(sequence_tokens.shape[0])
+ ]
+
+ return sequence_tokens, seek_outputs
+
+ def _stack_split_outputs(self, seek_outputs, model_output_type, device, kwargs):
+ # Stack back seek_outputs tensors after splitting them with the split_by_batch_index method
+ outputs = {}
+ for key in seek_outputs[0].keys():
+ if key == "sequences":
+ outputs[key] = torch.stack([v[key] for v in seek_outputs], dim=0).to(device)
+ if key in ["scores", "encoder_attentions", "encoder_hidden_states", "logits"]:
+ outputs[key] = tuple(
+ torch.stack([v[key][i] for v in seek_outputs]).to(device) for i in range(len(seek_outputs[0][key]))
+ )
+ if key in ["decoder_attentions", "decoder_hidden_states", "cross_attentions"]:
+ outputs[key] = tuple(
+ tuple(
+ torch.stack([v[key][i][j] for v in seek_outputs]).squeeze(1).to(device)
+ for j in range(len(seek_outputs[0][key][0]))
+ )
+ for i in range(len(seek_outputs[0][key]))
+ )
+ if key == "past_key_values":
+ past_key_value_type = kwargs.get("past_key_values")
+ if seek_outputs[0][key] is not None:
+ outputs[key] = tuple(
+ tuple(
+ torch.stack([v[key][i][j] for v in seek_outputs]).squeeze(1).to(device)
+ for j in range(len(seek_outputs[0][key][0]))
+ )
+ for i in range(len(seek_outputs[0][key]))
+ )
+ if past_key_value_type is not None and isinstance(past_key_value_type, EncoderDecoderCache):
+ outputs[key] = past_key_value_type.from_legacy_cache(outputs[key])
+ else:
+ outputs[key] = None
+
+ return model_output_type(**outputs)
+
+ def _need_fallback(
+ self,
+ seek_sequence,
+ seek_outputs,
+ index,
+ logits_processor,
+ generation_config,
+ vocab_size,
+ temperature,
+ ):
+ needs_fallback = False
+ should_skip = False
+ if generation_config.compression_ratio_threshold is not None:
+ compression_ratio = self._retrieve_compression_ratio(seek_sequence, vocab_size)
+
+ if compression_ratio > generation_config.compression_ratio_threshold:
+ needs_fallback = True
+
+ if generation_config.logprob_threshold is not None:
+ if hasattr(seek_outputs[0], "sequences_scores"):
+ logprobs = [s["sequences_scores"] for s in seek_outputs][index]
+ else:
+ scores = seek_outputs[index]["scores"]
+ logprobs = self._retrieve_avg_logprobs(
+ scores, seek_sequence, generation_config.eos_token_id, temperature
+ )
+
+ if logprobs < generation_config.logprob_threshold:
+ needs_fallback = True
+
+ if generation_config.no_speech_threshold is not None:
+ no_speech_prob = _get_attr_from_logit_processors(
+ logits_processor, WhisperNoSpeechDetection, "no_speech_prob"
+ )
+
+ if (
+ logprobs < generation_config.logprob_threshold
+ and no_speech_prob[index] > generation_config.no_speech_threshold
+ ):
+ needs_fallback = False
+ should_skip = True
+
+ return needs_fallback, should_skip
+
+ def _expand_variables_for_generation(
+ self, input_features, seek, max_frames, init_tokens, batch_size, condition_on_prev_tokens, generation_config
+ ):
+ if generation_config.num_return_sequences is not None and generation_config.num_return_sequences > 1:
+ batch_idx_map = list(range(batch_size * generation_config.num_return_sequences))
+ cur_bsz = len(batch_idx_map)
+ do_condition_on_prev_tokens = [condition_on_prev_tokens for _ in range(len(batch_idx_map))]
+ input_features = input_features.repeat_interleave(generation_config.num_return_sequences, dim=0)
+ seek = seek.repeat_interleave(generation_config.num_return_sequences, dim=0)
+ max_frames = max_frames.repeat_interleave(generation_config.num_return_sequences, dim=0)
+ init_tokens = init_tokens.repeat_interleave(generation_config.num_return_sequences, dim=0)
+ generation_config.num_return_sequences = 1
+ else:
+ cur_bsz = batch_size
+ batch_idx_map = list(range(cur_bsz))
+ do_condition_on_prev_tokens = [condition_on_prev_tokens for _ in range(cur_bsz)]
+
+ return (
+ batch_idx_map,
+ cur_bsz,
+ input_features,
+ seek,
+ max_frames,
+ init_tokens,
+ do_condition_on_prev_tokens,
+ )
+
+ @staticmethod
+ def _setup_no_speech_detection(logits_processor, segment_input, decoder_input_ids, kwargs):
+ set_inputs = _get_attr_from_logit_processors(logits_processor, WhisperNoSpeechDetection, "set_inputs")
+ extra_kwargs = {k: v for k, v in kwargs.items() if torch.is_tensor(v)}
+ set_inputs({"inputs": segment_input, "decoder_input_ids": decoder_input_ids, **extra_kwargs})
+
+ @staticmethod
+ def _retrieve_total_input_frames(input_features, input_stride, kwargs):
+ if input_features is not None:
+ return input_features.shape[0], input_features.shape[-1]
+
+ if "encoder_outputs" in kwargs:
+ encoder_outputs_shape = (
+ kwargs["encoder_outputs"][0].shape
+ if isinstance(kwargs["encoder_outputs"], BaseModelOutput)
+ else kwargs["encoder_outputs"].shape
+ )
+ return encoder_outputs_shape[0], encoder_outputs_shape[1] * input_stride
+
+ raise ValueError("Make sure to provide either `input_features` or `encoder_outputs` to `generate`.")
+
+ @staticmethod
+ def _maybe_warn_unused_inputs(
+ condition_on_prev_tokens,
+ temperature,
+ compression_ratio_threshold,
+ logprob_threshold,
+ no_speech_threshold,
+ total_input_frames,
+ ):
+ warning_prefix = (
+ f"Audio input consists of only {total_input_frames}. "
+ "Short-form transcription is activated."
+ "{}, but will be ignored."
+ )
+ if condition_on_prev_tokens is not None:
+ logger.warning(warning_prefix.format(f"condition_on_prev_tokens is set to {condition_on_prev_tokens}"))
+
+ if compression_ratio_threshold is not None:
+ logger.warning(
+ warning_prefix.format(f"compression_ratio_threshold is set to {compression_ratio_threshold}")
+ )
+
+ if logprob_threshold is not None:
+ logger.warning(warning_prefix.format(f"logprob_threshold is set to {logprob_threshold}"))
+
+ if no_speech_threshold is not None:
+ logger.warning(warning_prefix.format(f"no_speech_threshold is set to {no_speech_threshold}"))
+
+ # when passing temperature as a list it cannot just be ignored => throw error in this case
+ if isinstance(temperature, (list, tuple)):
+ raise ValueError(
+ f"Audio input consists of only {total_input_frames}. Short-form transcription is activated."
+ f"temperature cannot be set to {temperature} which can only be used for temperature fallback for long-form generation. Make sure to set `temperature` to a float value or `None` for short-form generation."
+ )
+
+ @staticmethod
+ def _set_return_outputs(return_dict_in_generate, return_token_timestamps, logprob_threshold, generation_config):
+ if return_dict_in_generate is None:
+ return_dict_in_generate = generation_config.return_dict_in_generate
+ else:
+ generation_config.return_dict_in_generate = return_dict_in_generate
+
+ generation_config.return_token_timestamps = return_token_timestamps
+ if return_token_timestamps:
+ generation_config.return_dict_in_generate = True
+ generation_config.output_attentions = True
+ generation_config.output_scores = True
+
+ if logprob_threshold is not None:
+ generation_config.return_dict_in_generate = True
+ generation_config.output_scores = True
+
+ return return_dict_in_generate
+
+ def _set_return_timestamps(self, return_timestamps, is_shortform, generation_config):
+ if return_timestamps is None and hasattr(generation_config, "return_timestamps"):
+ return_timestamps = generation_config.return_timestamps
+
+ if not is_shortform:
+ if return_timestamps is False:
+ raise ValueError(
+ "You have passed more than 3000 mel input features (> 30 seconds) which automatically enables long-form generation which "
+ "requires the model to predict timestamp tokens. Please either pass `return_timestamps=True` or make sure to pass no more than 3000 mel input features."
+ )
+
+ logger.info("Setting `return_timestamps=True` for long-form generation.")
+ return_timestamps = True
+
+ if return_timestamps and not hasattr(generation_config, "no_timestamps_token_id"):
+ raise ValueError(
+ "You are trying to return timestamps, but the generation config is not properly set. "
+ "Make sure to initialize the generation config with the correct attributes that are needed such as `no_timestamps_token_id`. "
+ "For more details on how to generate the approtiate config, refer to https://github.com/huggingface/transformers/issues/21878#issuecomment-1451902363"
+ )
+
+ generation_config.return_timestamps = return_timestamps
+
+ if hasattr(generation_config, "no_timestamps_token_id"):
+ timestamp_begin = generation_config.no_timestamps_token_id + 1
+ else:
+ # BC for models missing the `no_timestamps_token_id` in the generation config when generating short-form with no timestamps
+ # We set the timestamp begin token larger than the vocab size, such that the timestamp condition is never met in the decoding loop
+ timestamp_begin = self.config.vocab_size + 1
+
+ return timestamp_begin
+
+ @staticmethod
+ def _set_language_and_task(language, task, is_multilingual, generation_config):
+ if is_multilingual is not None:
+ if not hasattr(generation_config, "is_multilingual"):
+ raise ValueError(
+ "The generation config is outdated and is thus not compatible with the `is_multilingual` argument "
+ "to `generate`. Please update the generation config as per the instructions "
+ "https://github.com/huggingface/transformers/issues/25084#issuecomment-1664398224"
+ )
+ generation_config.is_multilingual = is_multilingual
+
+ if hasattr(generation_config, "is_multilingual") and not generation_config.is_multilingual:
+ if task is not None or language is not None:
+ raise ValueError(
+ "Cannot specify `task` or `language` for an English-only model. If the model is intended to be "
+ "multilingual, pass `is_multilingual=True` to generate, or update the generation config."
+ )
+
+ if language is not None:
+ if not hasattr(generation_config, "lang_to_id"):
+ raise ValueError(
+ "The generation config is outdated and is thus not compatible with the `language` argument "
+ "to `generate`. Either set the language using the `forced_decoder_ids` in the model config, "
+ "or update the generation config as per the instructions https://github.com/huggingface/transformers/issues/25084#issuecomment-1664398224"
+ )
+ generation_config.language = language
+
+ if task is not None:
+ if not hasattr(generation_config, "task_to_id"):
+ raise ValueError(
+ "The generation config is outdated and is thus not compatible with the `task` argument "
+ "to `generate`. Either set the task using the `forced_decoder_ids` in the model config, "
+ "or update the generation config as per the instructions https://github.com/huggingface/transformers/issues/25084#issuecomment-1664398224"
+ )
+ generation_config.task = task
+
+ def _retrieve_init_tokens(self, input_features, batch_size, generation_config, config, num_segment_frames, kwargs):
+ def replace_or_add(lst: List[int], num: int, itr: Iterator[int]):
+ """short function to replace num with a itr in lst"""
+ found = any(i in lst for i in itr)
+ if found:
+ lst = [num if i in itr else i for i in lst]
+ else:
+ lst.append(num)
+ return lst
+
+ def language_to_id(language: str) -> int:
+ language = language.lower()
+ if language in generation_config.lang_to_id.keys():
+ language_token = language
+ elif language in TO_LANGUAGE_CODE.keys():
+ language_token = f"<|{TO_LANGUAGE_CODE[language]}|>"
+ elif language in TO_LANGUAGE_CODE.values():
+ language_token = f"<|{language}|>"
+ else:
+ is_language_code = len(language) == 2
+ raise ValueError(
+ f"Unsupported language: {language}. Language should be one of:"
+ f" {list(TO_LANGUAGE_CODE.values()) if is_language_code else list(TO_LANGUAGE_CODE.keys())}."
+ )
+ if language_token not in generation_config.lang_to_id:
+ raise ValueError(
+ f"{language_token} is not supported by this specific model as it is not in the `generation_config.lang_to_id`."
+ "(You should just add it to the generation config)"
+ )
+
+ return generation_config.lang_to_id[language_token]
+
+ task = getattr(generation_config, "task", None)
+ language = getattr(generation_config, "language", None)
+
+ forced_decoder_ids = generation_config.forced_decoder_ids
+ if forced_decoder_ids is not None:
+ if language is None and task is None and forced_decoder_ids[0][1] is None:
+ logger.warning_once(
+ "Due to a bug fix in https://github.com/huggingface/transformers/pull/28687 transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English."
+ "This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass `language='en'`."
+ )
+ elif hasattr(config, "forced_decoder_ids") and config.forced_decoder_ids is not None:
+ forced_decoder_ids = config.forced_decoder_ids
+
+ if forced_decoder_ids is not None and task is not None:
+ logger.warning_once(
+ f"You have passed task={task}, but also have set `forced_decoder_ids` to {forced_decoder_ids} which creates a conflict. `forced_decoder_ids` will be ignored in favor of task={task}."
+ )
+ forced_decoder_ids = None
+ elif forced_decoder_ids is not None and language is not None:
+ logger.warning_once(
+ f"You have passed language={language}, but also have set `forced_decoder_ids` to {forced_decoder_ids} which creates a conflict. `forced_decoder_ids` will be ignored in favor of language={language}."
+ )
+ forced_decoder_ids = None
+
+ init_tokens = [generation_config.decoder_start_token_id]
+ if forced_decoder_ids is not None and forced_decoder_ids[0][0] == 1:
+ i = 1
+ while len(forced_decoder_ids) > 0 and forced_decoder_ids[0][0] == i:
+ init_tokens += [forced_decoder_ids[0][1]]
+ forced_decoder_ids = forced_decoder_ids[1:]
+ i += 1
+
+ if len(forced_decoder_ids) > 0:
+ raise ValueError(
+ f"You are using token ids in `forced_decoder_ids` that do not seem to correctly follow the prompt pattern of Whisper. Make sure that {forced_decoder_ids} has an entry for all indices >= 1 and < {forced_decoder_ids[0][0]}.",
+ )
+
+ # from v4.39 the forced decoder ids are always None in favour of decoder input ids
+ generation_config.forced_decoder_ids = None
+
+ is_lang_id_undefined = len(init_tokens) <= 1 or (len(init_tokens) > 1 and init_tokens[1] is None)
+
+ # Make sure language is a list of strings of the correct length
+ if isinstance(language, (list, tuple)):
+ if any(l is None for l in language):
+ raise TypeError(
+ "Expected `language` to be `None`, a single string (e.g. `'en'`), or a list of strings with length equal to the batch size (e.g. `('en', 'fr')` for a batch size of 2). Got a list containing `None`."
+ )
+ if len(language) != batch_size:
+ raise ValueError(
+ "When passing a list of languages, the length of the list must match the batch size. "
+ f"Expected length of {batch_size}, but got {len(language)} languages."
+ )
+ languages = language
+ elif language is None:
+ # Language will be detected for each item in batch
+ languages = [None] * batch_size
+ else:
+ languages = [language] # Use a length-1 list now, broadcast later
+
+ # Separate init_tokens for each language
+ init_tokens = [copy.copy(init_tokens) for _ in languages]
+
+ # Update init_tokens with languages
+ lang_ids = None
+ if language is not None:
+ lang_ids = [language_to_id(l) for l in languages]
+ elif hasattr(generation_config, "lang_to_id") and is_lang_id_undefined:
+ # language is not defined or intentially set to `None` to trigger language detection
+ lang_ids = self.detect_language(
+ input_features=input_features,
+ encoder_outputs=kwargs.get("encoder_outputs", None),
+ attention_mask=kwargs.get("attention_mask", None),
+ generation_config=generation_config,
+ num_segment_frames=num_segment_frames,
+ ).tolist()
+ if lang_ids is not None:
+ # append or replace lang_ids to init_tokens
+ for i in range(len(init_tokens)):
+ if len(init_tokens[i]) > 1:
+ init_tokens[i][1] = lang_ids[i]
+ else:
+ init_tokens[i].append(lang_ids[i])
+ del languages
+
+ # Update init_tokens with task
+ for i in range(len(init_tokens)):
+ if task is not None:
+ if task in TASK_IDS:
+ init_tokens[i].append(generation_config.task_to_id[generation_config.task])
+ task_id = generation_config.task_to_id[generation_config.task]
+
+ # if task is defined it'll overwrite task ids that might have already been defined via the generation_config
+ replace_or_add(init_tokens[i], task_id, generation_config.task_to_id.values())
+ else:
+ raise ValueError(f"The `{task}`task is not supported. The task should be one of `{TASK_IDS}`")
+ elif language is not None and hasattr(generation_config, "task_to_id"):
+ # if language is defined, but no task id is in `init_tokens`, default to transcribe
+ if not any(ti in init_tokens[i] for ti in generation_config.task_to_id.values()):
+ init_tokens[i].append(generation_config.task_to_id["transcribe"])
+
+ if (
+ not generation_config.return_timestamps
+ and hasattr(generation_config, "no_timestamps_token_id")
+ and init_tokens[i][-1] != generation_config.no_timestamps_token_id
+ ):
+ init_tokens[i].append(generation_config.no_timestamps_token_id)
+ elif (
+ generation_config.return_timestamps and init_tokens[i][-1] == generation_config.no_timestamps_token_id
+ ):
+ logger.info(
+ "<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `'True'`."
+ )
+ init_tokens[i] = init_tokens[i][:-1]
+
+ # let's make sure we don't pass `None` tokens as prompt tokens
+ init_tokens[i] = [t for t in init_tokens[i] if t is not None]
+
+ return torch.as_tensor(init_tokens, dtype=torch.long, device=self.device).expand(batch_size, -1)
+
+ def detect_language(
+ self,
+ input_features: Optional[torch.FloatTensor] = None,
+ attention_mask: Optional[torch.LongTensor] = None,
+ encoder_outputs: Optional[Union[torch.FloatTensor, BaseModelOutput]] = None,
+ generation_config: Optional[GenerationConfig] = None,
+ num_segment_frames: int = 3000,
+ ) -> torch.Tensor:
+ """
+ Detects language from log-mel input features or encoder_outputs
+
+ Parameters:
+ input_features (`torch.Tensor` of shape `(batch_size, feature_size, sequence_length)`, *optional*):
+ Float values of log-mel features extracted from the raw speech waveform. The raw speech waveform can be obtained by
+ loading a `.flac` or `.wav` audio file into an array of type `List[float]` or a `numpy.ndarray`, *e.g.* via
+ the soundfile library (`pip install soundfile`). To prepare the array into `input_features`, the
+ [`AutoFeatureExtractor`] should be used for extracting the mel features, padding and conversion into a
+ tensor of type `torch.FloatTensor`. See [`~WhisperFeatureExtractor.__call__`] for details.
+ encoder_outputs (`tuple(tuple(torch.FloatTensor)`, *optional*):
+ Tuple consists of (`last_hidden_state`, *optional*: `hidden_states`, *optional*: `attentions`)
+ `last_hidden_state` of shape `(batch_size, sequence_length, hidden_size)`, *optional*) is a sequence of
+ hidden-states at the output of the last layer of the encoder. Used in the cross-attention of the decoder.
+ generation_config (`~generation.GenerationConfig`, *optional*):
+ The generation configuration to be used as base parametrization for the generation call. `**kwargs`
+ passed to generate matching the attributes of `generation_config` will override them. If
+ `generation_config` is not provided, the default will be used, which had the following loading
+ priority: 1) from the `generation_config.json` model file, if it exists; 2) from the model
+ configuration. Please note that unspecified parameters will inherit [`~generation.GenerationConfig`]'s
+ default values, whose documentation should be checked to parameterize generation.
+ num_segment_frames (`int`, *optional*, defaults to 3000):
+ The number of log-mel frames the model expects
+
+ Return:
+ A `torch.LongTensor` representing the detected language ids.
+ """
+ if input_features is None and encoder_outputs is None:
+ raise ValueError("You have to specify either `input_features` or `encoder_outputs`")
+ elif input_features is not None and encoder_outputs is not None:
+ raise ValueError("Make sure to specificy only one of `input_features` or `encoder_outputs` - not both!")
+ elif input_features is not None:
+ inputs = {"input_features": input_features[:, :, :num_segment_frames]}
+ batch_size = input_features.shape[0]
+ elif encoder_outputs is not None:
+ inputs = {"encoder_outputs": encoder_outputs}
+ batch_size = (
+ encoder_outputs[0].shape[0] if isinstance(encoder_outputs, BaseModelOutput) else encoder_outputs[0]
+ )
+ if attention_mask is not None:
+ inputs["attention_mask"] = attention_mask
+
+ generation_config = generation_config or self.generation_config
+ decoder_input_ids = (
+ torch.ones((batch_size, 1), device=self.device, dtype=torch.long)
+ * generation_config.decoder_start_token_id
+ )
+
+ with torch.no_grad():
+ logits = self(**inputs, decoder_input_ids=decoder_input_ids).logits[:, -1]
+
+ non_lang_mask = torch.ones_like(logits[0], dtype=torch.bool)
+ non_lang_mask[list(generation_config.lang_to_id.values())] = False
+
+ logits[:, non_lang_mask] = -np.inf
+
+ lang_ids = logits.argmax(-1)
+
+ return lang_ids
+
+ @staticmethod
+ def _check_decoder_input_ids(kwargs):
+ decoder_input_ids = kwargs.get("decoder_input_ids", None)
+ assistant_model = kwargs.get("assistant_model", None)
+ if decoder_input_ids is not None and assistant_model is not None:
+ raise ValueError(
+ "Passing `decoder_input_ids` is deprecated. Consider passing `prompt_ids` instead.",
+ )
+
+ @staticmethod
+ def _set_num_frames(return_token_timestamps, generation_config, kwargs):
+ if return_token_timestamps:
+ if getattr(generation_config, "task", None) == "translate":
+ logger.warning("Token-level timestamps may not be reliable for task 'translate'.")
+ if not hasattr(generation_config, "alignment_heads"):
+ raise ValueError(
+ "Model generation config has no `alignment_heads`, token-level timestamps not available. "
+ "See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config."
+ )
+ generation_config.num_frames = kwargs.pop("num_frames", None)
+
+ @staticmethod
+ def _set_thresholds_and_condition(
+ generation_config,
+ logprob_threshold,
+ compression_ratio_threshold,
+ no_speech_threshold,
+ condition_on_prev_tokens,
+ ):
+ generation_config.logprob_threshold = (
+ logprob_threshold
+ if logprob_threshold is not None
+ else getattr(generation_config, "logprob_threshold", None)
+ )
+ generation_config.compression_ratio_threshold = (
+ compression_ratio_threshold
+ if compression_ratio_threshold is not None
+ else getattr(generation_config, "compression_ratio_threshold", None)
+ )
+ generation_config.no_speech_threshold = (
+ no_speech_threshold
+ if no_speech_threshold is not None
+ else getattr(generation_config, "no_speech_threshold", None)
+ )
+ generation_config.condition_on_prev_tokens = (
+ condition_on_prev_tokens
+ if condition_on_prev_tokens is not None
+ else getattr(generation_config, "condition_on_prev_tokens", None)
+ )
+
+ @staticmethod
+ def _set_prompt_condition_type(generation_config, prompt_condition_type):
+ allowed_cond_types = ["first-segment", "all-segments"]
+
+ # default to "first-segment"
+ prompt_condition_type = prompt_condition_type or allowed_cond_types[0]
+
+ if prompt_condition_type not in allowed_cond_types:
+ raise ValueError(
+ f"`prompt_condition_type={prompt_condition_type} does not exist. Make sure to set `prompt_condition_type` to one of {', '.join(allowed_cond_types)}"
+ )
+
+ if generation_config.condition_on_prev_tokens is not True and prompt_condition_type == "all-segments":
+ raise ValueError(
+ "Make sure to set `condition_on_prev_tokens=True` when setting `prompt_condition_type='all-segments'`."
+ )
+
+ generation_config.prompt_condition_type = prompt_condition_type
+
+ @staticmethod
+ def _set_condition_on_prev_tokens(condition_on_prev_tokens, generation_config):
+ condition_on_prev_tokens = (
+ condition_on_prev_tokens
+ if condition_on_prev_tokens is not None
+ else getattr(generation_config, "condition_on_prev_tokens", False)
+ )
+ generation_config.condition_on_prev_tokens = condition_on_prev_tokens
+
+ @staticmethod
+ def _retrieve_max_frames_and_seek(batch_size, attention_mask, total_input_frames, is_shortform):
+ if batch_size > 1 and not is_shortform and attention_mask is None:
+ raise ValueError(
+ "When doing batched long-form audio transcription, make sure to pass an `attention_mask`. You can retrieve the `attention_mask` by doing `processor(audio, ..., return_attention_mask=True)` "
+ )
+ elif batch_size > 1 and not is_shortform:
+ max_frames = attention_mask.sum(-1).cpu().to(torch.long)
+ seek = torch.zeros((batch_size,), dtype=torch.long)
+ else:
+ max_frames = torch.ones((batch_size,), dtype=torch.long) * total_input_frames
+ seek = torch.zeros((batch_size,), dtype=torch.long)
+
+ return max_frames, seek
+
+ def _retrieve_logit_processors(self, generation_config, logits_processor, begin_index, num_beams, device):
+ if generation_config.return_timestamps is True:
+ timestamp_processor = WhisperTimeStampLogitsProcessor(generation_config, begin_index=begin_index)
+ logits_processor = (
+ [timestamp_processor] if logits_processor is None else [timestamp_processor] + logits_processor
+ )
+
+ if generation_config.suppress_tokens is not None:
+ suppress_tokens_processor = SuppressTokensLogitsProcessor(generation_config.suppress_tokens, device=device)
+ logits_processor = (
+ [suppress_tokens_processor]
+ if logits_processor is None
+ else [suppress_tokens_processor] + logits_processor
+ )
+ generation_config.suppress_tokens = None
+
+ if generation_config.begin_suppress_tokens is not None:
+ begin_suppress_processor = SuppressTokensAtBeginLogitsProcessor(
+ generation_config.begin_suppress_tokens, begin_index=begin_index, device=device
+ )
+ logits_processor = (
+ [begin_suppress_processor]
+ if logits_processor is None
+ else [begin_suppress_processor] + logits_processor
+ )
+ generation_config.begin_suppress_tokens = None
+
+ if generation_config.no_speech_threshold is not None:
+ no_speech_detector = WhisperNoSpeechDetection(
+ no_speech_token=generation_config.no_timestamps_token_id - 1,
+ begin_index=begin_index,
+ scores_is_logprobs=num_beams > 1,
+ )
+ logits_processor = (
+ [no_speech_detector] if logits_processor is None else [no_speech_detector] + logits_processor
+ )
+ no_speech_detector.set_model(self)
+
+ return logits_processor
+
+ @staticmethod
+ def _maybe_reduce_batch(input_features, seek, max_frames, cur_bsz, batch_idx_map):
+ prev_bsz = cur_bsz
+ new_batch_idx_map = []
+ for i in range(prev_bsz):
+ prev_i = batch_idx_map[i]
+ if seek[prev_i] >= max_frames[prev_i]:
+ cut_index = i + (cur_bsz - prev_bsz)
+ cur_bsz -= 1
+ input_features = torch.cat([input_features[:cut_index], input_features[cut_index + 1 :]], dim=0)
+ else:
+ # cut out index that goes away
+ new_batch_idx_map.append(prev_i)
+
+ return input_features, cur_bsz, new_batch_idx_map
+
+ @staticmethod
+ def _get_input_segment(input_features, seek, seek_num_frames, num_segment_frames, cur_bsz, batch_idx_map):
+ if input_features is None:
+ return None
+
+ segment_input = []
+ for i in range(cur_bsz):
+ prev_i = batch_idx_map[i]
+ segment_input_slice = input_features[i : i + 1, :, seek[prev_i] : seek[prev_i] + seek_num_frames[prev_i]]
+
+ if segment_input_slice.shape[-1] < num_segment_frames:
+ # pad to 3000 if necessary
+ segment_input_slice = F.pad(
+ segment_input_slice, pad=(0, num_segment_frames - segment_input_slice.shape[-1])
+ )
+
+ segment_input.append(segment_input_slice)
+
+ segment_input = torch.cat(segment_input, dim=0)
+
+ return segment_input
+
+ @staticmethod
+ def _prepare_decoder_input_ids(
+ cur_bsz,
+ init_tokens,
+ current_segments,
+ batch_idx_map,
+ do_condition_on_prev_tokens,
+ prompt_ids,
+ generation_config,
+ config,
+ device,
+ suppress_tokens,
+ kwargs,
+ ):
+ if "decoder_input_ids" in kwargs:
+ decoder_input_ids = kwargs.pop("decoder_input_ids")
+
+ return decoder_input_ids, kwargs
+
+ cut_off_length = config.max_target_positions // 2 - 1
+
+ decoder_input_ids = init_tokens[batch_idx_map]
+
+ prev_start_of_text = getattr(generation_config, "prev_sot_token_id", None)
+ if prev_start_of_text is None:
+ prev_start_of_text = suppress_tokens[-2] if suppress_tokens is not None else None
+
+ if any(do_condition_on_prev_tokens) and len(current_segments[0]) > 0:
+ # according to https://github.com/openai/whisper/blob/e58f28804528831904c3b6f2c0e473f346223433/whisper/decoding.py#L609
+ active_segments = [current_segments[i] if do_condition_on_prev_tokens[i] else None for i in batch_idx_map]
+
+ if prompt_ids is not None and generation_config.prompt_condition_type == "all-segments":
+ prev_ids = prompt_ids
+ else:
+ one_tensor = torch.ones((cur_bsz, 1), device=device, dtype=torch.long)
+ prev_ids = prev_start_of_text * one_tensor[0] if prev_start_of_text is not None else None
+
+ padding = "max_length" if generation_config.cache_implementation == "static" else "longest"
+
+ prev_tokens = _pad_to_max_length(
+ active_segments,
+ generation_config.pad_token_id,
+ device=device,
+ padding_side="left",
+ padding=padding,
+ bos_token_tensor=prev_ids,
+ cut_off_length=cut_off_length,
+ )
+ decoder_input_ids = torch.cat([prev_tokens, decoder_input_ids], dim=-1)
+
+ kwargs["decoder_attention_mask"] = decoder_input_ids != generation_config.pad_token_id
+ elif prompt_ids is not None:
+ prev_tokens = prompt_ids[None].repeat(decoder_input_ids.shape[0], 1)
+ decoder_input_ids = torch.cat([prev_tokens, decoder_input_ids], dim=-1)
+ # make sure `"decoder_attention_mask"` is not passed to forward
+ kwargs.pop("decoder_attention_mask", None)
+ else:
+ # make sure `"decoder_attention_mask"` is not passed to forward
+ kwargs.pop("decoder_attention_mask", None)
+
+ return decoder_input_ids, kwargs
+
+ def _set_max_new_tokens_and_length(self, config, decoder_input_ids, generation_config):
+ max_new_tokens = generation_config.max_new_tokens if generation_config.max_new_tokens is not None else 0
+ if max_new_tokens + decoder_input_ids.shape[-1] > self.config.max_target_positions:
+ raise ValueError(
+ f"The length of `decoder_input_ids` equal `prompt_ids` plus special start tokens is {decoder_input_ids.shape[-1]}, and the `max_new_tokens` "
+ f"is {max_new_tokens}. Thus, the combined length of "
+ f"`decoder_input_ids` and `max_new_tokens` is: {max_new_tokens + decoder_input_ids.shape[-1]}. This exceeds the "
+ f"`max_target_positions` of the Whisper model: {self.config.max_target_positions}. "
+ "You should either reduce the length of your prompt, or reduce the value of `max_new_tokens`, "
+ f"so that their combined length is less than {self.config.max_target_positions}."
+ )
+
+ num_initial_tokens = min(config.max_target_positions // 2 - 1, decoder_input_ids.shape[-1] - 1)
+
+ # Make sure we don't get larger than `max_length`
+ if generation_config.max_length is not None and generation_config.max_new_tokens is None:
+ max_length = min(generation_config.max_length + num_initial_tokens, config.max_target_positions)
+ logger.info(
+ f"Increase max_length from {generation_config.max_length} to {max_length} since input is conditioned on previous segment."
+ )
+ elif (
+ generation_config.max_new_tokens is not None
+ and generation_config.max_new_tokens + decoder_input_ids.shape[-1] > config.max_target_positions
+ ):
+ max_new_tokens = config.max_target_positions - decoder_input_ids.shape[-1]
+ generation_config.max_new_tokens = max_new_tokens
+
+ @staticmethod
+ def _retrieve_compression_ratio(tokens, vocab_size):
+ """Compute byte length of zlib compressed token bytes vs. byte length of raw token bytes"""
+ length = int(math.log2(vocab_size) / 8) + 1
+ token_bytes = b"".join([t.to_bytes(length, "little") for t in tokens.tolist()])
+ compression_ratio = len(token_bytes) / len(zlib.compress(token_bytes))
+
+ return compression_ratio
+
+ @staticmethod
+ def _retrieve_avg_logprobs(scores, tokens, eos_token_id, temperature):
+ rescale_temperature = temperature if temperature > 0.0 else 1
+ scores = torch.stack(scores).to(tokens.device)
+
+ if scores.shape[0] > tokens.shape[0]:
+ scores = scores[: tokens.shape[0]]
+ else:
+ tokens = tokens[-scores.shape[0] :]
+
+ logprobs = F.log_softmax((scores * rescale_temperature).float(), dim=-1).to(scores.dtype)
+
+ # retrieve logprob of selected tokens and sum
+ sum_logprobs = sum((logprobs[i][tokens[i]] * (tokens[i] != eos_token_id)) for i in range(logprobs.shape[0]))
+ length = (tokens != eos_token_id).sum(-1) if eos_token_id is not None else tokens.shape[0]
+
+ avg_logprobs = sum_logprobs / (length + 1)
+ return avg_logprobs
+
+ @staticmethod
+ def _retrieve_segment(
+ seek_sequence,
+ seek_outputs,
+ time_offset,
+ timestamp_begin,
+ seek_num_frames,
+ time_precision,
+ input_stride,
+ prev_idx,
+ idx,
+ return_token_timestamps,
+ ):
+ # find the predicted "end of segment" predictions of Whisper
+ # "end of segment" predictions occur whenever Whisper predicts a timestamp token
+ timestamp_tokens: torch.Tensor = seek_sequence.ge(timestamp_begin)
+ single_timestamp_ending = timestamp_tokens[-2:].tolist() == [False, True]
+ timestamp_segment_indices = torch.where(timestamp_tokens[:-1] & timestamp_tokens[1:])[0]
+ timestamp_segment_indices.add_(1)
+ token_timestamps = seek_outputs[idx]["token_timestamps"] if return_token_timestamps else []
+
+ # If whisper predicted a "end of segment" via a timestep token, let's go ever each
+ # "end of segment" prediction and slice the decoding into segments accordingly
+ if len(timestamp_segment_indices) > 0:
+ # if the output contains two consecutive timestamp tokens
+ slices = timestamp_segment_indices.tolist()
+ segments = []
+ if single_timestamp_ending:
+ slices.append(len(seek_sequence))
+
+ last_slice = 0
+ # Add each segment to list of all segments
+ for current_slice in slices:
+ sliced_tokens = seek_sequence[last_slice:current_slice]
+ start_timestamp_pos = sliced_tokens[0].item() - timestamp_begin
+ end_timestamp_pos = sliced_tokens[-1].item() - timestamp_begin
+ segments.append(
+ {
+ "start": time_offset[prev_idx] + start_timestamp_pos * time_precision,
+ "end": time_offset[prev_idx] + end_timestamp_pos * time_precision,
+ "tokens": sliced_tokens,
+ "result": seek_outputs[idx],
+ }
+ )
+ if return_token_timestamps:
+ segments[-1]["token_timestamps"] = (
+ token_timestamps[last_slice:current_slice] + time_offset[prev_idx]
+ )
+ last_slice = current_slice
+
+ if single_timestamp_ending:
+ # single timestamp at the end means no speech after the last timestamp.
+ segment_offset = seek_num_frames[prev_idx]
+ else:
+ # otherwise, ignore the unfinished segment and seek to the last timestamp
+ # here we throw away all predictions after the last predicted "end of segment"
+ # since we are cutting right in the middle of an audio
+ last_timestamp_pos = seek_sequence[last_slice - 1].item() - timestamp_begin
+ segment_offset = last_timestamp_pos * input_stride
+ else:
+ # If whisper does not predict any "end of segment" token, then
+ # the whole decoding is considered a segment and we add it to the list of segments
+ timestamps = seek_sequence[timestamp_tokens.nonzero().flatten()]
+ last_timestamp_pos = seek_num_frames[prev_idx]
+ if timestamps.numel() > 0 and timestamps[-1].item() != timestamp_begin:
+ # no consecutive timestamps but it has a timestamp; use the last one.
+ last_timestamp_pos = timestamps[-1].item() - timestamp_begin
+ segments = [
+ {
+ "start": time_offset[prev_idx],
+ "end": time_offset[prev_idx] + last_timestamp_pos * time_precision,
+ "tokens": seek_sequence,
+ "result": seek_outputs[idx],
+ }
+ ]
+ if return_token_timestamps:
+ segments[-1]["token_timestamps"] = token_timestamps + time_offset[prev_idx]
+ segment_offset = seek_num_frames[prev_idx]
+
+ return segments, segment_offset
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/modeling_whisper.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/modeling_whisper.py
new file mode 100644
index 0000000000000000000000000000000000000000..35128981a161453aeece6d2a1fefe3cbf3bb7bcf
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/modeling_whisper.py
@@ -0,0 +1,2546 @@
+# coding=utf-8
+# Copyright 2022 The OpenAI Authors and The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""PyTorch Whisper model."""
+
+import math
+import os.path
+import random
+from typing import Optional, Tuple, Union
+
+import numpy as np
+import torch
+import torch.utils.checkpoint
+from torch import nn
+from torch.nn import CrossEntropyLoss
+
+from transformers.activations import ACT2FN
+from transformers.cache_utils import Cache, DynamicCache, EncoderDecoderCache, StaticCache
+from transformers.modeling_attn_mask_utils import AttentionMaskConverter
+from dataclasses import dataclass
+from transformers.modeling_outputs import (
+ BaseModelOutput,
+ BaseModelOutputWithPastAndCrossAttentions,
+ CausalLMOutputWithCrossAttentions,
+ Seq2SeqLMOutput,
+ Seq2SeqModelOutput,
+ SequenceClassifierOutput,
+)
+from transformers.modeling_utils import PreTrainedModel
+from transformers.utils import (
+ add_start_docstrings,
+ add_start_docstrings_to_model_forward,
+ is_flash_attn_2_available,
+ is_flash_attn_greater_or_equal_2_10,
+ logging,
+ replace_return_docstrings,
+)
+from .configuration_whisper import WhisperVQConfig
+from .generation_whisper import WhisperGenerationMixin
+
+if is_flash_attn_2_available():
+ from transformers.modeling_flash_attention_utils import _flash_attention_forward
+
+logger = logging.get_logger(__name__)
+
+_HIDDEN_STATES_START_POSITION = 1
+
+_CONFIG_FOR_DOC = "WhisperConfig"
+_CHECKPOINT_FOR_DOC = "openai/whisper-tiny"
+
+
+@dataclass
+class QuantizedBaseModelOutput(BaseModelOutput):
+ quantized_token_ids: Optional[torch.LongTensor] = None
+
+
+def vector_quantize(inputs, codebook):
+ embedding_size = codebook.size(1)
+ inputs_flatten = inputs.reshape(-1, embedding_size)
+ codebook_sqr = torch.sum(codebook ** 2, dim=1)
+ inputs_sqr = torch.sum(inputs_flatten ** 2, dim=1, keepdim=True)
+ # Compute the distances to the codebook
+ distances = torch.addmm(codebook_sqr + inputs_sqr,
+ inputs_flatten, codebook.t(), alpha=-2.0, beta=1.0)
+
+ _, indices_flatten = torch.min(distances, dim=1)
+ codes_flatten = torch.index_select(codebook, dim=0,
+ index=indices_flatten)
+ codes = codes_flatten.view_as(inputs)
+ return codes, indices_flatten, distances
+
+
+def mse_loss_with_mask(input, target, mask):
+ loss = torch.nn.functional.mse_loss(input, target, reduction='none')
+ loss = loss.mean(dim=-1)
+ loss = loss * mask
+ return loss.sum() / mask.sum()
+
+
+class CausalConv1d(nn.Conv1d):
+ def __init__(
+ self,
+ in_channels,
+ out_channels,
+ kernel_size,
+ stride=1,
+ padding=0,
+ dilation=1,
+ groups=1,
+ bias=True,
+ **kwargs
+ ):
+ super(CausalConv1d, self).__init__(
+ in_channels,
+ out_channels,
+ kernel_size,
+ stride=stride,
+ padding=0,
+ dilation=dilation,
+ groups=groups,
+ bias=bias,
+ **kwargs
+ )
+
+ self.left_padding = dilation * (kernel_size - 1)
+
+ def forward(self, inp):
+ x = torch.nn.functional.pad(inp.unsqueeze(2), (self.left_padding, 0, 0, 0)).squeeze(2)
+
+ return super(CausalConv1d, self).forward(x)
+
+
+# Copied from transformers.models.llama.modeling_llama._prepare_4d_causal_attention_mask_with_cache_position
+def _prepare_4d_causal_attention_mask_with_cache_position(
+ attention_mask: torch.Tensor,
+ sequence_length: int,
+ target_length: int,
+ dtype: torch.dtype,
+ device: torch.device,
+ min_dtype: float,
+ cache_position: torch.Tensor,
+ batch_size: int,
+):
+ """
+ Creates a causal 4D mask of shape `(batch_size, 1, query_length, key_value_length)` from a 2D mask of shape
+ `(batch_size, key_value_length)`, or if the input `attention_mask` is already 4D, do nothing.
+
+ Args:
+ attention_mask (`torch.Tensor`):
+ A 2D attention mask of shape `(batch_size, key_value_length)` or a 4D attention mask of shape `(batch_size, 1, query_length, key_value_length)`.
+ sequence_length (`int`):
+ The sequence length being processed.
+ target_length (`int`):
+ The target length: when generating with static cache, the mask should be as long as the static cache, to account for the 0 padding, the part of the cache that is not filled yet.
+ dtype (`torch.dtype`):
+ The dtype to use for the 4D attention mask.
+ device (`torch.device`):
+ The device to plcae the 4D attention mask on.
+ min_dtype (`float`):
+ The minimum value representable with the dtype `dtype`.
+ cache_position (`torch.Tensor`):
+ Indices depicting the position of the input sequence tokens in the sequence.
+ batch_size (`torch.Tensor`):
+ Batch size.
+ """
+ if attention_mask is not None and attention_mask.dim() == 4:
+ # In this case we assume that the mask comes already in inverted form and requires no inversion or slicing.
+ causal_mask = attention_mask
+ else:
+ causal_mask = torch.full((sequence_length, target_length), fill_value=min_dtype, dtype=dtype, device=device)
+ if sequence_length != 1:
+ causal_mask = torch.triu(causal_mask, diagonal=1)
+ causal_mask *= torch.arange(target_length, device=device) > cache_position.reshape(-1, 1)
+ causal_mask = causal_mask[None, None, :, :].expand(batch_size, 1, -1, -1)
+ if attention_mask is not None:
+ causal_mask = causal_mask.clone() # copy to contiguous memory for in-place edit
+ mask_length = attention_mask.shape[-1]
+ padding_mask = causal_mask[:, :, :, :mask_length] + attention_mask[:, None, None, :]
+ padding_mask = padding_mask == 0
+ causal_mask[:, :, :, :mask_length] = causal_mask[:, :, :, :mask_length].masked_fill(
+ padding_mask, min_dtype
+ )
+
+ return causal_mask
+
+
+def sinusoids(length: int, channels: int, max_timescale: float = 10000) -> torch.Tensor:
+ """Returns sinusoids for positional embedding"""
+ if channels % 2 != 0:
+ raise ValueError(
+ f"Number of channels has to be divisible by 2 for sinusoidal positional embeddings, got {channels} channels."
+ )
+ log_timescale_increment = math.log(max_timescale) / (channels // 2 - 1)
+ inv_timescales = torch.exp(-log_timescale_increment * torch.arange(channels // 2))
+ scaled_time = torch.arange(length).view(-1, 1) * inv_timescales.view(1, -1)
+ return torch.cat([scaled_time.sin(), scaled_time.cos()], dim=1)
+
+
+# Copied from transformers.models.bart.modeling_bart.shift_tokens_right
+def shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):
+ """
+ Shift input ids one token to the right.
+ """
+ shifted_input_ids = input_ids.new_zeros(input_ids.shape)
+ shifted_input_ids[:, 1:] = input_ids[:, :-1].clone()
+ shifted_input_ids[:, 0] = decoder_start_token_id
+
+ if pad_token_id is None:
+ raise ValueError("self.model.config.pad_token_id has to be defined.")
+ # replace possible -100 values in labels by `pad_token_id`
+ shifted_input_ids.masked_fill_(shifted_input_ids == -100, pad_token_id)
+
+ return shifted_input_ids
+
+
+# Copied from transformers.models.wav2vec2.modeling_wav2vec2._compute_mask_indices
+def _compute_mask_indices(
+ shape: Tuple[int, int],
+ mask_prob: float,
+ mask_length: int,
+ attention_mask: Optional[torch.LongTensor] = None,
+ min_masks: int = 0,
+) -> np.ndarray:
+ """
+ Computes random mask spans for a given shape. Used to implement [SpecAugment: A Simple Data Augmentation Method for
+ ASR](https://arxiv.org/abs/1904.08779). Note that this method is not optimized to run on TPU and should be run on
+ CPU as part of the preprocessing during training.
+
+ Args:
+ shape: The shape for which to compute masks. This should be of a tuple of size 2 where
+ the first element is the batch size and the second element is the length of the axis to span.
+ mask_prob: The percentage of the whole axis (between 0 and 1) which will be masked. The number of
+ independently generated mask spans of length `mask_length` is computed by
+ `mask_prob*shape[1]/mask_length`. Note that due to overlaps, `mask_prob` is an upper bound and the
+ actual percentage will be smaller.
+ mask_length: size of the mask
+ min_masks: minimum number of masked spans
+ attention_mask: A (right-padded) attention mask which independently shortens the feature axis of
+ each batch dimension.
+ """
+ batch_size, sequence_length = shape
+
+ if mask_length < 1:
+ raise ValueError("`mask_length` has to be bigger than 0.")
+
+ if mask_length > sequence_length:
+ raise ValueError(
+ f"`mask_length` has to be smaller than `sequence_length`, but got `mask_length`: {mask_length}"
+ f" and `sequence_length`: {sequence_length}`"
+ )
+
+ # epsilon is used for probabilistic rounding
+ epsilon = np.random.rand(1).item()
+
+ def compute_num_masked_span(input_length):
+ """Given input length, compute how many spans should be masked"""
+ num_masked_span = int(mask_prob * input_length / mask_length + epsilon)
+ num_masked_span = max(num_masked_span, min_masks)
+
+ # make sure num masked span <= sequence_length
+ if num_masked_span * mask_length > sequence_length:
+ num_masked_span = sequence_length // mask_length
+
+ # make sure num_masked span is also <= input_length - (mask_length - 1)
+ if input_length - (mask_length - 1) < num_masked_span:
+ num_masked_span = max(input_length - (mask_length - 1), 0)
+
+ return num_masked_span
+
+ # compute number of masked spans in batch
+ input_lengths = (
+ attention_mask.sum(-1).detach().tolist()
+ if attention_mask is not None
+ else [sequence_length for _ in range(batch_size)]
+ )
+
+ # SpecAugment mask to fill
+ spec_aug_mask = np.zeros((batch_size, sequence_length), dtype=bool)
+ spec_aug_mask_idxs = []
+
+ max_num_masked_span = compute_num_masked_span(sequence_length)
+
+ if max_num_masked_span == 0:
+ return spec_aug_mask
+
+ for input_length in input_lengths:
+ # compute num of masked spans for this input
+ num_masked_span = compute_num_masked_span(input_length)
+
+ # get random indices to mask
+ spec_aug_mask_idx = np.random.choice(
+ np.arange(input_length - (mask_length - 1)), num_masked_span, replace=False
+ )
+
+ # pick first sampled index that will serve as a dummy index to pad vector
+ # to ensure same dimension for all batches due to probabilistic rounding
+ # Picking first sample just pads those vectors twice.
+ if len(spec_aug_mask_idx) == 0:
+ # this case can only happen if `input_length` is strictly smaller then
+ # `sequence_length` in which case the last token has to be a padding
+ # token which we can use as a dummy mask id
+ dummy_mask_idx = sequence_length - 1
+ else:
+ dummy_mask_idx = spec_aug_mask_idx[0]
+
+ spec_aug_mask_idx = np.concatenate(
+ [spec_aug_mask_idx, np.ones(max_num_masked_span - num_masked_span, dtype=np.int32) * dummy_mask_idx]
+ )
+ spec_aug_mask_idxs.append(spec_aug_mask_idx)
+
+ spec_aug_mask_idxs = np.array(spec_aug_mask_idxs)
+
+ # expand masked indices to masked spans
+ spec_aug_mask_idxs = np.broadcast_to(
+ spec_aug_mask_idxs[:, :, None], (batch_size, max_num_masked_span, mask_length)
+ )
+ spec_aug_mask_idxs = spec_aug_mask_idxs.reshape(batch_size, max_num_masked_span * mask_length)
+
+ # add offset to the starting indexes so that indexes now create a span
+ offsets = np.arange(mask_length)[None, None, :]
+ offsets = np.broadcast_to(offsets, (batch_size, max_num_masked_span, mask_length)).reshape(
+ batch_size, max_num_masked_span * mask_length
+ )
+ spec_aug_mask_idxs = spec_aug_mask_idxs + offsets
+
+ # ensure that we cannot have indices larger than sequence_length
+ if spec_aug_mask_idxs.max() > sequence_length - 1:
+ spec_aug_mask_idxs[spec_aug_mask_idxs > sequence_length - 1] = sequence_length - 1
+
+ # scatter indices to mask
+ np.put_along_axis(spec_aug_mask, spec_aug_mask_idxs, 1, -1)
+
+ return spec_aug_mask
+
+
+class WhisperPositionalEmbedding(nn.Embedding):
+ def __init__(self, num_positions: int, embedding_dim: int, padding_idx: Optional[int] = None):
+ super().__init__(num_positions, embedding_dim)
+
+ def forward(self, input_ids, past_key_values_length=0, position_ids=None):
+ if position_ids is None:
+ return self.weight[past_key_values_length: past_key_values_length + input_ids.shape[1]]
+ else:
+ return self.weight[position_ids]
+
+
+class WhisperAttention(nn.Module):
+ """Multi-headed attention from 'Attention Is All You Need' paper"""
+
+ def __init__(
+ self,
+ embed_dim: int,
+ num_heads: int,
+ dropout: float = 0.0,
+ is_decoder: bool = False,
+ bias: bool = True,
+ is_causal: bool = False,
+ layer_idx: Optional[int] = None,
+ config: Optional[WhisperVQConfig] = None,
+ ):
+ super().__init__()
+ self.embed_dim = embed_dim
+ self.num_heads = num_heads
+ self.dropout = dropout
+ self.head_dim = embed_dim // num_heads
+ self.config = config
+
+ if (self.head_dim * num_heads) != self.embed_dim:
+ raise ValueError(
+ f"embed_dim must be divisible by num_heads (got `embed_dim`: {self.embed_dim}"
+ f" and `num_heads`: {num_heads})."
+ )
+ self.scaling = self.head_dim ** -0.5
+ self.is_decoder = is_decoder
+ self.is_causal = is_causal
+
+ if layer_idx is None and is_decoder:
+ logger.warning_once(
+ f"Instantiating a decoder {self.__class__.__name__} without passing `layer_idx` is not recommended and "
+ "will to errors during the forward call, if caching is used. Please make sure to provide a `layer_idx` "
+ "when creating this class."
+ )
+ self.layer_idx = layer_idx
+
+ self.k_proj = nn.Linear(embed_dim, embed_dim, bias=False)
+ self.v_proj = nn.Linear(embed_dim, embed_dim, bias=bias)
+ self.q_proj = nn.Linear(embed_dim, embed_dim, bias=bias)
+ self.out_proj = nn.Linear(embed_dim, embed_dim, bias=bias)
+
+ # Copied from transformers.models.bart.modeling_bart.BartAttention._shape with BART->whisper
+ def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
+ return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous()
+
+ def forward(
+ self,
+ hidden_states: torch.Tensor,
+ key_value_states: Optional[torch.Tensor] = None,
+ past_key_value: Optional[EncoderDecoderCache] = None,
+ attention_mask: Optional[torch.Tensor] = None,
+ layer_head_mask: Optional[torch.Tensor] = None,
+ output_attentions: bool = False,
+ cache_position: Optional[torch.LongTensor] = None,
+ ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+ """Input shape: Batch x Time x Channel"""
+
+ # if key_value_states are provided this layer is used as a cross-attention layer
+ # for the decoder
+ is_cross_attention = key_value_states is not None
+ bsz, tgt_len, _ = hidden_states.size()
+
+ # get query proj
+ query_states = self._shape(self.q_proj(hidden_states) * self.scaling, tgt_len, bsz)
+
+ if past_key_value is not None:
+ is_updated = past_key_value.is_updated.get(self.layer_idx)
+ if is_cross_attention:
+ # after the first generated id, we can subsequently re-use all key/value_states from cache
+ past_key_value.is_updated[self.layer_idx] = True
+ past_key_value = past_key_value.cross_attention_cache
+ else:
+ past_key_value = past_key_value.self_attention_cache
+
+ # use key_value_states if cross attention
+ current_states = key_value_states if key_value_states is not None else hidden_states
+ if is_cross_attention and past_key_value and is_updated:
+ # reuse k,v, cross_attentions
+ key_states = past_key_value.key_cache[self.layer_idx]
+ value_states = past_key_value.value_cache[self.layer_idx]
+ else:
+ key_states = self._shape(self.k_proj(current_states), -1, bsz)
+ value_states = self._shape(self.v_proj(current_states), -1, bsz)
+ if past_key_value is not None:
+ # save all key/value_states to cache to be re-used for fast auto-regressive generation
+ cache_position = cache_position if not is_cross_attention else None
+ key_states, value_states = past_key_value.update(
+ key_states, value_states, self.layer_idx, {"cache_position": cache_position}
+ )
+
+ attn_weights = torch.matmul(query_states, key_states.transpose(2, 3))
+
+ if attention_mask is not None: # no matter the length, we just slice it
+ causal_mask = attention_mask[:, :, :, : key_states.shape[-2]]
+ attn_weights = attn_weights + causal_mask
+
+ attn_weights = nn.functional.softmax(attn_weights, dim=-1)
+
+ if layer_head_mask is not None:
+ if layer_head_mask.size() != (self.num_heads,):
+ raise ValueError(
+ f"Head mask for a single layer should be of size {(self.num_heads,)}, but is"
+ f" {layer_head_mask.size()}"
+ )
+ attn_weights = layer_head_mask.view(1, -1, 1, 1) * attn_weights
+
+ attn_probs = nn.functional.dropout(attn_weights, p=self.dropout, training=self.training)
+ attn_output = torch.matmul(attn_probs, value_states)
+
+ if attn_output.size() != (bsz, self.num_heads, tgt_len, self.head_dim):
+ raise ValueError(
+ f"`attn_output` should be of size {(bsz, self.num_heads, tgt_len, self.head_dim)}, but is"
+ f" {attn_output.size()}"
+ )
+
+ attn_output = attn_output.transpose(1, 2)
+ # Use the `embed_dim` from the config (stored in the class) rather than `hidden_state` because `attn_output` can be
+ # partitioned across GPUs when using tensor-parallelism.
+ attn_output = attn_output.reshape(bsz, tgt_len, self.embed_dim)
+
+ attn_output = self.out_proj(attn_output)
+
+ return attn_output, attn_weights, past_key_value
+
+
+class WhisperFlashAttention2(WhisperAttention):
+ """
+ Whisper flash attention module. This module inherits from `WhisperAttention` as the weights of the module stays
+ untouched. The only required change would be on the forward pass where it needs to correctly call the public API of
+ flash attention and deal with padding tokens in case the input contains any of them.
+ """
+
+ # Copied from transformers.models.llama.modeling_llama.LlamaFlashAttention2.__init__
+ def __init__(self, *args, **kwargs):
+ super().__init__(*args, **kwargs)
+
+ # TODO: Should be removed once Flash Attention for RoCm is bumped to 2.1.
+ # flash_attn<2.1 generates top-left aligned causal mask, while what is needed here is bottom-right alignement, that was made default for flash_attn>=2.1. This attribute is used to handle this difference. Reference: https://github.com/Dao-AILab/flash-attention/releases/tag/v2.1.0.
+ # Beware that with flash_attn<2.1, using q_seqlen != k_seqlen (except for the case q_seqlen == 1) produces a wrong mask (top-left).
+ self._flash_attn_uses_top_left_mask = not is_flash_attn_greater_or_equal_2_10()
+
+ def forward(
+ self,
+ hidden_states: torch.Tensor,
+ key_value_states: Optional[torch.Tensor] = None,
+ past_key_value: Optional[EncoderDecoderCache] = None,
+ attention_mask: Optional[torch.Tensor] = None,
+ layer_head_mask: Optional[torch.Tensor] = None,
+ output_attentions: bool = False,
+ cache_position: Optional[torch.LongTensor] = None,
+ ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+ if isinstance(past_key_value, StaticCache):
+ raise ValueError(
+ "The `static` cache implementation is not compatible with `attn_implementation='flash_attention_2'`. "
+ "Use `attn_implementation='sdpa'` in the meantime, and open an issue at https://github.com/huggingface/transformers"
+ )
+ # WhisperFlashAttention2 attention does not support output_attentions
+ if output_attentions:
+ raise ValueError("WhisperFlashAttention2 attention does not support output_attentions")
+
+ # if key_value_states are provided this layer is used as a cross-attention layer
+ # for the decoder
+ is_cross_attention = key_value_states is not None
+ bsz, tgt_len, _ = hidden_states.size()
+
+ # get query proj
+ query_states = torch.reshape(self.q_proj(hidden_states), (bsz, tgt_len, self.num_heads, self.head_dim))
+
+ if past_key_value is not None:
+ is_updated = past_key_value.is_updated.get(self.layer_idx)
+ if is_cross_attention:
+ # after the first generated id, we can subsequently re-use all key/value_states from cache
+ past_key_value.is_updated[self.layer_idx] = True
+ past_key_value = past_key_value.cross_attention_cache
+ else:
+ past_key_value = past_key_value.self_attention_cache
+
+ # use key_value_states if cross attention
+ current_states = key_value_states if key_value_states is not None else hidden_states
+ if is_cross_attention and past_key_value and is_updated:
+ # reuse k,v, cross_attentions
+ key_states = past_key_value.key_cache[self.layer_idx]
+ value_states = past_key_value.value_cache[self.layer_idx]
+ else:
+ key_states = self._shape(self.k_proj(current_states), -1, bsz)
+ value_states = self._shape(self.v_proj(current_states), -1, bsz)
+ if past_key_value is not None:
+ # save all key/value_states to cache to be re-used for fast auto-regressive generation
+ cache_position = cache_position if not is_cross_attention else None
+ key_states, value_states = past_key_value.update(
+ key_states, value_states, self.layer_idx, {"cache_position": cache_position}
+ )
+
+ # TODO: These transpose are quite inefficient but Flash Attention requires the layout [batch_size, sequence_length, num_heads, head_dim]
+ # We would need to refactor the KV cache to be able to avoid many of these transpose/reshape/view.
+ key_states = key_states.transpose(1, 2)
+ value_states = value_states.transpose(1, 2)
+
+ causal_mask = attention_mask
+ if attention_mask is not None: # no matter the length, we just slice it
+ causal_mask = attention_mask[:, :, :, : key_states.shape[-2]]
+
+ # In PEFT, usually we cast the layer norms in float32 for training stability reasons
+ # therefore the input hidden states gets silently casted in float32. Hence, we need
+ # cast them back in the correct dtype just to be sure everything works as expected.
+ # This might slowdown training & inference so it is recommended to not cast the LayerNorms
+ # in fp32. (LlamaRMSNorm handles it correctly)
+
+ input_dtype = query_states.dtype
+ if input_dtype == torch.float32:
+ if torch.is_autocast_enabled():
+ target_dtype = torch.get_autocast_gpu_dtype()
+ # Handle the case where the model is quantized
+ elif hasattr(self.config, "_pre_quantization_dtype"):
+ target_dtype = self.config._pre_quantization_dtype
+ else:
+ target_dtype = self.q_proj.weight.dtype
+
+ logger.warning_once(
+ f"The input hidden states seems to be silently casted in float32, this might be related to"
+ f" the fact you have upcasted embedding or layer norm layers in float32. We will cast back the input in"
+ f" {target_dtype}."
+ )
+
+ query_states = query_states.to(target_dtype)
+ key_states = key_states.to(target_dtype)
+ value_states = value_states.to(target_dtype)
+
+ attn_output = _flash_attention_forward(
+ query_states,
+ key_states,
+ value_states,
+ causal_mask,
+ tgt_len,
+ dropout=self.dropout,
+ is_causal=self.is_causal,
+ use_top_left_mask=self._flash_attn_uses_top_left_mask,
+ )
+
+ attn_output = attn_output.reshape(bsz, tgt_len, -1)
+ attn_output = self.out_proj(attn_output)
+
+ if not output_attentions:
+ attn_weights = None
+
+ return attn_output, attn_weights, past_key_value
+
+
+class WhisperSdpaAttention(WhisperAttention):
+ def forward(
+ self,
+ hidden_states: torch.Tensor,
+ key_value_states: Optional[torch.Tensor] = None,
+ past_key_value: Optional[EncoderDecoderCache] = None,
+ attention_mask: Optional[torch.Tensor] = None,
+ layer_head_mask: Optional[torch.Tensor] = None,
+ output_attentions: bool = False,
+ cache_position: Optional[torch.LongTensor] = None,
+ ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
+ """Input shape: Batch x Time x Channel"""
+ if output_attentions or layer_head_mask is not None:
+ # TODO: Improve this warning with e.g. `model.config._attn_implementation = "manual"` once this is implemented.
+ logger.warning_once(
+ "WhisperModel is using WhisperSdpaAttention, but `torch.nn.functional.scaled_dot_product_attention` does not support `output_attentions=True` or `layer_head_mask` not None. Falling back to the manual attention"
+ ' implementation, but specifying the manual implementation will be required from Transformers version v5.0.0 onwards. This warning can be removed using the argument `attn_implementation="eager"` when loading the model.'
+ )
+ return super().forward(
+ hidden_states,
+ key_value_states=key_value_states,
+ past_key_value=past_key_value,
+ attention_mask=attention_mask,
+ layer_head_mask=layer_head_mask,
+ output_attentions=output_attentions,
+ cache_position=cache_position,
+ )
+
+ # if key_value_states are provided this layer is used as a cross-attention layer
+ # for the decoder
+ is_cross_attention = key_value_states is not None
+ bsz, tgt_len, _ = hidden_states.size()
+
+ # get query proj
+ query_states = self._shape(self.q_proj(hidden_states), tgt_len, bsz)
+
+ if past_key_value is not None:
+ is_updated = past_key_value.is_updated.get(self.layer_idx)
+ if is_cross_attention:
+ # after the first generated id, we can subsequently re-use all key/value_states from cache
+ past_key_value.is_updated[self.layer_idx] = True
+ past_key_value = past_key_value.cross_attention_cache
+ else:
+ past_key_value = past_key_value.self_attention_cache
+
+ # use key_value_states if cross attention
+ current_states = key_value_states if key_value_states is not None else hidden_states
+ if is_cross_attention and past_key_value and is_updated:
+ # reuse k,v, cross_attentions
+ key_states = past_key_value.key_cache[self.layer_idx]
+ value_states = past_key_value.value_cache[self.layer_idx]
+ else:
+ key_states = self._shape(self.k_proj(current_states), -1, bsz)
+ value_states = self._shape(self.v_proj(current_states), -1, bsz)
+ if past_key_value is not None:
+ # save all key/value_states to cache to be re-used for fast auto-regressive generation
+ cache_position = cache_position if not is_cross_attention else None
+ key_states, value_states = past_key_value.update(
+ key_states, value_states, self.layer_idx, {"cache_position": cache_position}
+ )
+
+ causal_mask = attention_mask
+ if attention_mask is not None: # no matter the length, we just slice it
+ causal_mask = attention_mask[:, :, :, : key_states.shape[-2]]
+
+ # We dispatch to SDPA's Flash Attention or Efficient kernels via this `is_causal` if statement instead of an inline conditional assignment
+ # in SDPA to support both torch.compile's dynamic shapes and full graph options. An inline conditional prevents dynamic shapes from compiling.
+ # The tgt_len > 1 is necessary to match with AttentionMaskConverter.to_causal_4d that does not create a causal mask in case tgt_len == 1.
+ is_causal = True if self.is_causal and causal_mask is None and tgt_len > 1 else False
+
+ # NOTE: SDPA with memory-efficient backend is currently (torch==2.1.2) bugged when using non-contiguous inputs and a custom attn_mask,
+ # but we are fine here as `_shape` do call `.contiguous()`. Reference: https://github.com/pytorch/pytorch/issues/112577
+ attn_output = torch.nn.functional.scaled_dot_product_attention(
+ query_states,
+ key_states,
+ value_states,
+ attn_mask=causal_mask,
+ dropout_p=self.dropout if self.training else 0.0,
+ is_causal=is_causal,
+ )
+
+ if attn_output.size() != (bsz, self.num_heads, tgt_len, self.head_dim):
+ raise ValueError(
+ f"`attn_output` should be of size {(bsz, self.num_heads, tgt_len, self.head_dim)}, but is"
+ f" {attn_output.size()}"
+ )
+
+ attn_output = attn_output.transpose(1, 2)
+
+ # Use the `embed_dim` from the config (stored in the class) rather than `hidden_state` because `attn_output` can be
+ # partitioned across GPUs when using tensor-parallelism.
+ attn_output = attn_output.reshape(bsz, tgt_len, self.embed_dim)
+
+ attn_output = self.out_proj(attn_output)
+
+ return attn_output, None, past_key_value
+
+
+WHISPER_ATTENTION_CLASSES = {
+ "eager": WhisperAttention,
+ # "flash_attention_2": WhisperFlashAttention2,
+ "sdpa": WhisperSdpaAttention,
+}
+
+
+# Copied from transformers.models.mbart.modeling_mbart.MBartEncoderLayer with MBart->Whisper, MBART->WHISPER
+class WhisperVQEncoderLayer(nn.Module):
+ def __init__(self, config: WhisperVQConfig, is_causal=False):
+ super().__init__()
+ self.embed_dim = config.d_model
+
+ self.self_attn = WHISPER_ATTENTION_CLASSES[config._attn_implementation](
+ embed_dim=self.embed_dim,
+ num_heads=config.encoder_attention_heads,
+ dropout=config.attention_dropout,
+ config=config,
+ is_causal=is_causal
+ )
+ self.is_causal = is_causal
+ if self.is_causal:
+ assert isinstance(self.self_attn, WhisperSdpaAttention), "Causal attention is only supported for SDPA"
+ self.self_attn_layer_norm = nn.LayerNorm(self.embed_dim)
+ self.dropout = config.dropout
+ self.activation_fn = ACT2FN[config.activation_function]
+ self.activation_dropout = config.activation_dropout
+ self.fc1 = nn.Linear(self.embed_dim, config.encoder_ffn_dim)
+ self.fc2 = nn.Linear(config.encoder_ffn_dim, self.embed_dim)
+ self.final_layer_norm = nn.LayerNorm(self.embed_dim)
+
+ def forward(
+ self,
+ hidden_states: torch.Tensor,
+ attention_mask: torch.Tensor,
+ layer_head_mask: torch.Tensor,
+ output_attentions: bool = False,
+ ) -> torch.Tensor:
+ """
+ Args:
+ hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
+ attention_mask (`torch.FloatTensor`): attention mask of size
+ `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
+ layer_head_mask (`torch.FloatTensor`): mask for attention heads in a given layer of size
+ `(encoder_attention_heads,)`.
+ output_attentions (`bool`, *optional*):
+ Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+ returned tensors for more detail.
+ """
+ residual = hidden_states
+ hidden_states = self.self_attn_layer_norm(hidden_states)
+ hidden_states, attn_weights, _ = self.self_attn(
+ hidden_states=hidden_states,
+ attention_mask=attention_mask if not self.is_causal else None,
+ layer_head_mask=layer_head_mask,
+ output_attentions=output_attentions,
+ )
+ hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
+ hidden_states = residual + hidden_states
+
+ residual = hidden_states
+ hidden_states = self.final_layer_norm(hidden_states)
+ hidden_states = self.activation_fn(self.fc1(hidden_states))
+ hidden_states = nn.functional.dropout(hidden_states, p=self.activation_dropout, training=self.training)
+ hidden_states = self.fc2(hidden_states)
+ hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
+ hidden_states = residual + hidden_states
+
+ if hidden_states.dtype == torch.float16 and (
+ torch.isinf(hidden_states).any() or torch.isnan(hidden_states).any()
+ ):
+ clamp_value = torch.finfo(hidden_states.dtype).max - 1000
+ hidden_states = torch.clamp(hidden_states, min=-clamp_value, max=clamp_value)
+
+ outputs = (hidden_states,)
+
+ if output_attentions:
+ outputs += (attn_weights,)
+
+ return outputs
+
+
+class WhisperDecoderLayer(nn.Module):
+ def __init__(self, config: WhisperVQConfig, layer_idx: int = None):
+ super().__init__()
+ self.embed_dim = config.d_model
+
+ self.self_attn = WHISPER_ATTENTION_CLASSES[config._attn_implementation](
+ embed_dim=self.embed_dim,
+ num_heads=config.decoder_attention_heads,
+ dropout=config.attention_dropout,
+ is_decoder=True,
+ is_causal=True,
+ layer_idx=layer_idx,
+ config=config,
+ )
+ self.dropout = config.dropout
+ self.activation_fn = ACT2FN[config.activation_function]
+ self.activation_dropout = config.activation_dropout
+
+ self.self_attn_layer_norm = nn.LayerNorm(self.embed_dim)
+ self.encoder_attn = WHISPER_ATTENTION_CLASSES[config._attn_implementation](
+ self.embed_dim,
+ config.decoder_attention_heads,
+ dropout=config.attention_dropout,
+ is_decoder=True,
+ layer_idx=layer_idx,
+ config=config,
+ )
+ self.encoder_attn_layer_norm = nn.LayerNorm(self.embed_dim)
+ self.fc1 = nn.Linear(self.embed_dim, config.decoder_ffn_dim)
+ self.fc2 = nn.Linear(config.decoder_ffn_dim, self.embed_dim)
+ self.final_layer_norm = nn.LayerNorm(self.embed_dim)
+
+ def forward(
+ self,
+ hidden_states: torch.Tensor,
+ attention_mask: Optional[torch.Tensor] = None,
+ encoder_hidden_states: Optional[torch.Tensor] = None,
+ encoder_attention_mask: Optional[torch.Tensor] = None,
+ layer_head_mask: Optional[torch.Tensor] = None,
+ cross_attn_layer_head_mask: Optional[torch.Tensor] = None,
+ past_key_value: Optional[EncoderDecoderCache] = None,
+ output_attentions: Optional[bool] = False,
+ use_cache: Optional[bool] = True,
+ cache_position: Optional[torch.LongTensor] = None,
+ ) -> torch.Tensor:
+ """
+ Args:
+ hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)`
+ attention_mask (`torch.FloatTensor`): attention mask of size
+ `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
+ encoder_hidden_states (`torch.FloatTensor`):
+ cross attention input to the layer of shape `(batch, seq_len, embed_dim)`
+ encoder_attention_mask (`torch.FloatTensor`): encoder attention mask of size
+ `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values.
+ layer_head_mask (`torch.FloatTensor`): mask for attention heads in a given layer of size
+ `(encoder_attention_heads,)`.
+ cross_attn_layer_head_mask (`torch.FloatTensor`): mask for cross-attention heads in a given layer of
+ size `(decoder_attention_heads,)`.
+ past_key_value (`Tuple(torch.FloatTensor)`): cached past key and value projection states
+ output_attentions (`bool`, *optional*):
+ Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+ returned tensors for more detail.
+ """
+ residual = hidden_states
+ hidden_states = self.self_attn_layer_norm(hidden_states)
+
+ # Self Attention
+ hidden_states, self_attn_weights, present_key_value = self.self_attn(
+ hidden_states=hidden_states,
+ past_key_value=past_key_value,
+ attention_mask=attention_mask,
+ layer_head_mask=layer_head_mask,
+ output_attentions=output_attentions,
+ cache_position=cache_position,
+ )
+ hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
+ hidden_states = residual + hidden_states
+
+ # Cross-Attention Block
+ cross_attn_weights = None
+ if encoder_hidden_states is not None:
+ residual = hidden_states
+ hidden_states = self.encoder_attn_layer_norm(hidden_states)
+ hidden_states, cross_attn_weights, cross_attn_present_key_value = self.encoder_attn(
+ hidden_states=hidden_states,
+ key_value_states=encoder_hidden_states,
+ attention_mask=encoder_attention_mask,
+ layer_head_mask=cross_attn_layer_head_mask,
+ past_key_value=past_key_value,
+ output_attentions=output_attentions,
+ )
+ hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
+ hidden_states = residual + hidden_states
+
+ # add cross-attn to positions 1 of present_key_value tuple
+ present_key_value = (present_key_value, cross_attn_present_key_value)
+
+ # Fully Connected
+ residual = hidden_states
+ hidden_states = self.final_layer_norm(hidden_states)
+ hidden_states = self.activation_fn(self.fc1(hidden_states))
+ hidden_states = nn.functional.dropout(hidden_states, p=self.activation_dropout, training=self.training)
+ hidden_states = self.fc2(hidden_states)
+ hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
+ hidden_states = residual + hidden_states
+
+ outputs = (hidden_states,)
+
+ if output_attentions:
+ outputs += (self_attn_weights, cross_attn_weights)
+
+ if use_cache:
+ outputs += (present_key_value,)
+
+ return outputs
+
+
+class WhisperPreTrainedModel(PreTrainedModel):
+ config_class = WhisperVQConfig
+ base_model_prefix = "model"
+ main_input_name = "input_features"
+ supports_gradient_checkpointing = True
+ _no_split_modules = ["WhisperEncoderLayer", "WhisperDecoderLayer"]
+ _supports_flash_attn_2 = True
+ _supports_sdpa = True
+ _supports_cache_class = True
+ _supports_static_cache = True
+
+ def _init_weights(self, module):
+ std = self.config.init_std
+ if isinstance(module, (nn.Linear, nn.Conv1d)):
+ module.weight.data.normal_(mean=0.0, std=std)
+ if module.bias is not None:
+ module.bias.data.zero_()
+ elif isinstance(module, nn.Embedding):
+ module.weight.data.normal_(mean=0.0, std=std)
+ if module.padding_idx is not None:
+ module.weight.data[module.padding_idx].zero_()
+ elif isinstance(module, WhisperVQEncoder):
+ with torch.no_grad():
+ embed_positions = module.embed_positions.weight
+ embed_positions.copy_(sinusoids(*embed_positions.shape))
+
+ def _get_feat_extract_output_lengths(self, input_lengths: torch.LongTensor):
+ """
+ Computes the output length of the convolutional layers
+ """
+ input_lengths = (input_lengths - 1) // 2 + 1
+
+ return input_lengths
+
+
+WHISPER_START_DOCSTRING = r"""
+ This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the
+ library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads
+ etc.)
+
+ This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass.
+ Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage
+ and behavior.
+
+ Parameters:
+ config ([`WhisperConfig`]):
+ Model configuration class with all the parameters of the model. Initializing with a config file does not
+ load the weights associated with the model, only the configuration. Check out the
+ [`~PreTrainedModel.from_pretrained`] method to load the model weights.
+"""
+
+WHISPER_INPUTS_DOCSTRING = r"""
+ Args:
+ input_features (`torch.FloatTensor` of shape `(batch_size, feature_size, sequence_length)`):
+ Float values mel features extracted from the raw speech waveform. Raw speech waveform can be obtained by
+ loading a `.flac` or `.wav` audio file into an array of type `List[float]` or a `numpy.ndarray`, *e.g.* via
+ the soundfile library (`pip install soundfile`). To prepare the array into `input_features`, the
+ [`AutoFeatureExtractor`] should be used for extracting the mel features, padding and conversion into a
+ tensor of type `torch.FloatTensor`. See [`~WhisperFeatureExtractor.__call__`]
+ attention_mask (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+ Mask to avoid performing *SpecAugment* data augmentation on padding token indices. Mask values selected in
+ `[0, 1]`:
+
+ - 1 for tokens that are **not masked**,
+ - 0 for tokens that are **masked**.
+
+ [What are attention masks?](../glossary#attention-mask)
+ decoder_input_ids (`torch.LongTensor` of shape `(batch_size, target_sequence_length)`, *optional*):
+ Indices of decoder input sequence tokens in the vocabulary.
+
+ Indices can be obtained using [`WhisperTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+ [`PreTrainedTokenizer.__call__`] for details.
+
+ [What are decoder input IDs?](../glossary#decoder-input-ids)
+
+ Whisper uses the `decoder_start_token_id` as the starting token for `decoder_input_ids` generation. If
+ `past_key_values` is used, optionally only the last `decoder_input_ids` have to be input (see
+ `past_key_values`).
+ decoder_attention_mask (`torch.LongTensor` of shape `(batch_size, target_sequence_length)`, *optional*):
+ Default behavior: generate a tensor that ignores pad tokens in `decoder_input_ids`. Causal mask will also
+ be used by default.
+
+ If you want to change padding behavior, you should read
+ [`modeling_whisper._prepare_decoder_attention_mask`] and modify to your needs. See diagram 1 in [the BART
+ paper](https://arxiv.org/abs/1910.13461) for more information on the default strategy.
+ head_mask (`torch.Tensor` of shape `(encoder_layers, encoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the attention modules in the encoder. Mask values selected in `[0, 1]`:
+
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+
+ decoder_head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the attention modules in the decoder. Mask values selected in `[0, 1]`:
+
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+
+ cross_attn_head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the cross-attention modules. Mask values selected in `[0, 1]`:
+
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+
+ encoder_outputs (`tuple(tuple(torch.FloatTensor)`, *optional*):
+ Tuple consists of (`last_hidden_state`, *optional*: `hidden_states`, *optional*: `attentions`)
+ `last_hidden_state` of shape `(batch_size, sequence_length, hidden_size)`, *optional*) is a sequence of
+ hidden-states at the output of the last layer of the encoder. Used in the cross-attention of the decoder.
+ past_key_values (`EncoderDecoderCache` or `tuple(tuple(torch.FloatTensor))`, *optional*):
+ Pre-computed hidden-states that can be used to speed up auto-regressive (sequential) decoding. There are
+ four sets of pre-computed hidden-states: key and values states in the self-attention blocks (2) and
+ in the cross-attention blocks (2). The `past_key_values` are returned when `use_cache=True` is passed or
+ when `config.use_cache=True`
+
+ Two formats are allowed:
+ - An [`~cache_utils.EncoderDecoderCache`] instance;
+ - Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of shape
+ `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape
+ `(batch_size, num_heads, encoder_sequence_length, embed_size_per_head)`.
+
+ If `past_key_values` are used, the user can optionally input only the last `decoder_input_ids` (those that
+ don't have their past key value states given to this model) of shape `(batch_size, 1)` instead of all
+ `decoder_input_ids` of shape `(batch_size, sequence_length)`.
+ decoder_inputs_embeds (`torch.FloatTensor` of shape `(batch_size, target_sequence_length, hidden_size)`, *optional*):
+ Optionally, instead of passing `decoder_input_ids` you can choose to directly pass an embedded
+ representation. If `past_key_values` is used, optionally only the last `decoder_inputs_embeds` have to be
+ input (see `past_key_values`). This is useful if you want more control over how to convert
+ `decoder_input_ids` indices into associated vectors than the model's internal embedding lookup matrix.
+ use_cache (`bool`, *optional*):
+ If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see
+ `past_key_values`).
+ output_attentions (`bool`, *optional*):
+ Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned
+ tensors for more detail.
+ output_hidden_states (`bool`, *optional*):
+ Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for
+ more detail.
+ return_dict (`bool`, *optional*):
+ Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+ cache_position (`torch.LongTensor` of shape `(sequence_length)`, *optional*):
+ Indices depicting the position of the input sequence tokens in the sequence. It is used to update the cache
+ in the correct position and to infer the complete sequence length.
+"""
+
+WHISPER_ENCODER_INPUTS_DOCSTRING = r"""
+ Args:
+ input_features (`torch.FloatTensor` of shape `(batch_size, feature_size, sequence_length)`):
+ Float values mel features extracted from the raw speech waveform. Raw speech waveform can be obtained by
+ loading a `.flac` or `.wav` audio file into an array of type `List[float]` or a `numpy.ndarray`, *e.g.* via
+ the soundfile library (`pip install soundfile`). To prepare the array into `input_features`, the
+ [`AutoFeatureExtractor`] should be used for extracting the mel features, padding and conversion into a
+ tensor of type `torch.FloatTensor`. See [`~WhisperFeatureExtractor.__call__`]
+ head_mask (`torch.Tensor` of shape `(encoder_layers, encoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the attention modules in the encoder. Mask values selected in `[0, 1]`:
+
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+ encoder_outputs (`tuple(tuple(torch.FloatTensor)`, *optional*):
+ Tuple consists of (`last_hidden_state`, *optional*: `hidden_states`, *optional*: `attentions`)
+ `last_hidden_state` of shape `(batch_size, sequence_length, hidden_size)`, *optional*) is a sequence of
+ hidden-states at the output of the last layer of the encoder.
+ output_attentions (`bool`, *optional*):
+ Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned
+ tensors for more detail.
+ output_hidden_states (`bool`, *optional*):
+ Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for
+ more detail.
+ return_dict (`bool`, *optional*):
+ Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+"""
+
+
+class WhisperVQEncoder(WhisperPreTrainedModel):
+ """
+ Transformer encoder consisting of *config.encoder_layers* self attention layers. Each layer is a
+ [`WhisperEncoderLayer`].
+
+ Args:
+ config: WhisperConfig
+ """
+
+ def __init__(self, config: WhisperVQConfig):
+ super().__init__(config)
+ self.config = config
+ self.dropout = config.dropout
+ self.layerdrop = config.encoder_layerdrop
+
+ embed_dim = config.d_model
+ self.num_mel_bins = config.num_mel_bins
+ self.padding_idx = config.pad_token_id
+ self.max_source_positions = config.max_source_positions
+ self.embed_scale = math.sqrt(embed_dim) if config.scale_embedding else 1.0
+ if config.encoder_causal_convolution:
+ conv_class = CausalConv1d
+ else:
+ conv_class = nn.Conv1d
+ self.conv1 = conv_class(self.num_mel_bins, embed_dim, kernel_size=3, padding=1)
+ self.conv2 = conv_class(embed_dim, embed_dim, kernel_size=3, stride=2, padding=1)
+
+ self.embed_positions = nn.Embedding(self.max_source_positions, embed_dim)
+ self.embed_positions.requires_grad_(False)
+ if config.quantize_encoder_only:
+ self.layers = nn.ModuleList([WhisperVQEncoderLayer(config,
+ is_causal=config.encoder_causal_attention or config.quantize_causal_encoder)
+ for _ in range(config.quantize_position)])
+ else:
+ self.layers = nn.ModuleList([WhisperVQEncoderLayer(config, is_causal=config.encoder_causal_attention or (
+ config.quantize_causal_encoder and layer_id < config.quantize_position)) for layer_id in
+ range(config.encoder_layers)])
+ self.layer_norm = nn.LayerNorm(config.d_model)
+
+ self.gradient_checkpointing = False
+ # Parameters related to pooling layer
+ self.pooling_layer = None
+ # Parameters related to quantization layer
+ self.codebook = None
+ self.embed_positions2 = None
+ self.quantize_loss = None
+ self.num_active_codes = None
+ self.quantize_ema_count = 0
+ # Save hiddens
+ self.save_hidden_dir = None
+ self.save_hidden_position = None
+ # Initialize weights and apply final processing
+ self.init_pooling_layer(config)
+ self.init_quantize_layer(config)
+ self.post_init()
+
+ def init_pooling_layer(self, config: WhisperVQConfig):
+ if config.pooling_kernel_size is not None:
+ if config.pooling_type == "max":
+ self.pooling_layer = nn.MaxPool1d(kernel_size=config.pooling_kernel_size)
+ elif config.pooling_type == "avg":
+ self.pooling_layer = nn.AvgPool1d(kernel_size=config.pooling_kernel_size)
+ else:
+ raise NotImplementedError(f"Pooling type {config.pooling_type} not implemented")
+
+ def init_quantize_layer(self, config: WhisperVQConfig, quantize_load_codebook=None):
+ if config.quantize_vocab_size is not None:
+ if config.pooling_position is not None:
+ assert config.quantize_position >= config.pooling_position
+ self.codebook = nn.Embedding(config.quantize_vocab_size, self.config.d_model)
+ if quantize_load_codebook is not None:
+ init_codes = np.load(quantize_load_codebook)
+ self.codebook.weight.data.copy_(torch.from_numpy(init_codes))
+ max_source_positions = self.max_source_positions
+ if config.pooling_kernel_size is not None:
+ max_source_positions = math.ceil(max_source_positions / self.config.pooling_kernel_size)
+ self.embed_positions2 = nn.Embedding(max_source_positions, self.config.d_model)
+ self.embed_positions2.weight.data.copy_(self.embed_positions.weight.data[:max_source_positions])
+ if config.quantize_ema_decay is not None:
+ self.codebook.weight.requires_grad = False
+ self.register_buffer("ema_count", torch.ones(config.quantize_vocab_size, dtype=torch.float))
+ self.register_buffer("ema_weight", self.codebook.weight.data.clone().float())
+
+ def _freeze_parameters(self):
+ for param in self.parameters():
+ param.requires_grad = False
+ self._requires_grad = False
+
+ def get_input_embeddings(self) -> nn.Module:
+ return self.conv1
+
+ def set_input_embeddings(self, value: nn.Module):
+ self.conv1 = value
+
+ def get_block_causal_attention_mask(self, attention_mask, block_size=50):
+ dtype = self.dtype
+ batch_size, seq_length = attention_mask.shape
+ causal_mask = torch.torch.tril(
+ torch.ones(1, seq_length, seq_length, dtype=torch.bool, device=attention_mask.device))
+ block_square_mask = []
+ for start in range(0, seq_length, block_size):
+ end = min(start + block_size, seq_length)
+ length = end - start
+ block_square_mask.append(causal_mask.new_ones((length, length)))
+ block_square_mask = torch.block_diag(*block_square_mask)
+ block_causal_mask = causal_mask | block_square_mask
+ block_causal_mask = block_causal_mask & attention_mask[:, None, :]
+ block_causal_mask = block_causal_mask.to(dtype=dtype) # fp16 compatibility
+ block_causal_mask = (1.0 - block_causal_mask) * torch.finfo(dtype).min
+ block_causal_mask = block_causal_mask.unsqueeze(1)
+ return block_causal_mask
+
+ def forward(
+ self,
+ input_features,
+ attention_mask=None,
+ head_mask=None,
+ output_attentions=None,
+ output_hidden_states=None,
+ return_dict=None,
+ quantized_token_ids=None
+ ):
+ r"""
+ Args:
+ input_features (`torch.LongTensor` of shape `(batch_size, feature_size, sequence_length)`):
+ Float values of mel features extracted from the raw speech waveform. Raw speech waveform can be
+ obtained by loading a `.flac` or `.wav` audio file into an array of type `List[float]` or a
+ `numpy.ndarray`, *e.g.* via the soundfile library (`pip install soundfile`). To prepare the array into
+ `input_features`, the [`AutoFeatureExtractor`] should be used for extracting the mel features, padding
+ and conversion into a tensor of type `torch.FloatTensor`. See [`~WhisperFeatureExtractor.__call__`]
+ attention_mask (`torch.Tensor`)`, *optional*):
+ Whisper does not support masking of the `input_features`, this argument is preserved for compatibility,
+ but it is not used. By default the silence in the input log mel spectrogram are ignored.
+ head_mask (`torch.Tensor` of shape `(encoder_layers, encoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the attention modules. Mask values selected in `[0, 1]`:
+
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+ output_attentions (`bool`, *optional*):
+ Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+ returned tensors for more detail.
+ output_hidden_states (`bool`, *optional*):
+ Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors
+ for more detail.
+ return_dict (`bool`, *optional*):
+ Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+ """
+
+ # expected_seq_length = self.config.max_source_positions * self.conv1.stride[0] * self.conv2.stride[0]
+ # if input_features.shape[-1] != expected_seq_length:
+ # raise ValueError(
+ # f"Whisper expects the mel input features to be of length {expected_seq_length}, but found {input_features.shape[-1]}. Make sure to pad the input mel features to {expected_seq_length}."
+ # )
+
+ batch_size, feature_size, seq_length = input_features.shape
+ seq_length = seq_length // (self.conv1.stride[0] * self.conv2.stride[0])
+
+ attention_mask = attention_mask[:, :: self.conv1.stride[0] * self.conv2.stride[0]]
+ if self.config.quantize_causal_block_size is not None:
+ extended_attention_mask = self.get_block_causal_attention_mask(attention_mask,
+ block_size=self.config.quantize_causal_block_size)
+ else:
+ extended_attention_mask = self.get_extended_attention_mask(attention_mask, (batch_size, seq_length))
+ output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+ output_hidden_states = (
+ output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+ )
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+ inputs_embeds = nn.functional.gelu(self.conv1(input_features))
+ inputs_embeds = nn.functional.gelu(self.conv2(inputs_embeds))
+
+ inputs_embeds = inputs_embeds.permute(0, 2, 1)
+ embed_pos = self.embed_positions.weight
+
+ hidden_states = inputs_embeds + embed_pos[:seq_length]
+ hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
+
+ encoder_states = () if output_hidden_states else None
+ all_attentions = () if output_attentions else None
+
+ assert attention_mask.shape[-1] == hidden_states.shape[1]
+ # check if head_mask has a correct number of layers specified if desired
+ if head_mask is not None:
+ assert head_mask.size()[0] == (
+ len(self.layers)
+ ), f"The head_mask should be specified for {len(self.layers)} layers, but it is for {head_mask.size()[0]}."
+ for idx, encoder_layer in enumerate(self.layers):
+ if output_hidden_states:
+ encoder_states = encoder_states + (hidden_states,)
+ # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description)
+ to_drop = False
+ if self.training:
+ dropout_probability = torch.rand([])
+ if dropout_probability < self.layerdrop: # skip the layer
+ to_drop = True
+
+ if to_drop:
+ layer_outputs = (None, None)
+ else:
+ if self.gradient_checkpointing and self.training:
+ layer_outputs = self._gradient_checkpointing_func(
+ encoder_layer.__call__,
+ hidden_states,
+ extended_attention_mask,
+ (head_mask[idx] if head_mask is not None else None),
+ output_attentions,
+ )
+ else:
+ layer_outputs = encoder_layer(
+ hidden_states,
+ extended_attention_mask,
+ layer_head_mask=(head_mask[idx] if head_mask is not None else None),
+ output_attentions=output_attentions,
+ )
+
+ hidden_states = layer_outputs[0]
+
+ if output_attentions:
+ all_attentions = all_attentions + (layer_outputs[1],)
+ if idx + 1 == self.config.pooling_position and self.config.pooling_kernel_size is not None:
+ hidden_states = hidden_states.permute(0, 2, 1)
+ if hidden_states.shape[-1] % self.config.pooling_kernel_size != 0:
+ hidden_states = torch.nn.functional.pad(hidden_states, (
+ 0, self.config.pooling_kernel_size - hidden_states.shape[-1] % self.config.pooling_kernel_size))
+ hidden_states = self.pooling_layer(hidden_states).permute(0, 2, 1)
+ attention_mask = attention_mask[:, ::self.config.pooling_kernel_size]
+ if self.config.quantize_causal_block_size is not None:
+ extended_attention_mask = self.get_block_causal_attention_mask(attention_mask, block_size=self.config.quantize_causal_block_size // self.config.pooling_kernel_size)
+ else:
+ extended_attention_mask = self.get_extended_attention_mask(attention_mask, (
+ batch_size, seq_length // self.config.pooling_kernel_size))
+
+ if idx + 1 == self.config.quantize_position and self.config.quantize_vocab_size is not None:
+ if quantized_token_ids is not None:
+ hidden_states = self.codebook(quantized_token_ids)
+ else:
+ hidden_quantized, indices_flat, distances = vector_quantize(hidden_states, self.codebook.weight)
+ quantized_token_ids = indices_flat.reshape(batch_size, hidden_quantized.shape[1])
+ if self.training:
+ encodings = torch.nn.functional.one_hot(indices_flat, self.config.quantize_vocab_size).float()
+ encodings = encodings * attention_mask.reshape(-1, 1)
+ n = torch.sum(encodings, dim=0)
+ torch.distributed.all_reduce(n, op=torch.distributed.ReduceOp.SUM)
+ self.num_active_codes = n.nonzero().shape[0]
+ if self.config.quantize_ema_decay:
+ hidden_flat = hidden_states.detach().float().reshape(-1, hidden_states.shape[-1])
+ with torch.autocast(device_type='cuda', dtype=torch.float32):
+ dw = torch.matmul(encodings.t(), hidden_flat)
+ torch.distributed.all_reduce(dw, op=torch.distributed.ReduceOp.SUM)
+ self.ema_count = self.ema_count * self.config.quantize_ema_decay + (
+ 1 - self.config.quantize_ema_decay) * n
+ total_count = torch.sum(self.ema_count)
+ self.ema_count = (self.ema_count + 1e-5) / (
+ total_count + self.config.quantize_vocab_size * 1e-5) * total_count
+ self.ema_weight = self.ema_weight * self.config.quantize_ema_decay + (
+ 1 - self.config.quantize_ema_decay) * dw
+ self.codebook.weight.data = self.ema_weight / self.ema_count.unsqueeze(1)
+ self.quantize_loss = self.config.quantize_loss_scale * self.config.quantize_commit_coefficient * mse_loss_with_mask(
+ hidden_states, hidden_quantized.detach(), attention_mask)
+ self.quantize_ema_count += 1
+ if self.config.quantize_restart_interval is not None and self.quantize_ema_count % self.config.quantize_restart_interval == 0:
+ rank, world_size = torch.distributed.get_rank(), torch.distributed.get_world_size()
+ segment_vocab_size = self.config.quantize_vocab_size // world_size
+ start_idx = segment_vocab_size * rank
+ ema_count_segment = self.ema_count[start_idx: start_idx + segment_vocab_size]
+ threshold = 1 * (
+ self.config.quantize_ema_decay ** self.config.quantize_restart_interval)
+ update_indices = (ema_count_segment < threshold).nonzero()[:, 0] + start_idx
+ num_update = update_indices.shape[0]
+ mask_flat = attention_mask.reshape(-1) > 0
+ hidden_selected = hidden_flat[mask_flat]
+ hidden_update = hidden_selected[random.sample(range(len(hidden_selected)), num_update)]
+ num_update = torch.as_tensor([num_update], dtype=torch.long,
+ device=hidden_states.device)
+ num_update_list = [torch.as_tensor([0], dtype=torch.long, device=hidden_states.device)
+ for _
+ in range(world_size)]
+ torch.distributed.all_gather(num_update_list, num_update)
+ update_indices_list = [
+ torch.zeros(num.item(), dtype=torch.long, device=hidden_states.device) for num in
+ num_update_list]
+ torch.distributed.all_gather(update_indices_list, update_indices)
+ update_indices = torch.cat(update_indices_list)
+ hidden_update_list = [
+ torch.zeros(num.item(), hidden_flat.shape[-1], dtype=hidden_update.dtype,
+ device=hidden_states.device) for num in num_update_list]
+ torch.distributed.all_gather(hidden_update_list, hidden_update)
+ hidden_update = torch.cat(hidden_update_list)
+ self.codebook.weight.data[update_indices] = hidden_update
+ self.ema_count[update_indices] = 1
+ self.ema_weight[update_indices] = hidden_update
+ if torch.distributed.get_rank() == 0:
+ print(f"restart {len(update_indices)} tokens")
+ else:
+ loss = self.config.quantize_loss_scale * (
+ self.config.quantize_commit_coefficient * mse_loss_with_mask(hidden_states,
+ hidden_quantized.detach(),
+ attention_mask) + mse_loss_with_mask(
+ hidden_quantized, hidden_states.detach(), attention_mask))
+ self.quantize_loss = loss
+ hidden_states = hidden_states + (hidden_quantized - hidden_states).detach()
+ else:
+ hidden_states = hidden_quantized
+ hidden_states = hidden_states + self.embed_positions2.weight[:hidden_states.shape[1]]
+
+ if idx + 1 == self.save_hidden_position:
+ import numpy as np
+ import uuid
+ to_save = []
+ for batch_idx, hidden_state in enumerate(hidden_states):
+ for seq_idx, hidden in enumerate(hidden_state):
+ if attention_mask[batch_idx, seq_idx]:
+ to_save.append(hidden.detach().cpu().numpy())
+ np.save(os.path.join(self.save_hidden_dir, f"{str(uuid.uuid4())}.npy"), to_save)
+ if not self.config.quantize_encoder_only:
+ hidden_states = self.layer_norm(hidden_states)
+ if output_hidden_states:
+ encoder_states = encoder_states + (hidden_states,)
+
+ if not return_dict:
+ return tuple(v for v in [hidden_states, encoder_states, all_attentions] if v is not None)
+ return QuantizedBaseModelOutput(
+ last_hidden_state=hidden_states, hidden_states=encoder_states, attentions=all_attentions,
+ quantized_token_ids=quantized_token_ids,
+ )
+
+
+class WhisperVQDecoder(WhisperPreTrainedModel):
+ """
+ Transformer decoder consisting of *config.decoder_layers* layers. Each layer is a [`WhisperDecoderLayer`]
+
+ Args:
+ config: WhisperConfig
+ """
+
+ main_input_name = "input_ids"
+
+ def __init__(self, config: WhisperVQConfig):
+ super().__init__(config)
+ self.dropout = config.dropout
+ self.layerdrop = config.decoder_layerdrop
+ self.padding_idx = config.pad_token_id
+ self.max_target_positions = config.max_target_positions
+ self.max_source_positions = config.max_source_positions
+ self.embed_scale = math.sqrt(config.d_model) if config.scale_embedding else 1.0
+
+ self.embed_tokens = nn.Embedding(config.vocab_size, config.d_model, self.padding_idx)
+ self.embed_positions = WhisperPositionalEmbedding(self.max_target_positions, config.d_model)
+
+ self.layers = nn.ModuleList(
+ [WhisperDecoderLayer(config, layer_idx) for layer_idx in range(config.decoder_layers)]
+ )
+ self._use_flash_attention_2 = config._attn_implementation == "flash_attention_2"
+ self._use_sdpa = config._attn_implementation == "sdpa"
+
+ self.layer_norm = nn.LayerNorm(config.d_model)
+
+ self.gradient_checkpointing = False
+ # Initialize weights and apply final processing
+ self.post_init()
+
+ def get_input_embeddings(self):
+ return self.embed_tokens
+
+ def set_input_embeddings(self, value):
+ self.embed_tokens = value
+
+ def forward(
+ self,
+ input_ids=None,
+ attention_mask=None,
+ encoder_hidden_states=None,
+ encoder_attention_mask=None,
+ head_mask=None,
+ cross_attn_head_mask=None,
+ past_key_values=None,
+ inputs_embeds=None,
+ position_ids=None,
+ use_cache=None,
+ output_attentions=None,
+ output_hidden_states=None,
+ return_dict=None,
+ cache_position=None,
+ ):
+ r"""
+ Args:
+ input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):
+ Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
+ provide it.
+
+ Indices can be obtained using [`WhisperTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+ [`PreTrainedTokenizer.__call__`] for details.
+
+ [What are input IDs?](../glossary#input-ids)
+ attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):
+ Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:
+
+ - 1 for tokens that are **not masked**,
+ - 0 for tokens that are **masked**.
+
+ [What are attention masks?](../glossary#attention-mask)
+ encoder_hidden_states (`torch.FloatTensor` of shape `(batch_size, encoder_sequence_length, hidden_size)`, *optional*):
+ Sequence of hidden-states at the output of the last layer of the encoder. Used in the cross-attention
+ of the decoder.]
+ encoder_attention_mask (`torch.LongTensor` of shape `(batch_size, encoder_sequence_length)`, *optional*):
+ head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the attention modules. Mask values selected in `[0, 1]`:
+
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+
+ cross_attn_head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the attention modules in encoder to avoid performing cross-attention
+ on hidden heads. Mask values selected in `[0, 1]`:
+
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+
+ past_key_values (`EncoderDecoderCache` or `tuple(tuple(torch.FloatTensor))`, *optional*):
+ Pre-computed hidden-states that can be used to speed up auto-regressive (sequential) decoding. There are
+ four sets of pre-computed hidden-states: key and values states in the self-attention blocks (2) and
+ in the cross-attention blocks (2). The `past_key_values` are returned when `use_cache=True` is passed or
+ when `config.use_cache=True`
+
+ Two formats are allowed:
+ - An [`~cache_utils.EncoderDecoderCache`] instance;
+ - Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of
+ shape `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape
+ `(batch_size, num_heads, encoder_sequence_length, embed_size_per_head)`.
+
+ If `past_key_values` are used, the user can optionally input only the last `decoder_input_ids` (those
+ that don't have their past key value states given to this model) of shape `(batch_size, 1)` instead of
+ all `decoder_input_ids` of shape `(batch_size, sequence_length)`.
+ inputs_embeds (`torch.FloatTensor` of
+ shape `(batch_size, sequence_length, hidden_size)`, *optional*): Optionally, instead of passing
+ `input_ids` you can choose to directly pass an embedded representation. This is useful if you want more
+ control over how to convert `input_ids` indices into associated vectors than the model's internal
+ embedding lookup matrix.
+ output_attentions (`bool`, *optional*):
+ Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+ returned tensors for more detail.
+ output_hidden_states (`bool`, *optional*):
+ Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors
+ for more detail.
+ return_dict (`bool`, *optional*):
+ Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+ cache_position (`torch.LongTensor` of shape `(sequence_length)`, *optional*):
+ Indices depicting the position of the input sequence tokens in the sequence. It is used to update the
+ cache in the correct position and to infer the complete sequence length.
+ """
+ output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+ output_hidden_states = (
+ output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+ )
+ use_cache = use_cache if use_cache is not None else self.config.use_cache
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+ # retrieve input_ids and inputs_embeds
+ if input_ids is not None and inputs_embeds is not None:
+ raise ValueError("You cannot specify both decoder_input_ids and decoder_inputs_embeds at the same time")
+ elif input_ids is not None:
+ input_shape = input_ids.size()
+ input_ids = input_ids.view(-1, input_shape[-1])
+ elif inputs_embeds is not None:
+ input_shape = inputs_embeds.size()[:-1]
+ else:
+ raise ValueError("You have to specify either decoder_input_ids or decoder_inputs_embeds")
+
+ if inputs_embeds is None:
+ inputs_embeds = self.embed_tokens(input_ids)
+ assert encoder_attention_mask.shape[-1] == encoder_hidden_states.shape[1]
+ encoder_extended_attention_mask = self.invert_attention_mask(encoder_attention_mask)
+
+ return_legacy_cache = False
+ return_self_attention_cache = False
+ if use_cache or past_key_values is not None:
+ if isinstance(past_key_values, Cache) and not isinstance(past_key_values, EncoderDecoderCache):
+ return_self_attention_cache = True
+ past_key_values = EncoderDecoderCache(past_key_values, DynamicCache())
+ elif not isinstance(past_key_values, EncoderDecoderCache):
+ return_legacy_cache = True
+ logger.warning_once(
+ "Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.43.0. "
+ "You should pass an instance of `EncoderDecoderCache` instead, e.g. "
+ "`past_key_values=EncoderDecoderCache.from_legacy_cache(past_key_values)`."
+ )
+ past_key_values = EncoderDecoderCache.from_legacy_cache(past_key_values)
+
+ past_key_values_length = 0
+ if cache_position is not None:
+ past_key_values_length = cache_position[0]
+ elif past_key_values is not None:
+ past_key_values_length = past_key_values.get_seq_length()
+
+ if cache_position is None:
+ cache_position = torch.arange(
+ past_key_values_length, past_key_values_length + input_shape[1], device=inputs_embeds.device
+ )
+
+ if position_ids is None:
+ position_ids = cache_position.unsqueeze(0)
+
+ # embed positions
+ if input_ids is not None:
+ positions = self.embed_positions(
+ input_ids, past_key_values_length=past_key_values_length, position_ids=position_ids
+ )
+ else:
+ positions = self.embed_positions(
+ inputs_embeds, past_key_values_length=past_key_values_length, position_ids=position_ids
+ )
+
+ hidden_states = inputs_embeds + positions.to(inputs_embeds.device)
+ hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
+
+ causal_mask = self._update_causal_mask(
+ attention_mask,
+ inputs_embeds,
+ cache_position,
+ past_key_values.self_attention_cache if past_key_values is not None else None,
+ output_attentions,
+ )
+
+ if self.gradient_checkpointing and self.training:
+ if use_cache:
+ logger.warning_once(
+ "`use_cache = True` is incompatible with gradient checkpointing. Setting `use_cache = False`..."
+ )
+ use_cache = False
+ # decoder layers
+ all_hidden_states = () if output_hidden_states else None
+ all_self_attns = () if output_attentions else None
+ all_cross_attentions = () if (output_attentions and encoder_hidden_states is not None) else None
+
+ # check if head_mask/cross_attn_head_mask has a correct number of layers specified if desired
+ for attn_mask, mask_name in zip([head_mask, cross_attn_head_mask], ["head_mask", "cross_attn_head_mask"]):
+ if attn_mask is not None:
+ assert attn_mask.size()[0] == (len(self.layers)), (
+ f"The `{mask_name}` should be specified for {len(self.layers)} layers, but it is for"
+ f" {head_mask.size()[0]}."
+ )
+ for idx, decoder_layer in enumerate(self.layers):
+ # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description)
+ if output_hidden_states:
+ all_hidden_states += (hidden_states,)
+ if self.training:
+ dropout_probability = torch.rand([])
+ if dropout_probability < self.layerdrop:
+ continue
+
+ if self.gradient_checkpointing and self.training:
+ layer_outputs = self._gradient_checkpointing_func(
+ decoder_layer.__call__,
+ hidden_states,
+ causal_mask,
+ encoder_hidden_states,
+ encoder_extended_attention_mask, # encoder attention mask
+ head_mask[idx] if head_mask is not None else None,
+ cross_attn_head_mask[idx] if cross_attn_head_mask is not None else None,
+ None, # past_key_value
+ output_attentions,
+ use_cache,
+ cache_position,
+ )
+ else:
+ layer_outputs = decoder_layer(
+ hidden_states,
+ attention_mask=causal_mask,
+ encoder_hidden_states=encoder_hidden_states,
+ encoder_attention_mask=encoder_extended_attention_mask,
+ layer_head_mask=(head_mask[idx] if head_mask is not None else None),
+ cross_attn_layer_head_mask=(
+ cross_attn_head_mask[idx] if cross_attn_head_mask is not None else None
+ ),
+ past_key_value=past_key_values if use_cache else None,
+ output_attentions=output_attentions,
+ use_cache=use_cache,
+ cache_position=cache_position,
+ )
+ hidden_states = layer_outputs[0]
+
+ if output_attentions:
+ all_self_attns += (layer_outputs[1],)
+
+ if encoder_hidden_states is not None:
+ all_cross_attentions += (layer_outputs[2],)
+
+ hidden_states = self.layer_norm(hidden_states)
+ # add hidden states from the last decoder layer
+ if output_hidden_states:
+ all_hidden_states += (hidden_states,)
+
+ next_cache = past_key_values if use_cache else None
+ if return_self_attention_cache:
+ next_cache = past_key_values.self_attention_cache
+ if return_legacy_cache:
+ next_cache = past_key_values.to_legacy_cache()
+ if not return_dict:
+ return tuple(
+ v
+ for v in [hidden_states, next_cache, all_hidden_states, all_self_attns, all_cross_attentions]
+ if v is not None
+ )
+ return BaseModelOutputWithPastAndCrossAttentions(
+ last_hidden_state=hidden_states,
+ past_key_values=next_cache,
+ hidden_states=all_hidden_states,
+ attentions=all_self_attns,
+ cross_attentions=all_cross_attentions,
+ )
+
+ # Copied from transformers.models.llama.modeling_llama.LlamaModel._update_causal_mask
+ def _update_causal_mask(
+ self,
+ attention_mask: torch.Tensor,
+ input_tensor: torch.Tensor,
+ cache_position: torch.Tensor,
+ past_key_values: Cache,
+ output_attentions: bool,
+ ):
+ # TODO: As of torch==2.2.0, the `attention_mask` passed to the model in `generate` is 2D and of dynamic length even when the static
+ # KV cache is used. This is an issue for torch.compile which then recaptures cudagraphs at each decode steps due to the dynamic shapes.
+ # (`recording cudagraph tree for symint key 13`, etc.), which is VERY slow. A workaround is `@torch.compiler.disable`, but this prevents using
+ # `fullgraph=True`. See more context in https://github.com/huggingface/transformers/pull/29114
+
+ if self.config._attn_implementation == "flash_attention_2":
+ if attention_mask is not None and 0.0 in attention_mask:
+ return attention_mask
+ return None
+
+ # For SDPA, when possible, we will rely on its `is_causal` argument instead of its `attn_mask` argument, in
+ # order to dispatch on Flash Attention 2. This feature is not compatible with static cache, as SDPA will fail
+ # to infer the attention mask.
+ past_seen_tokens = past_key_values.get_seq_length() if past_key_values is not None else 0
+ using_static_cache = isinstance(past_key_values, StaticCache)
+
+ # When output attentions is True, sdpa implementation's forward method calls the eager implementation's forward
+ if self.config._attn_implementation == "sdpa" and not using_static_cache and not output_attentions:
+ if AttentionMaskConverter._ignore_causal_mask_sdpa(
+ attention_mask,
+ inputs_embeds=input_tensor,
+ past_key_values_length=past_seen_tokens,
+ is_training=self.training,
+ ):
+ return None
+
+ dtype, device = input_tensor.dtype, input_tensor.device
+ min_dtype = torch.finfo(dtype).min
+ sequence_length = input_tensor.shape[1]
+ if using_static_cache:
+ target_length = past_key_values.get_max_length()
+ else:
+ target_length = (
+ attention_mask.shape[-1]
+ if isinstance(attention_mask, torch.Tensor)
+ else past_seen_tokens + sequence_length + 1
+ )
+
+ # In case the provided `attention` mask is 2D, we generate a causal mask here (4D).
+ causal_mask = _prepare_4d_causal_attention_mask_with_cache_position(
+ attention_mask,
+ sequence_length=sequence_length,
+ target_length=target_length,
+ dtype=dtype,
+ device=device,
+ min_dtype=min_dtype,
+ cache_position=cache_position,
+ batch_size=input_tensor.shape[0],
+ )
+
+ if (
+ self.config._attn_implementation == "sdpa"
+ and attention_mask is not None
+ and attention_mask.device.type == "cuda"
+ and not output_attentions
+ ):
+ # Attend to all tokens in fully masked rows in the causal_mask, for example the relevant first rows when
+ # using left padding. This is required by F.scaled_dot_product_attention memory-efficient attention path.
+ # Details: https://github.com/pytorch/pytorch/issues/110213
+ causal_mask = AttentionMaskConverter._unmask_unattended(causal_mask, min_dtype)
+
+ return causal_mask
+
+
+@add_start_docstrings(
+ "The bare Whisper Model outputting raw hidden-states without any specific head on top.",
+ WHISPER_START_DOCSTRING,
+)
+class WhisperVQModel(WhisperPreTrainedModel):
+ def __init__(self, config: WhisperVQConfig):
+ super().__init__(config)
+
+ self.encoder = WhisperVQEncoder(config)
+ self.decoder = WhisperVQDecoder(config)
+ # Initialize weights and apply final processing
+ self.post_init()
+
+ def get_input_embeddings(self):
+ return self.decoder.embed_tokens
+
+ def set_input_embeddings(self, value):
+ self.decoder.embed_tokens = value
+
+ def get_encoder(self):
+ return self.encoder
+
+ def get_decoder(self):
+ return self.decoder
+
+ def freeze_encoder(self):
+ """
+ Calling this function will disable the gradient computation for the Whisper encoder so that its parameters will
+ not be updated during training.
+ """
+ self.encoder._freeze_parameters()
+
+ def _mask_input_features(
+ self,
+ input_features: torch.FloatTensor,
+ attention_mask: Optional[torch.LongTensor] = None,
+ ):
+ """
+ Masks extracted features along time axis and/or along feature axis according to
+ [SpecAugment](https://arxiv.org/abs/1904.08779).
+ """
+
+ # `config.apply_spec_augment` can set masking to False
+ if not getattr(self.config, "apply_spec_augment", True):
+ return input_features
+
+ # generate indices & apply SpecAugment along time axis
+ batch_size, hidden_size, sequence_length = input_features.size()
+
+ if self.config.mask_time_prob > 0 and self.training:
+ # generate indices & apply SpecAugment along time axis
+ mask_time_indices = _compute_mask_indices(
+ (batch_size, sequence_length),
+ mask_prob=self.config.mask_time_prob,
+ mask_length=self.config.mask_time_length,
+ attention_mask=attention_mask,
+ min_masks=self.config.mask_time_min_masks,
+ )
+ mask_time_indices = torch.tensor(mask_time_indices, device=input_features.device, dtype=torch.bool)
+ mask_time_indices = mask_time_indices[:, None].expand(-1, hidden_size, -1)
+ input_features[mask_time_indices] = 0
+
+ if self.config.mask_feature_prob > 0 and self.training:
+ # generate indices & apply SpecAugment along feature axis
+ mask_feature_indices = _compute_mask_indices(
+ (batch_size, hidden_size),
+ mask_prob=self.config.mask_feature_prob,
+ mask_length=self.config.mask_feature_length,
+ min_masks=self.config.mask_feature_min_masks,
+ )
+ mask_feature_indices = torch.tensor(mask_feature_indices, device=input_features.device, dtype=torch.bool)
+ input_features[mask_feature_indices] = 0
+
+ return input_features
+
+ @add_start_docstrings_to_model_forward(WHISPER_INPUTS_DOCSTRING)
+ @replace_return_docstrings(output_type=Seq2SeqModelOutput, config_class=_CONFIG_FOR_DOC)
+ def forward(
+ self,
+ input_features: Optional[torch.FloatTensor] = None,
+ attention_mask: Optional[torch.LongTensor] = None,
+ decoder_input_ids: Optional[torch.LongTensor] = None,
+ decoder_attention_mask: Optional[torch.LongTensor] = None,
+ head_mask: Optional[torch.Tensor] = None,
+ decoder_head_mask: Optional[torch.Tensor] = None,
+ cross_attn_head_mask: Optional[torch.Tensor] = None,
+ encoder_outputs: Optional[Tuple[Tuple[torch.FloatTensor]]] = None,
+ past_key_values: Optional[Union[EncoderDecoderCache, Tuple[torch.FloatTensor]]] = None,
+ decoder_inputs_embeds: Optional[Tuple[torch.FloatTensor]] = None,
+ decoder_position_ids: Optional[Tuple[torch.LongTensor]] = None,
+ use_cache: Optional[bool] = None,
+ output_attentions: Optional[bool] = None,
+ output_hidden_states: Optional[bool] = None,
+ return_dict: Optional[bool] = None,
+ cache_position: Optional[torch.LongTensor] = None,
+ quantized_token_ids: Optional[torch.LongTensor] = None
+ ) -> Union[Tuple[torch.Tensor], Seq2SeqModelOutput]:
+ r"""
+ Returns:
+
+ Example:
+ ```python
+ >>> import torch
+ >>> from transformers import AutoFeatureExtractor, WhisperModel
+ >>> from datasets import load_dataset
+
+ >>> model = WhisperVQModel.from_pretrained("openai/whisper-base")
+ >>> feature_extractor = AutoFeatureExtractor.from_pretrained("openai/whisper-base")
+ >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
+ >>> inputs = feature_extractor(ds[0]["audio"]["array"], return_tensors="pt")
+ >>> input_features = inputs.input_features
+ >>> decoder_input_ids = torch.tensor([[1, 1]]) * model.config.decoder_start_token_id
+ >>> last_hidden_state = model(input_features, decoder_input_ids=decoder_input_ids).last_hidden_state
+ >>> list(last_hidden_state.shape)
+ [1, 2, 512]
+ ```"""
+ output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+ output_hidden_states = (
+ output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+ )
+ use_cache = use_cache if use_cache is not None else self.config.use_cache
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+ if encoder_outputs is None:
+ input_features = self._mask_input_features(input_features, attention_mask=attention_mask)
+
+ encoder_outputs = self.encoder(
+ input_features,
+ attention_mask=attention_mask,
+ head_mask=head_mask,
+ output_attentions=output_attentions,
+ output_hidden_states=output_hidden_states,
+ return_dict=return_dict,
+ quantized_token_ids=quantized_token_ids
+ )
+ # If the user passed a tuple for encoder_outputs, we wrap it in a BaseModelOutput when return_dict=True
+ elif return_dict and not isinstance(encoder_outputs, BaseModelOutput):
+ encoder_outputs = BaseModelOutput(
+ last_hidden_state=encoder_outputs[0],
+ hidden_states=encoder_outputs[1] if len(encoder_outputs) > 1 else None,
+ attentions=encoder_outputs[2] if len(encoder_outputs) > 2 else None,
+ )
+
+ # decoder outputs consists of (dec_features, past_key_value, dec_hidden, dec_attn)
+ attention_mask = attention_mask[:, ::self.encoder.conv1.stride[0] * self.encoder.conv2.stride[0]]
+ if self.encoder.config.pooling_kernel_size is not None:
+ attention_mask = attention_mask[:, ::self.encoder.config.pooling_kernel_size]
+ decoder_outputs = self.decoder(
+ input_ids=decoder_input_ids,
+ attention_mask=decoder_attention_mask,
+ encoder_attention_mask=attention_mask,
+ encoder_hidden_states=encoder_outputs[0],
+ head_mask=decoder_head_mask,
+ cross_attn_head_mask=cross_attn_head_mask,
+ past_key_values=past_key_values,
+ inputs_embeds=decoder_inputs_embeds,
+ position_ids=decoder_position_ids,
+ use_cache=use_cache,
+ output_attentions=output_attentions,
+ output_hidden_states=output_hidden_states,
+ return_dict=return_dict,
+ cache_position=cache_position,
+ )
+
+ if not return_dict:
+ return decoder_outputs + encoder_outputs
+
+ return Seq2SeqModelOutput(
+ last_hidden_state=decoder_outputs.last_hidden_state,
+ past_key_values=decoder_outputs.past_key_values,
+ decoder_hidden_states=decoder_outputs.hidden_states,
+ decoder_attentions=decoder_outputs.attentions,
+ cross_attentions=decoder_outputs.cross_attentions,
+ encoder_last_hidden_state=encoder_outputs.last_hidden_state,
+ encoder_hidden_states=encoder_outputs.hidden_states,
+ encoder_attentions=encoder_outputs.attentions,
+ )
+
+
+@add_start_docstrings(
+ "The Whisper Model with a language modeling head. Can be used for automatic speech recognition.",
+ WHISPER_START_DOCSTRING,
+)
+class WhisperVQForConditionalGeneration(WhisperGenerationMixin, WhisperPreTrainedModel):
+ base_model_prefix = "model"
+ _tied_weights_keys = ["proj_out.weight"]
+
+ def __init__(self, config: WhisperVQConfig):
+ super().__init__(config)
+ self.model = WhisperVQModel(config)
+ self.proj_out = nn.Linear(config.d_model, config.vocab_size, bias=False)
+ self.quantize_loss = None
+ # Initialize weights and apply final processing
+ self.post_init()
+
+ def get_encoder(self):
+ return self.model.get_encoder()
+
+ def get_decoder(self):
+ return self.model.get_decoder()
+
+ def get_output_embeddings(self):
+ return self.proj_out
+
+ def set_output_embeddings(self, new_embeddings):
+ self.proj_out = new_embeddings
+
+ def get_input_embeddings(self) -> nn.Module:
+ return self.model.get_input_embeddings()
+
+ def freeze_encoder(self):
+ """
+ Calling this function will disable the gradient computation for the Whisper encoder so that its parameters will
+ not be updated during training.
+ """
+ self.model.encoder._freeze_parameters()
+
+ @add_start_docstrings_to_model_forward(WHISPER_INPUTS_DOCSTRING)
+ @replace_return_docstrings(output_type=Seq2SeqLMOutput, config_class=_CONFIG_FOR_DOC)
+ def forward(
+ self,
+ input_features: Optional[torch.FloatTensor] = None,
+ attention_mask: Optional[torch.LongTensor] = None,
+ decoder_input_ids: Optional[torch.LongTensor] = None,
+ decoder_attention_mask: Optional[torch.LongTensor] = None,
+ head_mask: Optional[torch.Tensor] = None,
+ decoder_head_mask: Optional[torch.Tensor] = None,
+ cross_attn_head_mask: Optional[torch.Tensor] = None,
+ encoder_outputs: Optional[Tuple[Tuple[torch.FloatTensor]]] = None,
+ past_key_values: Optional[Union[EncoderDecoderCache, Tuple[torch.FloatTensor]]] = None,
+ decoder_inputs_embeds: Optional[Tuple[torch.FloatTensor]] = None,
+ decoder_position_ids: Optional[Tuple[torch.LongTensor]] = None,
+ labels: Optional[torch.LongTensor] = None,
+ use_cache: Optional[bool] = None,
+ output_attentions: Optional[bool] = None,
+ output_hidden_states: Optional[bool] = None,
+ return_dict: Optional[bool] = None,
+ cache_position: Optional[torch.LongTensor] = None,
+ quantized_token_ids: Optional[torch.LongTensor] = None
+ ) -> Union[Tuple[torch.Tensor], Seq2SeqLMOutput]:
+ r"""
+ labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+ Labels for computing the language modeling loss. Indices should either be in `[0, ..., config.vocab_size]`
+ or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored (masked), the loss is
+ only computed for the tokens with labels in `[0, ..., config.vocab_size]`.
+
+ Returns:
+
+ Example:
+
+ ```python
+ >>> import torch
+ >>> from transformers import AutoProcessor, WhisperForConditionalGeneration
+ >>> from datasets import load_dataset
+
+ >>> processor = AutoProcessor.from_pretrained("openai/whisper-tiny.en")
+ >>> model = WhisperVQForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
+
+ >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
+
+ >>> inputs = processor(ds[0]["audio"]["array"], return_tensors="pt")
+ >>> input_features = inputs.input_features
+
+ >>> generated_ids = model.generate(inputs=input_features)
+
+ >>> transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+ >>> transcription
+ ' Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel.'
+ ```"""
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+ if labels is not None:
+ if decoder_input_ids is None and decoder_inputs_embeds is None:
+ decoder_input_ids = shift_tokens_right(
+ labels, self.config.pad_token_id, self.config.decoder_start_token_id
+ )
+
+ outputs = self.model(
+ input_features,
+ attention_mask=attention_mask,
+ decoder_input_ids=decoder_input_ids,
+ encoder_outputs=encoder_outputs,
+ decoder_attention_mask=decoder_attention_mask,
+ head_mask=head_mask,
+ decoder_head_mask=decoder_head_mask,
+ cross_attn_head_mask=cross_attn_head_mask,
+ past_key_values=past_key_values,
+ decoder_inputs_embeds=decoder_inputs_embeds,
+ decoder_position_ids=decoder_position_ids,
+ use_cache=use_cache,
+ output_attentions=output_attentions,
+ output_hidden_states=output_hidden_states,
+ return_dict=return_dict,
+ cache_position=cache_position,
+ quantized_token_ids=quantized_token_ids
+ )
+ lm_logits = self.proj_out(outputs[0])
+
+ loss = None
+ if labels is not None:
+ loss_fct = CrossEntropyLoss()
+ # move labels to correct device to enable PP
+ labels = labels.to(lm_logits.device)
+ loss = loss_fct(lm_logits.view(-1, self.config.vocab_size), labels.reshape(-1))
+ if self.training and self.model.encoder.quantize_loss is not None:
+ loss = loss + self.model.encoder.quantize_loss
+
+ if not return_dict:
+ output = (lm_logits,) + outputs[1:]
+ return ((loss,) + output) if loss is not None else output
+
+ return Seq2SeqLMOutput(
+ loss=loss,
+ logits=lm_logits,
+ past_key_values=outputs.past_key_values,
+ decoder_hidden_states=outputs.decoder_hidden_states,
+ decoder_attentions=outputs.decoder_attentions,
+ cross_attentions=outputs.cross_attentions,
+ encoder_last_hidden_state=outputs.encoder_last_hidden_state,
+ encoder_hidden_states=outputs.encoder_hidden_states,
+ encoder_attentions=outputs.encoder_attentions,
+ )
+
+ def prepare_inputs_for_generation(
+ self,
+ decoder_input_ids,
+ past_key_values=None,
+ use_cache=None,
+ encoder_outputs=None,
+ attention_mask=None,
+ decoder_attention_mask=None,
+ cache_position=None,
+ quantized_token_ids=None,
+ **kwargs,
+ ):
+ decoder_position_ids = None
+ if decoder_attention_mask is not None:
+ decoder_position_ids = (decoder_attention_mask.cumsum(-1) - 1).clamp(min=0)
+
+ past_length = 0
+ if past_key_values is not None:
+ if isinstance(past_key_values, EncoderDecoderCache):
+ past_length = cache_position[0] if cache_position is not None else past_key_values.get_seq_length()
+ else:
+ past_length = past_key_values[0][0].shape[2]
+
+ # Some generation methods already pass only the last input ID
+ if decoder_input_ids.shape[1] > past_length:
+ remove_prefix_length = past_length
+ else:
+ # Default to old behavior: keep only final ID
+ remove_prefix_length = decoder_input_ids.shape[1] - 1
+
+ decoder_input_ids = decoder_input_ids[:, remove_prefix_length:]
+
+ if decoder_position_ids is not None:
+ decoder_position_ids = decoder_position_ids[:, remove_prefix_length:]
+ # This `clone` call is needed to avoid recapturing cuda graphs with `torch.compile`'s `mode="reduce-overhead`, as otherwise the input `position_ids` would have various stride during the decoding. Here, simply using `.contiguous()` is not sufficient as in the batch size = 1 case, `position_ids` is already contiguous but with varying stride which retriggers a capture.
+ decoder_position_ids = decoder_position_ids.clone(memory_format=torch.contiguous_format)
+
+ if cache_position is None:
+ cache_position = torch.arange(
+ past_length, past_length + decoder_input_ids.shape[1], device=decoder_input_ids.device
+ )
+ elif use_cache:
+ cache_position = cache_position[-decoder_input_ids.shape[1]:]
+
+ # The `contiguous()` here is necessary to have a static stride during decoding. torchdynamo otherwise
+ # recompiles graphs as the stride of the inputs is a guard. Ref: https://github.com/huggingface/transformers/pull/29114
+ decoder_input_ids = decoder_input_ids.contiguous()
+
+ if (
+ isinstance(past_key_values, EncoderDecoderCache)
+ and (
+ isinstance(past_key_values.self_attention_cache, StaticCache)
+ or isinstance(past_key_values.cross_attention_cache, StaticCache)
+ )
+ and decoder_attention_mask is not None
+ and decoder_attention_mask.ndim == 2
+ ):
+ batch_size, sequence_length = decoder_input_ids.shape
+ device = decoder_input_ids.device
+
+ dtype = self.proj_out.weight.dtype
+ min_dtype = torch.finfo(dtype).min
+
+ decoder_attention_mask = _prepare_4d_causal_attention_mask_with_cache_position(
+ decoder_attention_mask,
+ sequence_length=sequence_length,
+ target_length=past_key_values.self_attention_cache.get_max_length(),
+ dtype=dtype,
+ device=device,
+ min_dtype=min_dtype,
+ cache_position=cache_position,
+ batch_size=batch_size,
+ )
+
+ return {
+ "encoder_outputs": encoder_outputs,
+ "attention_mask": attention_mask,
+ "past_key_values": past_key_values,
+ "decoder_input_ids": decoder_input_ids,
+ "use_cache": use_cache,
+ "decoder_attention_mask": decoder_attention_mask,
+ "decoder_position_ids": decoder_position_ids,
+ "cache_position": cache_position,
+ "quantized_token_ids": quantized_token_ids
+ }
+
+ def _retrieve_init_tokens(self, input_features, batch_size, generation_config, config, num_segment_frames, kwargs):
+ if self.config.skip_language_detection:
+ return torch.as_tensor([[generation_config.decoder_start_token_id] for _ in range(batch_size)],
+ dtype=torch.long, device=self.device).expand(batch_size, -1)
+ else:
+ return super()._retrieve_init_tokens(input_features, batch_size, generation_config, config,
+ num_segment_frames, kwargs)
+
+
+class WhisperDecoderWrapper(WhisperPreTrainedModel):
+ """
+ This wrapper class is a helper class to correctly load pretrained checkpoints when the causal language model is
+ used in combination with the [`EncoderDecoderModel`] framework.
+ """
+
+ def __init__(self, config):
+ super().__init__(config)
+ config.is_encoder_decoder = False
+ self.decoder = WhisperVQDecoder(config)
+
+ def get_input_embeddings(self):
+ return self.decoder.embed_tokens
+
+ def set_input_embeddings(self, value):
+ self.decoder.embed_tokens = value
+
+ def forward(self, *args, **kwargs):
+ return self.decoder(*args, **kwargs)
+
+
+@add_start_docstrings(
+ """
+ Whisper decoder with a language modeling head on top (linear layer with weights tied to the input embeddings).
+ """,
+ WHISPER_START_DOCSTRING,
+)
+class WhisperForCausalLM(WhisperPreTrainedModel):
+ _tied_weights_keys = ["proj_out.weight"]
+ main_input_name = "input_ids"
+
+ def __init__(self, config):
+ super().__init__(config)
+ config.is_encoder_decoder = False
+ self.model = WhisperDecoderWrapper(config)
+
+ self.proj_out = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+
+ # Initialize weights and apply final processing
+ self.post_init()
+
+ def get_output_embeddings(self):
+ return self.proj_out
+
+ def set_output_embeddings(self, new_embeddings):
+ self.proj_out = new_embeddings
+
+ def get_input_embeddings(self) -> nn.Module:
+ return self.model.get_input_embeddings()
+
+ def set_input_embeddings(self, value):
+ self.model.set_input_embeddings(value)
+
+ def set_decoder(self, decoder):
+ self.model.decoder = decoder
+
+ def get_decoder(self):
+ return self.model.decoder
+
+ @replace_return_docstrings(output_type=CausalLMOutputWithCrossAttentions, config_class=_CONFIG_FOR_DOC)
+ def forward(
+ self,
+ input_ids: torch.LongTensor = None,
+ attention_mask: Optional[torch.Tensor] = None,
+ encoder_outputs: Optional[Tuple[torch.FloatTensor]] = None,
+ head_mask: Optional[torch.Tensor] = None,
+ cross_attn_head_mask: Optional[torch.Tensor] = None,
+ past_key_values: Optional[Tuple[Tuple[torch.FloatTensor]]] = None,
+ inputs_embeds: Optional[torch.FloatTensor] = None,
+ labels: Optional[torch.LongTensor] = None,
+ use_cache: Optional[bool] = None,
+ output_attentions: Optional[bool] = None,
+ output_hidden_states: Optional[bool] = None,
+ return_dict: Optional[bool] = None,
+ cache_position: Optional[torch.LongTensor] = None,
+ ) -> Union[Tuple, CausalLMOutputWithCrossAttentions]:
+ r"""
+ Args:
+ input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):
+ Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you
+ provide it. Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+ [`PreTrainedTokenizer.__call__`] for details. [What are input IDs?](../glossary#input-ids)
+ attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*):
+ Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`:
+ - 1 for tokens that are **not masked**,
+ - 0 for tokens that are **masked**.
+ [What are attention masks?](../glossary#attention-mask)
+ encoder_outputs (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):
+ Sequence of hidden-states at the output of the last layer of the encoder. Used in the cross-attention
+ if the model is configured as a decoder.
+ head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the attention modules. Mask values selected in `[0, 1]`:
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+ cross_attn_head_mask (`torch.Tensor` of shape `(decoder_layers, decoder_attention_heads)`, *optional*):
+ Mask to nullify selected heads of the cross-attention modules. Mask values selected in `[0, 1]`:
+ - 1 indicates the head is **not masked**,
+ - 0 indicates the head is **masked**.
+ past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or when `config.use_cache=True`):
+ Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of
+ shape `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of
+ shape `(batch_size, num_heads, encoder_sequence_length, embed_size_per_head)`. The two additional
+ tensors are only required when the model is used as a decoder in a Sequence to Sequence model. Contains
+ pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention
+ blocks) that can be used (see `past_key_values` input) to speed up sequential decoding. If
+ `past_key_values` are used, the user can optionally input only the last `decoder_input_ids` (those that
+ don't have their past key value states given to this model) of shape `(batch_size, 1)` instead of all
+ `decoder_input_ids` of shape `(batch_size, sequence_length)`.
+ inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*):
+ Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation.
+ This is useful if you want more control over how to convert `input_ids` indices into associated vectors
+ than the model's internal embedding lookup matrix.
+ labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
+ Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,
+ config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored
+ (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`.
+ use_cache (`bool`, *optional*):
+ If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding
+ (see `past_key_values`).
+ - 1 for tokens that are **not masked**,
+ - 0 for tokens that are **masked**.
+ output_attentions (`bool`, *optional*):
+ Whether or not to return the attentions tensors of all attention layers. See `attentions` under
+ returned tensors for more detail.
+ output_hidden_states (`bool`, *optional*):
+ Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors
+ for more detail.
+ return_dict (`bool`, *optional*):
+ Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
+ cache_position (`torch.LongTensor` of shape `(sequence_length)`, *optional*):
+ Indices depicting the position of the input sequence tokens in the sequence. It is used to update the cache
+ in the correct position and to infer the complete sequence length.
+
+ Returns:
+
+ Example:
+
+ ```python
+ >>> from transformers import WhisperForCausalLM, WhisperForConditionalGeneration, WhisperProcessor
+ >>> import torch
+ >>> from datasets import load_dataset
+
+ >>> processor = WhisperProcessor.from_pretrained("openai/whisper-large-v2")
+ >>> model = WhisperVQForConditionalGeneration.from_pretrained("openai/whisper-large-v2")
+
+ >>> assistant_model = WhisperForCausalLM.from_pretrained("distil-whisper/distil-large-v2")
+
+ >>> ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
+ >>> sample = ds[0]["audio"]
+ >>> input_features = processor(
+ ... sample["array"], sampling_rate=sample["sampling_rate"], return_tensors="pt"
+ ... ).input_features
+
+ >>> predicted_ids = model.generate(input_features, assistant_model=assistant_model)
+
+ >>> # decode token ids to text
+ >>> transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
+ >>> transcription
+ ' Mr. Quilter is the apostle of the middle classes and we are glad to welcome his gospel.'
+ ```"""
+ output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+ output_hidden_states = (
+ output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+ )
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+ # If the user passed a tuple or `BaseModelOutput` for encoder_outputs, we extract only the hidden states
+ if isinstance(encoder_outputs, (BaseModelOutput, tuple, list)):
+ encoder_outputs = encoder_outputs[0]
+
+ # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
+ outputs = self.model.decoder(
+ input_ids=input_ids,
+ attention_mask=attention_mask,
+ encoder_hidden_states=encoder_outputs,
+ head_mask=head_mask,
+ cross_attn_head_mask=cross_attn_head_mask,
+ past_key_values=past_key_values,
+ inputs_embeds=inputs_embeds,
+ use_cache=use_cache,
+ output_attentions=output_attentions,
+ output_hidden_states=output_hidden_states,
+ return_dict=return_dict,
+ cache_position=cache_position,
+ )
+
+ logits = self.proj_out(outputs[0])
+
+ loss = None
+ if labels is not None:
+ labels = labels.to(logits.device)
+ loss_fct = CrossEntropyLoss()
+ loss = loss_fct(logits.view(-1, self.config.vocab_size), labels.view(-1))
+
+ if not return_dict:
+ output = (logits,) + outputs[1:]
+ return (loss,) + output if loss is not None else output
+
+ return CausalLMOutputWithCrossAttentions(
+ loss=loss,
+ logits=logits,
+ past_key_values=outputs.past_key_values,
+ hidden_states=outputs.hidden_states,
+ attentions=outputs.attentions,
+ cross_attentions=outputs.cross_attentions,
+ )
+
+ def prepare_inputs_for_generation(
+ self,
+ input_ids,
+ past_key_values=None,
+ use_cache=None,
+ encoder_outputs=None,
+ attention_mask=None,
+ cache_position=None,
+ **kwargs,
+ ):
+ past_length = 0
+ if past_key_values is not None:
+ if isinstance(past_key_values, (Cache, EncoderDecoderCache)):
+ past_length = cache_position[0] if cache_position is not None else past_key_values.get_seq_length()
+ else:
+ past_length = past_key_values[0][0].shape[2]
+
+ # Some generation methods already pass only the last input ID
+ if input_ids.shape[1] > past_length:
+ remove_prefix_length = past_length
+ else:
+ # Default to old behavior: keep only final ID
+ remove_prefix_length = input_ids.shape[1] - 1
+
+ input_ids = input_ids[:, remove_prefix_length:]
+
+ if cache_position is None:
+ cache_position = torch.arange(past_length, past_length + input_ids.shape[1], device=input_ids.device)
+ elif use_cache:
+ cache_position = cache_position[-input_ids.shape[1]:]
+
+ return {
+ "encoder_outputs": encoder_outputs,
+ "past_key_values": past_key_values,
+ "input_ids": input_ids,
+ "use_cache": use_cache,
+ "attention_mask": attention_mask,
+ "cache_position": cache_position,
+ }
+
+ @staticmethod
+ def _reorder_cache(past_key_values, beam_idx):
+ reordered_past = ()
+ for layer_past in past_key_values:
+ reordered_past += (
+ tuple(past_state.index_select(0, beam_idx.to(past_state.device)) for past_state in layer_past),
+ )
+ return reordered_past
+
+
+@add_start_docstrings(
+ """
+ Whisper Encoder Model with a sequence classification head on top (a linear layer over the pooled output) for tasks
+ like SUPERB Keyword Spotting.
+ """,
+ WHISPER_ENCODER_INPUTS_DOCSTRING,
+)
+class WhisperForAudioClassification(WhisperPreTrainedModel):
+ def __init__(self, config):
+ super().__init__(config)
+
+ self.encoder = WhisperVQEncoder(config)
+ num_layers = config.num_hidden_layers + 1 # transformer layers + input embeddings
+ if config.use_weighted_layer_sum:
+ self.layer_weights = nn.Parameter(torch.ones(num_layers) / num_layers)
+ self.projector = nn.Linear(config.hidden_size, config.classifier_proj_size)
+ self.classifier = nn.Linear(config.classifier_proj_size, config.num_labels)
+
+ # Initialize weights and apply final processing
+ self.post_init()
+
+ def freeze_encoder(self):
+ """
+ Calling this function will disable the gradient computation for the Whisper encoder so that its parameters will
+ not be updated during training. Only the projection layers and classification head will be updated.
+ """
+ self.encoder._freeze_parameters()
+
+ def get_input_embeddings(self) -> nn.Module:
+ return self.encoder.get_input_embeddings()
+
+ def set_input_embeddings(self, value: nn.Module):
+ self.encoder.set_input_embeddings(value)
+
+ @add_start_docstrings_to_model_forward(WHISPER_ENCODER_INPUTS_DOCSTRING)
+ @replace_return_docstrings(output_type=SequenceClassifierOutput, config_class=_CONFIG_FOR_DOC)
+ def forward(
+ self,
+ input_features: Optional[torch.LongTensor] = None,
+ head_mask: Optional[torch.Tensor] = None,
+ encoder_outputs: Optional[Tuple[Tuple[torch.FloatTensor]]] = None,
+ labels: Optional[torch.LongTensor] = None,
+ output_attentions: Optional[bool] = None,
+ output_hidden_states: Optional[bool] = None,
+ return_dict: Optional[bool] = None,
+ ) -> Union[Tuple[torch.Tensor], SequenceClassifierOutput]:
+ r"""
+ labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*):
+ Labels for computing the sequence classification/regression loss. Indices should be in `[0, ...,
+ config.num_labels - 1]`. If `config.num_labels == 1` a regression loss is computed (Mean-Square loss), If
+ `config.num_labels > 1` a classification loss is computed (Cross-Entropy).
+
+ Returns:
+
+ Example:
+
+ ```python
+ >>> import torch
+ >>> from transformers import AutoFeatureExtractor, WhisperForAudioClassification
+ >>> from datasets import load_dataset
+
+ >>> feature_extractor = AutoFeatureExtractor.from_pretrained("sanchit-gandhi/whisper-medium-fleurs-lang-id")
+ >>> model = WhisperForAudioClassification.from_pretrained("sanchit-gandhi/whisper-medium-fleurs-lang-id")
+
+ >>> ds = load_dataset("google/fleurs", "all", split="validation", streaming=True)
+ >>> sample = next(iter(ds))
+
+ >>> inputs = feature_extractor(
+ ... sample["audio"]["array"], sampling_rate=sample["audio"]["sampling_rate"], return_tensors="pt"
+ ... )
+ >>> input_features = inputs.input_features
+
+ >>> with torch.no_grad():
+ ... logits = model(input_features).logits
+
+ >>> predicted_class_ids = torch.argmax(logits).item()
+ >>> predicted_label = model.config.id2label[predicted_class_ids]
+ >>> predicted_label
+ 'Afrikaans'
+ ```"""
+
+ output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+ output_hidden_states = (
+ output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+ )
+ if self.config.use_weighted_layer_sum:
+ output_hidden_states = True
+ elif output_hidden_states is None:
+ output_hidden_states = self.config.output_hidden_states
+
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+ if encoder_outputs is None:
+ encoder_outputs = self.encoder(
+ input_features,
+ head_mask=head_mask,
+ output_attentions=output_attentions,
+ output_hidden_states=output_hidden_states,
+ return_dict=return_dict,
+ )
+
+ if self.config.use_weighted_layer_sum:
+ hidden_states = encoder_outputs[_HIDDEN_STATES_START_POSITION]
+ hidden_states = torch.stack(hidden_states, dim=1)
+ norm_weights = nn.functional.softmax(self.layer_weights, dim=-1)
+ hidden_states = (hidden_states * norm_weights.view(-1, 1, 1)).sum(dim=1)
+ else:
+ hidden_states = encoder_outputs[0]
+
+ hidden_states = self.projector(hidden_states)
+ pooled_output = hidden_states.mean(dim=1)
+
+ logits = self.classifier(pooled_output)
+
+ loss = None
+
+ if labels is not None:
+ loss_fct = CrossEntropyLoss()
+ # move labels to correct device to enable PP
+ labels = labels.to(logits.device)
+ loss = loss_fct(logits.view(-1, self.config.num_labels), labels.view(-1))
+
+ if not return_dict:
+ output = (logits,) + encoder_outputs[1:]
+ return ((loss,) + output) if loss is not None else output
+
+ return SequenceClassifierOutput(
+ loss=loss,
+ logits=logits,
+ hidden_states=encoder_outputs.hidden_states,
+ attentions=encoder_outputs.attentions,
+ )
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/utils.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..c155274625173827e59fcd3fc9568fe18f3eb148
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/speech_tokenizer/utils.py
@@ -0,0 +1,84 @@
+import os
+import io
+import glob
+import math
+import tarfile
+import torch
+import torchaudio
+import safetensors
+from .configuration_whisper import WhisperVQConfig
+from .modeling_whisper import WhisperVQEncoder, WhisperVQForConditionalGeneration
+from transformers import WhisperFeatureExtractor, WhisperTokenizerFast
+
+
+def load_quantize_encoder(model_path):
+ config = WhisperVQConfig.from_pretrained(model_path)
+ config.quantize_encoder_only = True
+ model = WhisperVQEncoder(config)
+ state_dict = {}
+ for path in glob.glob(os.path.join(model_path, "model*.safetensors")):
+ with safetensors.safe_open(path, framework="pt", device="cpu") as f:
+ for key in f.keys():
+ if key.startswith("model.encoder."):
+ new_key = key[len("model.encoder."):]
+ if new_key.startswith("layer_norm"):
+ continue
+ if new_key.startswith("layers"):
+ layer_id = int(new_key.split(".")[1])
+ if layer_id >= config.quantize_position:
+ continue
+ state_dict[new_key] = f.get_tensor(key)
+ model.load_state_dict(state_dict)
+ model.eval()
+ model.cuda()
+ return model
+
+
+_resample_buffer: dict[int, torchaudio.transforms.Resample] = {}
+
+
+def extract_speech_token(model: WhisperVQEncoder, feature_extractor: WhisperFeatureExtractor, utts):
+ with torch.no_grad():
+ audios, indices = [], []
+ for idx, utt in enumerate(utts):
+ if isinstance(utt, tuple):
+ audio, sample_rate = utt
+ else:
+ audio, sample_rate = torchaudio.load(utt)
+ audio = audio.cuda()
+ if sample_rate != 16000:
+ if sample_rate not in _resample_buffer:
+ _resample_buffer[sample_rate] = torchaudio.transforms.Resample(
+ orig_freq=sample_rate,
+ new_freq=16000
+ ).to('cuda')
+ audio = _resample_buffer[sample_rate](audio)
+ # if audio.shape[0] > 1:
+ # audio = audio[:1]
+ audio = audio[0]
+ audio = audio.cpu().numpy()
+ time_step = 0
+ while time_step * 16000 < audio.shape[0]:
+ audio_segment = audio[time_step * 16000: (time_step + 30) * 16000]
+ audios.append(audio_segment)
+ indices.append(idx)
+ time_step += 30
+ pooling_kernel_size = model.config.pooling_kernel_size or 1
+ stride = model.conv1.stride[0] * model.conv2.stride[0] * pooling_kernel_size * feature_extractor.hop_length
+ all_speech_tokens = [[] for _ in range(len(utts))]
+ batch_size = 128
+ for start in range(0, len(audios), batch_size):
+ features = feature_extractor(audios[start: start + batch_size], sampling_rate=16000,
+ return_attention_mask=True, return_tensors="pt", device='cuda',
+ padding="longest", pad_to_multiple_of=stride)
+ features = features.to(device="cuda")
+ outputs = model(**features)
+ speech_tokens = outputs.quantized_token_ids
+ attention_mask = features.attention_mask[:, ::model.conv1.stride[0] * model.conv2.stride[0]]
+ attention_mask = attention_mask[:, ::model.config.pooling_kernel_size]
+ assert attention_mask.shape == speech_tokens.shape
+ for i in range(len(speech_tokens)):
+ idx = indices[start + i]
+ speech_token = speech_tokens[i][attention_mask[i].bool()].tolist()
+ all_speech_tokens[idx].extend(speech_token)
+ return all_speech_tokens
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.env.example b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.env.example
new file mode 100644
index 0000000000000000000000000000000000000000..a790e320464ebc778ca07f5bcd826a9c8412ed0e
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.env.example
@@ -0,0 +1,6 @@
+# example of file for storing private and user specific environment variables, like keys or system paths
+# rename it to ".env" (excluded from version control by default)
+# .env is loaded by train.py automatically
+# hydra allows you to reference variables in .yaml configs with special syntax: ${oc.env:MY_VAR}
+
+MY_VAR="/home/user/my/system/path"
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.github/PULL_REQUEST_TEMPLATE.md b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.github/PULL_REQUEST_TEMPLATE.md
new file mode 100644
index 0000000000000000000000000000000000000000..410bcd87a45297ab8f0d369574a032858b6b1811
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.github/PULL_REQUEST_TEMPLATE.md
@@ -0,0 +1,22 @@
+## What does this PR do?
+
+
+
+Fixes #\
+
+## Before submitting
+
+- [ ] Did you make sure **title is self-explanatory** and **the description concisely explains the PR**?
+- [ ] Did you make sure your **PR does only one thing**, instead of bundling different changes together?
+- [ ] Did you list all the **breaking changes** introduced by this pull request?
+- [ ] Did you **test your PR locally** with `pytest` command?
+- [ ] Did you **run pre-commit hooks** with `pre-commit run -a` command?
+
+## Did you have fun?
+
+Make sure you had fun coding 🙃
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.github/codecov.yml b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.github/codecov.yml
new file mode 100644
index 0000000000000000000000000000000000000000..c66853c4bd9991f730da5dda7dc9881986779558
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.github/codecov.yml
@@ -0,0 +1,15 @@
+coverage:
+ status:
+ # measures overall project coverage
+ project:
+ default:
+ threshold: 100% # how much decrease in coverage is needed to not consider success
+
+ # measures PR or single commit coverage
+ patch:
+ default:
+ threshold: 100% # how much decrease in coverage is needed to not consider success
+
+
+ # project: off
+ # patch: off
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.gitignore b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..cbec8b43a0414bbbf4cc9feae49b9dc091a60c92
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.gitignore
@@ -0,0 +1,163 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+### VisualStudioCode
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+*.code-workspace
+**/.vscode
+
+# JetBrains
+.idea/
+
+# Data & Models
+*.h5
+*.tar
+*.tar.gz
+
+# Lightning-Hydra-Template
+configs/local/default.yaml
+/data/
+/logs/
+.env
+
+# Aim logging
+.aim
+
+# Cython complied files
+matcha/utils/monotonic_align/core.c
+
+# Ignoring hifigan checkpoint
+generator_v1
+g_02500000
+gradio_cached_examples/
+synth_output/
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.pre-commit-config.yaml b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.pre-commit-config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e695f115eba12d84fe6f465c5d834dfa35c3d2ec
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.pre-commit-config.yaml
@@ -0,0 +1,59 @@
+default_language_version:
+ python: python3.10
+
+repos:
+ - repo: https://github.com/pre-commit/pre-commit-hooks
+ rev: v4.5.0
+ hooks:
+ # list of supported hooks: https://pre-commit.com/hooks.html
+ - id: trailing-whitespace
+ - id: end-of-file-fixer
+ # - id: check-docstring-first
+ - id: check-yaml
+ - id: debug-statements
+ - id: detect-private-key
+ - id: check-toml
+ - id: check-case-conflict
+ - id: check-added-large-files
+
+ # python code formatting
+ - repo: https://github.com/psf/black
+ rev: 23.12.1
+ hooks:
+ - id: black
+ args: [--line-length, "120"]
+
+ # python import sorting
+ - repo: https://github.com/PyCQA/isort
+ rev: 5.13.2
+ hooks:
+ - id: isort
+ args: ["--profile", "black", "--filter-files"]
+
+ # python upgrading syntax to newer version
+ - repo: https://github.com/asottile/pyupgrade
+ rev: v3.15.0
+ hooks:
+ - id: pyupgrade
+ args: [--py38-plus]
+
+ # python check (PEP8), programming errors and code complexity
+ - repo: https://github.com/PyCQA/flake8
+ rev: 7.0.0
+ hooks:
+ - id: flake8
+ args:
+ [
+ "--max-line-length", "120",
+ "--extend-ignore",
+ "E203,E402,E501,F401,F841,RST2,RST301",
+ "--exclude",
+ "logs/*,data/*,matcha/hifigan/*",
+ ]
+ additional_dependencies: [flake8-rst-docstrings==0.3.0]
+
+ # pylint
+ - repo: https://github.com/pycqa/pylint
+ rev: v3.0.3
+ hooks:
+ - id: pylint
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.project-root b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.project-root
new file mode 100644
index 0000000000000000000000000000000000000000..63eab774b9e36aa1a46cbd31b59cbd373bc5477f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.project-root
@@ -0,0 +1,2 @@
+# this file is required for inferring the project root directory
+# do not delete
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.pylintrc b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.pylintrc
new file mode 100644
index 0000000000000000000000000000000000000000..962864189eab99a66b315b80f5a9976e7a423d4a
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/.pylintrc
@@ -0,0 +1,525 @@
+[MASTER]
+
+# A comma-separated list of package or module names from where C extensions may
+# be loaded. Extensions are loading into the active Python interpreter and may
+# run arbitrary code.
+extension-pkg-whitelist=
+
+# Add files or directories to the blacklist. They should be base names, not
+# paths.
+ignore=CVS
+
+# Add files or directories matching the regex patterns to the blacklist. The
+# regex matches against base names, not paths.
+ignore-patterns=
+
+# Python code to execute, usually for sys.path manipulation such as
+# pygtk.require().
+#init-hook=
+
+# Use multiple processes to speed up Pylint. Specifying 0 will auto-detect the
+# number of processors available to use.
+jobs=1
+
+# Control the amount of potential inferred values when inferring a single
+# object. This can help the performance when dealing with large functions or
+# complex, nested conditions.
+limit-inference-results=100
+
+# List of plugins (as comma separated values of python modules names) to load,
+# usually to register additional checkers.
+load-plugins=
+
+# Pickle collected data for later comparisons.
+persistent=yes
+
+# Specify a configuration file.
+#rcfile=
+
+# When enabled, pylint would attempt to guess common misconfiguration and emit
+# user-friendly hints instead of false-positive error messages.
+suggestion-mode=yes
+
+# Allow loading of arbitrary C extensions. Extensions are imported into the
+# active Python interpreter and may run arbitrary code.
+unsafe-load-any-extension=no
+
+
+[MESSAGES CONTROL]
+
+# Only show warnings with the listed confidence levels. Leave empty to show
+# all. Valid levels: HIGH, INFERENCE, INFERENCE_FAILURE, UNDEFINED.
+confidence=
+
+# Disable the message, report, category or checker with the given id(s). You
+# can either give multiple identifiers separated by comma (,) or put this
+# option multiple times (only on the command line, not in the configuration
+# file where it should appear only once). You can also use "--disable=all" to
+# disable everything first and then reenable specific checks. For example, if
+# you want to run only the similarities checker, you can use "--disable=all
+# --enable=similarities". If you want to run only the classes checker, but have
+# no Warning level messages displayed, use "--disable=all --enable=classes
+# --disable=W".
+disable=missing-docstring,
+ too-many-public-methods,
+ too-many-lines,
+ bare-except,
+ ## for avoiding weird p3.6 CI linter error
+ ## TODO: see later if we can remove this
+ assigning-non-slot,
+ unsupported-assignment-operation,
+ ## end
+ line-too-long,
+ fixme,
+ wrong-import-order,
+ ungrouped-imports,
+ wrong-import-position,
+ import-error,
+ invalid-name,
+ too-many-instance-attributes,
+ arguments-differ,
+ arguments-renamed,
+ no-name-in-module,
+ no-member,
+ unsubscriptable-object,
+ raw-checker-failed,
+ bad-inline-option,
+ locally-disabled,
+ file-ignored,
+ suppressed-message,
+ useless-suppression,
+ deprecated-pragma,
+ use-symbolic-message-instead,
+ useless-object-inheritance,
+ too-few-public-methods,
+ too-many-branches,
+ too-many-arguments,
+ too-many-locals,
+ too-many-statements,
+ duplicate-code,
+ not-callable,
+ import-outside-toplevel,
+ logging-fstring-interpolation,
+ logging-not-lazy,
+ unused-argument,
+ no-else-return,
+ chained-comparison,
+ redefined-outer-name
+
+# Enable the message, report, category or checker with the given id(s). You can
+# either give multiple identifier separated by comma (,) or put this option
+# multiple time (only on the command line, not in the configuration file where
+# it should appear only once). See also the "--disable" option for examples.
+enable=c-extension-no-member
+
+
+[REPORTS]
+
+# Python expression which should return a note less than 10 (10 is the highest
+# note). You have access to the variables errors warning, statement which
+# respectively contain the number of errors / warnings messages and the total
+# number of statements analyzed. This is used by the global evaluation report
+# (RP0004).
+evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10)
+
+# Template used to display messages. This is a python new-style format string
+# used to format the message information. See doc for all details.
+#msg-template=
+
+# Set the output format. Available formats are text, parseable, colorized, json
+# and msvs (visual studio). You can also give a reporter class, e.g.
+# mypackage.mymodule.MyReporterClass.
+output-format=text
+
+# Tells whether to display a full report or only the messages.
+reports=no
+
+# Activate the evaluation score.
+score=yes
+
+
+[REFACTORING]
+
+# Maximum number of nested blocks for function / method body
+max-nested-blocks=5
+
+# Complete name of functions that never returns. When checking for
+# inconsistent-return-statements if a never returning function is called then
+# it will be considered as an explicit return statement and no message will be
+# printed.
+never-returning-functions=sys.exit
+
+
+[LOGGING]
+
+# Format style used to check logging format string. `old` means using %
+# formatting, while `new` is for `{}` formatting.
+logging-format-style=old
+
+# Logging modules to check that the string format arguments are in logging
+# function parameter format.
+logging-modules=logging
+
+
+[SPELLING]
+
+# Limits count of emitted suggestions for spelling mistakes.
+max-spelling-suggestions=4
+
+# Spelling dictionary name. Available dictionaries: none. To make it working
+# install python-enchant package..
+spelling-dict=
+
+# List of comma separated words that should not be checked.
+spelling-ignore-words=
+
+# A path to a file that contains private dictionary; one word per line.
+spelling-private-dict-file=
+
+# Tells whether to store unknown words to indicated private dictionary in
+# --spelling-private-dict-file option instead of raising a message.
+spelling-store-unknown-words=no
+
+
+[MISCELLANEOUS]
+
+# List of note tags to take in consideration, separated by a comma.
+notes=FIXME,
+ XXX,
+ TODO
+
+
+[TYPECHECK]
+
+# List of decorators that produce context managers, such as
+# contextlib.contextmanager. Add to this list to register other decorators that
+# produce valid context managers.
+contextmanager-decorators=contextlib.contextmanager
+
+# List of members which are set dynamically and missed by pylint inference
+# system, and so shouldn't trigger E1101 when accessed. Python regular
+# expressions are accepted.
+generated-members=numpy.*,torch.*
+
+# Tells whether missing members accessed in mixin class should be ignored. A
+# mixin class is detected if its name ends with "mixin" (case insensitive).
+ignore-mixin-members=yes
+
+# Tells whether to warn about missing members when the owner of the attribute
+# is inferred to be None.
+ignore-none=yes
+
+# This flag controls whether pylint should warn about no-member and similar
+# checks whenever an opaque object is returned when inferring. The inference
+# can return multiple potential results while evaluating a Python object, but
+# some branches might not be evaluated, which results in partial inference. In
+# that case, it might be useful to still emit no-member and other checks for
+# the rest of the inferred objects.
+ignore-on-opaque-inference=yes
+
+# List of class names for which member attributes should not be checked (useful
+# for classes with dynamically set attributes). This supports the use of
+# qualified names.
+ignored-classes=optparse.Values,thread._local,_thread._local
+
+# List of module names for which member attributes should not be checked
+# (useful for modules/projects where namespaces are manipulated during runtime
+# and thus existing member attributes cannot be deduced by static analysis. It
+# supports qualified module names, as well as Unix pattern matching.
+ignored-modules=
+
+# Show a hint with possible names when a member name was not found. The aspect
+# of finding the hint is based on edit distance.
+missing-member-hint=yes
+
+# The minimum edit distance a name should have in order to be considered a
+# similar match for a missing member name.
+missing-member-hint-distance=1
+
+# The total number of similar names that should be taken in consideration when
+# showing a hint for a missing member.
+missing-member-max-choices=1
+
+
+[VARIABLES]
+
+# List of additional names supposed to be defined in builtins. Remember that
+# you should avoid defining new builtins when possible.
+additional-builtins=
+
+# Tells whether unused global variables should be treated as a violation.
+allow-global-unused-variables=yes
+
+# List of strings which can identify a callback function by name. A callback
+# name must start or end with one of those strings.
+callbacks=cb_,
+ _cb
+
+# A regular expression matching the name of dummy variables (i.e. expected to
+# not be used).
+dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_
+
+# Argument names that match this expression will be ignored. Default to name
+# with leading underscore.
+ignored-argument-names=_.*|^ignored_|^unused_
+
+# Tells whether we should check for unused import in __init__ files.
+init-import=no
+
+# List of qualified module names which can have objects that can redefine
+# builtins.
+redefining-builtins-modules=six.moves,past.builtins,future.builtins,builtins,io
+
+
+[FORMAT]
+
+# Expected format of line ending, e.g. empty (any line ending), LF or CRLF.
+expected-line-ending-format=
+
+# Regexp for a line that is allowed to be longer than the limit.
+ignore-long-lines=^\s*(# )??$
+
+# Number of spaces of indent required inside a hanging or continued line.
+indent-after-paren=4
+
+# String used as indentation unit. This is usually " " (4 spaces) or "\t" (1
+# tab).
+indent-string=' '
+
+# Maximum number of characters on a single line.
+max-line-length=120
+
+# Maximum number of lines in a module.
+max-module-lines=1000
+
+# Allow the body of a class to be on the same line as the declaration if body
+# contains single statement.
+single-line-class-stmt=no
+
+# Allow the body of an if to be on the same line as the test if there is no
+# else.
+single-line-if-stmt=no
+
+
+[SIMILARITIES]
+
+# Ignore comments when computing similarities.
+ignore-comments=yes
+
+# Ignore docstrings when computing similarities.
+ignore-docstrings=yes
+
+# Ignore imports when computing similarities.
+ignore-imports=no
+
+# Minimum lines number of a similarity.
+min-similarity-lines=4
+
+
+[BASIC]
+
+# Naming style matching correct argument names.
+argument-naming-style=snake_case
+
+# Regular expression matching correct argument names. Overrides argument-
+# naming-style.
+argument-rgx=[a-z_][a-z0-9_]{0,30}$
+
+# Naming style matching correct attribute names.
+attr-naming-style=snake_case
+
+# Regular expression matching correct attribute names. Overrides attr-naming-
+# style.
+#attr-rgx=
+
+# Bad variable names which should always be refused, separated by a comma.
+bad-names=
+
+# Naming style matching correct class attribute names.
+class-attribute-naming-style=any
+
+# Regular expression matching correct class attribute names. Overrides class-
+# attribute-naming-style.
+#class-attribute-rgx=
+
+# Naming style matching correct class names.
+class-naming-style=PascalCase
+
+# Regular expression matching correct class names. Overrides class-naming-
+# style.
+#class-rgx=
+
+# Naming style matching correct constant names.
+const-naming-style=UPPER_CASE
+
+# Regular expression matching correct constant names. Overrides const-naming-
+# style.
+#const-rgx=
+
+# Minimum line length for functions/classes that require docstrings, shorter
+# ones are exempt.
+docstring-min-length=-1
+
+# Naming style matching correct function names.
+function-naming-style=snake_case
+
+# Regular expression matching correct function names. Overrides function-
+# naming-style.
+#function-rgx=
+
+# Good variable names which should always be accepted, separated by a comma.
+good-names=i,
+ j,
+ k,
+ x,
+ ex,
+ Run,
+ _
+
+# Include a hint for the correct naming format with invalid-name.
+include-naming-hint=no
+
+# Naming style matching correct inline iteration names.
+inlinevar-naming-style=any
+
+# Regular expression matching correct inline iteration names. Overrides
+# inlinevar-naming-style.
+#inlinevar-rgx=
+
+# Naming style matching correct method names.
+method-naming-style=snake_case
+
+# Regular expression matching correct method names. Overrides method-naming-
+# style.
+#method-rgx=
+
+# Naming style matching correct module names.
+module-naming-style=snake_case
+
+# Regular expression matching correct module names. Overrides module-naming-
+# style.
+#module-rgx=
+
+# Colon-delimited sets of names that determine each other's naming style when
+# the name regexes allow several styles.
+name-group=
+
+# Regular expression which should only match function or class names that do
+# not require a docstring.
+no-docstring-rgx=^_
+
+# List of decorators that produce properties, such as abc.abstractproperty. Add
+# to this list to register other decorators that produce valid properties.
+# These decorators are taken in consideration only for invalid-name.
+property-classes=abc.abstractproperty
+
+# Naming style matching correct variable names.
+variable-naming-style=snake_case
+
+# Regular expression matching correct variable names. Overrides variable-
+# naming-style.
+variable-rgx=[a-z_][a-z0-9_]{0,30}$
+
+
+[STRING]
+
+# This flag controls whether the implicit-str-concat-in-sequence should
+# generate a warning on implicit string concatenation in sequences defined over
+# several lines.
+check-str-concat-over-line-jumps=no
+
+
+[IMPORTS]
+
+# Allow wildcard imports from modules that define __all__.
+allow-wildcard-with-all=no
+
+# Analyse import fallback blocks. This can be used to support both Python 2 and
+# 3 compatible code, which means that the block might have code that exists
+# only in one or another interpreter, leading to false positives when analysed.
+analyse-fallback-blocks=no
+
+# Deprecated modules which should not be used, separated by a comma.
+deprecated-modules=optparse,tkinter.tix
+
+# Create a graph of external dependencies in the given file (report RP0402 must
+# not be disabled).
+ext-import-graph=
+
+# Create a graph of every (i.e. internal and external) dependencies in the
+# given file (report RP0402 must not be disabled).
+import-graph=
+
+# Create a graph of internal dependencies in the given file (report RP0402 must
+# not be disabled).
+int-import-graph=
+
+# Force import order to recognize a module as part of the standard
+# compatibility libraries.
+known-standard-library=
+
+# Force import order to recognize a module as part of a third party library.
+known-third-party=enchant
+
+
+[CLASSES]
+
+# List of method names used to declare (i.e. assign) instance attributes.
+defining-attr-methods=__init__,
+ __new__,
+ setUp
+
+# List of member names, which should be excluded from the protected access
+# warning.
+exclude-protected=_asdict,
+ _fields,
+ _replace,
+ _source,
+ _make
+
+# List of valid names for the first argument in a class method.
+valid-classmethod-first-arg=cls
+
+# List of valid names for the first argument in a metaclass class method.
+valid-metaclass-classmethod-first-arg=cls
+
+
+[DESIGN]
+
+# Maximum number of arguments for function / method.
+max-args=5
+
+# Maximum number of attributes for a class (see R0902).
+max-attributes=7
+
+# Maximum number of boolean expressions in an if statement.
+max-bool-expr=5
+
+# Maximum number of branch for function / method body.
+max-branches=12
+
+# Maximum number of locals for function / method body.
+max-locals=15
+
+# Maximum number of parents for a class (see R0901).
+max-parents=15
+
+# Maximum number of public methods for a class (see R0904).
+max-public-methods=20
+
+# Maximum number of return / yield for function / method body.
+max-returns=6
+
+# Maximum number of statements in function / method body.
+max-statements=50
+
+# Minimum number of public methods for a class (see R0903).
+min-public-methods=2
+
+
+[EXCEPTIONS]
+
+# Exceptions that will emit a warning when being caught. Defaults to
+# "BaseException, Exception".
+overgeneral-exceptions=builtins.BaseException,
+ builtins.Exception
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/LICENSE b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..858018e750da7be7b271bb7307e68d159ed67ef6
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 Shivam Mehta
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/MANIFEST.in b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/MANIFEST.in
new file mode 100644
index 0000000000000000000000000000000000000000..c013140cdfb9de19c4d4e73c73a44e33f33fa871
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/MANIFEST.in
@@ -0,0 +1,14 @@
+include README.md
+include LICENSE.txt
+include requirements.*.txt
+include *.cff
+include requirements.txt
+include matcha/VERSION
+recursive-include matcha *.json
+recursive-include matcha *.html
+recursive-include matcha *.png
+recursive-include matcha *.md
+recursive-include matcha *.py
+recursive-include matcha *.pyx
+recursive-exclude tests *
+prune tests*
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/Makefile b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..4b523dd17b13a19617c9cc9d9dad7f7d8d4c24a0
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/Makefile
@@ -0,0 +1,42 @@
+
+help: ## Show help
+ @grep -E '^[.a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
+
+clean: ## Clean autogenerated files
+ rm -rf dist
+ find . -type f -name "*.DS_Store" -ls -delete
+ find . | grep -E "(__pycache__|\.pyc|\.pyo)" | xargs rm -rf
+ find . | grep -E ".pytest_cache" | xargs rm -rf
+ find . | grep -E ".ipynb_checkpoints" | xargs rm -rf
+ rm -f .coverage
+
+clean-logs: ## Clean logs
+ rm -rf logs/**
+
+create-package: ## Create wheel and tar gz
+ rm -rf dist/
+ python setup.py bdist_wheel --plat-name=manylinux1_x86_64
+ python setup.py sdist
+ python -m twine upload dist/* --verbose --skip-existing
+
+format: ## Run pre-commit hooks
+ pre-commit run -a
+
+sync: ## Merge changes from main branch to your current branch
+ git pull
+ git pull origin main
+
+test: ## Run not slow tests
+ pytest -k "not slow"
+
+test-full: ## Run all tests
+ pytest
+
+train-ljspeech: ## Train the model
+ python matcha/train.py experiment=ljspeech
+
+train-ljspeech-min: ## Train the model with minimum memory
+ python matcha/train.py experiment=ljspeech_min_memory
+
+start_app: ## Start the app
+ python matcha/app.py
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/README.md b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..ebc6b7c0a76d30c33bf95583d629825c02183e31
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/README.md
@@ -0,0 +1,278 @@
+
+
+# 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching
+
+### [Shivam Mehta](https://www.kth.se/profile/smehta), [Ruibo Tu](https://www.kth.se/profile/ruibo), [Jonas Beskow](https://www.kth.se/profile/beskow), [Éva Székely](https://www.kth.se/profile/szekely), and [Gustav Eje Henter](https://people.kth.se/~ghe/)
+
+[](https://www.python.org/downloads/release/python-3100/)
+[](https://pytorch.org/get-started/locally/)
+[](https://pytorchlightning.ai/)
+[](https://hydra.cc/)
+[](https://black.readthedocs.io/en/stable/)
+[](https://pycqa.github.io/isort/)
+
+
+
+
+
+```
+
+- To batch synthesise from a file, run:
+
+```bash
+matcha-tts --file --batched
+```
+
+Additional arguments
+
+- Speaking rate
+
+```bash
+matcha-tts --text "
+```
+
+## ONNX support
+
+> Special thanks to [@mush42](https://github.com/mush42) for implementing ONNX export and inference support.
+
+It is possible to export Matcha checkpoints to [ONNX](https://onnx.ai/), and run inference on the exported ONNX graph.
+
+### ONNX export
+
+To export a checkpoint to ONNX, first install ONNX with
+
+```bash
+pip install onnx
+```
+
+then run the following:
+
+```bash
+python3 -m matcha.onnx.export matcha.ckpt model.onnx --n-timesteps 5
+```
+
+Optionally, the ONNX exporter accepts **vocoder-name** and **vocoder-checkpoint** arguments. This enables you to embed the vocoder in the exported graph and generate waveforms in a single run (similar to end-to-end TTS systems).
+
+**Note** that `n_timesteps` is treated as a hyper-parameter rather than a model input. This means you should specify it during export (not during inference). If not specified, `n_timesteps` is set to **5**.
+
+**Important**: for now, torch>=2.1.0 is needed for export since the `scaled_product_attention` operator is not exportable in older versions. Until the final version is released, those who want to export their models must install torch>=2.1.0 manually as a pre-release.
+
+### ONNX Inference
+
+To run inference on the exported model, first install `onnxruntime` using
+
+```bash
+pip install onnxruntime
+pip install onnxruntime-gpu # for GPU inference
+```
+
+then use the following:
+
+```bash
+python3 -m matcha.onnx.infer model.onnx --text "hey" --output-dir ./outputs
+```
+
+You can also control synthesis parameters:
+
+```bash
+python3 -m matcha.onnx.infer model.onnx --text "hey" --output-dir ./outputs --temperature 0.4 --speaking_rate 0.9 --spk 0
+```
+
+To run inference on **GPU**, make sure to install **onnxruntime-gpu** package, and then pass `--gpu` to the inference command:
+
+```bash
+python3 -m matcha.onnx.infer model.onnx --text "hey" --output-dir ./outputs --gpu
+```
+
+If you exported only Matcha to ONNX, this will write mel-spectrogram as graphs and `numpy` arrays to the output directory.
+If you embedded the vocoder in the exported graph, this will write `.wav` audio files to the output directory.
+
+If you exported only Matcha to ONNX, and you want to run a full TTS pipeline, you can pass a path to a vocoder model in `ONNX` format:
+
+```bash
+python3 -m matcha.onnx.infer model.onnx --text "hey" --output-dir ./outputs --vocoder hifigan.small.onnx
+```
+
+This will write `.wav` audio files to the output directory.
+
+## Citation information
+
+If you use our code or otherwise find this work useful, please cite our paper:
+
+```text
+@inproceedings{mehta2024matcha,
+ title={Matcha-{TTS}: A fast {TTS} architecture with conditional flow matching},
+ author={Mehta, Shivam and Tu, Ruibo and Beskow, Jonas and Sz{\'e}kely, {\'E}va and Henter, Gustav Eje},
+ booktitle={Proc. ICASSP},
+ year={2024}
+}
+```
+
+## Acknowledgements
+
+Since this code uses [Lightning-Hydra-Template](https://github.com/ashleve/lightning-hydra-template), you have all the powers that come with it.
+
+Other source code we would like to acknowledge:
+
+- [Coqui-TTS](https://github.com/coqui-ai/TTS/tree/dev): For helping me figure out how to make cython binaries pip installable and encouragement
+- [Hugging Face Diffusers](https://huggingface.co/): For their awesome diffusers library and its components
+- [Grad-TTS](https://github.com/huawei-noah/Speech-Backbones/tree/main/Grad-TTS): For the monotonic alignment search source code
+- [torchdyn](https://github.com/DiffEqML/torchdyn): Useful for trying other ODE solvers during research and development
+- [labml.ai](https://nn.labml.ai/transformers/rope/index.html): For the RoPE implementation
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/pyproject.toml b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/pyproject.toml
new file mode 100644
index 0000000000000000000000000000000000000000..74aa39300a61b8b3607dc634d68aa47013141ec5
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/pyproject.toml
@@ -0,0 +1,51 @@
+[build-system]
+requires = ["setuptools", "wheel", "cython==0.29.35", "numpy==1.24.3", "packaging"]
+
+[tool.black]
+line-length = 120
+target-version = ['py310']
+exclude = '''
+
+(
+ /(
+ \.eggs # exclude a few common directories in the
+ | \.git # root of the project
+ | \.hg
+ | \.mypy_cache
+ | \.tox
+ | \.venv
+ | _build
+ | buck-out
+ | build
+ | dist
+ )/
+ | foo.py # also separately exclude a file named foo.py in
+ # the root of the project
+)
+'''
+
+[tool.pytest.ini_options]
+addopts = [
+ "--color=yes",
+ "--durations=0",
+ "--strict-markers",
+ "--doctest-modules",
+]
+filterwarnings = [
+ "ignore::DeprecationWarning",
+ "ignore::UserWarning",
+]
+log_cli = "True"
+markers = [
+ "slow: slow tests",
+]
+minversion = "6.0"
+testpaths = "tests/"
+
+[tool.coverage.report]
+exclude_lines = [
+ "pragma: nocover",
+ "raise NotImplementedError",
+ "raise NotImplementedError()",
+ "if __name__ == .__main__.:",
+]
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/requirements.txt b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3e14a532cb14f99190404472915213940bfad4b9
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/requirements.txt
@@ -0,0 +1,45 @@
+# --------- pytorch --------- #
+torch>=2.0.0
+torchvision>=0.15.0
+lightning>=2.0.0
+torchmetrics>=0.11.4
+
+# --------- hydra --------- #
+hydra-core==1.3.2
+hydra-colorlog==1.2.0
+hydra-optuna-sweeper==1.2.0
+
+# --------- loggers --------- #
+# wandb
+# neptune-client
+# mlflow
+# comet-ml
+# aim>=3.16.2 # no lower than 3.16.2, see https://github.com/aimhubio/aim/issues/2550
+
+# --------- others --------- #
+rootutils # standardizing the project root setup
+pre-commit # hooks for applying linters on commit
+rich # beautiful text formatting in terminal
+pytest # tests
+# sh # for running bash commands in some tests (linux/macos only)
+phonemizer # phonemization of text
+tensorboard
+librosa
+Cython
+numpy
+einops
+inflect
+Unidecode
+scipy
+torchaudio
+matplotlib
+pandas
+conformer==0.3.2
+diffusers==0.25.0
+notebook
+ipywidgets
+gradio==3.43.2
+gdown
+wget
+seaborn
+piper_phonemize
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/setup.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/setup.py
new file mode 100644
index 0000000000000000000000000000000000000000..80d4aac04c6cd36859c5d753468ef2e105770098
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/setup.py
@@ -0,0 +1,45 @@
+#!/usr/bin/env python
+import os
+
+import numpy
+from Cython.Build import cythonize
+from setuptools import Extension, find_packages, setup
+
+exts = [
+ Extension(
+ name="matcha.utils.monotonic_align.core",
+ sources=["matcha/utils/monotonic_align/core.pyx"],
+ )
+]
+
+with open("README.md", encoding="utf-8") as readme_file:
+ README = readme_file.read()
+
+cwd = os.path.dirname(os.path.abspath(__file__))
+with open(os.path.join(cwd, "matcha", "VERSION")) as fin:
+ version = fin.read().strip()
+
+setup(
+ name="matcha-tts",
+ version=version,
+ description="🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching",
+ long_description=README,
+ long_description_content_type="text/markdown",
+ author="Shivam Mehta",
+ author_email="shivam.mehta25@gmail.com",
+ url="https://shivammehta25.github.io/Matcha-TTS",
+ install_requires=[str(r) for r in open(os.path.join(os.path.dirname(__file__), "requirements.txt"))],
+ include_dirs=[numpy.get_include()],
+ include_package_data=True,
+ packages=find_packages(exclude=["tests", "tests/*", "examples", "examples/*"]),
+ # use this to customize global commands available in the terminal after installing the package
+ entry_points={
+ "console_scripts": [
+ "matcha-data-stats=matcha.utils.generate_data_statistics:main",
+ "matcha-tts=matcha.cli:cli",
+ "matcha-tts-app=matcha.app:main",
+ ]
+ },
+ ext_modules=cythonize(exts, language_level=3),
+ python_requires=">=3.9.0",
+)
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/synthesis.ipynb b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/synthesis.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..dfbde30b5ad98f1368be3aa181145a4eac97da93
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/third_party/Matcha-TTS/synthesis.ipynb
@@ -0,0 +1,419 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "f37f4e3b-f764-4502-a6a2-6417bd9bfab9",
+ "metadata": {},
+ "source": [
+ "# Matcha-TTS: A fast TTS architecture with conditional flow matching\n",
+ "---\n",
+ "[Shivam Mehta](https://www.kth.se/profile/smehta), [Ruibo Tu](https://www.kth.se/profile/ruibo), [Jonas Beskow](https://www.kth.se/profile/beskow), [Éva Székely](https://www.kth.se/profile/szekely), and [Gustav Eje Henter](https://people.kth.se/~ghe/)\n",
+ "\n",
+ "We introduce Matcha-TTS, a new encoder-decoder architecture for speedy TTS acoustic modelling, trained using optimal-transport conditional flow matching (OT-CFM). This yields an ODE-based decoder capable of high output quality in fewer synthesis steps than models trained using score matching. Careful design choices additionally ensure each synthesis step is fast to run. The method is probabilistic, non-autoregressive, and learns to speak from scratch without external alignments. Compared to strong pre-trained baseline models, the Matcha-TTS system has the smallest memory footprint, rivals the speed of the fastest models on long utterances, and attains the highest mean opinion score in a listening test.\n",
+ "\n",
+ "Demo Page: https://shivammehta25.github.io/Matcha-TTS \\\n",
+ "Code: https://github.com/shivammehta25/Matcha-TTS\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "148f4bc0-c28e-4670-9a5e-4c7928ab8992",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "env: CUDA_VISIBLE_DEVICES=0\n"
+ ]
+ }
+ ],
+ "source": [
+ "%env CUDA_VISIBLE_DEVICES=0"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "8d5876c0-b47e-4c80-9e9c-62550f81b64e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import datetime as dt\n",
+ "from pathlib import Path\n",
+ "\n",
+ "import IPython.display as ipd\n",
+ "import numpy as np\n",
+ "import soundfile as sf\n",
+ "import torch\n",
+ "from tqdm.auto import tqdm\n",
+ "\n",
+ "# Hifigan imports\n",
+ "from matcha.hifigan.config import v1\n",
+ "from matcha.hifigan.denoiser import Denoiser\n",
+ "from matcha.hifigan.env import AttrDict\n",
+ "from matcha.hifigan.models import Generator as HiFiGAN\n",
+ "# Matcha imports\n",
+ "from matcha.models.matcha_tts import MatchaTTS\n",
+ "from matcha.text import sequence_to_text, text_to_sequence\n",
+ "from matcha.utils.model import denormalize\n",
+ "from matcha.utils.utils import get_user_data_dir, intersperse"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "b1a30306-588c-4f22-8d9b-e2676880b0e5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%load_ext autoreload\n",
+ "%autoreload 2\n",
+ "%matplotlib inline\n",
+ "# This allows for real time code changes being reflected in the notebook, no need to restart the kernel"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "a312856b-01a9-4d75-a4c8-4666dffa0692",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "88f3b3c3-d014-443b-84eb-e143cdec3e21",
+ "metadata": {},
+ "source": [
+ "## Filepaths"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "7640a4c1-44ce-447c-a8ff-45012fb7bddd",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "MATCHA_CHECKPOINT = get_user_data_dir()/\"matcha_ljspeech.ckpt\"\n",
+ "HIFIGAN_CHECKPOINT = get_user_data_dir() / \"hifigan_T2_v1\"\n",
+ "OUTPUT_FOLDER = \"synth_output\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "6477a3a9-71f2-4d2f-bb86-bdf3e31c2461",
+ "metadata": {},
+ "source": [
+ "## Load Matcha-TTS"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "26a16230-04ba-4825-a844-2fb5ab945e24",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model loaded! Parameter count: 18,204,193\n"
+ ]
+ }
+ ],
+ "source": [
+ "def load_model(checkpoint_path):\n",
+ " model = MatchaTTS.load_from_checkpoint(checkpoint_path, map_location=device)\n",
+ " model.eval()\n",
+ " return model\n",
+ "count_params = lambda x: f\"{sum(p.numel() for p in x.parameters()):,}\"\n",
+ "\n",
+ "\n",
+ "model = load_model(MATCHA_CHECKPOINT)\n",
+ "print(f\"Model loaded! Parameter count: {count_params(model)}\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3077b84b-e3b6-42e1-a84b-2f7084b13f92",
+ "metadata": {},
+ "source": [
+ "## Load HiFi-GAN (Vocoder)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "f6b68184-968d-4868-9029-f0c40e9e68af",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Removing weight norm...\n"
+ ]
+ }
+ ],
+ "source": [
+ "def load_vocoder(checkpoint_path):\n",
+ " h = AttrDict(v1)\n",
+ " hifigan = HiFiGAN(h).to(device)\n",
+ " hifigan.load_state_dict(torch.load(checkpoint_path, map_location=device)['generator'])\n",
+ " _ = hifigan.eval()\n",
+ " hifigan.remove_weight_norm()\n",
+ " return hifigan\n",
+ "\n",
+ "vocoder = load_vocoder(HIFIGAN_CHECKPOINT)\n",
+ "denoiser = Denoiser(vocoder, mode='zeros')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4cbc2ba0-09ff-40e2-9e60-6b77b534f9fb",
+ "metadata": {},
+ "source": [
+ "### Helper functions to synthesise"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "880a1879-24fd-4757-849c-850339120796",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "@torch.inference_mode()\n",
+ "def process_text(text: str):\n",
+ " x = torch.tensor(intersperse(text_to_sequence(text, ['english_cleaners2']), 0),dtype=torch.long, device=device)[None]\n",
+ " x_lengths = torch.tensor([x.shape[-1]],dtype=torch.long, device=device)\n",
+ " x_phones = sequence_to_text(x.squeeze(0).tolist())\n",
+ " return {\n",
+ " 'x_orig': text,\n",
+ " 'x': x,\n",
+ " 'x_lengths': x_lengths,\n",
+ " 'x_phones': x_phones\n",
+ " }\n",
+ "\n",
+ "\n",
+ "@torch.inference_mode()\n",
+ "def synthesise(text, spks=None):\n",
+ " text_processed = process_text(text)\n",
+ " start_t = dt.datetime.now()\n",
+ " output = model.synthesise(\n",
+ " text_processed['x'], \n",
+ " text_processed['x_lengths'],\n",
+ " n_timesteps=n_timesteps,\n",
+ " temperature=temperature,\n",
+ " spks=spks,\n",
+ " length_scale=length_scale\n",
+ " )\n",
+ " # merge everything to one dict \n",
+ " output.update({'start_t': start_t, **text_processed})\n",
+ " return output\n",
+ "\n",
+ "@torch.inference_mode()\n",
+ "def to_waveform(mel, vocoder):\n",
+ " audio = vocoder(mel).clamp(-1, 1)\n",
+ " audio = denoiser(audio.squeeze(0), strength=0.00025).cpu().squeeze()\n",
+ " return audio.cpu().squeeze()\n",
+ " \n",
+ "def save_to_folder(filename: str, output: dict, folder: str):\n",
+ " folder = Path(folder)\n",
+ " folder.mkdir(exist_ok=True, parents=True)\n",
+ " np.save(folder / f'{filename}', output['mel'].cpu().numpy())\n",
+ " sf.write(folder / f'{filename}.wav', output['waveform'], 22050, 'PCM_24')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "78f857e3-2ef7-4c86-b776-596c4d3cf875",
+ "metadata": {},
+ "source": [
+ "## Setup text to synthesise"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "2e0a9acd-0845-4192-ba09-b9683e28a3ac",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "texts = [\n",
+ " \"The Secret Service believed that it was very doubtful that any President would ride regularly in a vehicle with a fixed top, even though transparent.\"\n",
+ "]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a9da9e2d-99b9-4c6f-8a08-c828e2cba121",
+ "metadata": {},
+ "source": [
+ "### Hyperparameters"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "f0d216e5-4895-4da8-9d24-9e61021d2556",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "## Number of ODE Solver steps\n",
+ "n_timesteps = 10\n",
+ "\n",
+ "## Changes to the speaking rate\n",
+ "length_scale=1.0\n",
+ "\n",
+ "## Sampling temperature\n",
+ "temperature = 0.667"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b93aac89-c7f8-4975-8510-4e763c9689f4",
+ "metadata": {},
+ "source": [
+ "## Synthesis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "5a227963-aa12-43b9-a706-1168b6fc0ba5",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "8342d12401c54017b0e19b8d293a06bf",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ " 0%| | 0/1 [00:00\n",
+ " "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Number of ODE steps: 10\n",
+ "Mean RTF:\t\t\t\t0.017228 ± 0.000000\n",
+ "Mean RTF Waveform (incl. vocoder):\t0.021445 ± 0.000000\n"
+ ]
+ }
+ ],
+ "source": [
+ "outputs, rtfs = [], []\n",
+ "rtfs_w = []\n",
+ "for i, text in enumerate(tqdm(texts)):\n",
+ " output = synthesise(text) #, torch.tensor([15], device=device, dtype=torch.long).unsqueeze(0))\n",
+ " output['waveform'] = to_waveform(output['mel'], vocoder)\n",
+ "\n",
+ " # Compute Real Time Factor (RTF) with HiFi-GAN\n",
+ " t = (dt.datetime.now() - output['start_t']).total_seconds()\n",
+ " rtf_w = t * 22050 / (output['waveform'].shape[-1])\n",
+ "\n",
+ " ## Pretty print\n",
+ " print(f\"{'*' * 53}\")\n",
+ " print(f\"Input text - {i}\")\n",
+ " print(f\"{'-' * 53}\")\n",
+ " print(output['x_orig'])\n",
+ " print(f\"{'*' * 53}\")\n",
+ " print(f\"Phonetised text - {i}\")\n",
+ " print(f\"{'-' * 53}\")\n",
+ " print(output['x_phones'])\n",
+ " print(f\"{'*' * 53}\")\n",
+ " print(f\"RTF:\\t\\t{output['rtf']:.6f}\")\n",
+ " print(f\"RTF Waveform:\\t{rtf_w:.6f}\")\n",
+ " rtfs.append(output['rtf'])\n",
+ " rtfs_w.append(rtf_w)\n",
+ "\n",
+ " ## Display the synthesised waveform\n",
+ " ipd.display(ipd.Audio(output['waveform'], rate=22050))\n",
+ "\n",
+ " ## Save the generated waveform\n",
+ " save_to_folder(i, output, OUTPUT_FOLDER)\n",
+ "\n",
+ "print(f\"Number of ODE steps: {n_timesteps}\")\n",
+ "print(f\"Mean RTF:\\t\\t\\t\\t{np.mean(rtfs):.6f} ± {np.std(rtfs):.6f}\")\n",
+ "print(f\"Mean RTF Waveform (incl. vocoder):\\t{np.mean(rtfs_w):.6f} ± {np.std(rtfs_w):.6f}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e3e85c3f-1623-4647-b40c-fa96907656fc",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/web_demo.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/web_demo.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc183f0c8c41e2076ca4164b41edcd6d04cfe068
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4/web_demo.py
@@ -0,0 +1,267 @@
+import json
+import os.path
+import tempfile
+import sys
+import re
+import uuid
+import requests
+from argparse import ArgumentParser
+
+import torchaudio
+from transformers import WhisperFeatureExtractor, AutoTokenizer
+from speech_tokenizer.modeling_whisper import WhisperVQEncoder
+
+
+sys.path.insert(0, "./cosyvoice")
+sys.path.insert(0, "./third_party/Matcha-TTS")
+
+from speech_tokenizer.utils import extract_speech_token
+
+import gradio as gr
+import torch
+
+audio_token_pattern = re.compile(r"<\|audio_(\d+)\|>")
+
+from flow_inference import AudioDecoder
+from audio_process import AudioStreamProcessor
+
+if __name__ == "__main__":
+ parser = ArgumentParser()
+ parser.add_argument("--host", type=str, default="0.0.0.0")
+ parser.add_argument("--port", type=int, default="8888")
+ parser.add_argument("--flow-path", type=str, default="./glm-4-voice-decoder")
+ parser.add_argument("--model-path", type=str, default="THUDM/glm-4-voice-9b")
+ parser.add_argument("--tokenizer-path", type= str, default="THUDM/glm-4-voice-tokenizer")
+ args = parser.parse_args()
+
+ flow_config = os.path.join(args.flow_path, "config.yaml")
+ flow_checkpoint = os.path.join(args.flow_path, 'flow.pt')
+ hift_checkpoint = os.path.join(args.flow_path, 'hift.pt')
+ glm_tokenizer = None
+ device = "cuda"
+ audio_decoder: AudioDecoder = None
+ whisper_model, feature_extractor = None, None
+
+
+ def initialize_fn():
+ global audio_decoder, feature_extractor, whisper_model, glm_model, glm_tokenizer
+ if audio_decoder is not None:
+ return
+
+ # GLM
+ glm_tokenizer = AutoTokenizer.from_pretrained(args.model_path, trust_remote_code=True)
+
+ # Flow & Hift
+ audio_decoder = AudioDecoder(config_path=flow_config, flow_ckpt_path=flow_checkpoint,
+ hift_ckpt_path=hift_checkpoint,
+ device=device)
+
+ # Speech tokenizer
+ whisper_model = WhisperVQEncoder.from_pretrained(args.tokenizer_path).eval().to(device)
+ feature_extractor = WhisperFeatureExtractor.from_pretrained(args.tokenizer_path)
+
+
+ def clear_fn():
+ return [], [], '', '', '', None, None
+
+
+ def inference_fn(
+ temperature: float,
+ top_p: float,
+ max_new_token: int,
+ input_mode,
+ audio_path: str | None,
+ input_text: str | None,
+ history: list[dict],
+ previous_input_tokens: str,
+ previous_completion_tokens: str,
+ ):
+
+ if input_mode == "audio":
+ assert audio_path is not None
+ history.append({"role": "user", "content": {"path": audio_path}})
+ audio_tokens = extract_speech_token(
+ whisper_model, feature_extractor, [audio_path]
+ )[0]
+ if len(audio_tokens) == 0:
+ raise gr.Error("No audio tokens extracted")
+ audio_tokens = "".join([f"<|audio_{x}|>" for x in audio_tokens])
+ audio_tokens = "<|begin_of_audio|>" + audio_tokens + "<|end_of_audio|>"
+ user_input = audio_tokens
+ system_prompt = "User will provide you with a speech instruction. Do it step by step. First, think about the instruction and respond in a interleaved manner, with 13 text token followed by 26 audio tokens. "
+
+ else:
+ assert input_text is not None
+ history.append({"role": "user", "content": input_text})
+ user_input = input_text
+ system_prompt = "User will provide you with a text instruction. Do it step by step. First, think about the instruction and respond in a interleaved manner, with 13 text token followed by 26 audio tokens."
+
+
+ # Gather history
+ inputs = previous_input_tokens + previous_completion_tokens
+ inputs = inputs.strip()
+ if "<|system|>" not in inputs:
+ inputs += f"<|system|>\n{system_prompt}"
+ inputs += f"<|user|>\n{user_input}<|assistant|>streaming_transcription\n"
+
+ with torch.no_grad():
+ response = requests.post(
+ "http://localhost:10000/generate_stream",
+ data=json.dumps({
+ "prompt": inputs,
+ "temperature": temperature,
+ "top_p": top_p,
+ "max_new_tokens": max_new_token,
+ }),
+ stream=True
+ )
+ text_tokens, audio_tokens = [], []
+ audio_offset = glm_tokenizer.convert_tokens_to_ids('<|audio_0|>')
+ end_token_id = glm_tokenizer.convert_tokens_to_ids('<|user|>')
+ complete_tokens = []
+ prompt_speech_feat = torch.zeros(1, 0, 80).to(device)
+ flow_prompt_speech_token = torch.zeros(1, 0, dtype=torch.int64).to(device)
+ this_uuid = str(uuid.uuid4())
+ tts_speechs = []
+ tts_mels = []
+ prev_mel = None
+ is_finalize = False
+ block_size_list = [25,50,100,150,200]
+ block_size_idx = 0
+ block_size = block_size_list[block_size_idx]
+ audio_processor = AudioStreamProcessor()
+ for chunk in response.iter_lines():
+ token_id = json.loads(chunk)["token_id"]
+ if token_id == end_token_id:
+ is_finalize = True
+ if len(audio_tokens) >= block_size or (is_finalize and audio_tokens):
+ if block_size_idx < len(block_size_list) - 1:
+ block_size_idx += 1
+ block_size = block_size_list[block_size_idx]
+ tts_token = torch.tensor(audio_tokens, device=device).unsqueeze(0)
+
+ if prev_mel is not None:
+ prompt_speech_feat = torch.cat(tts_mels, dim=-1).transpose(1, 2)
+
+ tts_speech, tts_mel = audio_decoder.token2wav(tts_token, uuid=this_uuid,
+ prompt_token=flow_prompt_speech_token.to(device),
+ prompt_feat=prompt_speech_feat.to(device),
+ finalize=is_finalize)
+ prev_mel = tts_mel
+
+ audio_bytes = audio_processor.process(tts_speech.clone().cpu().numpy()[0], last=is_finalize)
+
+ tts_speechs.append(tts_speech.squeeze())
+ tts_mels.append(tts_mel)
+ if audio_bytes:
+ yield history, inputs, '', '', audio_bytes, None
+ flow_prompt_speech_token = torch.cat((flow_prompt_speech_token, tts_token), dim=-1)
+ audio_tokens = []
+ if not is_finalize:
+ complete_tokens.append(token_id)
+ if token_id >= audio_offset:
+ audio_tokens.append(token_id - audio_offset)
+ else:
+ text_tokens.append(token_id)
+ tts_speech = torch.cat(tts_speechs, dim=-1).cpu()
+ complete_text = glm_tokenizer.decode(complete_tokens, spaces_between_special_tokens=False)
+ with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
+ torchaudio.save(f, tts_speech.unsqueeze(0), 22050, format="wav")
+ history.append({"role": "assistant", "content": {"path": f.name, "type": "audio/wav"}})
+ history.append({"role": "assistant", "content": glm_tokenizer.decode(text_tokens, ignore_special_tokens=False)})
+ yield history, inputs, complete_text, '', None, (22050, tts_speech.numpy())
+
+
+ def update_input_interface(input_mode):
+ if input_mode == "audio":
+ return [gr.update(visible=True), gr.update(visible=False)]
+ else:
+ return [gr.update(visible=False), gr.update(visible=True)]
+
+
+ # Create the Gradio interface
+ with gr.Blocks(title="GLM-4-Voice Demo", fill_height=True) as demo:
+ with gr.Row():
+ temperature = gr.Number(
+ label="Temperature",
+ value=0.2
+ )
+
+ top_p = gr.Number(
+ label="Top p",
+ value=0.8
+ )
+
+ max_new_token = gr.Number(
+ label="Max new tokens",
+ value=2000,
+ )
+
+ chatbot = gr.Chatbot(
+ elem_id="chatbot",
+ bubble_full_width=False,
+ type="messages",
+ scale=1,
+ )
+
+ with gr.Row():
+ with gr.Column():
+ input_mode = gr.Radio(["audio", "text"], label="Input Mode", value="audio")
+ audio = gr.Audio(label="Input audio", type='filepath', show_download_button=True, visible=True)
+ text_input = gr.Textbox(label="Input text", placeholder="Enter your text here...", lines=2, visible=False)
+
+ with gr.Column():
+ submit_btn = gr.Button("Submit")
+ reset_btn = gr.Button("Clear")
+ output_audio = gr.Audio(label="Play", streaming=True,
+ autoplay=True, show_download_button=False)
+ complete_audio = gr.Audio(label="Last Output Audio (If Any)", show_download_button=True)
+
+
+
+ gr.Markdown("""## Debug Info""")
+ with gr.Row():
+ input_tokens = gr.Textbox(
+ label=f"Input Tokens",
+ interactive=False,
+ )
+
+ completion_tokens = gr.Textbox(
+ label=f"Completion Tokens",
+ interactive=False,
+ )
+
+ detailed_error = gr.Textbox(
+ label=f"Detailed Error",
+ interactive=False,
+ )
+
+ history_state = gr.State([])
+
+ respond = submit_btn.click(
+ inference_fn,
+ inputs=[
+ temperature,
+ top_p,
+ max_new_token,
+ input_mode,
+ audio,
+ text_input,
+ history_state,
+ input_tokens,
+ completion_tokens,
+ ],
+ outputs=[history_state, input_tokens, completion_tokens, detailed_error, output_audio, complete_audio]
+ )
+
+ respond.then(lambda s: s, [history_state], chatbot)
+
+ reset_btn.click(clear_fn, outputs=[chatbot, history_state, input_tokens, completion_tokens, detailed_error, output_audio, complete_audio])
+ input_mode.input(clear_fn, outputs=[chatbot, history_state, input_tokens, completion_tokens, detailed_error, output_audio, complete_audio]).then(update_input_interface, inputs=[input_mode], outputs=[audio, text_input])
+
+ initialize_fn()
+ # Launch the interface
+ demo.launch(
+ server_port=args.port,
+ server_name=args.host
+ )
diff --git a/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4_tokenizer.py b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4_tokenizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4adc4001b7d95f297be90bfd75419a7521b785f
--- /dev/null
+++ b/almeval/models/kimi_audio/kimia_infer/models/tokenizer/glm4_tokenizer.py
@@ -0,0 +1,35 @@
+import torch
+import librosa
+import os
+
+from transformers import WhisperFeatureExtractor
+from .glm4.speech_tokenizer.modeling_whisper import WhisperVQEncoder
+from .glm4.speech_tokenizer.utils import extract_speech_token
+from torch import nn
+
+
+class Glm4Tokenizer(nn.Module):
+ def __init__(self, tokenizer_path):
+ super().__init__()
+ self.whisper_model = WhisperVQEncoder.from_pretrained(tokenizer_path).eval()
+ self.feature_extractor = WhisperFeatureExtractor.from_pretrained(tokenizer_path)
+
+ def tokenize(self, speech=None, audio_path=None, sr=16000):
+ if audio_path:
+ audio, sr = librosa.load(audio_path, sr=16000)
+ audio = torch.tensor(audio).unsqueeze(0)
+ audio_info = (audio, sr)
+ else:
+ assert speech is not None
+ assert sr
+ if isinstance(speech, list):
+ speech = torch.tensor(speech).unsqueeze(0)
+ if len(speech.shape) == 1:
+ speech = speech.unsqueeze(0)
+ audio_info = (speech, sr)
+
+ audio_tokens = extract_speech_token(
+ self.whisper_model, self.feature_extractor, [audio_info]
+ )[0]
+ audio_tokens = torch.tensor(audio_tokens).unsqueeze(0)
+ return audio_tokens
diff --git a/almeval/models/kimi_audio/requirements.txt b/almeval/models/kimi_audio/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..37c2a26a0af56e014873fc44c32843ae272cb4c1
--- /dev/null
+++ b/almeval/models/kimi_audio/requirements.txt
@@ -0,0 +1,40 @@
+torch==2.4.1
+torchaudio==2.4.1
+packaging
+jinja2
+openai-whisper
+jsonlines
+pandas
+validators
+sty
+transformers
+librosa
+accelerate
+aiohttp
+colorama
+omegaconf==2.3.0
+sox
+six==1.16.0
+hyperpyyaml
+conformer==0.3.2
+diffusers
+pillow
+sentencepiece
+easydict
+fire
+ujson
+cairosvg
+immutabledict
+rich
+wget
+gdown
+datasets
+torchdyn==1.0.6
+huggingface_hub
+loguru
+decord
+blobfile
+timm
+sacrebleu==1.5.1
+soundfile
+tqdm
\ No newline at end of file
diff --git a/almeval/models/mini_example.py b/almeval/models/mini_example.py
new file mode 100644
index 0000000000000000000000000000000000000000..fabb06d4720008feb707fe04fc83853c53088fcc
--- /dev/null
+++ b/almeval/models/mini_example.py
@@ -0,0 +1,183 @@
+# ASR
+def asr_test(model):
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = model(messages, max_new_tokens=256)
+ print(text)
+
+# S2TT（support: en,zh,ja）
+def s2tt_test(model):
+ messages = [
+ {"role": "system", "content":"请仔细聆听这段语音，然后将其内容翻译成中文。"},
+ # {"role": "system", "content":"Please listen carefully to this audio and then translate its content into Chinese."},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = model(messages, max_new_tokens=256, temperature=0.1, do_sample=True)
+ print(text)
+
+
+# audio caption
+def audio_caption_test(model):
+ messages = [
+ {"role": "system", "content":"Please briefly explain the important events involved in this audio clip."},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/music_playing_followed_by_a_woman_speaking.wav"}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = model(messages, max_new_tokens=256, temperature=0.1, do_sample=True)
+ print(text)
+
+# S2ST（support: en,zh）
+def s2st_test(model, token2wav):
+ messages = [
+ {"role": "system", "content":"请仔细聆听这段语音，然后将其内容翻译成中文并用语音播报。"},
+ # {"role": "system", "content":"Please listen carefully to this audio and then translate its content into Chinese speech."},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ {"role": "assistant", "content": "", "eot": False}, # Insert for speech response
+ ]
+ tokens, text, audio = model(messages, max_tokens=2048, temperature=0.7, do_sample=True)
+ print(text)
+ #print(tokens)
+ audio = [x for x in audio if x < 6561] # remove audio padding
+ audio = token2wav(audio, prompt_wav='assets/default_female.wav')
+ with open('output-s2st.wav', 'wb') as f:
+ f.write(audio)
+
+# multi turn aqta
+def multi_turn_aqta_test(model):
+ history = [{"role": "system", "content": "You are a helpful assistant."}]
+ for round_idx, inp_audio in enumerate([
+ "assets/multi-turn-round1-听说荡口古镇从下个月开始取消门票了，你知道这事吗。.wav",
+ "assets/multi-turn-round2-新闻说九月十九号就免费开放了。好像整个古镇都升级改造了，现在变成开放式街区了。.wav"
+ ]):
+ print("round: ", round_idx)
+ history.append(
+ {"role": "human", "content": [{"type": "audio", "audio": inp_audio}]}
+ )
+ history.append(
+ {"role": "assistant", "content": None}
+ )
+ tokens, text, _ = model(history, max_new_tokens=256, temperature=0.5, do_sample=True)
+ print(text)
+ history.pop(-1)
+ history.append(
+ {"role": "assistant", "content": text}
+ )
+
+# multi turn aqaa
+def multi_turn_aqaa_test(model, token2wav):
+ history = [{"role": "system", "content": "You are a helpful assistant."}]
+ for round_idx, inp_audio in enumerate([
+ "assets/multi-turn-round1-听说荡口古镇从下个月开始取消门票了，你知道这事吗。.wav",
+ "assets/multi-turn-round2-新闻说九月十九号就免费开放了。好像整个古镇都升级改造了，现在变成开放式街区了。.wav"
+ ]):
+ print("round: ", round_idx)
+ history.append(
+ {"role": "human", "content": [{"type": "audio", "audio": inp_audio}]}
+ )
+ history.append(
+ {"role": "assistant", "content": "", "eot": False}, # Insert for speech response
+ )
+ tokens, text, audio = model(history, max_new_tokens=2048, temperature=0.7, do_sample=True)
+ print(text)
+ audio = [x for x in audio if x < 6561] # remove audio padding
+ audio = token2wav(audio, prompt_wav='assets/default_female.wav')
+ with open(f'output-round-{round_idx}.wav', 'wb') as f:
+ f.write(audio)
+ history.pop(-1)
+ history.append(
+ {
+ "role": "assistant",
+ "content":[
+ {"type": "text", "text":""},
+ {"type":"token", "token": tokens}
+ ]
+ }
+ )
+
+# Tool call & Web search
+def tool_call_test(model, token2wav):
+ history = [
+ {"role": "system", "content": "你的名字叫做小跃，是由阶跃星辰公司训练出来的语音大模型。\n你具备调用工具解决问题的能力，你需要根据用户的需求和上下文情景，自主选择是否调用系统提供的工具来协助用户。\n你情感细腻，观察能力强，擅长分析用户的内容，并作出善解人意的回复，说话的过程中时刻注意用户的感受，富有同理心，提供多样的情绪价值。\n今天是2025年8月28日，星期四\n请用默认女声与用户交流"},
+ {"role": "tool_json_schemas", "content": '[{"type": "function", "function": {"name": "search", "description": "搜索工具", "parameters": {"type": "object", "properties": {"query": {"type": "string", "description": "搜索关键词"}}, "required": ["query"], "additionalProperties": false}}}]'},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/帮我查一下今天上证指数的开盘价是多少.wav"}]},
+ {"role": "assistant", "content": "", "eot": False}, # Insert for speech response
+ ]
+ tokens, text, audio = model(history, max_new_tokens=4096, repetition_penalty=1.05, top_p=0.9, temperature=0.7, do_sample=True)
+ print(text)
+ audio = [x for x in audio if x < 6561] # remove audio padding
+ audio = token2wav(audio, prompt_wav='assets/default_female.wav')
+ with open('output-tool-call-1.wav', 'wb') as f:
+ f.write(audio)
+ history.pop(-1)
+ with open('assets/search_result.txt') as f:
+ search_result = f.read().strip()
+ history += [
+ {"role": "assistant", "content": [{"type": "text", "text": ""},
+ {"type": "token", "token": tokens}]},
+ {"role": "input", "content": [{"type": "text", "text": search_result},
+ {"type": "text", "text": '\n\n\n请用口语化形式总结检索结果，简短地回答用户的问题。'}]},
+ {"role": "assistant", "content": "", "eot": False}, # Insert for speech response
+ ]
+ tokens, text, audio = model(history, max_new_tokens=4096, repetition_penalty=1.05, top_p=0.9, temperature=0.7, do_sample=True)
+ print(text)
+ audio = [x for x in audio if x < 6561] # remove audio padding
+ audio = token2wav(audio, prompt_wav='assets/default_female.wav')
+ with open('output-tool-call-2.wav', 'wb') as f:
+ f.write(audio)
+
+# Paralingustic information understanding
+def paralinguistic_test(model, token2wav):
+ messages = [
+ {"role": "system", "content":"请用语音与我交流。"},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/paralinguistic_information_understanding.wav"}]},
+ {"role": "assistant", "content": "", "eot": False}, # Insert for speech response
+ ]
+ tokens, text, audio = model(messages, max_tokens=2048, temperature=0.7, do_sample=True)
+ print(text)
+ #print(tokens)
+ audio = [x for x in audio if x < 6561] # remove audio padding
+ audio = token2wav(audio, prompt_wav='assets/default_female.wav')
+ with open('output-paralinguistic.wav', 'wb') as f:
+ f.write(audio)
+
+# Audio understanding
+def mmau_test(model):
+ messages = [
+ {"role": "system", "content": "You are an expert in audio analysis, please analyze the audio content and answer the questions accurately."},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/mmau_test.wav"},
+ {"type": "text", "text": f"Which of the following best describes the male vocal in the audio? Please choose the answer from the following options: [Soft and melodic, Aggressive and talking, High-pitched and singing, Whispering] Output the final answer in ."}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = model(messages, max_new_tokens=256, num_beams=2)
+ print(text)
+
+# Universal audio caption
+def uac_test(model):
+ messages = [
+ {"role": "system", "content": "你是一位经验丰富的音频分析专家，擅长对各种语音音频进行深入细致的分析。你的任务不仅仅是将音频内容准确转写为文字，还要对说话人的声音特征（如性别、年龄、情绪状态）、背景声音、环境信息以及可能涉及的事件进行全面描述。请以专业、客观的视角，详细、准确地完成每一次分析和转写。"},
+ {"role": "human", "content": [{"type": "audio", "audio": "assets/music_playing_followed_by_a_woman_speaking.wav"}]},
+ {"role": "assistant", "content": None}
+ ]
+ _, text, _ = model(messages, max_new_tokens=1024, temperature=0.5, top_p=0.9, do_sample=True)
+ print(text)
+
+if __name__ == '__main__':
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+
+ model = StepAudio2('Step-Audio-2-mini')
+ token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+ asr_test(model)
+ s2tt_test(model)
+ audio_caption_test(model)
+ s2st_test(model, token2wav)
+ multi_turn_aqta_test(model)
+ multi_turn_aqaa_test(model, token2wav)
+ tool_call_test(model, token2wav)
+ paralinguistic_test(model, token2wav)
+ mmau_test(model)
+ uac_test(model)
diff --git a/almeval/models/patch.py b/almeval/models/patch.py
new file mode 100644
index 0000000000000000000000000000000000000000..3e2e7cf98a84af5df3cf7439cc051cf7490a687c
--- /dev/null
+++ b/almeval/models/patch.py
@@ -0,0 +1,89 @@
+import torch
+import torchaudio
+
+from ..utils.misc import print_once
+
+
+def patch_chatglm_model_init(original_init):
+ def new_init(self, config, empty_init=True, device=None):
+ print_once('Using patched chatglm model init')
+ # ensure device is torch.device type
+ if isinstance(device, str):
+ device = torch.device(device)
+
+ # ensure config.torch_dtype is torch.dtype type
+ if isinstance(config.torch_dtype, str):
+ config.torch_dtype = getattr(torch, config.torch_dtype)
+
+ # call original init function
+ original_init(self, config, empty_init=empty_init, device=device)
+
+ return new_init
+
+
+def patch_glm4_voice_update_model_kwargs_for_generation(
+ outputs,
+ model_kwargs,
+ is_encoder_decoder=False,
+ num_new_tokens=1,
+):
+ # modified the source code to support new version of transformers
+ # see: https://huggingface.co/THUDM/glm-4-voice-9b/discussions/2
+ print_once('Using patched glm4_voice update_model_kwargs_for_generation')
+ # update past_key_values
+ for possible_cache_name in ['past_key_values', 'mems', 'past_buckets_states', 'cache_params']:
+ if hasattr(outputs, possible_cache_name):
+ if possible_cache_name in ('past_buckets_states', 'mems'):
+ cache_name = 'past_key_values'
+ else:
+ cache_name = possible_cache_name
+ model_kwargs[cache_name] = getattr(outputs, possible_cache_name)
+ break
+
+ # update attention mask
+ if 'attention_mask' in model_kwargs:
+ attention_mask = model_kwargs['attention_mask']
+ model_kwargs['attention_mask'] = torch.cat(
+ [attention_mask, attention_mask.new_ones((attention_mask.shape[0], 1))], dim=-1
+ )
+
+ # update position ids
+ if 'position_ids' in model_kwargs:
+ position_ids = model_kwargs['position_ids']
+ new_position_id = position_ids[..., -1:].clone()
+ new_position_id += 1
+ model_kwargs['position_ids'] = torch.cat(
+ [position_ids, new_position_id], dim=-1
+ )
+
+ model_kwargs['is_first_forward'] = False
+
+ if model_kwargs.get('use_cache', True) and 'cache_position' in model_kwargs:
+ model_kwargs['cache_position'] = model_kwargs['cache_position'][-1:] + num_new_tokens
+
+ return model_kwargs
+
+
+def patch_baichuan_load_audio_waveform(self, uri, return_tensors=True, do_normalize=False):
+ # for mmau-test-mini: https://huggingface.co/baichuan-inc/Baichuan-Audio-Instruct/discussions/1#67e27c55ad5e6f59d8561187
+ print_once('Using patched baichuan load_audio_waveform')
+ # sample_rate, num_frames, num_channels, bits_per_sample, encoding=PCM_S
+ metadata = torchaudio.info(uri)
+ # assert(metadata.num_channels <= 2), "acoustic file with {} channels.".format(metadata.num_channels)
+ waveform_tensor, _ = torchaudio.load(uri, normalize=True)
+ if self.config.sampling_rate != metadata.sample_rate:
+ waveform_tensor = torchaudio.functional.resample(
+ waveform_tensor, metadata.sample_rate, self.config.sampling_rate, lowpass_filter_width=128)
+
+ # downmix to mono channel https://trac.ffmpeg.org/wiki/AudioChannelManipulation
+ if metadata.num_channels > 1:
+ waveform_tensor = torch.mean(waveform_tensor, dim=0, keepdim=True)
+
+ # normalized to zero mean
+ if do_normalize:
+ waveform_tensor = self.zero_mean_unit_var_norm(waveform_tensor)
+
+ if return_tensors: # (channels, samples)
+ return waveform_tensor
+ else:
+ return waveform_tensor.numpy()
diff --git a/almeval/models/qwen_audio.py b/almeval/models/qwen_audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..c0bee9a3bca8fadef2925b0b92d903273901d6ad
--- /dev/null
+++ b/almeval/models/qwen_audio.py
@@ -0,0 +1,145 @@
+import random
+
+import librosa
+import torch
+from transformers import AutoProcessor, Qwen2AudioForConditionalGeneration
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+
+class Qwen2Audio(BaseModel):
+ NAME = 'Qwen2-Audio-7B'
+
+ def __init__(self, model_path='Qwen/Qwen2-Audio-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ self.processor = AutoProcessor.from_pretrained(
+ model_path
+ )
+
+ self.model = Qwen2AudioForConditionalGeneration.from_pretrained(
+ model_path, device_map='cuda').eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ # from jsonl in: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = f'Detect the language and recognize the speech: <|{lang}|>'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English:'
+ elif meta['dataset_name'] == 'vocalsound':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Classify the human vocal sound to VocalSound in English:'
+ # help to invoke baesmodel continuous output
+ elif meta['interactive'] == 'Audio-QA':
+ prompt = ' Your answer to the question is:'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]} Your answer is:'
+ else:
+ prompt = msg['text'] + ' The answer is:'
+
+ return '<|audio_bos|><|AUDIO|><|audio_eos|>' + prompt
+
+ # 该模型是评测主力，只有chat才用chat模型
+ def generate_inner(self, msg: dict):
+ audio = None
+ # 从message中提取audio和text
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+ prompt = self.get_prompt(msg)
+
+ print_once(f'Prompt: {prompt}')
+ audio = librosa.load(
+ audio, sr=self.processor.feature_extractor.sampling_rate)[0]
+
+ inputs = self.processor(
+ text=prompt,
+ audios=audio,
+ return_tensors='pt',
+ sampling_rate=self.processor.feature_extractor.sampling_rate,
+ )
+ inputs = inputs.to('cuda')
+ generated_ids = self.model.generate(**inputs, max_new_tokens=256, min_new_tokens=1, do_sample=False,
+ top_k=None,
+ top_p=None)
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
+
+
+class Qwen2AudioChat(BaseModel):
+ NAME = 'Qwen2-Audio-7B-Instruct'
+
+ def __init__(self, model_path='Qwen/Qwen2-Audio-7B-Instruct', **kwargs):
+ self.processor = AutoProcessor.from_pretrained(
+ model_path, trust_remote_code=True
+ )
+
+ self.model = Qwen2AudioForConditionalGeneration.from_pretrained(
+ model_path, device_map='cuda'
+ )
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = ''
+ if msg['meta']['interactive'] == 'Audio-QA':
+ conversation = [{'role': 'user',
+ 'content': [{'type': 'audio',
+ 'audio_url': audio}]}]
+ else:
+ prompt = self.get_prompt(msg)
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/dfc7d31b0a3181c8be496155bbf9eb3049499b3c/README.md?plain=1#L134
+ conversation = [{'role': 'system', 'content': 'You are a helpful assistant.'},
+ {'role': 'user',
+ 'content': [{'type': 'audio', 'audio_url': audio},
+ {'type': 'text', 'text': prompt}]}]
+ #
+ text = self.processor.apply_chat_template(
+ conversation, add_generation_prompt=True, tokenize=False
+ )
+ audios = []
+ for message in conversation:
+ if isinstance(message['content'], list):
+ for ele in message['content']:
+ if ele['type'] == 'audio':
+ audios.append(
+ librosa.load(
+ ele['audio_url'],
+ sr=self.processor.feature_extractor.sampling_rate,
+ )[0]
+ )
+ inputs = self.processor(
+ text=text,
+ audios=audios,
+ return_tensors='pt',
+ padding=True,
+ sampling_rate=self.processor.feature_extractor.sampling_rate,
+ )
+ inputs = inputs.to('cuda')
+ generate_ids = self.model.generate(**inputs, max_new_tokens=256)
+ generate_ids = generate_ids[:, inputs.input_ids.size(1):]
+ answer = self.processor.batch_decode(
+ generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, answer
diff --git a/almeval/models/qwen_omni3B copy.py b/almeval/models/qwen_omni3B copy.py
new file mode 100644
index 0000000000000000000000000000000000000000..8c19b24b8ffdddbf066e4c7e8c3f41bf216d62a0
--- /dev/null
+++ b/almeval/models/qwen_omni3B copy.py
@@ -0,0 +1,175 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni_3B(BaseModel):
+ NAME = 'Qwen2.5-Omni-3B'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-3B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_linear_music_low/v1-20251128-154049/checkpoint-1688"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-3B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+
+
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B.py b/almeval/models/qwen_omni7B.py
new file mode 100644
index 0000000000000000000000000000000000000000..7485920a7d20adca9534de1b2e4911e2d2b8314a
--- /dev/null
+++ b/almeval/models/qwen_omni7B.py
@@ -0,0 +1,153 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ model_path
+ )
+
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ model_path, device_map='cuda').eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_aligner_llm.py b/almeval/models/qwen_omni7B_aligner_llm.py
new file mode 100644
index 0000000000000000000000000000000000000000..cabb9b08456e51f077a98207f85d1ee1ac830619
--- /dev/null
+++ b/almeval/models/qwen_omni7B_aligner_llm.py
@@ -0,0 +1,175 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni_3B(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-aligner-llm'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-LLM-aligner-noise-lora-1gpu-save300_linear/v1-20251210-154837/checkpoint-300"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+
+
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_encoder.py b/almeval/models/qwen_omni7B_encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..58dc970c44d5a1778577d045f084db64bf193dd6
--- /dev/null
+++ b/almeval/models/qwen_omni7B_encoder.py
@@ -0,0 +1,175 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni_3B(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-encoder'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder1-noise-lora-1gpu-save300_linear/v0-20251210-145749/checkpoint-1688"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+
+
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_encoder_aligner.py b/almeval/models/qwen_omni7B_encoder_aligner.py
new file mode 100644
index 0000000000000000000000000000000000000000..5aa2c8c7220c2ed2ae111eb66f3f445cdd11f8fd
--- /dev/null
+++ b/almeval/models/qwen_omni7B_encoder_aligner.py
@@ -0,0 +1,175 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni_3B(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-encoder-aligner'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-noise-lora-1gpu-save100_linear_new/v0-20251216-200644/checkpoint-300"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+
+
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_encoder_aligner_llm.py b/almeval/models/qwen_omni7B_encoder_aligner_llm.py
new file mode 100644
index 0000000000000000000000000000000000000000..c6549b63c640822d4b941ac049031f38db687148
--- /dev/null
+++ b/almeval/models/qwen_omni7B_encoder_aligner_llm.py
@@ -0,0 +1,175 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni_3B(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-all'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-all-noise-lora-1gpu-save300_linear1/v0-20251212-142256/checkpoint-1688"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+
+
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_l_after_ea.py b/almeval/models/qwen_omni7B_l_after_ea.py
new file mode 100644
index 0000000000000000000000000000000000000000..00104c61751a6ebec1aee75e4bd27769a457247a
--- /dev/null
+++ b/almeval/models/qwen_omni7B_l_after_ea.py
@@ -0,0 +1,175 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni_3B(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-l-after-ea'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_l_continue_from_ea300_noise/v0-20251216-200845/checkpoint-400"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+
+
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora1.py b/almeval/models/qwen_omni7B_lora1.py
new file mode 100644
index 0000000000000000000000000000000000000000..783b5e084ad7957fd054a62b06325caaf22e5731
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora1.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora1'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-noise_-5_to_10-lora-1gpu-save100_linear_new_bs16/v1-20251223-023452/checkpoint-300"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora1_ff.py b/almeval/models/qwen_omni7B_lora1_ff.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b045e6e0e9b173d7c0af926fa47d09a60fc9681
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora1_ff.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora1-ff'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-ff-lora-1gpu-save100_sqrt_bwd_new_bs16/v0-20251220-061159/checkpoint-300"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora2.py b/almeval/models/qwen_omni7B_lora2.py
new file mode 100644
index 0000000000000000000000000000000000000000..7e7e63f1d6f4b9d03f6761c5ffc74b13e83bdf6a
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora2.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora2'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-noise_-5_to_10-lora-1gpu-save100_linear_new_bs16/v1-20251223-023452/checkpoint-600"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora2_ff.py b/almeval/models/qwen_omni7B_lora2_ff.py
new file mode 100644
index 0000000000000000000000000000000000000000..741f177bea99d9869936a9b07bd0f9975477f736
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora2_ff.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora2-ff'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-ff-lora-1gpu-save100_sqrt_bwd_new_bs16/v0-20251220-061159/checkpoint-600"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora3.py b/almeval/models/qwen_omni7B_lora3.py
new file mode 100644
index 0000000000000000000000000000000000000000..7ed2c488aa42a9e52e61ebd37bb85b3e46c318c1
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora3.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora3'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-noise_-5_to_10-lora-1gpu-save100_linear_new_bs16/v1-20251223-023452/checkpoint-900"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora3_ff.py b/almeval/models/qwen_omni7B_lora3_ff.py
new file mode 100644
index 0000000000000000000000000000000000000000..0e64ec130edb52d288022de705169f1e62d76539
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora3_ff.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora3-ff'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-ff-lora-1gpu-save100_sqrt_bwd_new_bs16/v0-20251220-061159/checkpoint-900"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora4.py b/almeval/models/qwen_omni7B_lora4.py
new file mode 100644
index 0000000000000000000000000000000000000000..7f291ae36e3f37c94a59917ea78dffa048214ea0
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora4.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora4'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-noise_-5_to_10-lora-1gpu-save100_linear_new_bs16/v1-20251223-023452/checkpoint-1200"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora4_ff.py b/almeval/models/qwen_omni7B_lora4_ff.py
new file mode 100644
index 0000000000000000000000000000000000000000..beafdb54ac80e7713615e52d24d42bb78961cc6b
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora4_ff.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora4-ff'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-ff-lora-1gpu-save100_sqrt_bwd_new_bs16/v0-20251220-061159/checkpoint-1200"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora5.py b/almeval/models/qwen_omni7B_lora5.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b0eed435c14af3acdd10eebee80b0ea42f0f611
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora5.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora5'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-noise_-5_to_10-lora-1gpu-save100_linear_new_bs16/v1-20251223-023452/checkpoint-1500"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora5_ff.py b/almeval/models/qwen_omni7B_lora5_ff.py
new file mode 100644
index 0000000000000000000000000000000000000000..2d757013864fbc7300d95482c96ddf66182a67d7
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora5_ff.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora5-ff'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-ff-lora-1gpu-save100_sqrt_bwd_new_bs16/v0-20251220-061159/checkpoint-1500"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora6.py b/almeval/models/qwen_omni7B_lora6.py
new file mode 100644
index 0000000000000000000000000000000000000000..83d0e6466ce52af897d80165bee884891ff5ac57
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora6.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora6'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-noise_-5_to_10-lora-1gpu-save100_linear_new_bs16/v1-20251223-023452/checkpoint-1688"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/qwen_omni7B_lora6_ff.py b/almeval/models/qwen_omni7B_lora6_ff.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8c25407b83e1bb83f139df625ad6821ee81e225
--- /dev/null
+++ b/almeval/models/qwen_omni7B_lora6_ff.py
@@ -0,0 +1,173 @@
+import random
+
+import torch
+from qwen_omni_utils import process_mm_info
+from transformers import (Qwen2_5OmniForConditionalGeneration,
+ Qwen2_5OmniProcessor)
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+from peft import PeftModel, PeftConfig
+class Qwen2_5Omni(BaseModel):
+ NAME = 'Qwen2.5-Omni-7B-lora6-ff'
+
+ def __init__(self, model_path='Qwen/Qwen2.5-Omni-7B', **kwargs):
+ assert model_path is not None
+ self.model_path = model_path
+ # self.processor = Qwen2_5OmniProcessor.from_pretrained(
+ # model_path
+ # )
+
+ # self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ # model_path, device_map='cuda').eval()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_omni7B-encoder+align-ff-lora-1gpu-save100_sqrt_bwd_new_bs16/v0-20251220-061159/checkpoint-1688"
+ # adapter_dir = "/workspace/intern/pangkaiyu/dg/output_asr_3b_1gpu_s300_sqrt_bwd/v1-20251111-135055/checkpoint-3000"
+
+ # 2) 读取 LoRA 配置，拿到基座模型名（若字段缺失就手填）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "Qwen/Qwen2.5-Omni-3B"
+ base_model_path = "Qwen/Qwen2.5-Omni-7B"
+
+ # 3) 加载基座模型 & 处理器
+ self.model = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+ base_model_path,
+ # torch_dtype=torch.bfloat16,
+ device_map="auto",
+ )
+ self.processor = Qwen2_5OmniProcessor.from_pretrained(base_model_path)
+
+ # 4) 挂载 LoRA 适配器
+ self.model = PeftModel.from_pretrained(self.model, adapter_dir)
+ self.model.eval()
+ random.seed(0)
+ torch.cuda.empty_cache()
+
+ def get_prompt(self, msg: dict):
+ # according to https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ assert 'lang' in meta
+ lang = meta['lang']
+ if lang == 'zh':
+ prompt = '请将这段中文语音转换为纯文本，去掉标点符号。'
+ elif lang == 'en':
+ prompt = 'Transcribe the English audio into text without any punctuation marks.'
+ else:
+ raise NotImplementedError
+ elif meta['dataset_name'] == 'vocalsound':
+ # from https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ prompt = 'Classify the given human vocal sound in English.'
+ elif meta['dataset_name'] == 'meld':
+ # from: https://github.com/QwenLM/Qwen2-Audio/blob/main/eval_audio/EVALUATION.md
+ prompt = 'Recognize the emotion with keywords in English.'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'Listen to the given audio carefully and answer this question: {msg["text"]}.'
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def get_system_prompt(self, msg: dict):
+ meta = msg['meta']
+ if meta is None:
+ return ''
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/6c1784249f8aa498a0893ec442e20557c2fa5773/web_demo.py#L41C29-L41C192
+ system_prompt = 'You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.'
+ if meta['task'] == 'ASR':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/blob/main/cookbooks/universal_audio_understanding.ipynb
+ system_prompt = 'You are a speech recognition model.'
+ elif meta['dataset_name'] in ['vocalsound', 'Nonspeech7k']:
+ system_prompt = 'You are a vocal sound classification model.'
+ elif meta['dataset_name'] == 'meld':
+ system_prompt = 'You are a speech emotion recognition model.'
+ elif meta['interactive'] == 'Audio-QA' or meta['audio_type'] == 'AudioEvent':
+ # from: https://github.com/QwenLM/Qwen2.5-Omni/issues/178#issuecomment-2808125247
+ system_prompt = 'You are a helpful assistant.'
+ return system_prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ task_prompt = self.get_prompt(msg)
+ system_prompt = self.get_system_prompt(msg)
+
+ if msg['meta']['interactive'] == 'Audio-analysis':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': task_prompt
+ },
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ elif msg['meta']['interactive'] == 'Audio-QA':
+ messages = [
+ {'role': 'system',
+ 'content': [
+ {
+ 'type': 'text',
+ 'text': system_prompt
+ }
+ ]
+ },
+ {'role': 'user',
+ 'content': [
+ {
+ 'type': 'audio',
+ 'audio': audio
+ }
+ ]
+ },
+ ]
+ else:
+ raise NotImplementedError
+ # only for dump
+ prompt = system_prompt + '\n' + task_prompt
+ print_once(f'Prompt: {prompt}')
+
+ text = self.processor.apply_chat_template(
+ messages, tokenize=False, add_generation_prompt=True)
+ audios, images, videos = process_mm_info(
+ messages, use_audio_in_video=True)
+ assert audio is not None
+
+ inputs = self.processor(text=text,
+ audio=audios,
+ images=images,
+ videos=videos,
+ return_tensors='pt',
+ padding=True, use_audio_in_video=True)
+
+ inputs = inputs.to('cuda').to(self.model.dtype)
+
+ if msg['meta']['task'] == 'ASR':
+ # https://github.com/QwenLM/Qwen2.5-Omni/issues/79
+ generated_ids = self.model.generate(**inputs, use_audio_in_video=True, return_audio=False,
+ thinker_max_new_tokens=256, thinker_do_sample=False, repetition_penalty=1.0)
+
+ else:
+ generated_ids = self.model.generate(
+ **inputs, use_audio_in_video=True, return_audio=False, thinker_do_sample=False)
+
+ generated_ids = generated_ids[:, inputs.input_ids.size(1):]
+ pred = self.processor.batch_decode(
+ generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+ )[0]
+ return prompt, pred
diff --git a/almeval/models/step2audiomini.py b/almeval/models/step2audiomini.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f3bd528ec505336724807b743d5f2a7b50748bf
--- /dev/null
+++ b/almeval/models/step2audiomini.py
@@ -0,0 +1,275 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-origin"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-noise_-5_to_10-lora-1gpu-bs16_1_gckF/v0-20251225-035519/checkpoint-300"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+ base_model_path = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ # self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_a_lora1.py b/almeval/models/step2audiomini_a_lora1.py
new file mode 100644
index 0000000000000000000000000000000000000000..aa5c3d5270446c699a284b0aefce837bc1718991
--- /dev/null
+++ b/almeval/models/step2audiomini_a_lora1.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-a-lora1"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_llm-lora-1gpu-bs16_1_gckF/v0-20260104-202331/checkpoint-8000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_a_lora2.py b/almeval/models/step2audiomini_a_lora2.py
new file mode 100644
index 0000000000000000000000000000000000000000..43a35759a36003b4311937c22ea84cae37de6b2d
--- /dev/null
+++ b/almeval/models/step2audiomini_a_lora2.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-a-lora2"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_llm-lora-1gpu-bs16_1_gckF/v0-20260104-202331/checkpoint-10000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_a_lora3.py b/almeval/models/step2audiomini_a_lora3.py
new file mode 100644
index 0000000000000000000000000000000000000000..75eec72b7641037b60c8b198b91c6da2b10ea58b
--- /dev/null
+++ b/almeval/models/step2audiomini_a_lora3.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-a-lora3"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_llm-lora-1gpu-bs16_1_gckF/v0-20260104-202331/checkpoint-12000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_a_lora4.py b/almeval/models/step2audiomini_a_lora4.py
new file mode 100644
index 0000000000000000000000000000000000000000..9292f7b31a9ed3c8fdd5a6e119c91ea01d9343aa
--- /dev/null
+++ b/almeval/models/step2audiomini_a_lora4.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-a-lora4"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_llm-lora-1gpu-bs16_1_gckF/v0-20260104-202331/checkpoint-14000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_a_lora5.py b/almeval/models/step2audiomini_a_lora5.py
new file mode 100644
index 0000000000000000000000000000000000000000..00193aef0f323305470f0aa12689a484d4d37a2b
--- /dev/null
+++ b/almeval/models/step2audiomini_a_lora5.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-a-lora5"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_llm-lora-1gpu-bs16_1_gckF/v0-20260104-202331/checkpoint-16000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_a_lora6.py b/almeval/models/step2audiomini_a_lora6.py
new file mode 100644
index 0000000000000000000000000000000000000000..72293b5886d7bca3320ddb4d4ee57db8cdc7384b
--- /dev/null
+++ b/almeval/models/step2audiomini_a_lora6.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-a-lora6"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_llm-lora-1gpu-bs16_1_gckF/v0-20260104-202331/checkpoint-18000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_all_lora1.py b/almeval/models/step2audiomini_all_lora1.py
new file mode 100644
index 0000000000000000000000000000000000000000..ecae2a19052ff106d70181fca4ac6c5e9adfec32
--- /dev/null
+++ b/almeval/models/step2audiomini_all_lora1.py
@@ -0,0 +1,275 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-all-lora1"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_low-lora-1gpu-bs16_1_gckF/v0-20260104-202710/checkpoint-2000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio-2-mini"
+ # base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_all_lora2.py b/almeval/models/step2audiomini_all_lora2.py
new file mode 100644
index 0000000000000000000000000000000000000000..db9ce73c4c02aa32ed9bc892a565ae798f014435
--- /dev/null
+++ b/almeval/models/step2audiomini_all_lora2.py
@@ -0,0 +1,275 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-all-lora2"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_low-lora-1gpu-bs16_1_gckF/v0-20260104-202710/checkpoint-4000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio-2-mini"
+ # base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_all_lora3.py b/almeval/models/step2audiomini_all_lora3.py
new file mode 100644
index 0000000000000000000000000000000000000000..149016520b166ec2e05197626a96f69ee20edd09
--- /dev/null
+++ b/almeval/models/step2audiomini_all_lora3.py
@@ -0,0 +1,275 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-all-lora3"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_low-lora-1gpu-bs16_1_gckF/v0-20260104-202710/checkpoint-6000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio-2-mini"
+ # base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_all_lora4.py b/almeval/models/step2audiomini_all_lora4.py
new file mode 100644
index 0000000000000000000000000000000000000000..18087fa333427ee4691316935fed660c295c2ec3
--- /dev/null
+++ b/almeval/models/step2audiomini_all_lora4.py
@@ -0,0 +1,275 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-all-lora4"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_low-lora-1gpu-bs16_1_gckF/v0-20260104-202710/checkpoint-8000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+ base_model_path = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_all_lora5.py b/almeval/models/step2audiomini_all_lora5.py
new file mode 100644
index 0000000000000000000000000000000000000000..11c78abdd9baeb2bc30a96933cc8e6d786c0112f
--- /dev/null
+++ b/almeval/models/step2audiomini_all_lora5.py
@@ -0,0 +1,275 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-all-lora5"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_low-lora-1gpu-bs16_1_gckF/v0-20260104-202710/checkpoint-10000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+ base_model_path = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_all_lora6.py b/almeval/models/step2audiomini_all_lora6.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ec9e93bbd1a55a8f6bfc8170d4f28025f5b11e5
--- /dev/null
+++ b/almeval/models/step2audiomini_all_lora6.py
@@ -0,0 +1,275 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-all-lora6"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_low-lora-1gpu-bs16_1_gckF/v0-20260104-202710/checkpoint-12000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ # base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+ base_model_path = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora1.py b/almeval/models/step2audiomini_lora1.py
new file mode 100644
index 0000000000000000000000000000000000000000..d045aafffd5b956a10f2f4fdc97da203f1bf8ad1
--- /dev/null
+++ b/almeval/models/step2audiomini_lora1.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora1"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-2000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora1_s.py b/almeval/models/step2audiomini_lora1_s.py
new file mode 100644
index 0000000000000000000000000000000000000000..3b9eef107b5cd7ea76e46f18b60917e4f8a24dda
--- /dev/null
+++ b/almeval/models/step2audiomini_lora1_s.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora1-s"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-2000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora2.py b/almeval/models/step2audiomini_lora2.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a9c8aa0d13e5eedcb931c0ea48005826e21261e
--- /dev/null
+++ b/almeval/models/step2audiomini_lora2.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora2"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-4000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256,do_sample=False,temperature=0.0,top_p=1.0,num_beams=1)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora2_s.py b/almeval/models/step2audiomini_lora2_s.py
new file mode 100644
index 0000000000000000000000000000000000000000..670f758075b93711a3911a0ed707466551a03cdb
--- /dev/null
+++ b/almeval/models/step2audiomini_lora2_s.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora2-s"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-4000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256,do_sample=False,temperature=0.0,top_p=1.0,num_beams=1)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora3.py b/almeval/models/step2audiomini_lora3.py
new file mode 100644
index 0000000000000000000000000000000000000000..164ec6968541f1b169cf5539a6718dd93e5c0679
--- /dev/null
+++ b/almeval/models/step2audiomini_lora3.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora3"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-6000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora3_s.py b/almeval/models/step2audiomini_lora3_s.py
new file mode 100644
index 0000000000000000000000000000000000000000..58f276c9fd1d3e905cd8e9f8027cebb06c17d7f5
--- /dev/null
+++ b/almeval/models/step2audiomini_lora3_s.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora3-s"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-6000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora4.py b/almeval/models/step2audiomini_lora4.py
new file mode 100644
index 0000000000000000000000000000000000000000..e2fefdb6bc3e115e34bbe25a7ec073d47146a3cd
--- /dev/null
+++ b/almeval/models/step2audiomini_lora4.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora4"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-8000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora4_s.py b/almeval/models/step2audiomini_lora4_s.py
new file mode 100644
index 0000000000000000000000000000000000000000..37e98acc3729f572a85e408112a9a70d54fc1670
--- /dev/null
+++ b/almeval/models/step2audiomini_lora4_s.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora4-s"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-8000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora5.py b/almeval/models/step2audiomini_lora5.py
new file mode 100644
index 0000000000000000000000000000000000000000..6e74a12edff81ddcf615fb3dad5c8479a6a6b3e1
--- /dev/null
+++ b/almeval/models/step2audiomini_lora5.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora5"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-10000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora5_s.py b/almeval/models/step2audiomini_lora5_s.py
new file mode 100644
index 0000000000000000000000000000000000000000..29b36e268488803dd2234956390f2186d6dbe4dd
--- /dev/null
+++ b/almeval/models/step2audiomini_lora5_s.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora5-s"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-10000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora6.py b/almeval/models/step2audiomini_lora6.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f16282f46c3813b9515192bd13adbefe3a418e7
--- /dev/null
+++ b/almeval/models/step2audiomini_lora6.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora6"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-12000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step2audiomini_lora6_s.py b/almeval/models/step2audiomini_lora6_s.py
new file mode 100644
index 0000000000000000000000000000000000000000..a961cc16d0f5cf72a798054ee7dbfd103d705c39
--- /dev/null
+++ b/almeval/models/step2audiomini_lora6_s.py
@@ -0,0 +1,274 @@
+import os
+from typing import Any
+
+import torch
+import torchaudio
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+
+import sys, os, importlib.util
+from contextlib import contextmanager
+
+STEP_AUDIO2 = "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/Step-Audio2"
+
+def _load_module_as(name: str, file_path: str):
+ spec = importlib.util.spec_from_file_location(name, file_path)
+ mod = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(mod) # type: ignore
+ return mod
+
+@contextmanager
+def _temp_sys_path(path: str):
+ old = list(sys.path)
+ try:
+ if path in sys.path:
+ sys.path.remove(path)
+ sys.path.insert(0, path)
+ yield
+ finally:
+ sys.path[:] = old
+
+def import_stepaudio2_no_conflict():
+ # 备份当前顶层 utils（可能是你项目的 utils）
+ old_utils = sys.modules.get("utils", None)
+
+ # 关键：把 Step-Audio2 的 utils.py 临时注册成顶层 utils
+ step_utils = _load_module_as("utils", os.path.join(STEP_AUDIO2, "utils.py"))
+ sys.modules["utils"] = step_utils
+
+ try:
+ with _temp_sys_path(STEP_AUDIO2):
+ # 强制从 Step-Audio2 目录重新导入
+ sys.modules.pop("stepaudio2", None)
+ sys.modules.pop("token2wav", None)
+
+ from stepaudio2 import StepAudio2
+ from token2wav import Token2wav
+ return StepAudio2, Token2wav
+ finally:
+ # 恢复原 utils，避免影响你其他模块
+ if old_utils is None:
+ sys.modules.pop("utils", None)
+ else:
+ sys.modules["utils"] = old_utils
+
+StepAudio2, Token2wav = import_stepaudio2_no_conflict()
+
+# class StepAudio2Mini(BaseModel):
+# NAME = 'Step-Audio-2-mini'
+
+# def __init__(self, model_path: str | None = None):
+# super().__init__()
+
+# self.model = StepAudio2('Step-Audio-2-mini')
+# # self.token2wav = Token2wav('Step-Audio-2-mini/token2wav')
+# self.model_path = model_path or "stepfun-ai/Step-Audio-2-mini"
+
+
+import torch
+from peft import PeftConfig, PeftModel
+
+class StepAudio2Mini(BaseModel):
+ NAME = "Step-Audio-2-mini-lora6-s"
+
+ def __init__(self, model_path: str | None = None, **kwargs):
+ super().__init__()
+
+ adapter_dir = "/workspace/intern/pangkaiyu/dg/output_step_audio2_mini-encoder+align-whole1226_signal_new1_dpdc_high-lora-1gpu-bs16_1_gckF/v0-20260104-202946/checkpoint-12000"
+
+ # 1) 读 LoRA 配置，拿到训练时的 base（非常重要：避免 base 不一致导致 keys 对不上）
+ peft_cfg = PeftConfig.from_pretrained(adapter_dir)
+ base_model_path = peft_cfg.base_model_name_or_path or "stepfun-ai/Step-Audio-2-mini"
+
+ # 2) 仍然用 StepAudio2 封装（保持你现在 messages+audio 的调用方式不变）
+ self.model = StepAudio2(base_model_path)
+
+ # 3) 把 LoRA 挂到内部 HF 模型上（这一步才能覆盖 vit/aligner）
+ self.model.llm = PeftModel.from_pretrained(self.model.llm, adapter_dir, is_trainable=False)
+ self.model.llm.eval()
+
+ torch.cuda.empty_cache()
+
+ # 4) 可选：简单检查一下是否真的加载到了 LoRA 权重
+ sd_keys = list(self.model.llm.state_dict().keys())
+ lora_keys = [k for k in sd_keys if "lora_" in k]
+ print(f"[LoRA] loaded lora params: {len(lora_keys)}")
+ if len(lora_keys) == 0:
+ print("[LoRA][WARN] 没发现 lora_ 权重键，说明 adapter 可能没挂上/目录不对")
+
+ def generate_inner(self, msg: dict):
+
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+
+ prompt = '请记录下你所听到的语音内容。'
+ messages = [
+ {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ {"role": "assistant", "content": None}
+ ]
+ tokens, text, _ = self.model(messages, max_new_tokens=256)
+ print(text)
+ return prompt, text
+
+ # # Step-Audio 2 mini: 走 processor + end2end 模型（trust_remote_code 很关键）
+ # self.processor = AutoProcessor.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # # 有些 processor 不暴露 tokenizer，兜底用 AutoTokenizer
+ # self.tokenizer = getattr(self.processor, "tokenizer", None) or AutoTokenizer.from_pretrained(
+ # self.model_path, trust_remote_code=True
+ # )
+ # self.model = AutoModelForCausalLM.from_pretrained(
+ # self.model_path,
+ # torch_dtype=torch.bfloat16,
+ # device_map="auto",
+ # trust_remote_code=True,
+ # ).eval()
+
+ # # ========== 音频加载 ==========
+ # @staticmethod
+ # def load_audio(path: str) -> tuple[torch.Tensor, int]:
+ # # torchaudio: [channels, T]
+ # wav, sr = torchaudio.load(path)
+ # if wav.dim() == 2 and wav.size(0) > 1:
+ # wav = wav.mean(dim=0) # 转单声道
+ # else:
+ # wav = wav.squeeze(0)
+ # wav = wav.to(torch.float32)
+ # return wav, sr
+
+ # # ========== prompt ==========
+ # @staticmethod
+ # def get_prompt(msg: dict) -> str:
+ # meta = msg.get("meta", {}) or {}
+ # if meta.get("task") == "ASR":
+ # # 你可以按需换成 “去标点” 版本
+ # return "请将音频内容转写为文字，只输出转写结果。"
+ # return msg.get("text", "请识别音频内容，只输出结果。")
+
+ # # ========== chat template（关键：只传 string content，别传 dict audio） ==========
+ # def apply_chat_template(self, system_prompt: str, user_text: str) -> str:
+ # # 确保有 占位（Step-Audio2 常见用法）
+ # if "" not in user_text:
+ # user_text = f"{user_text}\n"
+
+ # messages = [
+ # {"role": "system", "content": system_prompt},
+ # {"role": "user", "content": user_text},
+ # ]
+
+ # def asr_test(model):
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": "assets/give_me_a_brief_introduction_to_the_great_wall.wav"}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = model(messages, max_new_tokens=256)
+ # print(text)
+
+
+ # # 优先走 tokenizer.apply_chat_template（避免 processor 里 jinja 对多模态结构更挑）
+ # if hasattr(self.tokenizer, "apply_chat_template"):
+ # try:
+ # return self.tokenizer.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 再兜底 processor.apply_chat_template
+ # if hasattr(self.processor, "apply_chat_template"):
+ # try:
+ # return self.processor.apply_chat_template(
+ # messages, tokenize=False, add_generation_prompt=True
+ # )
+ # except Exception:
+ # pass
+
+ # # 最后兜底：不用模板，直接拼（不会最优，但能跑）
+ # return system_prompt + "\n" + user_text + "\n"
+
+ # # ========== 推理 ==========
+ # def inference(self, text: str, wav: torch.Tensor, sr: int) -> str:
+ # # processor 的入参命名在不同 repo 可能略有差异：audios / audio
+ # inputs = None
+ # candidates: list[dict[str, Any]] = [
+ # {"audios": wav, "sampling_rate": sr},
+ # {"audio": wav, "sampling_rate": sr},
+ # {"audios": [wav], "sampling_rate": sr},
+ # {"audio": [wav], "sampling_rate": sr},
+ # ]
+ # last_err = None
+ # for kw in candidates:
+ # try:
+ # inputs = self.processor(
+ # text=text,
+ # return_tensors="pt",
+ # padding=True,
+ # **kw,
+ # )
+ # break
+ # except Exception as e:
+ # last_err = e
+ # continue
+ # if inputs is None:
+ # raise RuntimeError(f"processor() 无法接受音频参数，最后一次错误：{repr(last_err)}")
+
+ # # 挪到模型设备
+ # for k, v in list(inputs.items()):
+ # if isinstance(v, torch.Tensor):
+ # inputs[k] = v.to(self.model.device)
+
+ # with torch.inference_mode():
+ # out = self.model.generate(
+ # **inputs,
+ # max_new_tokens=256,
+ # do_sample=False, # ASR 建议关采样，更稳定
+ # temperature=0.0,
+ # )
+
+ # # 去掉 prompt 部分，只解码新增 tokens（如果有 input_ids）
+ # if "input_ids" in inputs:
+ # gen_ids = out[:, inputs["input_ids"].shape[-1]:]
+ # else:
+ # gen_ids = out
+
+ # pred = self.tokenizer.batch_decode(gen_ids, skip_special_tokens=True)[0]
+ # return pred.strip()
+
+ # ========== Evalkit 入口 ==========
+ # def generate_inner(self, msg: dict):
+
+ # audio = msg['audio']
+ # if len(audio) == 1:
+ # audio = audio[0]
+
+ # prompt = '请记录下你所听到的语音内容。'
+ # messages = [
+ # {"role": "system", "content": "请记录下你所听到的语音内容。"},
+ # {"role": "human", "content": [{"type": "audio", "audio": audio}]},
+ # {"role": "assistant", "content": None}
+ # ]
+ # tokens, text, _ = self.model(messages, max_new_tokens=256)
+ # return prompt, text
+
+ # audio = msg["audio"]
+ # if isinstance(audio, list):
+ # assert len(audio) == 1, "当前实现只支持单条音频"
+ # audio = audio[0]
+
+ # system_prompt = self.get_prompt(msg)
+ # user_text = msg.get("text") or "请识别以下语音内容："
+
+ # print_once(f"System prompt: {system_prompt}")
+ # print_once(f"User text: {user_text}")
+
+ # chat_text = self.apply_chat_template(system_prompt, user_text)
+
+ # wav, sr = self.load_audio(audio)
+ # pred = self.inference(chat_text, wav, sr)
+ # return system_prompt, pred
diff --git a/almeval/models/step_audio.py b/almeval/models/step_audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..453d2af96afd6864c819c64dc244acc11bad2f3a
--- /dev/null
+++ b/almeval/models/step_audio.py
@@ -0,0 +1,120 @@
+import os
+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+from ..utils.misc import print_once
+from .base import BaseModel
+from .stepaudio.tokenizer import StepAudioTokenizer
+from .stepaudio.utils import load_audio, load_optimus_ths_lib
+from huggingface_hub import snapshot_download
+
+
+class StepAudio(BaseModel):
+ NAME = 'StepAudio'
+
+ def __init__(self, model_path: str | None = None):
+ super().__init__()
+ # step-audio requires tokenizer & llm, if model_path is local path, try to find tokenizer & llm in the path
+ # else, load from huggingface
+ if model_path is not None:
+ tokenizer_path = os.path.join(model_path, 'Step-Audio-Tokenizer')
+ llm_path = os.path.join(model_path, 'Step-Audio-Chat')
+ else:
+ tokenizer_path = snapshot_download('stepfun-ai/Step-Audio-Tokenizer')
+ llm_path = snapshot_download('stepfun-ai/Step-Audio-Chat')
+
+ load_optimus_ths_lib(os.path.join(llm_path, 'lib'))
+ self.llm_tokenizer = AutoTokenizer.from_pretrained(
+ llm_path, trust_remote_code=True
+ )
+ self.encoder = StepAudioTokenizer(tokenizer_path)
+ self.llm = AutoModelForCausalLM.from_pretrained(
+ llm_path,
+ torch_dtype=torch.bfloat16,
+ device_map='auto',
+ trust_remote_code=True,
+ )
+
+ def inference(self, messages: list):
+ text_with_audio = self.apply_chat_template(messages)
+ token_ids = self.llm_tokenizer.encode(
+ text_with_audio, return_tensors='pt')
+ token_ids = token_ids.to('cuda')
+ outputs = self.llm.generate(
+ token_ids, max_new_tokens=2048, temperature=0.7, top_p=0.9, do_sample=True
+ )
+ output_token_ids = outputs[:, token_ids.shape[-1]: -1].tolist()[0]
+ output_text = self.llm_tokenizer.decode(output_token_ids)
+ return output_text
+
+ @staticmethod
+ def get_prompt(msg: dict):
+ # according to https://arxiv.org/pdf/2502.11946
+ meta = msg['meta']
+ if meta['task'] == 'ASR':
+ prompt = '请记录下你所听到的语音内容。'
+
+ # a general prompt for audio-qa
+ elif meta['interactive'] == 'Audio-QA':
+ prompt = '请回答音频中的问题。'
+ elif meta['audio_type'] == 'AudioEvent':
+ prompt = f'请听音频后回答如下问题： {msg["text"]} '
+ else:
+ prompt = msg['text']
+ return prompt
+
+ def generate_inner(self, msg: dict):
+ audio = msg['audio']
+ if len(audio) == 1:
+ audio = audio[0]
+ prompt = self.get_prompt(msg)
+
+ system_msg = {
+ 'role': 'system',
+ 'content': prompt
+ }
+
+ print_once(f'Prompt: {prompt}')
+ x = [system_msg,
+ {'role': 'user',
+ 'content': {'type': 'audio', 'audio': audio}}]
+ text = self.inference(x)
+ return prompt, text
+
+ def encode_audio(self, audio: str | torch.Tensor, sr=None):
+ if isinstance(audio, str):
+ audio_wav, sr = load_audio(audio)
+ else:
+ assert sr is not None
+ audio_wav = audio
+ audio_tokens = self.encoder(audio_wav, sr)
+ return audio_tokens
+
+ def apply_chat_template(self, messages: list):
+ text_with_audio = ''
+ for msg in messages:
+ role = msg['role']
+ content = msg['content']
+ if role == 'user':
+ role = 'human'
+ if isinstance(content, str):
+ text_with_audio += f'<|BOT|>{role}\n{content}<|EOT|>'
+ elif isinstance(content, dict):
+ if content['type'] == 'text':
+ text_with_audio += f"<|BOT|>{role}\n{content['text']}<|EOT|>"
+ elif content['type'] == 'audio':
+ if isinstance(content['audio'], torch.Tensor):
+ assert 'audio_sr' in msg
+ audio_tokens = self.encode_audio(
+ content['audio'], msg['audio_sr'])
+ else:
+ audio_tokens = self.encode_audio(content['audio'])
+ text_with_audio += f'<|BOT|>{role}\n{audio_tokens}<|EOT|>'
+ elif content is None:
+ text_with_audio += f'<|BOT|>{role}\n'
+ else:
+ raise ValueError(f'Unsupported content type: {type(content)}')
+ if not text_with_audio.endswith('<|BOT|>assistant\n'):
+ text_with_audio += '<|BOT|>assistant\n'
+ return text_with_audio
diff --git a/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/1_8_tedlium_test1.done b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/1_8_tedlium_test1.done
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/1_8_tedlium_test1.done
@@ -0,0 +1 @@
+done
\ No newline at end of file
diff --git a/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/2_8_tedlium_test1.done b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/2_8_tedlium_test1.done
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/2_8_tedlium_test1.done
@@ -0,0 +1 @@
+done
\ No newline at end of file
diff --git a/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/3_8_tedlium_test1.done b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/3_8_tedlium_test1.done
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/3_8_tedlium_test1.done
@@ -0,0 +1 @@
+done
\ No newline at end of file
diff --git a/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/4_8_tedlium_test1.done b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/4_8_tedlium_test1.done
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/4_8_tedlium_test1.done
@@ -0,0 +1 @@
+done
\ No newline at end of file
diff --git a/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/5_8_tedlium_test1.done b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/5_8_tedlium_test1.done
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/5_8_tedlium_test1.done
@@ -0,0 +1 @@
+done
\ No newline at end of file
diff --git a/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/6_8_tedlium_test1.done b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/6_8_tedlium_test1.done
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/6_8_tedlium_test1.done
@@ -0,0 +1 @@
+done
\ No newline at end of file
diff --git a/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/7_8_tedlium_test1.done b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/7_8_tedlium_test1.done
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/ff_5e-6_sqrt_bwd/Qwen2.5-Omni-7B-lora5-ff/tedlium_test1/7_8_tedlium_test1.done
@@ -0,0 +1 @@
+done
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/Qwen2.5-Omni-7B-lora2_LibriSpeech.jsonl b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/Qwen2.5-Omni-7B-lora2_LibriSpeech.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..0fb20779a24e7d6c79f98b12932707997114df08
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/Qwen2.5-Omni-7B-lora2_LibriSpeech.jsonl
@@ -0,0 +1,5559 @@
+{"index": 0, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0003.flac", "answer": "THERE WAS SOMETHING IN HIS AIR AND MANNER THAT BETRAYED TO THE SCOUT THE UTTER CONFUSION OF THE STATE OF HIS MIND", "subset": "test_clean", "task_type": "understanding", "prediction": "there was something in his air and manner that betrayed to the scout the utter confusion of the state of his mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0012.flac", "answer": "FOUR OR FIVE OF THE LATTER ONLY LINGERED ABOUT THE DOOR OF THE PRISON OF UNCAS WARY BUT CLOSE OBSERVERS OF THE MANNER OF THEIR CAPTIVE", "subset": "test_clean", "task_type": "understanding", "prediction": "four or five of the latter only lingered about the door of the prison of uncas wary but close observers of the manner of their captive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0026.flac", "answer": "WELL WHAT CAN'T BE DONE BY MAIN COURAGE IN WAR MUST BE DONE BY CIRCUMVENTION", "subset": "test_clean", "task_type": "understanding", "prediction": "well what can t be done by main courage in war must be done by circumvention", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0022.flac", "answer": "THE DELAWARES ARE CHILDREN OF THE TORTOISE AND THEY OUTSTRIP THE DEER", "subset": "test_clean", "task_type": "understanding", "prediction": "the delawares are children of the tortoise and they outstrip the deer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0002.flac", "answer": "IN OTHER WORDS WHILE HE HAD IMPLICIT FAITH IN THE ABILITY OF BALAAM'S ASS TO SPEAK HE WAS SOMEWHAT SKEPTICAL ON THE SUBJECT OF A BEAR'S SINGING AND YET HE HAD BEEN ASSURED OF THE LATTER ON THE TESTIMONY OF HIS OWN EXQUISITE ORGANS", "subset": "test_clean", "task_type": "understanding", "prediction": "in other words while he had implicit faith in the ability of balaam s ass to speak he was somewhat sceptical on the subject of a bear s singing and yet he had been assured of the latter on the testimony of his own exquisite organs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0025.flac", "answer": "SO UNCAS YOU HAD BETTER TAKE THE LEAD WHILE I WILL PUT ON THE SKIN AGAIN AND TRUST TO CUNNING FOR WANT OF SPEED", "subset": "test_clean", "task_type": "understanding", "prediction": "so uncas you had better take the lead while i will put on the skin again and trust to cunning for want of speed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 6, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0010.flac", "answer": "THE TASK WILL NOT BE DIFFICULT RETURNED DAVID HESITATING THOUGH I GREATLY FEAR YOUR PRESENCE WOULD RATHER INCREASE THAN MITIGATE HIS UNHAPPY FORTUNES", "subset": "test_clean", "task_type": "understanding", "prediction": "the task will not be difficult returned david hesitating though i greatly fear your presence would rather increase than mitigate his unhappy fortunes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 7, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0001.flac", "answer": "IN HIS RETURN TO THE CAMP HIS ACUTE AND PRACTISED INTELLECTS WERE INTENTLY ENGAGED IN DEVISING MEANS TO COUNTERACT A WATCHFULNESS AND SUSPICION ON THE PART OF HIS ENEMIES THAT HE KNEW WERE IN NO DEGREE INFERIOR TO HIS OWN", "subset": "test_clean", "task_type": "understanding", "prediction": "in his return to the camp his acute and practiced intellects were intently engaged in devising means to counteract a watchfulness and suspicion on the part of his enemies that he knew were in no degree inferior to his own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 8, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0005.flac", "answer": "THE BEAR SHOOK HIS SHAGGY SIDES AND THEN A WELL KNOWN VOICE REPLIED", "subset": "test_clean", "task_type": "understanding", "prediction": "the bear shook his shaggy sides and then a well known voice replied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 9, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0017.flac", "answer": "THEN AS IF SATISFIED OF THEIR SAFETY THE SCOUT LEFT HIS POSITION AND SLOWLY ENTERED THE PLACE", "subset": "test_clean", "task_type": "understanding", "prediction": "then as if satisfied of their safety the scout left his position and slowly entered the place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 10, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0015.flac", "answer": "BUT THE BEAR INSTEAD OF OBEYING MAINTAINED THE SEAT IT HAD TAKEN AND GROWLED", "subset": "test_clean", "task_type": "understanding", "prediction": "but the bear instead of obeying maintained the seat it had taken and growled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 11, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0019.flac", "answer": "UNCAS OCCUPIED A DISTANT CORNER IN A RECLINING ATTITUDE BEING RIGIDLY BOUND BOTH HANDS AND FEET BY STRONG AND PAINFUL WITHES", "subset": "test_clean", "task_type": "understanding", "prediction": "uncas occupied a distant corner in a reclining attitude being rigidly bound both hands and feet by strong and painful withs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 12, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0011.flac", "answer": "THE LODGE IN WHICH UNCAS WAS CONFINED WAS IN THE VERY CENTER OF THE VILLAGE AND IN A SITUATION PERHAPS MORE DIFFICULT THAN ANY OTHER TO APPROACH OR LEAVE WITHOUT OBSERVATION", "subset": "test_clean", "task_type": "understanding", "prediction": "the lodge in which uncas was confined was in the very centre of the village and in a situation perhaps more difficult than any other to approach or leave without observation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 13, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0004.flac", "answer": "THE INGENIOUS HAWKEYE WHO RECALLED THE HASTY MANNER IN WHICH THE OTHER HAD ABANDONED HIS POST AT THE BEDSIDE OF THE SICK WOMAN WAS NOT WITHOUT HIS SUSPICIONS CONCERNING THE SUBJECT OF SO MUCH SOLEMN DELIBERATION", "subset": "test_clean", "task_type": "understanding", "prediction": "the ingenious hawkeye who recalled the hasty manner in which the other had abandoned his post at the bedside of the sick woman was not without his suspicions concerning the subject of so much solemn deliberation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 14, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0016.flac", "answer": "THE CUNNING MAN IS AFRAID THAT HIS BREATH WILL BLOW UPON HIS BROTHERS AND TAKE AWAY THEIR COURAGE TOO CONTINUED DAVID IMPROVING THE HINT HE RECEIVED THEY MUST STAND FURTHER OFF", "subset": "test_clean", "task_type": "understanding", "prediction": "the cunning man is afraid that his breath will blow upon his brothers and take away their courage too continued david improving the hint he received they must stand further off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 15, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0007.flac", "answer": "COME COME RETURNED HAWKEYE UNCASING HIS HONEST COUNTENANCE THE BETTER TO ASSURE THE WAVERING CONFIDENCE OF HIS COMPANION YOU MAY SEE A SKIN WHICH IF IT BE NOT AS WHITE AS ONE OF THE GENTLE ONES HAS NO TINGE OF RED TO IT THAT THE WINDS OF THE HEAVEN AND THE SUN HAVE NOT BESTOWED NOW LET US TO BUSINESS", "subset": "test_clean", "task_type": "understanding", "prediction": "come come returned hawkeye encasing his honest countenance the better to assure the wavering confidence of his companion you may see a skin which if it be not as white as one of the gentle ones has no tinge of red to it that the winds of the heaven and the sun have not bestowed now let us to business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 16, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0014.flac", "answer": "THEY DREW BACK A LITTLE FROM THE ENTRANCE AND MOTIONED TO THE SUPPOSED CONJURER TO ENTER", "subset": "test_clean", "task_type": "understanding", "prediction": "they drew back a little from the entrance and motioned to the supposed conjurer to enter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 17, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0009.flac", "answer": "I GREATLY MOURN THAT ONE SO WELL DISPOSED SHOULD DIE IN HIS IGNORANCE AND I HAVE SOUGHT A GOODLY HYMN CAN YOU LEAD ME TO HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "i greatly mourn that one so well disposed should die in his ignorance and i have sought a goodly him can you lead me to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 18, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0029.flac", "answer": "IF YOU ARE NOT THEN KNOCKED ON THE HEAD YOUR BEING A NON COMPOSSER WILL PROTECT YOU AND YOU'LL THEN HAVE A GOOD REASON TO EXPECT TO DIE IN YOUR BED", "subset": "test_clean", "task_type": "understanding", "prediction": "if you are not then knocked on the head your being a non composser will protect you and you will then have a good reason to expect to die in your bed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 19, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0035.flac", "answer": "THEN HEAVING A HEAVY SIGH PROBABLY AMONG THE LAST HE EVER DREW IN PINING FOR A CONDITION HE HAD SO LONG ABANDONED HE ADDED IT IS WHAT I WOULD WISH TO PRACTISE MYSELF AS ONE WITHOUT A CROSS OF BLOOD THOUGH IT IS NOT ALWAYS EASY TO DEAL WITH AN INDIAN AS YOU WOULD WITH A FELLOW CHRISTIAN", "subset": "test_clean", "task_type": "understanding", "prediction": "then heaving a heavy sigh probably among the last he ever drew in pining for a condition he had so long abandoned he added it is what i would wish to practise myself as one without a cross of blood though it is not always easy to deal with an indian as you would with a fellow christian", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 20, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0023.flac", "answer": "UNCAS WHO HAD ALREADY APPROACHED THE DOOR IN READINESS TO LEAD THE WAY NOW RECOILED AND PLACED HIMSELF ONCE MORE IN THE BOTTOM OF THE LODGE", "subset": "test_clean", "task_type": "understanding", "prediction": "uncas who had already approached the door in readiness to lead the way now recoiled and placed himself once more in the bottom of the lodge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 21, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0030.flac", "answer": "SO CHOOSE FOR YOURSELF TO MAKE A RUSH OR TARRY HERE", "subset": "test_clean", "task_type": "understanding", "prediction": "so choose for yourself to make a rush or tarry here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 22, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0031.flac", "answer": "BRAVELY AND GENEROUSLY HAS HE BATTLED IN MY BEHALF AND THIS AND MORE WILL I DARE IN HIS SERVICE", "subset": "test_clean", "task_type": "understanding", "prediction": "bravely and generously has he battled in my behalf and this and more will i dare in his service", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 23, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0032.flac", "answer": "KEEP SILENT AS LONG AS MAY BE AND IT WOULD BE WISE WHEN YOU DO SPEAK TO BREAK OUT SUDDENLY IN ONE OF YOUR SHOUTINGS WHICH WILL SERVE TO REMIND THE INDIANS THAT YOU ARE NOT ALTOGETHER AS RESPONSIBLE AS MEN SHOULD BE", "subset": "test_clean", "task_type": "understanding", "prediction": "keep silent as long as may be and it would be wise when you do speak to break out suddenly in one of your shoutings which will serve to remind the indians that you are not altogether as responsible as men should be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 24, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0036.flac", "answer": "GOD BLESS YOU FRIEND I DO BELIEVE YOUR SCENT IS NOT GREATLY WRONG WHEN THE MATTER IS DULY CONSIDERED AND KEEPING ETERNITY BEFORE THE EYES THOUGH MUCH DEPENDS ON THE NATURAL GIFTS AND THE FORCE OF TEMPTATION", "subset": "test_clean", "task_type": "understanding", "prediction": "god bless you friend i do believe your scent is not greatly wrong when the matter is duly considered and keeping eternity before the eyes though much depends on the natural gifts and the force of temptation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 25, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0033.flac", "answer": "IF HOWEVER THEY TAKE YOUR SCALP AS I TRUST AND BELIEVE THEY WILL NOT DEPEND ON IT UNCAS AND I WILL NOT FORGET THE DEED BUT REVENGE IT AS BECOMES TRUE WARRIORS AND TRUSTY FRIENDS", "subset": "test_clean", "task_type": "understanding", "prediction": "if however they take your scalp as i trust and believe they will not depend on it uncas and i will not forget the deed but revenge it as becomes true warriors and trusty friends", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 26, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0041.flac", "answer": "UNCAS CAST HIS SKIN AND STEPPED FORTH IN HIS OWN BEAUTIFUL PROPORTIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "uncas cast his skin and stepped forth in his own beautiful proportions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 27, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0006.flac", "answer": "CAN THESE THINGS BE RETURNED DAVID BREATHING MORE FREELY AS THE TRUTH BEGAN TO DAWN UPON HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "can these things be returned david breathing more freely as the truth began to dawn upon him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 28, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0013.flac", "answer": "DELIVERED IN A STRONG TONE OF ASSENT ANNOUNCED THE GRATIFICATION THE SAVAGE WOULD RECEIVE IN WITNESSING SUCH AN EXHIBITION OF WEAKNESS IN AN ENEMY SO LONG HATED AND SO MUCH FEARED", "subset": "test_clean", "task_type": "understanding", "prediction": "delivered in a strong tone of assent announced the gratification the savage would receive in witnessing such an exhibition of weakness in an enemy so long hated and so much feared", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 29, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0020.flac", "answer": "THE SCOUT WHO HAD LEFT DAVID AT THE DOOR TO ASCERTAIN THEY WERE NOT OBSERVED THOUGHT IT PRUDENT TO PRESERVE HIS DISGUISE UNTIL ASSURED OF THEIR PRIVACY", "subset": "test_clean", "task_type": "understanding", "prediction": "the scout who had left david at the door to ascertain they were not observed thought it prudent to preserve his disguise until assured of their privacy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 30, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0021.flac", "answer": "WHAT SHALL WE DO WITH THE MINGOES AT THE DOOR THEY COUNT SIX AND THIS SINGER IS AS GOOD AS NOTHING", "subset": "test_clean", "task_type": "understanding", "prediction": "what shall we do with the mingos at the door they count six and the singer is as good as nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 31, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0040.flac", "answer": "HE HAD NO OCCASION TO DELAY FOR AT THE NEXT INSTANT A BURST OF CRIES FILLED THE OUTER AIR AND RAN ALONG THE WHOLE EXTENT OF THE VILLAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "he had no occasion to delay for at the next instant a burst of cries filled the outer air and ran along the whole extent of the village", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 32, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0008.flac", "answer": "THE YOUNG MAN IS IN BONDAGE AND MUCH I FEAR HIS DEATH IS DECREED", "subset": "test_clean", "task_type": "understanding", "prediction": "the young man is in bondage and much i fear his death is decreed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 33, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0028.flac", "answer": "MY PURSUITS ARE PEACEFUL AND MY TEMPER I HUMBLY TRUST IS GREATLY GIVEN TO MERCY AND LOVE RETURNED DAVID A LITTLE NETTLED AT SO DIRECT AN ATTACK ON HIS MANHOOD BUT THERE ARE NONE WHO CAN SAY THAT I HAVE EVER FORGOTTEN MY FAITH IN THE LORD EVEN IN THE GREATEST STRAITS", "subset": "test_clean", "task_type": "understanding", "prediction": "my pursuits are peaceful and my temper i humbly trust is greatly given to mercy and love returned david a little nettled at so direct an attack on his manhood but there are none who can say that i have ever forgotten my faith in the lord even in the greatest straits", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 34, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0024.flac", "answer": "BUT HAWKEYE WHO WAS TOO MUCH OCCUPIED WITH HIS OWN THOUGHTS TO NOTE THE MOVEMENT CONTINUED SPEAKING MORE TO HIMSELF THAN TO HIS COMPANION", "subset": "test_clean", "task_type": "understanding", "prediction": "but hawkeye who was too much occupied with his own thoughts to note the movement continued speaking more to himself than to his companion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 35, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0037.flac", "answer": "THE DELAWARE DOG HE SAID LEANING FORWARD AND PEERING THROUGH THE DIM LIGHT TO CATCH THE EXPRESSION OF THE OTHER'S FEATURES IS HE AFRAID", "subset": "test_clean", "task_type": "understanding", "prediction": "the delaware dog he said leaning forward and peering through the dim light to catch the expression of the other s features is he afraid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 36, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0027.flac", "answer": "AS SOON AS THESE DISPOSITIONS WERE MADE THE SCOUT TURNED TO DAVID AND GAVE HIM HIS PARTING INSTRUCTIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "as soon as these dispositions were made the scout turned to davin and gave him his parting instructions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 37, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0018.flac", "answer": "IT WAS SILENT AND GLOOMY BEING TENANTED SOLELY BY THE CAPTIVE AND LIGHTED BY THE DYING EMBERS OF A FIRE WHICH HAD BEEN USED FOR THE PURPOSED OF COOKERY", "subset": "test_clean", "task_type": "understanding", "prediction": "it was silent and gloomy being tenanted solely by the captive and lighted by the dying embers of a fire which had been used for the purpose of cookery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 38, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0000.flac", "answer": "NOTWITHSTANDING THE HIGH RESOLUTION OF HAWKEYE HE FULLY COMPREHENDED ALL THE DIFFICULTIES AND DANGER HE WAS ABOUT TO INCUR", "subset": "test_clean", "task_type": "understanding", "prediction": "notwithstanding the high resolution of hawkeye he fully comprehended all the difficulties and danger he was about to incur", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 39, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0039.flac", "answer": "THE MOHICAN STARTED ON HIS FEET AND SHOOK HIS SHAGGY COVERING AS THOUGH THE ANIMAL HE COUNTERFEITED WAS ABOUT TO MAKE SOME DESPERATE EFFORT", "subset": "test_clean", "task_type": "understanding", "prediction": "the mohican started on his feet and shook his shaggy covering as though the animal he counterfeited was about to make some desperate effort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 40, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0034.flac", "answer": "HOLD SAID DAVID PERCEIVING THAT WITH THIS ASSURANCE THEY WERE ABOUT TO LEAVE HIM I AM AN UNWORTHY AND HUMBLE FOLLOWER OF ONE WHO TAUGHT NOT THE DAMNABLE PRINCIPLE OF REVENGE", "subset": "test_clean", "task_type": "understanding", "prediction": "hold said david perceiving that with this assurance they were about to leave him i am an unworthy and humble follower of one who taught not the damnable principle of revenge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 41, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0038.flac", "answer": "WILL THE HURONS HEAR HIS GROANS", "subset": "test_clean", "task_type": "understanding", "prediction": "will the hurons hear his groans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 42, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0005.flac", "answer": "YET HERE ARE WE WITHIN A SHORT RANGE OF THE SCAROONS AND NOT A SIGN OF A TRAIL HAVE WE CROSSED", "subset": "test_clean", "task_type": "understanding", "prediction": "yet here are we within a short range of the skeruons and not a sign of a trail have we crossed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 43, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0009.flac", "answer": "IT WOULD HAVE BEEN MORE WONDERFUL HAD HE SPOKEN WITHOUT A BIDDING", "subset": "test_clean", "task_type": "understanding", "prediction": "it would have been more wonderful had he spoken without a bidding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 44, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0004.flac", "answer": "DISTRUSTING HIS OWN JUDGMENT HIS APPEALS TO THE OPINION OF CHINGACHGOOK WERE FREQUENT AND EARNEST", "subset": "test_clean", "task_type": "understanding", "prediction": "distrusting his own judgment his appeals to the opinion of chingachgook were frequent and earnest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 45, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0015.flac", "answer": "THE WHOLE PARTY CROWDED TO THE SPOT WHERE UNCAS POINTED OUT THE IMPRESSION OF A MOCCASIN IN THE MOIST ALLUVION", "subset": "test_clean", "task_type": "understanding", "prediction": "the whole party crowded to the spot where uncas pointed out the impression of a moccasin in the moist alluvium", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 46, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0016.flac", "answer": "RUN BACK UNCAS AND BRING ME THE SIZE OF THE SINGER'S FOOT", "subset": "test_clean", "task_type": "understanding", "prediction": "run back uncas and bring me the size of the singer s foot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 47, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0011.flac", "answer": "IF A ROCK OR A RIVULET OR A BIT OF EARTH HARDER THAN COMMON SEVERED THE LINKS OF THE CLEW THEY FOLLOWED THE TRUE EYE OF THE SCOUT RECOVERED THEM AT A DISTANCE AND SELDOM RENDERED THE DELAY OF A SINGLE MOMENT NECESSARY", "subset": "test_clean", "task_type": "understanding", "prediction": "if a rock or a rivulet or a bit of earth harder than common severed the links of the clue they followed the true eye of the scout recovered them at a distance and seldom rendered the delay of a single moment necessary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 48, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0014.flac", "answer": "THE EXAMINATION HOWEVER RESULTED IN NO DISCOVERY", "subset": "test_clean", "task_type": "understanding", "prediction": "the examination however resulted in no discovery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 49, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0007.flac", "answer": "CHINGACHGOOK HAD CAUGHT THE LOOK AND MOTIONING WITH HIS HAND HE BADE HIM SPEAK", "subset": "test_clean", "task_type": "understanding", "prediction": "chingachgook had caught the look and motioning with his hand he bade him speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 50, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0010.flac", "answer": "SEE SAID UNCAS POINTING NORTH AND SOUTH AT THE EVIDENT MARKS OF THE BROAD TRAIL ON EITHER SIDE OF HIM THE DARK HAIR HAS GONE TOWARD THE FOREST", "subset": "test_clean", "task_type": "understanding", "prediction": "see said uncas pointing north and south at the evident marks of the broad trail on either side of him the dark hair has gone toward the forest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 51, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0006.flac", "answer": "LET US RETRACE OUR STEPS AND EXAMINE AS WE GO WITH KEENER EYES", "subset": "test_clean", "task_type": "understanding", "prediction": "let us retrace our steps and examine as we go with keener eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 52, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0008.flac", "answer": "THE EYES OF THE WHOLE PARTY FOLLOWED THE UNEXPECTED MOVEMENT AND READ THEIR SUCCESS IN THE AIR OF TRIUMPH THAT THE YOUTH ASSUMED", "subset": "test_clean", "task_type": "understanding", "prediction": "the eyes of the whole party followed the unexpected movement and read their success in the air of triumph that the youth assumed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 53, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0000.flac", "answer": "SINCE THE PERIOD OF OUR TALE THE ACTIVE SPIRIT OF THE COUNTRY HAS SURROUNDED IT WITH A BELT OF RICH AND THRIVING SETTLEMENTS THOUGH NONE BUT THE HUNTER OR THE SAVAGE IS EVER KNOWN EVEN NOW TO PENETRATE ITS WILD RECESSES", "subset": "test_clean", "task_type": "understanding", "prediction": "since the period of our tale the active spirit of the country has surrounded it with a belt of rich and thriving settlements though none but the hunter or the savage is ever known even now to penetrate its wild recesses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 54, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0002.flac", "answer": "AFTER PROCEEDING A FEW MILES THE PROGRESS OF HAWKEYE WHO LED THE ADVANCE BECAME MORE DELIBERATE AND WATCHFUL", "subset": "test_clean", "task_type": "understanding", "prediction": "after proceeding a few miles the progress of hawkeye who led the advance became more deliberate and watchful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 55, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0001.flac", "answer": "THE DEWS WERE SUFFERED TO EXHALE AND THE SUN HAD DISPERSED THE MISTS AND WAS SHEDDING A STRONG AND CLEAR LIGHT IN THE FOREST WHEN THE TRAVELERS RESUMED THEIR JOURNEY", "subset": "test_clean", "task_type": "understanding", "prediction": "the dews were suffered to exhale and the sun had dispersed the mists and was shedding a strong and clear light in the forest when the travellers resumed their journey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 56, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0013.flac", "answer": "A CIRCLE OF A FEW HUNDRED FEET IN CIRCUMFERENCE WAS DRAWN AND EACH OF THE PARTY TOOK A SEGMENT FOR HIS PORTION", "subset": "test_clean", "task_type": "understanding", "prediction": "a circle of a few hundred feet in circumference was drawn and each of the party took a segment for his portion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 57, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0012.flac", "answer": "EXTINGUISHED BRANDS WERE LYING AROUND A SPRING THE OFFALS OF A DEER WERE SCATTERED ABOUT THE PLACE AND THE TREES BORE EVIDENT MARKS OF HAVING BEEN BROWSED BY THE HORSES", "subset": "test_clean", "task_type": "understanding", "prediction": "extinguished brands were lying around a spring the offals of a deer were scattered about the place and the trees bore evident marks of having been browsed by the horses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 58, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122612/1320-122612-0003.flac", "answer": "HE OFTEN STOPPED TO EXAMINE THE TREES NOR DID HE CROSS A RIVULET WITHOUT ATTENTIVELY CONSIDERING THE QUANTITY THE VELOCITY AND THE COLOR OF ITS WATERS", "subset": "test_clean", "task_type": "understanding", "prediction": "he often stopped to examine the trees nor did he cross a rivulet without attentively considering the quantity the velocity and the colour of its waters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 59, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0010.flac", "answer": "HOW CHEERFULLY HE SEEMS TO GRIN HOW NEATLY SPREAD HIS CLAWS AND WELCOME LITTLE FISHES IN WITH GENTLY SMILING JAWS", "subset": "test_clean", "task_type": "understanding", "prediction": "how cheerfully he seems to grin how neatly spread his claws and welcome little fishes in with gently smiling jaws", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 60, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0020.flac", "answer": "WE WON'T TALK ABOUT HER ANY MORE IF YOU'D RATHER NOT WE INDEED", "subset": "test_clean", "task_type": "understanding", "prediction": "we won t talk about her any more if you d rather not we indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 61, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0009.flac", "answer": "I SHALL NEVER GET TO TWENTY AT THAT RATE", "subset": "test_clean", "task_type": "understanding", "prediction": "i shall never get to twenty at that rate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 62, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0008.flac", "answer": "I'LL TRY IF I KNOW ALL THE THINGS I USED TO KNOW", "subset": "test_clean", "task_type": "understanding", "prediction": "ill try if i know all the things i used to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 63, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0014.flac", "answer": "AND I DECLARE IT'S TOO BAD THAT IT IS", "subset": "test_clean", "task_type": "understanding", "prediction": "and i declare it is too bad that it is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 64, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0011.flac", "answer": "NO I'VE MADE UP MY MIND ABOUT IT IF I'M MABEL I'LL STAY DOWN HERE", "subset": "test_clean", "task_type": "understanding", "prediction": "no i have made up my mind about it if i am mabel i will stay down here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 65, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0018.flac", "answer": "I AM VERY TIRED OF SWIMMING ABOUT HERE O MOUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am very tired of swimming about here o mouse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 66, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0004.flac", "answer": "ALICE TOOK UP THE FAN AND GLOVES AND AS THE HALL WAS VERY HOT SHE KEPT FANNING HERSELF ALL THE TIME SHE WENT ON TALKING DEAR DEAR HOW QUEER EVERYTHING IS TO DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "alice took up the fan and gloves and as the hall was very hot she kept fanning herself all the time she went on talking dear dear how queer everything is to day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 67, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0001.flac", "answer": "POOR ALICE", "subset": "test_clean", "task_type": "understanding", "prediction": "poor alice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 68, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0002.flac", "answer": "IT WAS THE WHITE RABBIT RETURNING SPLENDIDLY DRESSED WITH A PAIR OF WHITE KID GLOVES IN ONE HAND AND A LARGE FAN IN THE OTHER HE CAME TROTTING ALONG IN A GREAT HURRY MUTTERING TO HIMSELF AS HE CAME OH THE DUCHESS THE DUCHESS", "subset": "test_clean", "task_type": "understanding", "prediction": "it was the white rabbit returning splendidly dressed with a pair of white kid gloves in one hand and a large fan in the other he came trotting along in a great hurry muttering to himself as he came oh the duchess the duchess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 69, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0007.flac", "answer": "I ALMOST THINK I CAN REMEMBER FEELING A LITTLE DIFFERENT", "subset": "test_clean", "task_type": "understanding", "prediction": "i almost think i can remember feeling a little different", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 70, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0006.flac", "answer": "I WONDER IF I'VE BEEN CHANGED IN THE NIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "i wonder if i have been changed in the night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 71, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0019.flac", "answer": "CRIED ALICE AGAIN FOR THIS TIME THE MOUSE WAS BRISTLING ALL OVER AND SHE FELT CERTAIN IT MUST BE REALLY OFFENDED", "subset": "test_clean", "task_type": "understanding", "prediction": "cried alice again for this time the mouse was bristling all over and she felt certain it must be really offended", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 72, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0000.flac", "answer": "AND HOW ODD THE DIRECTIONS WILL LOOK", "subset": "test_clean", "task_type": "understanding", "prediction": "and how odd the directions will look", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 73, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0017.flac", "answer": "THAT WILL BE A QUEER THING TO BE SURE", "subset": "test_clean", "task_type": "understanding", "prediction": "that will be a queer thing to be sure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 74, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0005.flac", "answer": "AND YESTERDAY THINGS WENT ON JUST AS USUAL", "subset": "test_clean", "task_type": "understanding", "prediction": "and yesterday things went on just as usual", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 75, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0003.flac", "answer": "OH WON'T SHE BE SAVAGE IF I'VE KEPT HER WAITING", "subset": "test_clean", "task_type": "understanding", "prediction": "oh wont she be savage if i have kept her waiting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 76, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0012.flac", "answer": "IT'LL BE NO USE THEIR PUTTING THEIR HEADS DOWN AND SAYING COME UP AGAIN DEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "it will be no use their putting their heads down and saying come up again dear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 77, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0015.flac", "answer": "I WISH I HADN'T CRIED SO MUCH SAID ALICE AS SHE SWAM ABOUT TRYING TO FIND HER WAY OUT", "subset": "test_clean", "task_type": "understanding", "prediction": "i wish i hadnt cried so much said alice as she swam about trying to find her way out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 78, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0013.flac", "answer": "I AM SO VERY TIRED OF BEING ALL ALONE HERE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am so very tired of being all alone here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 79, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123440/260-123440-0016.flac", "answer": "I SHALL BE PUNISHED FOR IT NOW I SUPPOSE BY BEING DROWNED IN MY OWN TEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "i shall be punished for it now i suppose by being drowned in my own tears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 80, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0027.flac", "answer": "I CAN DISTINGUISH THE EYE OF THE ICHTHYOSAURUS GLOWING LIKE A RED HOT COAL AND AS LARGE AS A MAN'S HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "i can distinguish the eye of the ichthyosaurus glowing like a red hot coal and as large as a man s head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 81, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0001.flac", "answer": "THE HORIZON SEEMS EXTREMELY DISTANT", "subset": "test_clean", "task_type": "understanding", "prediction": "the horizon seems extremely distant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 82, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0003.flac", "answer": "YOU SEEM ANXIOUS MY UNCLE I SAID SEEING HIM CONTINUALLY WITH HIS GLASS TO HIS EYE ANXIOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "you seem anxious my uncle i said seeing him continually with his glass to his eye anxious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 83, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0007.flac", "answer": "HE CALLED THIS SEA A POND AND OUR LONG VOYAGE TAKING A LITTLE SAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "he called this sea a pond and our long voyage taking a little sail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 84, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0029.flac", "answer": "THOSE HUGE CREATURES ATTACKED EACH OTHER WITH THE GREATEST ANIMOSITY", "subset": "test_clean", "task_type": "understanding", "prediction": "those huge creatures attacked each other with the greatest animosity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 85, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0028.flac", "answer": "ITS JAW IS ENORMOUS AND ACCORDING TO NATURALISTS IT IS ARMED WITH NO LESS THAN ONE HUNDRED AND EIGHTY TWO TEETH", "subset": "test_clean", "task_type": "understanding", "prediction": "its jaw is enormous and according to naturalists it is armed with no less than one hundred and eighty two teeth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 86, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0023.flac", "answer": "THE RAFT WAS HEAVED UP ON A WATERY MOUNTAIN AND PITCHED DOWN AGAIN AT A DISTANCE OF TWENTY FATHOMS", "subset": "test_clean", "task_type": "understanding", "prediction": "the raft was heaved up on a watery mountain and pitched down again at a distance of twenty fathoms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 87, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0021.flac", "answer": "DURING HIS WATCH I SLEPT", "subset": "test_clean", "task_type": "understanding", "prediction": "during his watch i slept", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 88, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0006.flac", "answer": "WE ARE LOSING TIME AND THE FACT IS I HAVE NOT COME ALL THIS WAY TO TAKE A LITTLE SAIL UPON A POND ON A RAFT", "subset": "test_clean", "task_type": "understanding", "prediction": "we are losing time and the fact is i have not come all this way to take a little sail upon a pond on a raft", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 89, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0019.flac", "answer": "I SUPPOSE PROFESSOR LIEDENBROCK WAS OF MY OPINION TOO AND EVEN SHARED MY FEARS FOR AFTER HAVING EXAMINED THE PICK HIS EYES TRAVERSED THE OCEAN FROM SIDE TO SIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "i suppose professor lidenbrock was of my opinion too and even shared my fears for after having examined the pick his eyes traversed the ocean from side to side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 90, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0024.flac", "answer": "THERE'S A WHALE A WHALE CRIED THE PROFESSOR", "subset": "test_clean", "task_type": "understanding", "prediction": "there is a whale a whale cried the professor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 91, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0013.flac", "answer": "THE SHADOW OF THE RAFT WAS CLEARLY OUTLINED UPON THE SURFACE OF THE WAVES", "subset": "test_clean", "task_type": "understanding", "prediction": "the shadow of the raft was clearly outlined upon the surface of the waves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 92, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0008.flac", "answer": "THEREFORE DON'T TALK TO ME ABOUT VIEWS AND PROSPECTS", "subset": "test_clean", "task_type": "understanding", "prediction": "therefore dont talk to me about views and prospects", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 93, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0005.flac", "answer": "I AM NOT COMPLAINING THAT THE RATE IS SLOW BUT THAT THE SEA IS SO WIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am not complaining that the rate is slow but that the seat is so wide", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 94, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0022.flac", "answer": "TWO HOURS AFTERWARDS A TERRIBLE SHOCK AWOKE ME", "subset": "test_clean", "task_type": "understanding", "prediction": "two hours afterwards a terrible shock awoke me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 95, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0004.flac", "answer": "ONE MIGHT BE WITH LESS REASON THAN NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "one might be with less reason than now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 96, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0018.flac", "answer": "I SAW AT THE HAMBURG MUSEUM THE SKELETON OF ONE OF THESE CREATURES THIRTY FEET IN LENGTH", "subset": "test_clean", "task_type": "understanding", "prediction": "i saw at the hamburg museum the skeleton of one of these creatures thirty feet in length", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 97, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0000.flac", "answer": "SATURDAY AUGUST FIFTEENTH THE SEA UNBROKEN ALL ROUND NO LAND IN SIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "saturday august fifteenth the sea unbroken all round no land in sight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 98, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0011.flac", "answer": "NOTHING NEW WEATHER UNCHANGED THE WIND FRESHENS", "subset": "test_clean", "task_type": "understanding", "prediction": "nothing new weather unchanged the wind freshens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 99, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0014.flac", "answer": "TRULY THIS SEA IS OF INFINITE WIDTH", "subset": "test_clean", "task_type": "understanding", "prediction": "truly this sea is of infinite width", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0020.flac", "answer": "TUESDAY AUGUST EIGHTEENTH", "subset": "test_clean", "task_type": "understanding", "prediction": "tuesday august eighteenth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0031.flac", "answer": "AS FOR THE ICHTHYOSAURUS HAS HE RETURNED TO HIS SUBMARINE CAVERN", "subset": "test_clean", "task_type": "understanding", "prediction": "as for the ichthyosaurus has he returned to his submarine cavern", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0025.flac", "answer": "FLIGHT WAS OUT OF THE QUESTION NOW THE REPTILES ROSE THEY WHEELED AROUND OUR LITTLE RAFT WITH A RAPIDITY GREATER THAN THAT OF EXPRESS TRAINS", "subset": "test_clean", "task_type": "understanding", "prediction": "flight was out of the question now the reptiles rose they wheeled around our little raft with a rapidity greater than that of express trains", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0016.flac", "answer": "THESE THOUGHTS AGITATED ME ALL DAY AND MY IMAGINATION SCARCELY CALMED DOWN AFTER SEVERAL HOURS SLEEP", "subset": "test_clean", "task_type": "understanding", "prediction": "these thoughts agitated me all day and my imagination scarcely calmed down after several hours sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0002.flac", "answer": "ALL MY DANGER AND SUFFERINGS WERE NEEDED TO STRIKE A SPARK OF HUMAN FEELING OUT OF HIM BUT NOW THAT I AM WELL HIS NATURE HAS RESUMED ITS SWAY", "subset": "test_clean", "task_type": "understanding", "prediction": "all my danger and sufferings were needed to strike a spark of human feeling out of him but now that i am well his nature has resumed its sway", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0026.flac", "answer": "TWO MONSTERS ONLY WERE CREATING ALL THIS COMMOTION AND BEFORE MY EYES ARE TWO REPTILES OF THE PRIMITIVE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "two monsters only were creating all this commotion and before my eyes are two reptiles of the primitive world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0009.flac", "answer": "I TAKE THIS AS MY ANSWER AND I LEAVE THE PROFESSOR TO BITE HIS LIPS WITH IMPATIENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "i take this as my answer and i leave the professor to bite his lips with impatience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0010.flac", "answer": "SUNDAY AUGUST SIXTEENTH", "subset": "test_clean", "task_type": "understanding", "prediction": "sunday august sixteenth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0017.flac", "answer": "I SHUDDER AS I RECALL THESE MONSTERS TO MY REMEMBRANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "i shudder as i recall these monsters to my remembrance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0012.flac", "answer": "BUT THERE SEEMED NO REASON TO FEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "but there seemed no reason of fear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0015.flac", "answer": "IT MUST BE AS WIDE AS THE MEDITERRANEAN OR THE ATLANTIC AND WHY NOT", "subset": "test_clean", "task_type": "understanding", "prediction": "it must be as wide as the mediterranean or the atlantic and why not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123286/260-123286-0030.flac", "answer": "SUDDENLY THE ICHTHYOSAURUS AND THE PLESIOSAURUS DISAPPEAR BELOW LEAVING A WHIRLPOOL EDDYING IN THE WATER", "subset": "test_clean", "task_type": "understanding", "prediction": "suddenly the ichthyosaurus and the plesiosaurus disappear below leaving a whirlpool eddying in the water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0011.flac", "answer": "BUT IF WE HAVE NOW CEASED TO ADVANCE WHY DO WE YET LEAVE THAT SAIL LOOSE WHICH AT THE FIRST SHOCK OF THE TEMPEST MAY CAPSIZE US IN A MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "but if we have now ceased to advance why do we yet leave that sail loose which at the first shock of a tempest may capsize us in a moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0027.flac", "answer": "A SUFFOCATING SMELL OF NITROGEN FILLS THE AIR IT ENTERS THE THROAT IT FILLS THE LUNGS", "subset": "test_clean", "task_type": "understanding", "prediction": "a suffocating smell of nitrogen fills the air it enters the throat it fills the lungs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0016.flac", "answer": "I REFER TO THE THERMOMETER IT INDICATES THE FIGURE IS OBLITERATED", "subset": "test_clean", "task_type": "understanding", "prediction": "i refer to the thermometer it indicates the figure is obliterated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0017.flac", "answer": "IS THE ATMOSPHERIC CONDITION HAVING ONCE REACHED THIS DENSITY TO BECOME FINAL", "subset": "test_clean", "task_type": "understanding", "prediction": "is the atmospheric conditioning having once reached this density to become final", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0015.flac", "answer": "FROM THE UNDER SURFACE OF THE CLOUDS THERE ARE CONTINUAL EMISSIONS OF LURID LIGHT ELECTRIC MATTER IS IN CONTINUAL EVOLUTION FROM THEIR COMPONENT MOLECULES THE GASEOUS ELEMENTS OF THE AIR NEED TO BE SLAKED WITH MOISTURE FOR INNUMERABLE COLUMNS OF WATER RUSH UPWARDS INTO THE AIR AND FALL BACK AGAIN IN WHITE FOAM", "subset": "test_clean", "task_type": "understanding", "prediction": "from the under surface of the clouds there are continual emissions of lurid light electric matter is in continual evolution from their component molecules the gaseous elements of the air need to be slaked with moisture for innumerable columns of water rush upwards into the air and fall back again in white foam", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0008.flac", "answer": "THERE'S A HEAVY STORM COMING ON I CRIED POINTING TOWARDS THE HORIZON", "subset": "test_clean", "task_type": "understanding", "prediction": "there is a heavy storm coming on i cried pointing towards the horizon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0019.flac", "answer": "AT NOON THE VIOLENCE OF THE STORM REDOUBLES", "subset": "test_clean", "task_type": "understanding", "prediction": "at noon the violence of the storm redoubles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0014.flac", "answer": "HANS STIRS NOT", "subset": "test_clean", "task_type": "understanding", "prediction": "hans stirs not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0006.flac", "answer": "THE ATMOSPHERE IS EVIDENTLY CHARGED AND SURCHARGED WITH ELECTRICITY", "subset": "test_clean", "task_type": "understanding", "prediction": "the atmosphere as evidently charged and surcharged with electricity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0026.flac", "answer": "WE SHALL BE BLOWN UP BUT NO THE DAZZLING DISK OF MYSTERIOUS LIGHT NIMBLY LEAPS ASIDE IT APPROACHES HANS WHO FIXES HIS BLUE EYE UPON IT STEADILY IT THREATENS THE HEAD OF MY UNCLE WHO FALLS UPON HIS KNEES WITH HIS HEAD DOWN TO AVOID IT", "subset": "test_clean", "task_type": "understanding", "prediction": "we shall be blown up but no the dazzling disk of mysterious light nimbly leaps aside it approaches hans who fixes his blue eye upon it steadily it threatens the head of my uncle who falls upon his knees with his head down to avoid it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0012.flac", "answer": "THAT WILL BE SAFEST NO NO NEVER", "subset": "test_clean", "task_type": "understanding", "prediction": "that will be the safest no no never", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0007.flac", "answer": "THE WIND NEVER LULLS BUT TO ACQUIRE INCREASED STRENGTH THE VAST BANK OF HEAVY CLOUDS IS A HUGE RESERVOIR OF FEARFUL WINDY GUSTS AND RUSHING STORMS", "subset": "test_clean", "task_type": "understanding", "prediction": "the wind never lulls but to acquire increased strength the vast bank of heavy clouds is a huge reservoir of fearful windy gusts and rushing storms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0013.flac", "answer": "THE PILED UP VAPOURS CONDENSE INTO WATER AND THE AIR PUT INTO VIOLENT ACTION TO SUPPLY THE VACUUM LEFT BY THE CONDENSATION OF THE MISTS ROUSES ITSELF INTO A WHIRLWIND", "subset": "test_clean", "task_type": "understanding", "prediction": "the piled up vapours condensed into water and the air put into violent action to supply the vacuum left by the condensation of the mist rouses itself into a whirlwind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0000.flac", "answer": "THE ROARINGS BECOME LOST IN THE DISTANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "the roarings become lost in the distance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0001.flac", "answer": "THE WEATHER IF WE MAY USE THAT TERM WILL CHANGE BEFORE LONG", "subset": "test_clean", "task_type": "understanding", "prediction": "the weather if we may use the term will change before long", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0010.flac", "answer": "ON THE MAST ALREADY I SEE THE LIGHT PLAY OF A LAMBENT SAINT ELMO'S FIRE THE OUTSTRETCHED SAIL CATCHES NOT A BREATH OF WIND AND HANGS LIKE A SHEET OF LEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "on the mast already i see the light play of a lamen saint elmo s fire the outstretched sail catches not a breath of wind and hangs like a sheet of lead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0018.flac", "answer": "THE RAFT BEARS ON STILL TO THE SOUTH EAST", "subset": "test_clean", "task_type": "understanding", "prediction": "the raft bears on still to the south east", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0021.flac", "answer": "THE WAVES RISE ABOVE OUR HEADS", "subset": "test_clean", "task_type": "understanding", "prediction": "the waves rise above our heads", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0022.flac", "answer": "THEY SEEM TO BE WE ARE LOST BUT I AM NOT SURE", "subset": "test_clean", "task_type": "understanding", "prediction": "they seem to be we are lost but i am not sure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0002.flac", "answer": "THE ATMOSPHERE IS CHARGED WITH VAPOURS PERVADED WITH THE ELECTRICITY GENERATED BY THE EVAPORATION OF SALINE WATERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the atmosphere is charged with vapors pervaded with the electricity generated by the evaporation of saline waters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0004.flac", "answer": "THE AIR IS HEAVY THE SEA IS CALM", "subset": "test_clean", "task_type": "understanding", "prediction": "the air is heavy the sea is calm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0023.flac", "answer": "HE NODS HIS CONSENT", "subset": "test_clean", "task_type": "understanding", "prediction": "he nods his consent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0020.flac", "answer": "EACH OF US IS LASHED TO SOME PART OF THE RAFT", "subset": "test_clean", "task_type": "understanding", "prediction": "each of us is lashed to some part of the raft", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0005.flac", "answer": "FROM TIME TO TIME A FLEECY TUFT OF MIST WITH YET SOME GLEAMING LIGHT LEFT UPON IT DROPS DOWN UPON THE DENSE FLOOR OF GREY AND LOSES ITSELF IN THE OPAQUE AND IMPENETRABLE MASS", "subset": "test_clean", "task_type": "understanding", "prediction": "from time to time a fleecy tuft of mist with yet some gleaming light left upon it drops down upon the dense floor of gray and loses itself in the opaque and impenetrable mass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0028.flac", "answer": "WE SUFFER STIFLING PAINS", "subset": "test_clean", "task_type": "understanding", "prediction": "we suffer stifling pains", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0024.flac", "answer": "THE FIREBALL HALF OF IT WHITE HALF AZURE BLUE AND THE SIZE OF A TEN INCH SHELL MOVED SLOWLY ABOUT THE RAFT BUT REVOLVING ON ITS OWN AXIS WITH ASTONISHING VELOCITY AS IF WHIPPED ROUND BY THE FORCE OF THE WHIRLWIND", "subset": "test_clean", "task_type": "understanding", "prediction": "the fire ball half of it white half azure blue and the size of a ten inch shell moved slowly about the raft but revolving on its own axis with astonishing velocity as if whipped round by the force of the whirlwind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0003.flac", "answer": "THE ELECTRIC LIGHT CAN SCARCELY PENETRATE THROUGH THE DENSE CURTAIN WHICH HAS DROPPED OVER THE THEATRE ON WHICH THE BATTLE OF THE ELEMENTS IS ABOUT TO BE WAGED", "subset": "test_clean", "task_type": "understanding", "prediction": "the electric light can scarcely penetrate through the dense curtain which is dropped over the theatre on which the battle of the elements is about to be waged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0025.flac", "answer": "HERE IT COMES THERE IT GLIDES NOW IT IS UP THE RAGGED STUMP OF THE MAST THENCE IT LIGHTLY LEAPS ON THE PROVISION BAG DESCENDS WITH A LIGHT BOUND AND JUST SKIMS THE POWDER MAGAZINE HORRIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "here it comes there it glides now it is up the ragged stump of the mast thence it lightly leaps on the provision bag descends with a light bound and just skims the powder magazine horrible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/260/123288/260-123288-0009.flac", "answer": "THOSE CLOUDS SEEM AS IF THEY WERE GOING TO CRUSH THE SEA", "subset": "test_clean", "task_type": "understanding", "prediction": "those clouds seem as if they were going to crush the sea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0045.flac", "answer": "CAPTAIN MARTIN SAID I SHALL GIVE YOU A PISTOL TO HELP PROTECT YOURSELF IF WORSE COMES TO WORST", "subset": "test_clean", "task_type": "understanding", "prediction": "captain martin said i shall give you a pistol to help protect yourself if worse comes to worst", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0012.flac", "answer": "SEVERAL HUNDRED FREE STATE MEN PROMPTLY RESPONDED TO THE SUMMONS", "subset": "test_clean", "task_type": "understanding", "prediction": "several hundred free state men promptly responded to the summons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0006.flac", "answer": "COMING BY WAY OF THE MISSOURI RIVER TOWNS HE FELL FIRST AMONG BORDER RUFFIAN COMPANIONSHIP AND INFLUENCES AND PERHAPS HAVING HIS INCLINATIONS ALREADY MOLDED BY HIS WASHINGTON INSTRUCTIONS HIS EARLY IMPRESSIONS WERE DECIDEDLY ADVERSE TO THE FREE STATE CAUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "coming by way of the missouri river towns he fell first among border ruffian companionship and influences and perhaps having his inclinations already molded by his washington instructions his early impressions were decidedly adverse to the free state cause", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0022.flac", "answer": "FROM THESE AGAIN SPRANG BARRICADED AND FORTIFIED DWELLINGS CAMPS AND SCOUTING PARTIES FINALLY CULMINATING IN ROVING GUERRILLA BANDS HALF PARTISAN HALF PREDATORY", "subset": "test_clean", "task_type": "understanding", "prediction": "from these again sprang barricaded and fortified dwellings camps and scout parties finally culminating in roving guerrilla bands half partisan half predatory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0014.flac", "answer": "THE LEADERS OF THE CONSPIRACY BECAME DISTRUSTFUL OF THEIR POWER TO CRUSH THE TOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "the leaders of the conspiracy became distrustful of their power to crush the town", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0039.flac", "answer": "THE INMATES BEING REMOVED AT THE APPOINTED HOUR A FEW CANNON BALLS WERE FIRED THROUGH THE STONE WALLS", "subset": "test_clean", "task_type": "understanding", "prediction": "the inmates being removed at the appointed hour a few cannon balls were fired through the stone walls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0036.flac", "answer": "HE PLANTED A COMPANY BEFORE THE HOTEL AND DEMANDED A SURRENDER OF THE ARMS BELONGING TO THE FREE STATE MILITARY COMPANIES", "subset": "test_clean", "task_type": "understanding", "prediction": "he planted a company before the hotel and demanded a surrender of the arms belonging to the free state military companies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0035.flac", "answer": "THE MILITARY FORCE PARTLY RABBLE PARTLY ORGANIZED HAD MEANWHILE MOVED INTO THE TOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "the military force partly rabble partly organized had meanwhile moved into the town", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0009.flac", "answer": "ALL DISSENT ALL NON COMPLIANCE ALL HESITATION ALL MERE SILENCE EVEN WERE IN THEIR STRONGHOLD TOWNS LIKE LEAVENWORTH BRANDED AS ABOLITIONISM DECLARED TO BE HOSTILITY TO THE PUBLIC WELFARE AND PUNISHED WITH PROSCRIPTION PERSONAL VIOLENCE EXPULSION AND FREQUENTLY DEATH", "subset": "test_clean", "task_type": "understanding", "prediction": "all dissent all noncompliance all hesitation all mere silence even were in their stronghold towns like leavenworth branded as abolitionism declared to be hostility to the public welfare and punished with proscription personal violence expulsion and frequently death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0019.flac", "answer": "TO EMBARRASS THIS DAMAGING EXPOSURE JUDGE LECOMPTE ISSUED A WRIT AGAINST THE EX GOVERNOR ON A FRIVOLOUS CHARGE OF CONTEMPT", "subset": "test_clean", "task_type": "understanding", "prediction": "to embarrass this damaging exposure judge lecompte issued a writ against the ex governor on a frivolous charge of contempt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0044.flac", "answer": "HERE HE WAS PLACED IN THE CUSTODY OF CAPTAIN MARTIN OF THE KICKAPOO RANGERS WHO PROVED A KIND JAILER AND MATERIALLY ASSISTED IN PROTECTING HIM FROM THE DANGEROUS INTENTIONS OF THE MOB WHICH AT THAT TIME HELD LEAVENWORTH UNDER A REIGN OF TERROR", "subset": "test_clean", "task_type": "understanding", "prediction": "here he was placed in the custody of captain martin of the kickapoo rangers who proved a kind jailer and materially assisted in protecting him from the dangerous intentions of the mob which at that time held leavenworth under the reign of terror", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0016.flac", "answer": "THE GOVERNOR ON HIS PART BECOMING DOUBTFUL OF THE LEGALITY OF EMPLOYING MISSOURI MILITIA TO ENFORCE KANSAS LAWS WAS ALSO EAGER TO SECURE THE HELP OF FEDERAL TROOPS", "subset": "test_clean", "task_type": "understanding", "prediction": "the governor on his part becoming doubtful of the legality of employing missouri militia to enforce kansas laws was also eager to secure the help of federal troops", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0043.flac", "answer": "IN A FEW DAYS AN OFFICER CAME WITH A REQUISITION FROM GOVERNOR SHANNON AND TOOK THE PRISONER BY LAND TO WESTPORT AND AFTERWARDS FROM THERE TO KANSAS CITY AND LEAVENWORTH", "subset": "test_clean", "task_type": "understanding", "prediction": "in a few days an officer came with a requisition from governor shannon and took the prisoner by land to westport and afterwards from there to kansas city and leavenworth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0005.flac", "answer": "THIS WAS A FORMIDABLE ARRAY OF ADVANTAGES SLAVERY WAS PLAYING WITH LOADED DICE", "subset": "test_clean", "task_type": "understanding", "prediction": "this was a formable array of advantages slavery was playing with loaded dice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0040.flac", "answer": "IN THIS INCIDENT CONTRASTING THE CREATIVE AND THE DESTRUCTIVE SPIRIT OF THE FACTIONS THE EMIGRANT AID SOCIETY OF MASSACHUSETTS FINDS ITS MOST HONORABLE AND TRIUMPHANT VINDICATION", "subset": "test_clean", "task_type": "understanding", "prediction": "in this incident contrasting the creative and the destructive spirit of the factions the immigrant aid society of massachusetts finds its most honorable and triumphant vindication", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0026.flac", "answer": "IN THE SHOOTING OF SHERIFF JONES IN LAWRENCE AND IN THE REFUSAL OF EX GOVERNOR BEEDER TO ALLOW THE DEPUTY MARSHAL TO ARREST HIM THEY DISCOVERED GRAVE OFFENSES AGAINST THE TERRITORIAL AND UNITED STATES LAWS", "subset": "test_clean", "task_type": "understanding", "prediction": "in the shooting of sheriff jones in lawrence and in the refusal of ex governor reeder to allow the deputy marshal to arrest him they discovered grave offenses against the territorial and the united states laws", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0029.flac", "answer": "TEN DAYS WERE CONSUMED IN THESE NEGOTIATIONS BUT THE SPIRIT OF VENGEANCE REFUSED TO YIELD", "subset": "test_clean", "task_type": "understanding", "prediction": "ten days were consumed in these negotiations but the spirit of vengeance refused to yield", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0007.flac", "answer": "HIS RECEPTION SPEECH AT WESTPORT IN WHICH HE MAINTAINED THE LEGALITY OF THE LEGISLATURE AND HIS DETERMINATION TO ENFORCE THEIR LAWS DELIGHTED HIS PRO SLAVERY AUDITORS", "subset": "test_clean", "task_type": "understanding", "prediction": "his reception speech at westport in which he maintained the legality of the legislature and his determination to enforce their laws delighted his pro slavery auditors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0025.flac", "answer": "THEIR ASSUMED CHARACTER CHANGED WITH THEIR CHANGING OPPORTUNITIES OR NECESSITIES", "subset": "test_clean", "task_type": "understanding", "prediction": "their assumed character changed with their changing opportunities or necessities", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0020.flac", "answer": "THE INCIDENT WAS NOT VIOLENT NOR EVEN DRAMATIC NO POSSE WAS SUMMONED NO FURTHER EFFORT MADE AND REEDER FEARING PERSONAL VIOLENCE SOON FLED IN DISGUISE", "subset": "test_clean", "task_type": "understanding", "prediction": "the incident was not violent nor even dramatic no posse was summoned no further effort made and reeder fearing personal violence soon fled in disguise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0023.flac", "answer": "THEIR DISTINCTIVE CHARACTERS HOWEVER DISPLAY ONE BROAD AND UNFAILING DIFFERENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "their distinctive characters however display one broad and unfailing difference", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0018.flac", "answer": "LITTLE BY LITTLE HOWEVER THE LATTER BECAME HEMMED AND BOUND IN THE MESHES OF THE VARIOUS DEVICES AND PROCEEDINGS WHICH THE TERRITORIAL OFFICIALS EVOLVED FROM THE BOGUS LAWS", "subset": "test_clean", "task_type": "understanding", "prediction": "little by little however the latter became hemmed and bound in the meshes of the various devices and proceedings which the territorial officials evolved from the bogus laws", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0038.flac", "answer": "ATCHISON WHO HAD BEEN HARANGUING THE MOB PLANTED HIS TWO GUNS BEFORE THE BUILDING AND TRAINED THEM UPON IT", "subset": "test_clean", "task_type": "understanding", "prediction": "atchison who had been haranguing the mob planted his two guns before the building and trained them upon it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0037.flac", "answer": "HALF AN HOUR LATER TURNING A DEAF EAR TO ALL REMONSTRANCE HE GAVE THE PROPRIETORS UNTIL FIVE O'CLOCK TO REMOVE THEIR FAMILIES AND PERSONAL PROPERTY FROM THE FREE STATE HOTEL", "subset": "test_clean", "task_type": "understanding", "prediction": "half an hour later turning a deaf ear to all remonstrance he gave the proprietors until five o clock to remove their families and personal property from the free state hotel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0041.flac", "answer": "THE WHOLE PROCEEDING WAS SO CHILDISH THE MISERABLE PLOT SO TRANSPARENT THE OUTRAGE SO GROSS AS TO BRING DISGUST TO THE BETTER CLASS OF BORDER RUFFIANS WHO WERE WITNESSES AND ACCESSORIES", "subset": "test_clean", "task_type": "understanding", "prediction": "the whole proceeding was so childish the miserable plot so transparent the outrage so gross as to bring disgust to the better class of border ruffians who were witnesses and accessories", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0031.flac", "answer": "HE CONTINUED HIS PRETENDED SEARCH AND TO GIVE COLOR TO HIS ERRAND MADE TWO ARRESTS", "subset": "test_clean", "task_type": "understanding", "prediction": "he continued his pretended search and to give color to his errand made two arrests", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0008.flac", "answer": "ALL THE TERRITORIAL DIGNITARIES WERE PRESENT GOVERNOR SHANNON PRESIDED JOHN CALHOUN THE SURVEYOR GENERAL MADE THE PRINCIPAL SPEECH A DENUNCIATION OF THE ABOLITIONISTS SUPPORTING THE TOPEKA MOVEMENT CHIEF JUSTICE LECOMPTE DIGNIFIED THE OCCASION WITH APPROVING REMARKS", "subset": "test_clean", "task_type": "understanding", "prediction": "all the territorial dignitaries were present governor shannon presided john calhoun the surveyor general made the principal speech a denunciation of the abolitionists supporting the topeka movement chief justice leconte dignified the occasion with approving remarks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0021.flac", "answer": "BUT THE AFFAIR WAS MAGNIFIED AS A CROWNING PROOF THAT THE FREE STATE MEN WERE INSURRECTIONISTS AND OUTLAWS", "subset": "test_clean", "task_type": "understanding", "prediction": "but the affair was magnified as a crowning proof that the free state men were insurrectionists and outlaws", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0002.flac", "answer": "THAT SUMMER'S EMIGRATION HOWEVER BEING MAINLY FROM THE FREE STATES GREATLY CHANGED THE RELATIVE STRENGTH OF THE TWO PARTIES", "subset": "test_clean", "task_type": "understanding", "prediction": "that summers immigration however being mainly from the free states greatly changed the relative strengths of the two parties", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0000.flac", "answer": "THE BOGUS LEGISLATURE NUMBERED THIRTY SIX MEMBERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the bogus legislature numbered thirty six members", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0017.flac", "answer": "SHERIFF JONES HAD HIS POCKETS ALWAYS FULL OF WRITS ISSUED IN THE SPIRIT OF PERSECUTION BUT WAS OFTEN BAFFLED BY THE SHARP WITS AND READY RESOURCES OF THE FREE STATE PEOPLE AND SOMETIMES DEFIED OUTRIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "sheriff jones had his pockets always full of writs issued in the spirit of persecution but was often baffled by the sharp wits and ready resources of the free state people and sometimes defied outright", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0024.flac", "answer": "THE FREE STATE MEN CLUNG TO THEIR PRAIRIE TOWNS AND PRAIRIE RAVINES WITH ALL THE OBSTINACY AND COURAGE OF TRUE DEFENDERS OF THEIR HOMES AND FIRESIDES", "subset": "test_clean", "task_type": "understanding", "prediction": "the free state men clung to their prairie towns and prairie ravines with all the obstinacy and courage of true defenders of their homes and firesides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0013.flac", "answer": "IT WAS IN FACT THE BEST WEAPON OF ITS DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "it was in fact the best weapon of its day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0001.flac", "answer": "THIS WAS AT THE MARCH ELECTION EIGHTEEN FIFTY FIVE", "subset": "test_clean", "task_type": "understanding", "prediction": "this was at the march election eighteen fifty five", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0004.flac", "answer": "THE FREE STATE MEN HAD ONLY THEIR CONVICTIONS THEIR INTELLIGENCE THEIR COURAGE AND THE MORAL SUPPORT OF THE NORTH THE CONSPIRACY HAD ITS SECRET COMBINATION THE TERRITORIAL OFFICIALS THE LEGISLATURE THE BOGUS LAWS THE COURTS THE MILITIA OFFICERS THE PRESIDENT AND THE ARMY", "subset": "test_clean", "task_type": "understanding", "prediction": "the free state men had only their convictions their intelligence their courage and the moral support of the north the conspiracy had its secret combination the territorial officials the legislature the bogus laws the courts the militia officers the president and the army", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0034.flac", "answer": "TO THEIR SORROW THEY WERE SOON UNDECEIVED", "subset": "test_clean", "task_type": "understanding", "prediction": "to their sorrow they were soon undeceived", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0046.flac", "answer": "IN THE EARLY MORNING OF THE NEXT DAY MAY TWENTY NINTH A COMPANY OF DRAGOONS WITH ONE EMPTY SADDLE CAME DOWN FROM THE FORT AND WHILE THE PRO SLAVERY MEN STILL SLEPT THE PRISONER AND HIS ESCORT WERE ON THEIR WAY ACROSS THE PRAIRIES TO LECOMPTON IN THE CHARGE OF OFFICERS OF THE UNITED STATES ARMY", "subset": "test_clean", "task_type": "understanding", "prediction": "in the early morning of the next day may twenty ninth a company of dragoons with one empty saddle came down from the fort and while the pro slavery men still slept the prisoner and his escort were on their way across the prairies to lecompton in the charge of officers of the united states army", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0015.flac", "answer": "ONE OF HIS MILITIA GENERALS SUGGESTED THAT THE GOVERNOR SHOULD REQUIRE THE OUTLAWS AT LAWRENCE AND ELSEWHERE TO SURRENDER THE SHARPS RIFLES ANOTHER WROTE ASKING HIM TO CALL OUT THE GOVERNMENT TROOPS AT FORT LEAVENWORTH", "subset": "test_clean", "task_type": "understanding", "prediction": "one of his militia generals suggested that the governor should require the outlaws at lawrence and elsewhere to surrender the sharpshooters rifles another wrote asking him to call out the government troops at fort leavenworth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0003.flac", "answer": "FOR GENERAL SERVICE THEREFORE REQUIRING NO SPECIAL EFFORT THE NUMERICAL STRENGTH OF THE FACTIONS WAS ABOUT EQUAL WHILE ON EXTRAORDINARY OCCASIONS THE TWO THOUSAND BORDER RUFFIAN RESERVE LYING A LITTLE FARTHER BACK FROM THE STATE LINE COULD AT ANY TIME EASILY TURN THE SCALE", "subset": "test_clean", "task_type": "understanding", "prediction": "for general service therefore requiring no special effort the numerical strength of the factions was about equal while on extraordinary occasions the two thousand border ruffian reserve lying a little farther back from the state line could at any time easily turn the scale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0027.flac", "answer": "FOOTNOTE SUMNER TO SHANNON MAY TWELFTH EIGHTEEN FIFTY SIX", "subset": "test_clean", "task_type": "understanding", "prediction": "footnote sumner to shannon may twelfth eighteen fifty six", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0032.flac", "answer": "THE FREE STATE HOTEL A STONE BUILDING IN DIMENSIONS FIFTY BY SEVENTY FEET THREE STORIES HIGH AND HANDSOMELY FURNISHED PREVIOUSLY OCCUPIED ONLY FOR LODGING ROOMS ON THAT DAY FOR THE FIRST TIME OPENED ITS TABLE ACCOMMODATIONS TO THE PUBLIC AND PROVIDED A FREE DINNER IN HONOR OF THE OCCASION", "subset": "test_clean", "task_type": "understanding", "prediction": "the free state hotel a stone building in dimensions fifty by seventy feet three stories high and handsomely furnished previously occupied only for lodging rooms on that day for the first time opened its table accommodations to the public and provided a free dinner in honor of the occasion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0042.flac", "answer": "RELOCATED FOOTNOTE GOVERNOR ROBINSON BEING ON HIS WAY EAST THE STEAMBOAT ON WHICH HE WAS TRAVELING STOPPED AT LEXINGTON MISSOURI", "subset": "test_clean", "task_type": "understanding", "prediction": "relocated footnote governor robinson being on his way east the steamboat on which he was traveling stopped at lexington missouri", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0028.flac", "answer": "PRIVATE PERSONS WHO HAD LEASED THE FREE STATE HOTEL VAINLY BESOUGHT THE VARIOUS AUTHORITIES TO PREVENT THE DESTRUCTION OF THEIR PROPERTY", "subset": "test_clean", "task_type": "understanding", "prediction": "private persons who had leased the free state hotel vainly besought the various authorities to prevent the destruction of their property", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0033.flac", "answer": "AS HE HAD PROMISED TO PROTECT THE HOTEL THE REASSURED CITIZENS BEGAN TO LAUGH AT THEIR OWN FEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "as he had promised to protect the hotel the reassured citizens began to laugh at their own fears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0011.flac", "answer": "THE PRESENT CHAPTERS CAN ONLY TOUCH UPON THE MORE SALIENT MOVEMENTS OF THE CIVIL WAR IN KANSAS WHICH HAPPILY WERE NOT SANGUINARY IF HOWEVER THE INDIVIDUAL AND MORE ISOLATED CASES OF BLOODSHED COULD BE DESCRIBED THEY WOULD SHOW A STARTLING AGGREGATE OF BARBARITY AND LOSS OF LIFE FOR OPINION'S SAKE", "subset": "test_clean", "task_type": "understanding", "prediction": "the present chapters can only touch upon the more salient movements of the civil war in kansas which happily are not sanguinary if however the individual and more isolated cases of bloodshed could be described they would show a startling aggregate of barbarity and a loss of life for opinion sake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0010.flac", "answer": "OF THE LYNCHINGS THE MOBS AND THE MURDERS IT WOULD BE IMPOSSIBLE EXCEPT IN A VERY EXTENDED WORK TO NOTE THE FREQUENT AND ATROCIOUS DETAILS", "subset": "test_clean", "task_type": "understanding", "prediction": "of the lynchings the mobs and the murders it would be impossible except in a very extended work to note the frequent and atrocious details", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7729/102255/7729-102255-0030.flac", "answer": "HE SUMMONED HALF A DOZEN CITIZENS TO JOIN HIS POSSE WHO FOLLOWED OBEYED AND ASSISTED HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "he summoned half a dozen citizens to join his posse who followed obeyed and assisted him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0059.flac", "answer": "THIS MISSUS POYSER SAID BLUSHING AND BELIEVING THAT THE CAPTAIN WAS REALLY INTERESTED IN HER MILK PANS AND WOULD ADJUST HIS OPINION OF HER TO THE APPEARANCE OF HER DAIRY", "subset": "test_clean", "task_type": "understanding", "prediction": "this mrs poyser said blushing and believing that the captain was really interested in her milk pans and would adjust his opinion of her to the appearance of her dairy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0046.flac", "answer": "I DELIGHT IN YOUR KITCHEN", "subset": "test_clean", "task_type": "understanding", "prediction": "my delight in your kitchen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0035.flac", "answer": "BUT NOT MORE THAN WHAT'S IN THE BIBLE AUNT SAID DINAH", "subset": "test_clean", "task_type": "understanding", "prediction": "but not more than what is in the bible aunt said dinah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0013.flac", "answer": "HER TONGUE WAS NOT LESS KEEN THAN HER EYE AND WHENEVER A DAMSEL CAME WITHIN EARSHOT SEEMED TO TAKE UP AN UNFINISHED LECTURE AS A BARREL ORGAN TAKES UP A TUNE PRECISELY AT THE POINT WHERE IT HAD LEFT OFF", "subset": "test_clean", "task_type": "understanding", "prediction": "her tongue was not less keen than her eye and whenever a damsel came within earshot seemed to take up an unfinished luxure as a barrel organ takes up a tune precisely at the point where it had left off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0019.flac", "answer": "COMB THE WOOL FOR THE WHITTAWS INDEED", "subset": "test_clean", "task_type": "understanding", "prediction": "comb the wool for the widows indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0020.flac", "answer": "THAT'S WHAT YOU'D LIKE TO BE DOING IS IT", "subset": "test_clean", "task_type": "understanding", "prediction": "that is what you would like to be doing is it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0011.flac", "answer": "DO NOT SUPPOSE HOWEVER THAT MISSUS POYSER WAS ELDERLY OR SHREWISH IN HER APPEARANCE SHE WAS A GOOD LOOKING WOMAN NOT MORE THAN EIGHT AND THIRTY OF FAIR COMPLEXION AND SANDY HAIR WELL SHAPEN LIGHT FOOTED", "subset": "test_clean", "task_type": "understanding", "prediction": "do not suppose however that mrs poyser was elderly or shrewish in her appearance she was a good looking woman not more than eight and thirty of fair complexion and sandy hair well shapen light footed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0016.flac", "answer": "SPINNING INDEED", "subset": "test_clean", "task_type": "understanding", "prediction": "spinning indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0028.flac", "answer": "NO NO NO TOTTY UD GET HER FEET WET SAID MISSUS POYSER CARRYING AWAY HER IRON", "subset": "test_clean", "task_type": "understanding", "prediction": "no no no totty ud get her feet wet said mrs poyser carrying away her iron", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0042.flac", "answer": "I HANNA COMMON PATIENCE WITH YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "i had a common patience with you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0022.flac", "answer": "MISTER OTTLEY'S INDEED", "subset": "test_clean", "task_type": "understanding", "prediction": "mr oatley s indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0056.flac", "answer": "I THINK I SHOULD BE DOING YOU A SERVICE TO TURN YOU OUT OF SUCH A PLACE", "subset": "test_clean", "task_type": "understanding", "prediction": "i think i should be doing you a service to turn you out of such a place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0032.flac", "answer": "I OFTEN HEARD HER TALK OF YOU IN THE SAME SORT OF WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "i often heard her talk of you in the same sort of way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0039.flac", "answer": "I'VE STRONG ASSURANCE THAT NO EVIL WILL HAPPEN TO YOU AND MY UNCLE AND THE CHILDREN FROM ANYTHING I'VE DONE", "subset": "test_clean", "task_type": "understanding", "prediction": "i have strong assurance that no evil will happen to you and my uncle and the children from anything i have done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0024.flac", "answer": "MUNNY MY IRON'S TWITE TOLD PEASE PUT IT DOWN TO WARM", "subset": "test_clean", "task_type": "understanding", "prediction": "money my irons twight told please put it down to warm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0015.flac", "answer": "TO ALL APPEARANCE MOLLY HAD GOT THROUGH HER AFTER DINNER WORK IN AN EXEMPLARY MANNER HAD CLEANED HERSELF WITH GREAT DISPATCH AND NOW CAME TO ASK SUBMISSIVELY IF SHE SHOULD SIT DOWN TO HER SPINNING TILL MILKING TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "to all appearance molly had got through her after dinner work in an exemplary manner had cleaned herself with great despatch and now came to ask submissively if she should sit down to her spinning till milking time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0001.flac", "answer": "BUT THE WINDOWS ARE PATCHED WITH WOODEN PANES AND THE DOOR I THINK IS LIKE THE GATE IT IS NEVER OPENED", "subset": "test_clean", "task_type": "understanding", "prediction": "but the windows are patched with wooden panes and the door i think is like the gate it is never opened", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0029.flac", "answer": "DID EVER ANYBODY SEE THE LIKE SCREAMED MISSUS POYSER RUNNING TOWARDS THE TABLE WHEN HER EYE HAD FALLEN ON THE BLUE STREAM", "subset": "test_clean", "task_type": "understanding", "prediction": "did ever anybody see the like screamed mrs poyser running towards the table when her eye had fallen on the blue stream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0012.flac", "answer": "THE FAMILY LIKENESS BETWEEN HER AND HER NIECE DINAH MORRIS WITH THE CONTRAST BETWEEN HER KEENNESS AND DINAH'S SERAPHIC GENTLENESS OF EXPRESSION MIGHT HAVE SERVED A PAINTER AS AN EXCELLENT SUGGESTION FOR A MARTHA AND MARY", "subset": "test_clean", "task_type": "understanding", "prediction": "the family likeness between her and her niece dinah morris with the contrast between her keenness and dinahs seraphic gentleness of expression might have served a painter as an excellent suggestion for a martha and mary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0018.flac", "answer": "WHO TAUGHT YOU TO SCRUB A FLOOR I SHOULD LIKE TO KNOW", "subset": "test_clean", "task_type": "understanding", "prediction": "who taught you to scrub a floor i should like to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0010.flac", "answer": "HETTY SORREL OFTEN TOOK THE OPPORTUNITY WHEN HER AUNT'S BACK WAS TURNED OF LOOKING AT THE PLEASING REFLECTION OF HERSELF IN THOSE POLISHED SURFACES FOR THE OAK TABLE WAS USUALLY TURNED UP LIKE A SCREEN AND WAS MORE FOR ORNAMENT THAN FOR USE AND SHE COULD SEE HERSELF SOMETIMES IN THE GREAT ROUND PEWTER DISHES THAT WERE RANGED ON THE SHELVES ABOVE THE LONG DEAL DINNER TABLE OR IN THE HOBS OF THE GRATE WHICH ALWAYS SHONE LIKE JASPER", "subset": "test_clean", "task_type": "understanding", "prediction": "hetty surrill often took the opportunity when her aunt s back was turned of looking at the pleasing reflection of herself in those polished services for the oak table was usually turned up like a screen and was more for ornament than for use and she could see herself sometimes in the great round pewter dishes that were ranged on the shelves above the long deal dinner table or in the hobbs of the grate which always shone like jasper", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0014.flac", "answer": "THE FACT THAT IT WAS CHURNING DAY WAS ANOTHER REASON WHY IT WAS INCONVENIENT TO HAVE THE WHITTAWS AND WHY CONSEQUENTLY MISSUS POYSER SHOULD SCOLD MOLLY THE HOUSEMAID WITH UNUSUAL SEVERITY", "subset": "test_clean", "task_type": "understanding", "prediction": "the fact that it was churning day was another reason why it was inconvenient to have the widows and why consequently mrs poyser should scold molly the housemaid with unusual severity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0002.flac", "answer": "FOR IT IS A SOLID HEAVY HANDSOME DOOR AND MUST ONCE HAVE BEEN IN THE HABIT OF SHUTTING WITH A SONOROUS BANG BEHIND A LIVERIED LACKEY WHO HAD JUST SEEN HIS MASTER AND MISTRESS OFF THE GROUNDS IN A CARRIAGE AND PAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "for it is a solid heavy handsome door and must once have been in the habit of shutting with a sonorous bang behind the liveried lacquey who had just seen his master and mistress off the grounds in a carriage and pair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0049.flac", "answer": "NO SIR HE ISN'T HE'S GONE TO ROSSETER TO SEE MISTER WEST THE FACTOR ABOUT THE WOOL", "subset": "test_clean", "task_type": "understanding", "prediction": "no sir he isn t he s gone to rossiter to see mr west the factor about the wool", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0021.flac", "answer": "THAT'S THE WAY WITH YOU THAT'S THE ROAD YOU'D ALL LIKE TO GO HEADLONGS TO RUIN", "subset": "test_clean", "task_type": "understanding", "prediction": "that is the way with you that is the road you would all like to go headlongs to ruin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0043.flac", "answer": "BY THIS TIME THE TWO GENTLEMEN HAD REACHED THE PALINGS AND HAD GOT DOWN FROM THEIR HORSES IT WAS PLAIN THEY MEANT TO COME IN", "subset": "test_clean", "task_type": "understanding", "prediction": "by this time the two gentlemen had reached the palings and had got down from their horses it was plain they meant to come in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0005.flac", "answer": "SEVERAL CLOTHES HORSES A PILLION A SPINNING WHEEL AND AN OLD BOX WIDE OPEN AND STUFFED FULL OF COLOURED RAGS", "subset": "test_clean", "task_type": "understanding", "prediction": "several clothes horses a pillion a spinning wheel and an old box wide open and stuffed full of colored rags", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0041.flac", "answer": "DIRECTION", "subset": "test_clean", "task_type": "understanding", "prediction": "direction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0030.flac", "answer": "TOTTY HOWEVER HAD DESCENDED FROM HER CHAIR WITH GREAT SWIFTNESS AND WAS ALREADY IN RETREAT TOWARDS THE DAIRY WITH A SORT OF WADDLING RUN AND AN AMOUNT OF FAT ON THE NAPE OF HER NECK WHICH MADE HER LOOK LIKE THE METAMORPHOSIS OF A WHITE SUCKLING PIG", "subset": "test_clean", "task_type": "understanding", "prediction": "totty however had descended from her chair with great swiftness and was already in retreat towards the dairy with a sort of waddling run and an amount of fat on the nape of her neck which made her look like the metamorphosis of a white sucking pig", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0055.flac", "answer": "BUT YOU KNOW MORE ABOUT THAT THAN I DO SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "but you know more about that than i do sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0040.flac", "answer": "I DIDN'T PREACH WITHOUT DIRECTION", "subset": "test_clean", "task_type": "understanding", "prediction": "i did n t preach without direction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0023.flac", "answer": "YOU'RE A RARE UN FOR SITTING DOWN TO YOUR WORK A LITTLE WHILE AFTER IT'S TIME TO PUT BY", "subset": "test_clean", "task_type": "understanding", "prediction": "you are a rare un for sitting down to your work a little while after it is time to put by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0045.flac", "answer": "OH SIR DON'T MENTION IT SAID MISSUS POYSER", "subset": "test_clean", "task_type": "understanding", "prediction": "oh sir dont mention it said mrs poyser", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0053.flac", "answer": "FOR IF HE'S ANYWHERE ON THE FARM WE CAN SEND FOR HIM IN A MINUTE", "subset": "test_clean", "task_type": "understanding", "prediction": "for if he is anywhere on the farm we can send for him in a minute", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0004.flac", "answer": "AND WHAT THROUGH THE LEFT HAND WINDOW", "subset": "test_clean", "task_type": "understanding", "prediction": "and what through the left hand window", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0051.flac", "answer": "NO THANK YOU I'LL JUST LOOK AT THE WHELPS AND LEAVE A MESSAGE ABOUT THEM WITH YOUR SHEPHERD", "subset": "test_clean", "task_type": "understanding", "prediction": "no thank you i will just look at the whelps and leave a message about them with your shepherd", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0031.flac", "answer": "AND SHE WAS VERY FOND OF YOU TOO AUNT RACHEL", "subset": "test_clean", "task_type": "understanding", "prediction": "and she was very fond of you too aunt rachel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0052.flac", "answer": "I MUST COME ANOTHER DAY AND SEE YOUR HUSBAND I WANT TO HAVE A CONSULTATION WITH HIM ABOUT HORSES", "subset": "test_clean", "task_type": "understanding", "prediction": "i must come another day and see your husband i want to have a consultation with him about horses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0048.flac", "answer": "SAID CAPTAIN DONNITHORNE SEATING HIMSELF WHERE HE COULD SEE ALONG THE SHORT PASSAGE TO THE OPEN DAIRY DOOR", "subset": "test_clean", "task_type": "understanding", "prediction": "said captain donnythorne seating himself where he could see along the short passage to the open dairy door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0034.flac", "answer": "AND THERE'S LINEN IN THE HOUSE AS I COULD WELL SPARE YOU FOR I'VE GOT LOTS O SHEETING AND TABLE CLOTHING AND TOWELLING AS ISN'T MADE UP", "subset": "test_clean", "task_type": "understanding", "prediction": "and there is linen in the house as i could well spare you for i got lots of sheeting and table clothing and toweling as isn t made up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0000.flac", "answer": "IT IS A VERY FINE OLD PLACE OF RED BRICK SOFTENED BY A PALE POWDERY LICHEN WHICH HAS DISPERSED ITSELF WITH HAPPY IRREGULARITY SO AS TO BRING THE RED BRICK INTO TERMS OF FRIENDLY COMPANIONSHIP WITH THE LIMESTONE ORNAMENTS SURROUNDING THE THREE GABLES THE WINDOWS AND THE DOOR PLACE", "subset": "test_clean", "task_type": "understanding", "prediction": "it is a very fine old place of red brick softened by a pale powdery lichen which has dispersed itself with happy irregularity so as to bring the red brick into terms of friendly companionship with the limestone ornaments surrounding the three gables the windows and the door place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0037.flac", "answer": "WE CAN ALL BE SERVANTS OF GOD WHEREVER OUR LOT IS CAST BUT HE GIVES US DIFFERENT SORTS OF WORK ACCORDING AS HE FITS US FOR IT AND CALLS US TO IT", "subset": "test_clean", "task_type": "understanding", "prediction": "we can all be servants of god wherever our lot is cast but he gives us different sorts of work according as he fits us for it and calls us to it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0047.flac", "answer": "POYSER IS NOT AT HOME IS HE", "subset": "test_clean", "task_type": "understanding", "prediction": "poyser is not at home is he", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0033.flac", "answer": "WHEN SHE HAD THAT BAD ILLNESS AND I WAS ONLY ELEVEN YEARS OLD SHE USED TO SAY YOU'LL HAVE A FRIEND ON EARTH IN YOUR AUNT RACHEL IF I'M TAKEN FROM YOU FOR SHE HAS A KIND HEART AND I'M SURE I'VE FOUND IT SO", "subset": "test_clean", "task_type": "understanding", "prediction": "when she had that bad illness and i was only eleven years old she used to say you will have a friend on earth in your aunt rachel if i am taken from you for she has a kind heart and i am sure i have found it so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0060.flac", "answer": "OH I'VE NO DOUBT IT'S IN CAPITAL ORDER", "subset": "test_clean", "task_type": "understanding", "prediction": "oh i have no doubt it is in capital order", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0003.flac", "answer": "A LARGE OPEN FIREPLACE WITH RUSTY DOGS IN IT AND A BARE BOARDED FLOOR AT THE FAR END FLEECES OF WOOL STACKED UP IN THE MIDDLE OF THE FLOOR SOME EMPTY CORN BAGS", "subset": "test_clean", "task_type": "understanding", "prediction": "a large open fireplace with rusty dogs in it and a bare boarded floor at the far end fleeces of wool stacked up in the middle of the floor some empty corn bags", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0057.flac", "answer": "I KNOW HIS FARM IS IN BETTER ORDER THAN ANY OTHER WITHIN TEN MILES OF US AND AS FOR THE KITCHEN HE ADDED SMILING I DON'T BELIEVE THERE'S ONE IN THE KINGDOM TO BEAT IT", "subset": "test_clean", "task_type": "understanding", "prediction": "i know his farm is in better order than any other within ten miles of us and as for the kitchen he added smiling i don t believe there is one in the kingdom to beat it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0009.flac", "answer": "FOR THE GREAT BARN DOORS ARE THROWN WIDE OPEN AND MEN ARE BUSY THERE MENDING THE HARNESS UNDER THE SUPERINTENDENCE OF MISTER GOBY THE WHITTAW OTHERWISE SADDLER WHO ENTERTAINS THEM WITH THE LATEST TREDDLESTON GOSSIP", "subset": "test_clean", "task_type": "understanding", "prediction": "where the great barn doors are thrown wide open and men are busy there mending the harness under the superintendence of mr goby the whittaw otherwise saddler who entertains them with the latest treddleston gossip", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0007.flac", "answer": "THE HISTORY OF THE HOUSE IS PLAIN NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "the history of the house is plain now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0038.flac", "answer": "I CAN NO MORE HELP SPENDING MY LIFE IN TRYING TO DO WHAT I CAN FOR THE SOULS OF OTHERS THAN YOU COULD HELP RUNNING IF YOU HEARD LITTLE TOTTY CRYING AT THE OTHER END OF THE HOUSE THE VOICE WOULD GO TO YOUR HEART YOU WOULD THINK THE DEAR CHILD WAS IN TROUBLE OR IN DANGER AND YOU COULDN'T REST WITHOUT RUNNING TO HELP HER AND COMFORT HER", "subset": "test_clean", "task_type": "understanding", "prediction": "i can no more help spending my life in trying to do what i can for the souls of others than you could help running if you heard little tottie crying at the other end of the house the voice would go to your heart you would think the dear child was in trouble or in danger and you could n t rest without running to help her and comfort her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0027.flac", "answer": "MUNNY I TOULD IKE TO DO INTO DE BARN TO TOMMY TO SEE DE WHITTAWD", "subset": "test_clean", "task_type": "understanding", "prediction": "money i did like to do into the barn to tommy to see the wid od", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0054.flac", "answer": "OH SIR SAID MISSUS POYSER RATHER ALARMED YOU WOULDN'T LIKE IT AT ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "oh sir said mrs poyser rather alarmed you wouldnt like it at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0044.flac", "answer": "SAID MISTER IRWINE WITH HIS STATELY CORDIALITY", "subset": "test_clean", "task_type": "understanding", "prediction": "said mr irwine with his stately cordiality", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0006.flac", "answer": "AT THE EDGE OF THIS BOX THERE LIES A GREAT WOODEN DOLL WHICH SO FAR AS MUTILATION IS CONCERNED BEARS A STRONG RESEMBLANCE TO THE FINEST GREEK SCULPTURE AND ESPECIALLY IN THE TOTAL LOSS OF ITS NOSE", "subset": "test_clean", "task_type": "understanding", "prediction": "at the edge of this box there lies a great wooden doll which so far as mutilation is concerned bears a strong resemblance to the finest greek sculpture and especially in the total loss of its nose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0008.flac", "answer": "BUT THERE IS ALWAYS A STRONGER SENSE OF LIFE WHEN THE SUN IS BRILLIANT AFTER RAIN AND NOW HE IS POURING DOWN HIS BEAMS AND MAKING SPARKLES AMONG THE WET STRAW AND LIGHTING UP EVERY PATCH OF VIVID GREEN MOSS ON THE RED TILES OF THE COW SHED AND TURNING EVEN THE MUDDY WATER THAT IS HURRYING ALONG THE CHANNEL TO THE DRAIN INTO A MIRROR FOR THE YELLOW BILLED DUCKS WHO ARE SEIZING THE OPPORTUNITY OF GETTING A DRINK WITH AS MUCH BODY IN IT AS POSSIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "but there is always a stronger sense of life when the sun is brilliant after rain and now he is pouring down his beams and making sparkles among the wet straw and lighting up every patch of vivid green moss and the red tiles of the cowshed and turning even the muddy water that is hurrying along the channel to the drain into a mirror for the yellow billed ducks who are seizing the opportunity of getting a drink with as much body in it as possible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0050.flac", "answer": "BUT THERE'S FATHER THE BARN SIR IF HE'D BE OF ANY USE", "subset": "test_clean", "task_type": "understanding", "prediction": "but there is father in the barn sir if he would be of any use", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0036.flac", "answer": "NAY DEAR AUNT YOU NEVER HEARD ME SAY THAT ALL PEOPLE ARE CALLED TO FORSAKE THEIR WORK AND THEIR FAMILIES", "subset": "test_clean", "task_type": "understanding", "prediction": "nay dear aunt you never heard me say that all people are called to forsake their work and their families", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0025.flac", "answer": "COLD IS IT MY DARLING BLESS YOUR SWEET FACE", "subset": "test_clean", "task_type": "understanding", "prediction": "cold is it my darling bless your sweet face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0058.flac", "answer": "BY THE BY I'VE NEVER SEEN YOUR DAIRY I MUST SEE YOUR DAIRY MISSUS POYSER", "subset": "test_clean", "task_type": "understanding", "prediction": "by the bye i have never seen your dairy am i to see your dairy mrs poyser", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0026.flac", "answer": "SHE'S GOING TO PUT THE IRONING THINGS AWAY", "subset": "test_clean", "task_type": "understanding", "prediction": "she is going to put the ironing things away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2094/142345/2094-142345-0017.flac", "answer": "I NEVER KNEW YOUR EQUALS FOR GALLOWSNESS", "subset": "test_clean", "task_type": "understanding", "prediction": "i never knew your equals for gallowsness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0016.flac", "answer": "FAREWELL MADAM", "subset": "test_clean", "task_type": "understanding", "prediction": "farewell madam", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0014.flac", "answer": "TO THOSE DUTIES YOU HAVE NOT YET BEEN CALLED AND WHEN YOU ARE YOU WILL BE LESS EAGER FOR CELEBRITY", "subset": "test_clean", "task_type": "understanding", "prediction": "to those duties you have not yet been called and when you are you will be less eager for celebrity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0042.flac", "answer": "UNFORTUNATELY THE FRACTURE COULD NOT BE SET TILL SIX O'CLOCK THE NEXT MORNING AS NO SURGEON WAS TO BE HAD BEFORE THAT TIME AND SHE NOW LIES AT OUR HOUSE IN A VERY DOUBTFUL AND DANGEROUS STATE", "subset": "test_clean", "task_type": "understanding", "prediction": "unfortunately the fracture cannot be set till six o clock the next morning as no surgeon was to be had before that time and she now lies at our house in a very doubtful and dangerous state", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0038.flac", "answer": "AND MEANTIME I KNOW THE GREATNESS OF JEHOVAH I ACKNOWLEDGE THE PERFECTION OF HIS WORD I ADORE THE PURITY OF THE CHRISTIAN FAITH MY THEORY IS RIGHT MY PRACTICE HORRIBLY WRONG", "subset": "test_clean", "task_type": "understanding", "prediction": "and meantime i know the greatness of jehovah i acknowledge the perfection of his word i adore the purity of the christian faith my theory is right my practice horribly wrong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0036.flac", "answer": "MY EYES FILL WITH TEARS WHEN I CONTRAST THE BLISS OF SUCH A STATE BRIGHTENED BY HOPES OF THE FUTURE WITH THE MELANCHOLY STATE I NOW LIVE IN UNCERTAIN THAT I EVER FELT TRUE CONTRITION WANDERING IN THOUGHT AND DEED LONGING FOR HOLINESS WHICH I SHALL NEVER NEVER OBTAIN SMITTEN AT TIMES TO THE HEART WITH THE CONVICTION THAT GHASTLY CALVINISTIC DOCTRINES ARE TRUE DARKENED IN SHORT BY THE VERY SHADOWS OF SPIRITUAL DEATH", "subset": "test_clean", "task_type": "understanding", "prediction": "my eyes fill with tears when i contrast the bliss of such a state brightened by hopes of the future with the melancholy state i now live in uncertain that i ever felt true contrition wandering in thought and deed longing for holiness which i shall never never obtain smitten at times to the heart with the conviction that ghastly calvinistic doctrines are true darkened in short by the very shadows of spiritual death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0017.flac", "answer": "THOUGH I MAY BE BUT AN UNGRACIOUS ADVISER YOU WILL ALLOW ME THEREFORE TO SUBSCRIBE MYSELF WITH THE BEST WISHES FOR YOUR HAPPINESS HERE AND HEREAFTER YOUR TRUE FRIEND ROBERT SOUTHEY", "subset": "test_clean", "task_type": "understanding", "prediction": "though i may be but an ungracious adviser you will allow me therefore to subscribe myself with the best wishes for your happiness here and hereafter your true friend robert southey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0052.flac", "answer": "SHE HAD ANOTHER WEIGHT ON HER MIND THIS CHRISTMAS", "subset": "test_clean", "task_type": "understanding", "prediction": "she had another weight on her mind this christmas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0019.flac", "answer": "I HAD NOT VENTURED TO HOPE FOR SUCH A REPLY SO CONSIDERATE IN ITS TONE SO NOBLE IN ITS SPIRIT", "subset": "test_clean", "task_type": "understanding", "prediction": "i have not ventured to hope for such a reply so considerate in its tone so noble in its spirit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0008.flac", "answer": "AND SO LIFE AND DEATH HAVE DISPERSED THE CIRCLE OF VIOLENT RADICALS AND DISSENTERS INTO WHICH TWENTY YEARS AGO THE LITTLE QUIET RESOLUTE CLERGYMAN'S DAUGHTER WAS RECEIVED AND BY WHOM SHE WAS TRULY LOVED AND HONOURED", "subset": "test_clean", "task_type": "understanding", "prediction": "and so life and death have dispersed the circle of violent radicals and dissenters into which twenty years ago the little quiet resolute clergyman s daughter was received and by whom she was truly loved and honored", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0010.flac", "answer": "I AM NOT DEPRECIATING IT WHEN I SAY THAT IN THESE TIMES IT IS NOT RARE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am not depreciating it when i say that in these times it is not rare", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0006.flac", "answer": "HER FEEBLE HEALTH GAVE HER HER YIELDING MANNER FOR SHE COULD NEVER OPPOSE ANY ONE WITHOUT GATHERING UP ALL HER STRENGTH FOR THE STRUGGLE", "subset": "test_clean", "task_type": "understanding", "prediction": "her feeble health gave her her yielding manner for she could never oppose any one without gathering up all her strength for the struggle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0035.flac", "answer": "I WISH IT WOULD RECUR AGAIN BUT IT WILL TAKE TWO OR THREE INTERVIEWS BEFORE THE STIFFNESS THE ESTRANGEMENT OF THIS LONG SEPARATION WILL WEAR AWAY", "subset": "test_clean", "task_type": "understanding", "prediction": "i wish it were to recur again but it will take two or three interviews before the stiffness the estrangement of this long separation will wear away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0026.flac", "answer": "P S PRAY SIR EXCUSE ME FOR WRITING TO YOU A SECOND TIME I COULD NOT HELP WRITING PARTLY TO TELL YOU HOW THANKFUL I AM FOR YOUR KINDNESS AND PARTLY TO LET YOU KNOW THAT YOUR ADVICE SHALL NOT BE WASTED HOWEVER SORROWFULLY AND RELUCTANTLY IT MAY BE AT FIRST FOLLOWED C B", "subset": "test_clean", "task_type": "understanding", "prediction": "p s pray sir excuse me for writing to you a second time i could not help writing partly to tell you how thankful i am for your kindness and partly to let you know that your advice shall not be wasted however sorrowfully and reluctantly it may be at first followed c b", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0003.flac", "answer": "SURELY IT MUST BE BECAUSE WE ARE IN DANGER OF LOVING EACH OTHER TOO WELL OF LOSING SIGHT OF THE CREATOR IN IDOLATRY OF THE CREATURE", "subset": "test_clean", "task_type": "understanding", "prediction": "surely it must be because we are in danger of loving each other too well of losing sight of the creator in idolatry of the creature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0056.flac", "answer": "I DOUBT WHETHER BRANWELL WAS MAINTAINING HIMSELF AT THIS TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "i doubt whether branwell was maintaining himself at this time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0032.flac", "answer": "COME COME I AM GETTING REALLY TIRED OF YOUR ABSENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "come come i am getting really tired of your absence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0039.flac", "answer": "THE CHRISTMAS HOLIDAYS CAME AND SHE AND ANNE RETURNED TO THE PARSONAGE AND TO THAT HAPPY HOME CIRCLE IN WHICH ALONE THEIR NATURES EXPANDED AMONGST ALL OTHER PEOPLE THEY SHRIVELLED UP MORE OR LESS", "subset": "test_clean", "task_type": "understanding", "prediction": "the christmas holidays came and she and anne returned to the parsonage and to that happy home circle in which alone their natures expanded amongst all other people they shriveled up more or less", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0027.flac", "answer": "I CANNOT DENY MYSELF THE GRATIFICATION OF INSERTING SOUTHEY'S REPLY", "subset": "test_clean", "task_type": "understanding", "prediction": "i cannot deny myself the gratification of inserting so these reply", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0043.flac", "answer": "HOWEVER REMEMBERING WHAT YOU TOLD ME NAMELY THAT YOU HAD COMMENDED THE MATTER TO A HIGHER DECISION THAN OURS AND THAT YOU WERE RESOLVED TO SUBMIT WITH RESIGNATION TO THAT DECISION WHATEVER IT MIGHT BE I HOLD IT MY DUTY TO YIELD ALSO AND TO BE SILENT IT MAY BE ALL FOR THE BEST", "subset": "test_clean", "task_type": "understanding", "prediction": "however remembering what you told me namely that you had commended the matter to a higher decision than ours and that you were resolved to submit with resignation to that decision whatever it might be i hold it my duty to yield also and to be silent and may be all for the best", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0033.flac", "answer": "SATURDAY AFTER SATURDAY COMES ROUND AND I CAN HAVE NO HOPE OF HEARING YOUR KNOCK AT THE DOOR AND THEN BEING TOLD THAT MISS E IS COME OH DEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "saturday after saturday comes around and i can have no hope of hearing your knock at the door and then being told that missy is come oh dear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0007.flac", "answer": "HE SPOKE FRENCH PERFECTLY I HAVE BEEN TOLD WHEN NEED WAS BUT DELIGHTED USUALLY IN TALKING THE BROADEST YORKSHIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "he spoke french perfectly i have been told when need was but delighted usually in talking the broadest yorkshire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0053.flac", "answer": "BUT ANNE HAD BEGUN TO SUFFER JUST BEFORE THE HOLIDAYS AND CHARLOTTE WATCHED OVER HER YOUNGER SISTERS WITH THE JEALOUS VIGILANCE OF SOME WILD CREATURE THAT CHANGES HER VERY NATURE IF DANGER THREATENS HER YOUNG", "subset": "test_clean", "task_type": "understanding", "prediction": "but anne had begun to suffer just before the holidays and charlotte watched over her younger sisters with the jealous vigilance of some wild creature that changes her very nature if danger threatens her young", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0002.flac", "answer": "WHY ARE WE TO BE DIVIDED", "subset": "test_clean", "task_type": "understanding", "prediction": "why are we to be divided", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0015.flac", "answer": "BUT DO NOT SUPPOSE THAT I DISPARAGE THE GIFT WHICH YOU POSSESS NOR THAT I WOULD DISCOURAGE YOU FROM EXERCISING IT I ONLY EXHORT YOU SO TO THINK OF IT AND SO TO USE IT AS TO RENDER IT CONDUCIVE TO YOUR OWN PERMANENT GOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "but do not suppose that i disparage the gift which you possess nor that i would discourage you from exercising it i only exhort you so to think of it and so to use it as to render it conducive to your own permanent good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0046.flac", "answer": "A GOOD NEIGHBOUR OF THE BRONTES A CLEVER INTELLIGENT YORKSHIRE WOMAN WHO KEEPS A DRUGGIST'S SHOP IN HAWORTH AND FROM HER OCCUPATION HER EXPERIENCE AND EXCELLENT SENSE HOLDS THE POSITION OF VILLAGE DOCTRESS AND NURSE AND AS SUCH HAS BEEN A FRIEND IN MANY A TIME OF TRIAL AND SICKNESS AND DEATH IN THE HOUSEHOLDS ROUND TOLD ME A CHARACTERISTIC LITTLE INCIDENT CONNECTED WITH TABBY'S FRACTURED LEG", "subset": "test_clean", "task_type": "understanding", "prediction": "a good neighbour of the brontes a clever intelligent yorkshire woman who keeps a druggist shop in haworth and from her occupation her excellent sense holds the position of village doctress and nurse and as such has been a friend in many a time of trial and sickness and death in the households round told me a characteristic little incident connected with tabby s fractured leg", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0022.flac", "answer": "IN THE EVENINGS I CONFESS I DO THINK BUT I NEVER TROUBLE ANY ONE ELSE WITH MY THOUGHTS", "subset": "test_clean", "task_type": "understanding", "prediction": "in the evenings i confess i do think but i never trouble anyone else with my thoughts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0012.flac", "answer": "YOU WILL SAY THAT A WOMAN HAS NO NEED OF SUCH A CAUTION THERE CAN BE NO PERIL IN IT FOR HER", "subset": "test_clean", "task_type": "understanding", "prediction": "you will say that a woman has no need of such a caution there can be no peril in it for her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0021.flac", "answer": "I THOUGHT IT THEREFORE MY DUTY WHEN I LEFT SCHOOL TO BECOME A GOVERNESS", "subset": "test_clean", "task_type": "understanding", "prediction": "i thought it therefore my duty when i left school to become a governess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0011.flac", "answer": "BUT IT IS NOT WITH A VIEW TO DISTINCTION THAT YOU SHOULD CULTIVATE THIS TALENT IF YOU CONSULT YOUR OWN HAPPINESS", "subset": "test_clean", "task_type": "understanding", "prediction": "but it is not with a view to distinction that you should cultivate this talent if you consult your own happiness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0023.flac", "answer": "I CAREFULLY AVOID ANY APPEARANCE OF PREOCCUPATION AND ECCENTRICITY WHICH MIGHT LEAD THOSE I LIVE AMONGST TO SUSPECT THE NATURE OF MY PURSUITS", "subset": "test_clean", "task_type": "understanding", "prediction": "i carefully avoid any appearance of preoccupation and eccentricity which might lead those i live amongst to suspect the nature of my pursuits", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0020.flac", "answer": "I KNOW THE FIRST LETTER I WROTE TO YOU WAS ALL SENSELESS TRASH FROM BEGINNING TO END BUT I AM NOT ALTOGETHER THE IDLE DREAMING BEING IT WOULD SEEM TO DENOTE", "subset": "test_clean", "task_type": "understanding", "prediction": "i know the first letter i wrote to you was all senseless trash from beginning to end but i am not altogether the idle dreaming being it would seem to denote", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0025.flac", "answer": "AGAIN I THANK YOU THIS INCIDENT I SUPPOSE WILL BE RENEWED NO MORE IF I LIVE TO BE AN OLD WOMAN I SHALL REMEMBER IT THIRTY YEARS HENCE AS A BRIGHT DREAM", "subset": "test_clean", "task_type": "understanding", "prediction": "again i thank you this incident i suppose will be renewed no more if i live to be an old woman i shall remember it thirty years hence as a bright dream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0037.flac", "answer": "IF CHRISTIAN PERFECTION BE NECESSARY TO SALVATION I SHALL NEVER BE SAVED MY HEART IS A VERY HOTBED FOR SINFUL THOUGHTS AND WHEN I DECIDE ON AN ACTION I SCARCELY REMEMBER TO LOOK TO MY REDEEMER FOR DIRECTION", "subset": "test_clean", "task_type": "understanding", "prediction": "if christian perfection be necessary to salvation i shall never be saved my heart is a very hotbed for sinful thoughts and when i decide on an action i scarcely remember to look to my redeemer for direction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0045.flac", "answer": "I AM NOT GOOD ENOUGH FOR YOU AND YOU MUST BE KEPT FROM THE CONTAMINATION OF TOO INTIMATE SOCIETY", "subset": "test_clean", "task_type": "understanding", "prediction": "i am not good enough for you and you must be kept from the contamination of too intimate society", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0001.flac", "answer": "WHY ARE WE TO BE DENIED EACH OTHER'S SOCIETY", "subset": "test_clean", "task_type": "understanding", "prediction": "why are we to be denied each others society", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0041.flac", "answer": "SHE WAS GONE OUT INTO THE VILLAGE ON SOME ERRAND WHEN AS SHE WAS DESCENDING THE STEEP STREET HER FOOT SLIPPED ON THE ICE AND SHE FELL IT WAS DARK AND NO ONE SAW HER MISCHANCE TILL AFTER A TIME HER GROANS ATTRACTED THE ATTENTION OF A PASSER BY", "subset": "test_clean", "task_type": "understanding", "prediction": "she was gone out into the village on some errand when as she was descending the steep street her foot slipped on the ice and she fell it was dark and no one saw her mischance till after a time her groans attracted the attention of a passer by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0028.flac", "answer": "KESWICK MARCH TWENTY SECOND EIGHTEEN THIRTY SEVEN DEAR MADAM", "subset": "test_clean", "task_type": "understanding", "prediction": "keswick march twenty second eighteen thirty seven dear madam", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0055.flac", "answer": "STILL HER HEART HAD RECEIVED A SHOCK IN THE PERCEPTION OF ANNE'S DELICACY AND ALL THESE HOLIDAYS SHE WATCHED OVER HER WITH THE LONGING FOND ANXIETY WHICH IS SO FULL OF SUDDEN PANGS OF FEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "still her heart had received a shock in the perception of anne s delicacy and all these holidays she watched over her with the longing fond anxiety which is so full of sudden pangs of fear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0040.flac", "answer": "INDEED THERE WERE ONLY ONE OR TWO STRANGERS WHO COULD BE ADMITTED AMONG THE SISTERS WITHOUT PRODUCING THE SAME RESULT", "subset": "test_clean", "task_type": "understanding", "prediction": "indeed there were only one or two strangers who could be admitted among the sisters without producing the same result", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0009.flac", "answer": "JANUARY AND FEBRUARY OF EIGHTEEN THIRTY SEVEN HAD PASSED AWAY AND STILL THERE WAS NO REPLY FROM SOUTHEY", "subset": "test_clean", "task_type": "understanding", "prediction": "january and february of eighteen thirty seven had passed away and still there was no reply from southey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0047.flac", "answer": "TABBY HAD LIVED WITH THEM FOR TEN OR TWELVE YEARS AND WAS AS CHARLOTTE EXPRESSED IT ONE OF THE FAMILY", "subset": "test_clean", "task_type": "understanding", "prediction": "tabby had lived with them for ten or twelve years and was as charlotte expressed it one of the family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0049.flac", "answer": "THIS DECISION WAS COMMUNICATED TO THE GIRLS", "subset": "test_clean", "task_type": "understanding", "prediction": "this decision was communicated to the girls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0044.flac", "answer": "AFTER THIS DISAPPOINTMENT I NEVER DARE RECKON WITH CERTAINTY ON THE ENJOYMENT OF A PLEASURE AGAIN IT SEEMS AS IF SOME FATALITY STOOD BETWEEN YOU AND ME", "subset": "test_clean", "task_type": "understanding", "prediction": "after this disappointment i never dare reckon with certainty on the enjoyment of a pleasure again it seems as if some fatality stood between you and me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0034.flac", "answer": "IN THIS MONOTONOUS LIFE OF MINE THAT WAS A PLEASANT EVENT", "subset": "test_clean", "task_type": "understanding", "prediction": "in this monotonous life of mine that was a pleasant event", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0000.flac", "answer": "AND OFTEN HAS MY MOTHER SAID WHILE ON HER LAP I LAID MY HEAD SHE FEARED FOR TIME I WAS NOT MADE BUT FOR ETERNITY", "subset": "test_clean", "task_type": "understanding", "prediction": "and often has my mother said while on her lap i laid my head she feared for time i was not made but for eternity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0013.flac", "answer": "THE MORE SHE IS ENGAGED IN HER PROPER DUTIES THE LESS LEISURE WILL SHE HAVE FOR IT EVEN AS AN ACCOMPLISHMENT AND A RECREATION", "subset": "test_clean", "task_type": "understanding", "prediction": "the more she is engaged in her proper duties the less leisure will she have for it even as an accomplishment and a recreation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0048.flac", "answer": "HE REFUSED AT FIRST TO LISTEN TO THE CAREFUL ADVICE IT WAS REPUGNANT TO HIS LIBERAL NATURE", "subset": "test_clean", "task_type": "understanding", "prediction": "he refused at first to listen to the careful advice it was repugnant to his liberal nature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0031.flac", "answer": "ON AUGUST TWENTY SEVENTH EIGHTEEN THIRTY SEVEN SHE WRITES", "subset": "test_clean", "task_type": "understanding", "prediction": "on august twenty seventh eighteen thirty seven she writes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0030.flac", "answer": "OF THIS SECOND LETTER ALSO SHE SPOKE AND TOLD ME THAT IT CONTAINED AN INVITATION FOR HER TO GO AND SEE THE POET IF EVER SHE VISITED THE LAKES", "subset": "test_clean", "task_type": "understanding", "prediction": "of this second letter also she spoke and told me that it contained an invitation for her to go and see the poet if ever she visited the lakes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0029.flac", "answer": "YOUR LETTER HAS GIVEN ME GREAT PLEASURE AND I SHOULD NOT FORGIVE MYSELF IF I DID NOT TELL YOU SO", "subset": "test_clean", "task_type": "understanding", "prediction": "your letter has given me great pleasure and i should not forgive myself if i did not tell you so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0051.flac", "answer": "AT TEA TIME THEY WERE SAD AND SILENT AND THE MEAL WENT AWAY UNTOUCHED BY ANY OF THE THREE", "subset": "test_clean", "task_type": "understanding", "prediction": "at tea time they were sad and silent and the meal went away untouched by any of the three", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0018.flac", "answer": "SIR MARCH SIXTEENTH", "subset": "test_clean", "task_type": "understanding", "prediction": "sir march sixteenth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0024.flac", "answer": "I DON'T ALWAYS SUCCEED FOR SOMETIMES WHEN I'M TEACHING OR SEWING I WOULD RATHER BE READING OR WRITING BUT I TRY TO DENY MYSELF AND MY FATHER'S APPROBATION AMPLY REWARDED ME FOR THE PRIVATION", "subset": "test_clean", "task_type": "understanding", "prediction": "i don always succeed for sometimes when i am teaching or sewing i would rather be reading or writing but i try to deny myself and my father s approbation amply rewarded me for the privation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0004.flac", "answer": "WE USED TO DISPUTE ABOUT POLITICS AND RELIGION", "subset": "test_clean", "task_type": "understanding", "prediction": "we used to dispute about politics and religion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0050.flac", "answer": "TABBY HAD TENDED THEM IN THEIR CHILDHOOD THEY AND NONE OTHER SHOULD TEND HER IN HER INFIRMITY AND AGE", "subset": "test_clean", "task_type": "understanding", "prediction": "tabby had tended them in their childhood they and none other should tend her in her infirmity and age", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0005.flac", "answer": "SHE A TORY AND CLERGYMAN'S DAUGHTER WAS ALWAYS IN A MINORITY OF ONE IN OUR HOUSE OF VIOLENT DISSENT AND RADICALISM", "subset": "test_clean", "task_type": "understanding", "prediction": "she a tory and clergyman s daughter was always in a minority of one in our house of violent dissent and radicalism", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3575/170457/3575-170457-0054.flac", "answer": "STUNG BY ANXIETY FOR THIS LITTLE SISTER SHE UPBRAIDED MISS W FOR HER FANCIED INDIFFERENCE TO ANNE'S STATE OF HEALTH", "subset": "test_clean", "task_type": "understanding", "prediction": "stung by anxiety for this little sister she upbraided miss w for her fancied indifference to anne s state of health", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0040.flac", "answer": "IN THIS WAY THE FETE OF THE WHOLE COURT WAS A FETE ALSO FOR THE MYSTERIOUS INHABITANTS OF THE FOREST FOR CERTAINLY THE DEER IN THE BRAKE THE PHEASANT ON THE BRANCH THE FOX IN ITS HOLE WERE ALL LISTENING", "subset": "test_clean", "task_type": "understanding", "prediction": "in this way the fete of the whole court was a fete also for the mysterious inhabitants of the forest for certainly the deer in the brake the pheasant on the branch the fox in its hole were all listening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0010.flac", "answer": "WHEN SHE PERCEIVED THE YOUNG MAN SHE ROSE LIKE A WOMAN SURPRISED IN THE MIDST OF IDEAS SHE WAS DESIROUS OF CONCEALING FROM HERSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "when she perceived the young man she rose like a woman surprised in the midst of ideas she was desirous of concealing from herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0017.flac", "answer": "WHAT ALREADY HERE THEY SAID TO HER", "subset": "test_clean", "task_type": "understanding", "prediction": "what already here they said to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0036.flac", "answer": "I GIVE MY CONSENT", "subset": "test_clean", "task_type": "understanding", "prediction": "i give my consent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0039.flac", "answer": "IN FACT THE SOUND OF MADAME'S AND THE QUEEN'S CARRIAGES COULD BE HEARD IN THE DISTANCE UPON THE HARD DRY GROUND OF THE ROADS FOLLOWED BY THE MOUNTED CAVALIERS", "subset": "test_clean", "task_type": "understanding", "prediction": "in fact the sound of madame s and the queen s carriages could be heard in the distance upon the hard dry ground of the roads followed by the mountain cavaliers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0032.flac", "answer": "YES BUT PERHAPS I FRIGHTENED HER IN WHAT WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "yes but perhaps i frightened her in what way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0025.flac", "answer": "EXQUISITE SOFT TURF OF THE WOODS THE HAPPINESS WHICH YOUR FRIENDSHIP CONFERS UPON ME", "subset": "test_clean", "task_type": "understanding", "prediction": "exquisite soft turf of the woods the happiness which your friendship confers upon me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0022.flac", "answer": "I AM A WOMAN AND THERE ARE FEW LIKE ME WHOEVER LOVES ME FLATTERS ME WHOEVER FLATTERS ME PLEASES ME AND WHOEVER PLEASES WELL SAID MONTALAIS YOU DO NOT FINISH", "subset": "test_clean", "task_type": "understanding", "prediction": "i am a woman and there are few like me whoever loves me flatters me whoever flatters me pleases me and whoever pleases well said montalais you do not finish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0008.flac", "answer": "THE ARROW PIERCED HIS HEART AND WOUNDED HIM MORTALLY", "subset": "test_clean", "task_type": "understanding", "prediction": "the arrow pierced his heart and wounded him mortally", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0037.flac", "answer": "OH I AM SPEAKING SERIOUSLY REPLIED MONTALAIS AND MY OPINION IN THIS CASE IS QUITE AS GOOD AS THE KING'S I SUPPOSE IS IT NOT LOUISE", "subset": "test_clean", "task_type": "understanding", "prediction": "oh i am speaking seriously replied montalais and my opinion in this case is quite as good as the king s i suppose is it not louise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0020.flac", "answer": "NO MORE THAN THE DANCING", "subset": "test_clean", "task_type": "understanding", "prediction": "no more than the dancing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0031.flac", "answer": "YOU ARE POSITIVE THEN", "subset": "test_clean", "task_type": "understanding", "prediction": "you are positive then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0018.flac", "answer": "I HAVE BEEN HERE THIS QUARTER OF AN HOUR REPLIED LA VALLIERE", "subset": "test_clean", "task_type": "understanding", "prediction": "i have been here this quarter of an hour replied lavalier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0021.flac", "answer": "LA VALLIERE IS QUITE A POETESS SAID TONNAY CHARENTE", "subset": "test_clean", "task_type": "understanding", "prediction": "lavalier is quite a poetess said tonie charente", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0030.flac", "answer": "SHE WAS HERE JUST NOW SAID THE COUNT", "subset": "test_clean", "task_type": "understanding", "prediction": "she was here just now said the count", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0035.flac", "answer": "GOOD GRACIOUS HAS THE KING ANY RIGHT TO INTERFERE IN MATTERS OF THAT KIND", "subset": "test_clean", "task_type": "understanding", "prediction": "good gracious has the king any right to interfere in matters of that kind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0027.flac", "answer": "TO SAY NOTHING SAID MONTALAIS SO THAT WHEN MADEMOISELLE DE TONNAY CHARENTE THINKS ATHENAIS IS THE ONLY ONE WHO KNOWS IT", "subset": "test_clean", "task_type": "understanding", "prediction": "to say nothing said montalais so that when mademoiselle d etonay charenton thinks ethan a is the only one who knows it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0016.flac", "answer": "OH MADEMOISELLE WHY HAVE I NOT A DEVOTED SISTER OR A TRUE FRIEND SUCH AS YOURSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "oh mademoiselle why have i not a devoted sister or a true friend such as yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0034.flac", "answer": "IT SEEMS THE KING WILL NOT CONSENT TO IT", "subset": "test_clean", "task_type": "understanding", "prediction": "it seems the king will not consent to it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0011.flac", "answer": "REMAIN I IMPLORE YOU THE EVENING IS MOST LOVELY", "subset": "test_clean", "task_type": "understanding", "prediction": "remain i implore you the evening is most lovely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0004.flac", "answer": "EXPLAIN YOURSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "explain yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0000.flac", "answer": "EVERY ONE COULD OBSERVE HIS AGITATION AND PROSTRATION A PROSTRATION WHICH WAS INDEED THE MORE REMARKABLE SINCE PEOPLE WERE NOT ACCUSTOMED TO SEE HIM WITH HIS ARMS HANGING LISTLESSLY BY HIS SIDE HIS HEAD BEWILDERED AND HIS EYES WITH ALL THEIR BRIGHT INTELLIGENCE BEDIMMED", "subset": "test_clean", "task_type": "understanding", "prediction": "every one could observe his agitation and prostration a prostration which was indeed the more remarkable since people were not accustomed to see him with his arms hanging listlessly by his side his head bewildered and his eyes with all their bright intelligence bedimmed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0029.flac", "answer": "THE YOUNG GIRLS HAD INDEED MADE THEMSELVES SMALL INDEED INVISIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "the young girls had indeed made themselves small indeed invisible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0038.flac", "answer": "LET US RUN THEN SAID ALL THREE AND GRACEFULLY LIFTING UP THE LONG SKIRTS OF THEIR SILK DRESSES THEY LIGHTLY RAN ACROSS THE OPEN SPACE BETWEEN THE LAKE AND THE THICKEST COVERT OF THE PARK", "subset": "test_clean", "task_type": "understanding", "prediction": "let us run then said all three and gracefully lifting up the long skirts of their silk dresses they lightly ran across the open space between the lake and the thickest covert of the park", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0002.flac", "answer": "DO YOU THINK SO SHE REPLIED WITH INDIFFERENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "do you think so she replied with indifference", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0006.flac", "answer": "THE PRINCESS INQUIRED NO", "subset": "test_clean", "task_type": "understanding", "prediction": "the princess inquired no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0001.flac", "answer": "UPON THIS MADAME DEIGNED TO TURN HER EYES LANGUISHINGLY TOWARDS THE COMTE OBSERVING", "subset": "test_clean", "task_type": "understanding", "prediction": "upon this madame deigned to turn her eyes languishingly towards the comte observing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0028.flac", "answer": "QUICK QUICK THEN AMONG THE HIGH REED GRASS SAID MONTALAIS STOOP ATHENAIS YOU ARE SO TALL", "subset": "test_clean", "task_type": "understanding", "prediction": "quick quick then among the high reed grass said montalais stoop athene you are so tall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0005.flac", "answer": "I ALLUDE TO THE GODDESS", "subset": "test_clean", "task_type": "understanding", "prediction": "i allude to the goddess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0007.flac", "answer": "SHE THEN ROSE HUMMING THE AIR TO WHICH SHE WAS PRESENTLY GOING TO DANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "she then rose humming the air to which she was presently going to dance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0026.flac", "answer": "WELL SAID MADEMOISELLE DE TONNAY CHARENTE I ALSO THINK A GOOD DEAL BUT I TAKE CARE", "subset": "test_clean", "task_type": "understanding", "prediction": "well said mademoiselle dittonechellante i also think a good deal but i take care", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0013.flac", "answer": "I REMEMBER NOW AND I CONGRATULATE MYSELF DO YOU LOVE ANY ONE", "subset": "test_clean", "task_type": "understanding", "prediction": "i remember now and i congratulate myself do you love any one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0023.flac", "answer": "IT IS TOO DIFFICULT REPLIED MADEMOISELLE DE TONNAY CHARENTE LAUGHING LOUDLY", "subset": "test_clean", "task_type": "understanding", "prediction": "it is too difficult replied mademoiselle dethune charente laughing loudly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0003.flac", "answer": "YES THE CHARACTER WHICH YOUR ROYAL HIGHNESS ASSUMED IS IN PERFECT HARMONY WITH YOUR OWN", "subset": "test_clean", "task_type": "understanding", "prediction": "yes the character which your royal highness assumed is in perfect harmony with your own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0015.flac", "answer": "THERE CANNOT BE A DOUBT HE RECEIVED YOU KINDLY FOR IN FACT YOU RETURNED WITHOUT HIS PERMISSION", "subset": "test_clean", "task_type": "understanding", "prediction": "there cannot be a doubt he received you kindly for in fact you returned without his permission", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0014.flac", "answer": "FORGIVE ME I HARDLY KNOW WHAT I AM SAYING A THOUSAND TIMES FORGIVE ME MADAME WAS RIGHT QUITE RIGHT THIS BRUTAL EXILE HAS COMPLETELY TURNED MY BRAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "forgive me i hardly know what i am saying a thousand times forgive me madame was right quite right this brutal exile has completely turned my brain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0033.flac", "answer": "HOW IS IT LA VALLIERE SAID MADEMOISELLE DE TONNAY CHARENTE THAT THE VICOMTE DE BRAGELONNE SPOKE OF YOU AS LOUISE", "subset": "test_clean", "task_type": "understanding", "prediction": "how is it la valliere said mademoiselle de tencin that the vicomte de bragelonne spoke of you as louise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0012.flac", "answer": "INDEED AH", "subset": "test_clean", "task_type": "understanding", "prediction": "indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0019.flac", "answer": "DID NOT THE DANCING AMUSE YOU NO", "subset": "test_clean", "task_type": "understanding", "prediction": "did not the dancing amuse you no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0024.flac", "answer": "LOOK YONDER DO YOU NOT SEE THE MOON SLOWLY RISING SILVERING THE TOPMOST BRANCHES OF THE CHESTNUTS AND THE OAKS", "subset": "test_clean", "task_type": "understanding", "prediction": "look yonder do you not see the moon slowly rising silvering the topmost branches of the chestnuts and the oaks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75947/7127-75947-0009.flac", "answer": "A QUARTER OF AN HOUR AFTERWARDS HE RETURNED TO THE THEATER BUT IT WILL BE READILY BELIEVED THAT IT WAS ONLY A POWERFUL EFFORT OF REASON OVER HIS GREAT EXCITEMENT THAT ENABLED HIM TO GO BACK OR PERHAPS FOR LOVE IS THUS STRANGELY CONSTITUTED HE FOUND IT IMPOSSIBLE EVEN TO REMAIN MUCH LONGER SEPARATED FROM THE PRESENCE OF ONE WHO HAD BROKEN HIS HEART", "subset": "test_clean", "task_type": "understanding", "prediction": "a quarter of an hour afterwards he returned to the theatre but it will be readily believed that it was only a powerful effort of reason over his great excitement that enabled him to go back or perhaps for love is thus strangely constituted he found it impossible even to remain much longer separated from the presence of one who had broken his heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0019.flac", "answer": "YES IT IS SUPPRESSED", "subset": "test_clean", "task_type": "understanding", "prediction": "yes it is suppressed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0016.flac", "answer": "THE SEASONS ALLIES OF SPRING FOLLOWED HIM CLOSELY TO FORM A QUADRILLE WHICH AFTER MANY WORDS OF MORE OR LESS FLATTERING IMPORT WAS THE COMMENCEMENT OF THE DANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "the seasons allies of spring followed him closely to form a quadrille which after many words of more or less flattering import was the commencement of the dance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0018.flac", "answer": "THERE WAS SOMETHING IN HIS CARRIAGE WHICH RESEMBLED THE BUOYANT MOVEMENTS OF AN IMMORTAL AND HE DID NOT DANCE SO MUCH AS SEEM TO SOAR ALONG", "subset": "test_clean", "task_type": "understanding", "prediction": "there was something in his carriage which resembled the buoyant movements of an immortal and he did not dance so much as seemed to soar along", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0003.flac", "answer": "GENTLEMEN TO YOUR POSTS WHEREUPON SAINT AIGNAN AND VILLEROY TOOK THEIR LEAVE", "subset": "test_clean", "task_type": "understanding", "prediction": "gentlemen to your posts whereupon saint aignan and villeroy took their leave", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0009.flac", "answer": "NOT AT ALL YOU ARE ON THE CONTRARY MOST AGREEABLE TO ME", "subset": "test_clean", "task_type": "understanding", "prediction": "not at all you are on the contrary most agreeable to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0010.flac", "answer": "YOUR MAJESTY'S PLAN THEN IN THIS AFFAIR IS", "subset": "test_clean", "task_type": "understanding", "prediction": "your majesty s plan then in this affair is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0023.flac", "answer": "THE KING SEEMED ONLY PLEASED WITH EVERY ONE PRESENT", "subset": "test_clean", "task_type": "understanding", "prediction": "the king seemed only pleased with every one present", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0013.flac", "answer": "THE KING HAD COMPLETED HIS TOILETTE BY NINE O'CLOCK HE APPEARED IN AN OPEN CARRIAGE DECORATED WITH BRANCHES OF TREES AND FLOWERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the king had completed his toilet by nine o clock he appeared in an open carriage decorated with branches of trees and flowers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0007.flac", "answer": "IT IS NECESSARY THEREFORE THAT HE SHOULD COMPLY THE KING FROWNED", "subset": "test_clean", "task_type": "understanding", "prediction": "it is necessary therefore that he should comply the king frowned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0004.flac", "answer": "CERTAINLY SIRE BUT I MUST HAVE MONEY TO DO THAT WHAT", "subset": "test_clean", "task_type": "understanding", "prediction": "certainly sire but i must have money to do that what", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0020.flac", "answer": "FAR FROM IT SIRE YOUR MAJESTY HAVING GIVEN NO DIRECTIONS ABOUT IT THE MUSICIANS HAVE RETAINED IT", "subset": "test_clean", "task_type": "understanding", "prediction": "far from it sire your majesty having given no directions about it the musicians have retained it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0024.flac", "answer": "MONSIEUR WAS THE ONLY ONE WHO DID NOT UNDERSTAND ANYTHING ABOUT THE MATTER", "subset": "test_clean", "task_type": "understanding", "prediction": "monsieur was the only one who did not understand anything about the matter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0000.flac", "answer": "AT THE CONCLUSION OF THE BANQUET WHICH WAS SERVED AT FIVE O'CLOCK THE KING ENTERED HIS CABINET WHERE HIS TAILORS WERE AWAITING HIM FOR THE PURPOSE OF TRYING ON THE CELEBRATED COSTUME REPRESENTING SPRING WHICH WAS THE RESULT OF SO MUCH IMAGINATION AND HAD COST SO MANY EFFORTS OF THOUGHT TO THE DESIGNERS AND ORNAMENT WORKERS OF THE COURT", "subset": "test_clean", "task_type": "understanding", "prediction": "at the conclusion of the banquet which was served at five o clock the king entered his cabinet where his tailors were awaiting him for the purpose of trying on the celebrated costume representing spring which was the result of so much imagination and had cost so many efforts of thought to the designers and ornament workers of the court", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0011.flac", "answer": "YOU WILL TAKE THEM FROM MY PRIVATE TREASURE", "subset": "test_clean", "task_type": "understanding", "prediction": "you will take them from my private treasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0001.flac", "answer": "AH VERY WELL", "subset": "test_clean", "task_type": "understanding", "prediction": "ah very well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0027.flac", "answer": "DISDAINFUL OF A SUCCESS OF WHICH MADAME SHOWED NO ACKNOWLEDGEMENT HE THOUGHT OF NOTHING BUT BOLDLY REGAINING THE MARKED PREFERENCE OF THE PRINCESS", "subset": "test_clean", "task_type": "understanding", "prediction": "disdainful of a success of which madame showed no acknowledgment he thought of nothing but boldly regaining the marked preference of the princess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0026.flac", "answer": "WHEN THE MUSIC BY ITS BURSTS OF MELODY CARRIED AWAY THESE ILLUSTRIOUS DANCERS WHEN THE SIMPLE UNTUTORED PANTOMIME OF THAT PERIOD ONLY THE MORE NATURAL ON ACCOUNT OF THE VERY INDIFFERENT ACTING OF THE AUGUST ACTORS HAD REACHED ITS CULMINATING POINT OF TRIUMPH THE THEATER SHOOK WITH TUMULTUOUS APPLAUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "when the music by its bursts of melody carried away these illustrious dancers when the simple untutored pantomime of that period only the more natural on account of the very indifferent acting of the august actors had reached its culminating point of triumph the theatre shook with tumultuous applause", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0006.flac", "answer": "HE HAS GIVEN THEM WITH TOO MUCH GRACE NOT TO HAVE OTHERS STILL TO GIVE IF THEY ARE REQUIRED WHICH IS THE CASE AT THE PRESENT MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "he has given them with too much grace not to have others still to give if they are required which is the case at the present moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0021.flac", "answer": "YES SIRE AND READY DRESSED FOR THE BALLET", "subset": "test_clean", "task_type": "understanding", "prediction": "yes sire and ready dressed for the ballet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0008.flac", "answer": "DOES YOUR MAJESTY THEN NO LONGER BELIEVE THE DISLOYAL ATTEMPT", "subset": "test_clean", "task_type": "understanding", "prediction": "does your majesty then no longer believe the disloyal attempt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0017.flac", "answer": "HIS LEGS THE BEST SHAPED AT COURT WERE DISPLAYED TO GREAT ADVANTAGE IN FLESH COLORED SILKEN HOSE OF SILK SO FINE AND SO TRANSPARENT THAT IT SEEMED ALMOST LIKE FLESH ITSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "his legs the best shaped at court were displayed to great advantage in flesh colored silken hose of silk so fine and so transparent that it seemed almost like flesh itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0015.flac", "answer": "SUDDENLY FOR THE PURPOSE OF RESTORING PEACE AND ORDER SPRING ACCOMPANIED BY HIS WHOLE COURT MADE HIS APPEARANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "suddenly for the purpose of restoring peace and order spurring accompanied by his whole court made his appearance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0002.flac", "answer": "LET HIM COME IN THEN SAID THE KING AND AS IF COLBERT HAD BEEN LISTENING AT THE DOOR FOR THE PURPOSE OF KEEPING HIMSELF AU COURANT WITH THE CONVERSATION HE ENTERED AS SOON AS THE KING HAD PRONOUNCED HIS NAME TO THE TWO COURTIERS", "subset": "test_clean", "task_type": "understanding", "prediction": "let him come in then said the king and as if colbert had been listening at the door for the purpose of keeping himself au courant with the conversation he entered as soon as the king had pronounced his name to the two courtiers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0022.flac", "answer": "SIRE HE SAID YOUR MAJESTY'S MOST DEVOTED SERVANT APPROACHES TO PERFORM A SERVICE ON THIS OCCASION WITH SIMILAR ZEAL THAT HE HAS ALREADY SHOWN ON THE FIELD OF BATTLE", "subset": "test_clean", "task_type": "understanding", "prediction": "sire he said your majesty s most devoted servant approaches to perform a service on this occasion with similar zeal that he has already shown on the field of battle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0014.flac", "answer": "THE QUEENS HAD TAKEN THEIR SEATS UPON A MAGNIFICENT DIAS OR PLATFORM ERECTED UPON THE BORDERS OF THE LAKE IN A THEATER OF WONDERFUL ELEGANCE OF CONSTRUCTION", "subset": "test_clean", "task_type": "understanding", "prediction": "the queens had taken their seats upon a magnificent dais or platform erected upon the borders of the lake in a theatre of wonderful elegance of construction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0005.flac", "answer": "WHAT DO YOU MEAN INQUIRED LOUIS", "subset": "test_clean", "task_type": "understanding", "prediction": "what do you mean inquired louise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0012.flac", "answer": "THE NEWS CIRCULATED WITH THE RAPIDITY OF LIGHTNING DURING ITS PROGRESS IT KINDLED EVERY VARIETY OF COQUETRY DESIRE AND WILD AMBITION", "subset": "test_clean", "task_type": "understanding", "prediction": "the news circulated with the rapidity of lightning during its progress it kindled every variety of coquetry desire and wild ambition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0025.flac", "answer": "THE BALLET BEGAN THE EFFECT WAS MORE THAN BEAUTIFUL", "subset": "test_clean", "task_type": "understanding", "prediction": "the ballet began the effect was more than beautiful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0028.flac", "answer": "BY DEGREES ALL HIS HAPPINESS ALL HIS BRILLIANCY SUBSIDED INTO REGRET AND UNEASINESS SO THAT HIS LIMBS LOST THEIR POWER HIS ARMS HUNG HEAVILY BY HIS SIDES AND HIS HEAD DROOPED AS THOUGH HE WAS STUPEFIED", "subset": "test_clean", "task_type": "understanding", "prediction": "by degrees all his happiness all his brilliancy subsided into regret and uneasiness so that his limbs lost their power his arms hung heavily by his sides and his head drooped as though he was stupefied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7127/75946/7127-75946-0029.flac", "answer": "THE KING WHO HAD FROM THIS MOMENT BECOME IN REALITY THE PRINCIPAL DANCER IN THE QUADRILLE CAST A LOOK UPON HIS VANQUISHED RIVAL", "subset": "test_clean", "task_type": "understanding", "prediction": "the king who had from this moment become in reality the principal dancer in the quadrille cast a look upon his vanquished rival", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0036.flac", "answer": "A FURTHER STAGE IS RECOGNITION", "subset": "test_clean", "task_type": "understanding", "prediction": "a further stage is recognition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0034.flac", "answer": "WHENEVER THE SENSE OF FAMILIARITY OCCURS WITHOUT A DEFINITE OBJECT IT LEADS US TO SEARCH THE ENVIRONMENT UNTIL WE ARE SATISFIED THAT WE HAVE FOUND THE APPROPRIATE OBJECT WHICH LEADS US TO THE JUDGMENT THIS IS FAMILIAR", "subset": "test_clean", "task_type": "understanding", "prediction": "whenever the sense of familiarity occurs without a definite object it leads us to search the environment until we are satisfied that we have found the appropriate object which leads us to the judgment this is familiar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0024.flac", "answer": "THE FIRST OF OUR VAGUE BUT INDUBITABLE DATA IS THAT THERE IS KNOWLEDGE OF THE PAST", "subset": "test_clean", "task_type": "understanding", "prediction": "the first of our vague but indubitable data is that there is knowledge of the past", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0017.flac", "answer": "THERE MAY BE A SPECIFIC FEELING WHICH COULD BE CALLED THE FEELING OF PASTNESS ESPECIALLY WHERE IMMEDIATE MEMORY IS CONCERNED", "subset": "test_clean", "task_type": "understanding", "prediction": "there may be a specific feeling which could be called the feeling of pastness especially where immediate memory is concerned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0021.flac", "answer": "REMEMBERING HAS TO BE A PRESENT OCCURRENCE IN SOME WAY RESEMBLING OR RELATED TO WHAT IS REMEMBERED", "subset": "test_clean", "task_type": "understanding", "prediction": "remembering has to be a present occurrence in some way resembling or related to what is remembered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0040.flac", "answer": "THERE ARE HOWEVER SEVERAL POINTS IN WHICH SUCH AN ACCOUNT OF RECOGNITION IS INADEQUATE TO BEGIN WITH IT MIGHT SEEM AT FIRST SIGHT MORE CORRECT TO DEFINE RECOGNITION AS I HAVE SEEN THIS BEFORE THAN AS THIS HAS EXISTED BEFORE", "subset": "test_clean", "task_type": "understanding", "prediction": "there are however several points in which such an account of recognition is inadequate to begin with it might seem at first sight more correct to define recognition as i have seen this before than as this has existed before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0001.flac", "answer": "WHAT IS CALLED PERCEPTION DIFFERS FROM SENSATION BY THE FACT THAT THE SENSATIONAL INGREDIENTS BRING UP HABITUAL ASSOCIATES IMAGES AND EXPECTATIONS OF THEIR USUAL CORRELATES ALL OF WHICH ARE SUBJECTIVELY INDISTINGUISHABLE FROM THE SENSATION", "subset": "test_clean", "task_type": "understanding", "prediction": "what is called perception differs from sensation by the fact that the sensational ingredients bring up habitual associates images and expectations of their usual correlates all of which are subjectively indistinguishable from the sensation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0042.flac", "answer": "THUS IF I RECOGNIZE A THING THE OCCASION OF ITS PREVIOUS EXISTENCE IN VIRTUE OF WHICH I RECOGNIZE IT FORMS PART OF MY EXPERIENCE BY DEFINITION RECOGNITION WILL BE ONE OF THE MARKS BY WHICH MY EXPERIENCE IS SINGLED OUT FROM THE REST OF THE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "thus if i recognise a thing the occasion of its previous existence in virtue of which i recognise it forms part of my experience by definition recognition will be one of the marks by which my experience is singled out from the rest of the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0022.flac", "answer": "SOME POINTS MAY BE TAKEN AS FIXED AND SUCH AS ANY THEORY OF MEMORY MUST ARRIVE AT", "subset": "test_clean", "task_type": "understanding", "prediction": "some points may be taken as fixed and such as any theory of memory must arrive at", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0007.flac", "answer": "HABIT IS A CONCEPT INVOLVING THE OCCURRENCE OF SIMILAR EVENTS AT DIFFERENT TIMES IF THE BEHAVIOURIST FEELS CONFIDENT THAT THERE IS SUCH A PHENOMENON AS HABIT THAT CAN ONLY BE BECAUSE HE TRUSTS HIS MEMORY WHEN IT ASSURES HIM THAT THERE HAVE BEEN OTHER TIMES", "subset": "test_clean", "task_type": "understanding", "prediction": "habit is a concept involving the occurrence of similar events at different times if the behaviorist feels confident that there is such a phenomenon as habit that can only be because he trusts his memory when it assures him that there have been other times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0025.flac", "answer": "WE MIGHT PROVISIONALLY THOUGH PERHAPS NOT QUITE CORRECTLY DEFINE MEMORY AS THAT WAY OF KNOWING ABOUT THE PAST WHICH HAS NO ANALOGUE IN OUR KNOWLEDGE OF THE FUTURE SUCH A DEFINITION WOULD AT LEAST SERVE TO MARK THE PROBLEM WITH WHICH WE ARE CONCERNED THOUGH SOME EXPECTATIONS MAY DESERVE TO RANK WITH MEMORY AS REGARDS IMMEDIACY", "subset": "test_clean", "task_type": "understanding", "prediction": "we might provisionally though perhaps not quite correctly define memory as that way of knowing about the past which has no analogue in our knowledge of the future such a definition would at least serve to mark the problem with which we are concerned though some expectations may deserve to rank with memory as regards immediacy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0039.flac", "answer": "THIS KNOWLEDGE IS MEMORY IN ONE SENSE THOUGH IN ANOTHER IT IS NOT", "subset": "test_clean", "task_type": "understanding", "prediction": "this knowledge is memory in one sense though in another it is not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0018.flac", "answer": "THERE IS OF COURSE A DIFFERENCE BETWEEN KNOWING THE TEMPORAL RELATION OF A REMEMBERED EVENT TO THE PRESENT AND KNOWING THE TIME ORDER OF TWO REMEMBERED EVENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "there is of course a difference between knowing the temporal relation of a remembered event to the present and knowing the time order of two remembered events", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0020.flac", "answer": "IF WE HAD RETAINED THE SUBJECT OR ACT IN KNOWLEDGE THE WHOLE PROBLEM OF MEMORY WOULD HAVE BEEN COMPARATIVELY SIMPLE", "subset": "test_clean", "task_type": "understanding", "prediction": "if we had retained the subject or act in knowledge the whole problem of memory would have been comparatively simple", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0038.flac", "answer": "WE ARE OF COURSE IN FACT ABLE TO JUDGE WHEN WE RECOGNIZE AN OBJECT THAT WE HAVE SEEN IT BEFORE BUT THIS JUDGMENT IS SOMETHING OVER AND ABOVE RECOGNITION IN THIS FIRST SENSE AND MAY VERY PROBABLY BE IMPOSSIBLE TO ANIMALS THAT NEVERTHELESS HAVE THE EXPERIENCE OF RECOGNITION IN THIS FIRST SENSE OF THE WORD", "subset": "test_clean", "task_type": "understanding", "prediction": "we are of course in fact able to judge when we recognise an object that we have seen it before but this judgment is something over and above recognition in this first sense and may very probably be impossible to animals that nevertheless have the experience of recognition in this first sense of the word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0026.flac", "answer": "THIS DISTINCTION IS VITAL TO THE UNDERSTANDING OF MEMORY BUT IT IS NOT SO EASY TO CARRY OUT IN PRACTICE AS IT IS TO DRAW IN THEORY", "subset": "test_clean", "task_type": "understanding", "prediction": "this distinction is vital to the understanding of memory but it is not so easy to carry out in practice as it is to draw in theory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0027.flac", "answer": "A GRAMOPHONE BY THE HELP OF SUITABLE RECORDS MIGHT RELATE TO US THE INCIDENTS OF ITS PAST AND PEOPLE ARE NOT SO DIFFERENT FROM GRAMOPHONES AS THEY LIKE TO BELIEVE", "subset": "test_clean", "task_type": "understanding", "prediction": "a gramophone by the help of suitable records might relate to us the incidents of its past and people are not so different from gramophones as they like to believe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0019.flac", "answer": "IT WOULD SEEM THAT ONLY RATHER RECENT EVENTS CAN BE PLACED AT ALL ACCURATELY BY MEANS OF FEELINGS GIVING THEIR TEMPORAL RELATION TO THE PRESENT BUT IT IS CLEAR THAT SUCH FEELINGS MUST PLAY AN ESSENTIAL PART IN THE PROCESS OF DATING REMEMBERED EVENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "it would seem that only rather recent events can be placed at all accurately by means of feelings giving their temporal relation to the present but it is clear that such feelings must play an essential part in the process of dating remembered events", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0006.flac", "answer": "THE BEHAVIOURIST WHO ATTEMPTS TO MAKE PSYCHOLOGY A RECORD OF BEHAVIOUR HAS TO TRUST HIS MEMORY IN MAKING THE RECORD", "subset": "test_clean", "task_type": "understanding", "prediction": "the behaviorist who attempts to make psychology a record of behavior has to trust his memory in making the record", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0016.flac", "answer": "IN ACTUAL FACT THERE ARE DOUBTLESS VARIOUS FACTORS THAT CONCUR IN GIVING US THE FEELING OF GREATER OR LESS REMOTENESS IN SOME REMEMBERED EVENT", "subset": "test_clean", "task_type": "understanding", "prediction": "in actual fact there are doubtless various factors that concur in giving us the feeling of greater or less remoteness in some remembered event", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0032.flac", "answer": "IT IS THIS THAT IS OF INTEREST TO THEORY OF KNOWLEDGE", "subset": "test_clean", "task_type": "understanding", "prediction": "it is this that is adventurous to theory of knowledge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0037.flac", "answer": "RECOGNITION IN THIS SENSE DOES NOT NECESSARILY INVOLVE MORE THAN A HABIT OF ASSOCIATION THE KIND OF OBJECT WE ARE SEEING AT THE MOMENT IS ASSOCIATED WITH THE WORD CAT OR WITH AN AUDITORY IMAGE OF PURRING OR WHATEVER OTHER CHARACTERISTIC WE MAY HAPPEN TO RECOGNIZE IN THE CAT OF THE MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "recognition in this sense does not necessarily involve more than a habit of association the kind of object we are seeing at the moment is associated with the word cat or with an auditory image of purring or whatever other characteristic we may happen to recognise in the cat of the moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0015.flac", "answer": "THEY MUST HAVE SOME CHARACTERISTIC WHICH MAKES US REGARD THEM AS REFERRING TO MORE OR LESS REMOTE PORTIONS OF THE PAST", "subset": "test_clean", "task_type": "understanding", "prediction": "they must have some characteristic which makes us regard them as referring to more or less remote portions of the past", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0043.flac", "answer": "OF COURSE THE WORDS THIS HAS EXISTED BEFORE ARE A VERY INADEQUATE TRANSLATION OF WHAT ACTUALLY HAPPENS WHEN WE FORM A JUDGMENT OF RECOGNITION BUT THAT IS UNAVOIDABLE WORDS ARE FRAMED TO EXPRESS A LEVEL OF THOUGHT WHICH IS BY NO MEANS PRIMITIVE AND ARE QUITE INCAPABLE OF EXPRESSING SUCH AN ELEMENTARY OCCURRENCE AS RECOGNITION", "subset": "test_clean", "task_type": "understanding", "prediction": "of course the words this has existed before are a very inadequate translation of what actually happens when we form a judgment of recognition but that is unavoidable words are framed to express a level of thought which is by no means primitive and are quite incapable of expressing such an elementary occurrence as recognition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0013.flac", "answer": "IN AN IMAGE OF A WELL KNOWN FACE FOR EXAMPLE SOME PARTS MAY FEEL MORE FAMILIAR THAN OTHERS WHEN THIS HAPPENS WE HAVE MORE BELIEF IN THE ACCURACY OF THE FAMILIAR PARTS THAN IN THAT OF THE UNFAMILIAR PARTS", "subset": "test_clean", "task_type": "understanding", "prediction": "in an image of a well known face for example some parts may feel more familiar than others when this happens we have more belief in the accuracy of the familiar parts than in that of the unfamiliar parts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0010.flac", "answer": "WE SOMETIMES HAVE IMAGES THAT ARE BY NO MEANS PECULIARLY VAGUE WHICH YET WE DO NOT TRUST FOR EXAMPLE UNDER THE INFLUENCE OF FATIGUE WE MAY SEE A FRIEND'S FACE VIVIDLY AND CLEARLY BUT HORRIBLY DISTORTED", "subset": "test_clean", "task_type": "understanding", "prediction": "we sometimes have images that are by no means peculiarly vague which yet we do not trust for example under the influence of fatigue we may see a friend s face vividly and clearly but horribly distorted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0005.flac", "answer": "ALL THAT I AM DOING IS TO USE ITS LOGICAL TENABILITY AS A HELP IN THE ANALYSIS OF WHAT OCCURS WHEN WE REMEMBER", "subset": "test_clean", "task_type": "understanding", "prediction": "all that i am doing is to use its logical tenability as a help in the analysis of what occurs when we remember", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0035.flac", "answer": "THUS NO KNOWLEDGE AS TO THE PAST IS TO BE DERIVED FROM THE FEELING OF FAMILIARITY ALONE", "subset": "test_clean", "task_type": "understanding", "prediction": "thus no knowledge as to the past is to be derived from the feeling of familiarity alone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0029.flac", "answer": "THE FACT THAT A MAN CAN RECITE A POEM DOES NOT SHOW THAT HE REMEMBERS ANY PREVIOUS OCCASION ON WHICH HE HAS RECITED OR READ IT", "subset": "test_clean", "task_type": "understanding", "prediction": "the fact that a man can recite a poem does not show that he remembers any previous occasion on which he has recited or read it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0041.flac", "answer": "THE DEFINITION OF MY EXPERIENCE IS DIFFICULT BROADLY SPEAKING IT IS EVERYTHING THAT IS CONNECTED WITH WHAT I AM EXPERIENCING NOW BY CERTAIN LINKS OF WHICH THE VARIOUS FORMS OF MEMORY ARE AMONG THE MOST IMPORTANT", "subset": "test_clean", "task_type": "understanding", "prediction": "the definition of my experience is difficult broadly speaking it is everything that is connected with what i am experiencing now by certain links of which the various forms of memory are among the most important", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0012.flac", "answer": "FAMILIARITY IS A FEELING CAPABLE OF DEGREES", "subset": "test_clean", "task_type": "understanding", "prediction": "familiarity is a feeling capable of degrees", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0000.flac", "answer": "THE ANALYSIS OF KNOWLEDGE WILL OCCUPY US UNTIL THE END OF THE THIRTEENTH LECTURE AND IS THE MOST DIFFICULT PART OF OUR WHOLE ENTERPRISE", "subset": "test_clean", "task_type": "understanding", "prediction": "the analysis of knowledge will occupy us until the end of the thirteenth lecture and is the most difficult part of our whole enterprise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0008.flac", "answer": "BUT I DO NOT THINK SUCH AN INFERENCE IS WARRANTED", "subset": "test_clean", "task_type": "understanding", "prediction": "but i do not think such an inference is warranted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0003.flac", "answer": "AND WHAT SORT OF EVIDENCE IS LOGICALLY POSSIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "and what sort of evidence is logically possible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0030.flac", "answer": "SEMON'S TWO BOOKS MENTIONED IN AN EARLIER LECTURE DO NOT TOUCH KNOWLEDGE MEMORY AT ALL CLOSELY", "subset": "test_clean", "task_type": "understanding", "prediction": "simmons two books mentioned in an earlier lecture do not touch knowledge memory at all closely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0004.flac", "answer": "THERE IS NO LOGICAL IMPOSSIBILITY IN THE HYPOTHESIS THAT THE WORLD SPRANG INTO BEING FIVE MINUTES AGO EXACTLY AS IT THEN WAS WITH A POPULATION THAT REMEMBERED A WHOLLY UNREAL PAST", "subset": "test_clean", "task_type": "understanding", "prediction": "there is no logical impossibility in the hypothesis that the world sprang into being five minutes ago exactly as it then was with a population that remembered a wholly unreal past", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0031.flac", "answer": "THEY GIVE LAWS ACCORDING TO WHICH IMAGES OF PAST OCCURRENCES COME INTO OUR MINDS BUT DO NOT DISCUSS OUR BELIEF THAT THESE IMAGES REFER TO PAST OCCURRENCES WHICH IS WHAT CONSTITUTES KNOWLEDGE MEMORY", "subset": "test_clean", "task_type": "understanding", "prediction": "they give laws according to which images of past occurrences come into our minds but do not discuss our belief that these images refer to past occurrences which is what constitutes knowledge memory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0023.flac", "answer": "IN THIS CASE AS IN MOST OTHERS WHAT MAY BE TAKEN AS CERTAIN IN ADVANCE IS RATHER VAGUE", "subset": "test_clean", "task_type": "understanding", "prediction": "in this case as in most others what may be taken as certain in advance is rather vague", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0028.flac", "answer": "I CAN SET TO WORK NOW TO REMEMBER THINGS I NEVER REMEMBERED BEFORE SUCH AS WHAT I HAD TO EAT FOR BREAKFAST THIS MORNING AND IT CAN HARDLY BE WHOLLY HABIT THAT ENABLES ME TO DO THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "i can set to work now to remember things i never remembered before such as what i had to eat for breakfast this morning and it can hardly be wholly habit that enables me to do this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0033.flac", "answer": "IT IS BY NO MEANS ALWAYS RELIABLE ALMOST EVERYBODY HAS AT SOME TIME EXPERIENCED THE WELL KNOWN ILLUSION THAT ALL THAT IS HAPPENING NOW HAPPENED BEFORE AT SOME TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "it is by no means always reliable almost everybody has at some time experienced the well known illusion that all that is happening now happened before at some time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0014.flac", "answer": "I COME NOW TO THE OTHER CHARACTERISTIC WHICH MEMORY IMAGES MUST HAVE IN ORDER TO ACCOUNT FOR OUR KNOWLEDGE OF THE PAST", "subset": "test_clean", "task_type": "understanding", "prediction": "i come now to the other characteristic which memory images must have in order to account for our knowledge of the past", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0009.flac", "answer": "OUR CONFIDENCE OR LACK OF CONFIDENCE IN THE ACCURACY OF A MEMORY IMAGE MUST IN FUNDAMENTAL CASES BE BASED UPON A CHARACTERISTIC OF THE IMAGE ITSELF SINCE WE CANNOT EVOKE THE PAST BODILY AND COMPARE IT WITH THE PRESENT IMAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "our confidence or lack of confidence in the accuracy of a memory image must in fundamental cases be based upon a characteristic of the image itself since we cannot evoke the past bodily and compare it with the present image", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0002.flac", "answer": "WHETHER OR NOT THIS PRINCIPLE IS LIABLE TO EXCEPTIONS EVERYONE WOULD AGREE THAT IS HAS A BROAD MEASURE OF TRUTH THOUGH THE WORD EXACTLY MIGHT SEEM AN OVERSTATEMENT AND IT MIGHT SEEM MORE CORRECT TO SAY THAT IDEAS APPROXIMATELY REPRESENT IMPRESSIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "whether or not this principle is liable to exceptions every one would agree that it has a broad measure of truth though the word exactly might seem an overstatement and it might seem more correct to say that ideas approximately represent impressions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8230/279154/8230-279154-0011.flac", "answer": "SOME IMAGES LIKE SOME SENSATIONS FEEL VERY FAMILIAR WHILE OTHERS FEEL STRANGE", "subset": "test_clean", "task_type": "understanding", "prediction": "some images like some sensations feel very familiar while others feel strange", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0027.flac", "answer": "YET THAT TASK WAS NOT SO EASY AS YOU MAY SUPPOSE", "subset": "test_clean", "task_type": "understanding", "prediction": "yet that task was not so easy as you may suppose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0011.flac", "answer": "I AM MY DEAR AND ALL STRANGERS ARE WELCOME TO MY HOME", "subset": "test_clean", "task_type": "understanding", "prediction": "i am my dear and all strangers are welcome to my home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0000.flac", "answer": "HE WORE BLUE SILK STOCKINGS BLUE KNEE PANTS WITH GOLD BUCKLES A BLUE RUFFLED WAIST AND A JACKET OF BRIGHT BLUE BRAIDED WITH GOLD", "subset": "test_clean", "task_type": "understanding", "prediction": "he wore blue silk stockings blue knee pants with gold buckles a blue ruffled waist and a jacket of bright blue braided with gold", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0001.flac", "answer": "HIS HAT HAD A PEAKED CROWN AND A FLAT BRIM AND AROUND THE BRIM WAS A ROW OF TINY GOLDEN BELLS THAT TINKLED WHEN HE MOVED", "subset": "test_clean", "task_type": "understanding", "prediction": "his hat had a peaked crown and a flat brim and around the brim was a row of tiny golden bells that tinkled when he moved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0021.flac", "answer": "I THINK THE NEXT GLASS CAT THE MAGICIAN MAKES WILL HAVE NEITHER BRAINS NOR HEART FOR THEN IT WILL NOT OBJECT TO CATCHING MICE AND MAY PROVE OF SOME USE TO US", "subset": "test_clean", "task_type": "understanding", "prediction": "i think the next glass cat the magician makes will have neither brains nor heart for then it will not object to catching mice and may prove of some use to us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0010.flac", "answer": "UNC KNOCKED AT THE DOOR OF THE HOUSE AND A CHUBBY PLEASANT FACED WOMAN DRESSED ALL IN BLUE OPENED IT AND GREETED THE VISITORS WITH A SMILE", "subset": "test_clean", "task_type": "understanding", "prediction": "unk knocked at the door of the house and a chubby pleasant faced woman dressed all in blue opened it and greeted the visitors with a smile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0019.flac", "answer": "YOU MUST KNOW SAID MARGOLOTTE WHEN THEY WERE ALL SEATED TOGETHER ON THE BROAD WINDOW SEAT THAT MY HUSBAND FOOLISHLY GAVE AWAY ALL THE POWDER OF LIFE HE FIRST MADE TO OLD MOMBI THE WITCH WHO USED TO LIVE IN THE COUNTRY OF THE GILLIKINS TO THE NORTH OF HERE", "subset": "test_clean", "task_type": "understanding", "prediction": "you must know said margarotte when they were all seated together on the broad window seat that my husband foolishly gave away all the powder of life he first made to old mombi the witch who used to live in the country of the gillikins to the north of here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0017.flac", "answer": "AT ONE END STOOD A GREAT FIREPLACE IN WHICH A BLUE LOG WAS BLAZING WITH A BLUE FLAME AND OVER THE FIRE HUNG FOUR KETTLES IN A ROW ALL BUBBLING AND STEAMING AT A GREAT RATE", "subset": "test_clean", "task_type": "understanding", "prediction": "at one end stood a great fireplace in which a blue log was blazing with a blue flame and over the fire hung four kettles in a row all bubbling and steaming at a great rate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0031.flac", "answer": "AT THE EMERALD CITY WHERE OUR PRINCESS OZMA LIVES GREEN IS THE POPULAR COLOR", "subset": "test_clean", "task_type": "understanding", "prediction": "at the emerald city where our princess ozma lives green is the popular color", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0029.flac", "answer": "SOMETIMES IT IS CALLED A CRAZY QUILT BECAUSE THE PATCHES AND COLORS ARE SO MIXED UP", "subset": "test_clean", "task_type": "understanding", "prediction": "sometimes it is called a crazy quilt because the patches and colors are so mixed up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0020.flac", "answer": "THE FIRST LOT WE TESTED ON OUR GLASS CAT WHICH NOT ONLY BEGAN TO LIVE BUT HAS LIVED EVER SINCE", "subset": "test_clean", "task_type": "understanding", "prediction": "the first lot we tested on our glass hat which not only began to live but has lived ever since", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0016.flac", "answer": "THE WOMAN SEEMED THOUGHTFUL", "subset": "test_clean", "task_type": "understanding", "prediction": "the woman seemed thoughtful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0023.flac", "answer": "YOU SEE I'VE LIVED ALL MY LIFE WITH UNC NUNKIE THE SILENT ONE AND THERE WAS NO ONE TO TELL ME ANYTHING", "subset": "test_clean", "task_type": "understanding", "prediction": "you see i have lived all my life with unc nunkie the silent one and there was no one to tell me anything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0008.flac", "answer": "ALL THE MORNING THEY TRUDGED UP THE MOUNTAIN PATH AND AT NOON UNC AND OJO SAT ON A FALLEN TREE TRUNK AND ATE THE LAST OF THE BREAD WHICH THE OLD MUNCHKIN HAD PLACED IN HIS POCKET", "subset": "test_clean", "task_type": "understanding", "prediction": "all the morning they trudged up the mountain path and at noon unk and ojo sat on a fallen tree trunk and ate the last of the bread which the old munchkin had placed in his pocket", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0005.flac", "answer": "NO ONE WOULD DISTURB THEIR LITTLE HOUSE EVEN IF ANYONE CAME SO FAR INTO THE THICK FOREST WHILE THEY WERE GONE", "subset": "test_clean", "task_type": "understanding", "prediction": "no one would disturb their little house even if any one came so far into the thick forest while they were gone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0024.flac", "answer": "THAT IS ONE REASON YOU ARE OJO THE UNLUCKY SAID THE WOMAN IN A SYMPATHETIC TONE", "subset": "test_clean", "task_type": "understanding", "prediction": "that is one reason you are ojo the unlucky said the woman in sympathetic tone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0022.flac", "answer": "I'M AFRAID I DON'T KNOW MUCH ABOUT THE LAND OF OZ", "subset": "test_clean", "task_type": "understanding", "prediction": "i am afraid i don't know much about the land of oz", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0007.flac", "answer": "HE KNEW IT WOULD TAKE THEM TO THE HOUSE OF THE CROOKED MAGICIAN WHOM HE HAD NEVER SEEN BUT WHO WAS THEIR NEAREST NEIGHBOR", "subset": "test_clean", "task_type": "understanding", "prediction": "he knew it would take them to the house of the crooked magician whom he had never seen but who was their nearest neighbor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0013.flac", "answer": "AND YOU MUST BE OJO THE UNLUCKY SHE ADDED", "subset": "test_clean", "task_type": "understanding", "prediction": "and you must be ojo the unlucky she added", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0018.flac", "answer": "IT TAKES ME SEVERAL YEARS TO MAKE THIS MAGIC POWDER BUT AT THIS MOMENT I AM PLEASED TO SAY IT IS NEARLY DONE YOU SEE I AM MAKING IT FOR MY GOOD WIFE MARGOLOTTE WHO WANTS TO USE SOME OF IT FOR A PURPOSE OF HER OWN", "subset": "test_clean", "task_type": "understanding", "prediction": "it takes me several years to make this magic powder but at this moment i am pleased to say it is nearly done you see i am making it for my good wife margolotte who wants to use some of it for a purpose of her own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0028.flac", "answer": "A BED QUILT MADE OF PATCHES OF DIFFERENT KINDS AND COLORS OF CLOTH ALL NEATLY SEWED TOGETHER", "subset": "test_clean", "task_type": "understanding", "prediction": "a bed quilt made of patches of different kinds and colors of cloth all neatly sewed together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0006.flac", "answer": "AT THE FOOT OF THE MOUNTAIN THAT SEPARATED THE COUNTRY OF THE MUNCHKINS FROM THE COUNTRY OF THE GILLIKINS THE PATH DIVIDED", "subset": "test_clean", "task_type": "understanding", "prediction": "at the foot of the mountain that separated the country of the munchkins from the country of the gillikins the path divided", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0026.flac", "answer": "BUT FIRST I WILL TELL YOU THAT FOR MANY YEARS I HAVE LONGED FOR A SERVANT TO HELP ME WITH THE HOUSEWORK AND TO COOK THE MEALS AND WASH THE DISHES", "subset": "test_clean", "task_type": "understanding", "prediction": "but first i will tell you that for many years i have longed for a servant to help me with the housework and to cook the meals and wash the dishes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0030.flac", "answer": "WHEN I FOUND IT I SAID TO MYSELF THAT IT WOULD DO NICELY FOR MY SERVANT GIRL FOR WHEN SHE WAS BROUGHT TO LIFE SHE WOULD NOT BE PROUD NOR HAUGHTY AS THE GLASS CAT IS FOR SUCH A DREADFUL MIXTURE OF COLORS WOULD DISCOURAGE HER FROM TRYING TO BE AS DIGNIFIED AS THE BLUE MUNCHKINS ARE", "subset": "test_clean", "task_type": "understanding", "prediction": "when i found it i said to myself that it would do nicely for my servant girl for when she was brought to life she would not be proud nor haughty as the glass cat is for such a dreadful mixture of colors would discourage her from trying to be as dignified as the blue munchkins are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0015.flac", "answer": "WE ARE TRAVELING REPLIED OJO AND WE STOPPED AT YOUR HOUSE JUST TO REST AND REFRESH OURSELVES", "subset": "test_clean", "task_type": "understanding", "prediction": "we are traveling replied ojo and we stopped at your house just to rest and refresh ourselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0025.flac", "answer": "I THINK I MUST SHOW YOU MY PATCHWORK GIRL SAID MARGOLOTTE LAUGHING AT THE BOY'S ASTONISHMENT FOR SHE IS RATHER DIFFICULT TO EXPLAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "i think i must show you my patchwork girl said margolotte laughing at the boy s astonishment for she is rather difficult to explain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0002.flac", "answer": "INSTEAD OF SHOES THE OLD MAN WORE BOOTS WITH TURNOVER TOPS AND HIS BLUE COAT HAD WIDE CUFFS OF GOLD BRAID", "subset": "test_clean", "task_type": "understanding", "prediction": "instead of shoes the old man wore boots with turn over tops and his blue coat had wide cuffs of gold braid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0014.flac", "answer": "OJO HAD NEVER EATEN SUCH A FINE MEAL IN ALL HIS LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "ojo had never eaten such a fine meal in all his life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0032.flac", "answer": "I WILL SHOW YOU WHAT A GOOD JOB I DID AND SHE WENT TO A TALL CUPBOARD AND THREW OPEN THE DOORS", "subset": "test_clean", "task_type": "understanding", "prediction": "i will show you what a good job i did and she went to a tall cupboard and threw open the doors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0003.flac", "answer": "FOR A LONG TIME HE HAD WISHED TO EXPLORE THE BEAUTIFUL LAND OF OZ IN WHICH THEY LIVED", "subset": "test_clean", "task_type": "understanding", "prediction": "for a long time he had wished to explore the beautiful land of oz in which they lived", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0009.flac", "answer": "THEN THEY STARTED ON AGAIN AND TWO HOURS LATER CAME IN SIGHT OF THE HOUSE OF DOCTOR PIPT", "subset": "test_clean", "task_type": "understanding", "prediction": "then they started on again and two hours later came in sight of the house of doctor pipt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0004.flac", "answer": "WHEN THEY WERE OUTSIDE UNC SIMPLY LATCHED THE DOOR AND STARTED UP THE PATH", "subset": "test_clean", "task_type": "understanding", "prediction": "when they were outside ung simply latched the door and started up the path", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1180/1284-1180-0012.flac", "answer": "WE HAVE COME FROM A FAR LONELIER PLACE THAN THIS A LONELIER PLACE", "subset": "test_clean", "task_type": "understanding", "prediction": "we have come from a far lonelier place than this a lonelier place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0019.flac", "answer": "I NOW USE THEM AS ORNAMENTAL STATUARY IN MY GARDEN", "subset": "test_clean", "task_type": "understanding", "prediction": "i now use them as ornamental statuary in my garden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0002.flac", "answer": "THE HEAD OF THE PATCHWORK GIRL WAS THE MOST CURIOUS PART OF HER", "subset": "test_clean", "task_type": "understanding", "prediction": "the head of the patchwork girl was the most curious part of her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0003.flac", "answer": "THE HAIR WAS OF BROWN YARN AND HUNG DOWN ON HER NECK IN SEVERAL NEAT BRAIDS", "subset": "test_clean", "task_type": "understanding", "prediction": "the hair was of brown yarn and hung down on her neck in several neat braids", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0008.flac", "answer": "I THINK THAT WILL DO SHE CONTINUED FOR THE OTHER QUALITIES ARE NOT NEEDED IN A SERVANT", "subset": "test_clean", "task_type": "understanding", "prediction": "i think that will do she continued for the other qualities are not needed in a servant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0007.flac", "answer": "SHE POURED INTO THE DISH A QUANTITY FROM EACH OF THESE BOTTLES", "subset": "test_clean", "task_type": "understanding", "prediction": "she poured into the dish a quantity from each of these bottles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0006.flac", "answer": "WELL THAT MAY BE TRUE AGREED MARGOLOTTE BUT ON THE CONTRARY A SERVANT WITH TOO MUCH BRAINS IS SURE TO BECOME INDEPENDENT AND HIGH AND MIGHTY AND FEEL ABOVE HER WORK", "subset": "test_clean", "task_type": "understanding", "prediction": "well that may be true agreed margolotte but on the contrary a servant with too much brains is sure to become independent and high and mighty and feel above her work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0020.flac", "answer": "DEAR ME WHAT A CHATTERBOX YOU'RE GETTING TO BE UNC REMARKED THE MAGICIAN WHO WAS PLEASED WITH THE COMPLIMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "dear me what a chatterbox you are getting to be young remarked the magician who was pleased with the compliment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0004.flac", "answer": "GOLD IS THE MOST COMMON METAL IN THE LAND OF OZ AND IS USED FOR MANY PURPOSES BECAUSE IT IS SOFT AND PLIABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "gold is the most common metal in the land of oz and is used for many purposes because it is soft and pliable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0015.flac", "answer": "MOST PEOPLE TALK TOO MUCH SO IT IS A RELIEF TO FIND ONE WHO TALKS TOO LITTLE", "subset": "test_clean", "task_type": "understanding", "prediction": "most people talk too much so it is a relief to find one who talks too little", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0005.flac", "answer": "NO I FORGOT ALL ABOUT THE BRAINS EXCLAIMED THE WOMAN", "subset": "test_clean", "task_type": "understanding", "prediction": "no i forgot all about the brains exclaimed the woman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0014.flac", "answer": "HE SELECTED A SMALL GOLD BOTTLE WITH A PEPPER BOX TOP SO THAT THE POWDER MIGHT BE SPRINKLED ON ANY OBJECT THROUGH THE SMALL HOLES", "subset": "test_clean", "task_type": "understanding", "prediction": "he selected a small gold bottle with a pepper box top so that the powder might be sprinkled on any object through the small holes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0009.flac", "answer": "SHE RAN TO HER HUSBAND'S SIDE AT ONCE AND HELPED HIM LIFT THE FOUR KETTLES FROM THE FIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "she ran to her husband side at once and helped him lift the four caddles from the fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0018.flac", "answer": "IT TRULY IS ASSERTED THE MAGICIAN", "subset": "test_clean", "task_type": "understanding", "prediction": "it truly is asserted the magician", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0000.flac", "answer": "OJO EXAMINED THIS CURIOUS CONTRIVANCE WITH WONDER", "subset": "test_clean", "task_type": "understanding", "prediction": "ojo examined this curious contrivance with wonder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0017.flac", "answer": "THE WIZARD OF OZ WHO USED TO BE A HUMBUG AND KNEW NO MAGIC AT ALL HAS BEEN TAKING LESSONS OF GLINDA AND I'M TOLD HE IS GETTING TO BE A PRETTY GOOD WIZARD BUT HE IS MERELY THE ASSISTANT OF THE GREAT SORCERESS", "subset": "test_clean", "task_type": "understanding", "prediction": "the wizard of oz who used to be a humbug and knew no magic at all has been taking lessons of glinda and i am told he is getting to be a pretty good wizard but he is merely the assistant of the great sorceress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0021.flac", "answer": "ASKED THE VOICE IN SCORNFUL ACCENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "asked the voice in scornful accents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0010.flac", "answer": "THEIR CONTENTS HAD ALL BOILED AWAY LEAVING IN THE BOTTOM OF EACH KETTLE A FEW GRAINS OF FINE WHITE POWDER", "subset": "test_clean", "task_type": "understanding", "prediction": "their contents had all boiled away leaving in the bottom of each kettle a few grains of fine white powder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0001.flac", "answer": "MARGOLOTTE HAD FIRST MADE THE GIRL'S FORM FROM THE PATCHWORK QUILT AND THEN SHE HAD DRESSED IT WITH A PATCHWORK SKIRT AND AN APRON WITH POCKETS IN IT USING THE SAME GAY MATERIAL THROUGHOUT", "subset": "test_clean", "task_type": "understanding", "prediction": "margolotte had first made the girl s form from the patchwork quilt and then she had dressed it with a patchwork skirt and an apron with pockets in it using the same gay material throughout", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0013.flac", "answer": "OJO BECAME A BIT UNEASY AT THIS FOR HE HAD ALREADY PUT QUITE A LOT OF THE CLEVERNESS POWDER IN THE DISH BUT HE DARED NOT INTERFERE AND SO HE COMFORTED HIMSELF WITH THE THOUGHT THAT ONE CANNOT HAVE TOO MUCH CLEVERNESS", "subset": "test_clean", "task_type": "understanding", "prediction": "ojo became a bit uneasy at this for he had already put quite a lot of the cleverness powder in the dish but he dared not interfere and so he comforted himself with the thought that one cannot have too much cleverness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0011.flac", "answer": "VERY CAREFULLY THE MAGICIAN REMOVED THIS POWDER PLACING IT ALL TOGETHER IN A GOLDEN DISH WHERE HE MIXED IT WITH A GOLDEN SPOON", "subset": "test_clean", "task_type": "understanding", "prediction": "very carefully the magician removed this powder placing it all together in a golden dish where he mixed it with a golden spoon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0012.flac", "answer": "NO ONE SAW HIM DO THIS FOR ALL WERE LOOKING AT THE POWDER OF LIFE BUT SOON THE WOMAN REMEMBERED WHAT SHE HAD BEEN DOING AND CAME BACK TO THE CUPBOARD", "subset": "test_clean", "task_type": "understanding", "prediction": "no one saw him do this for all were looking at the powder of life but soon the woman remembered what she had been doing and came back to the cupboard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/1181/1284-1181-0016.flac", "answer": "I AM NOT ALLOWED TO PERFORM MAGIC EXCEPT FOR MY OWN AMUSEMENT HE TOLD HIS VISITORS AS HE LIGHTED A PIPE WITH A CROOKED STEM AND BEGAN TO SMOKE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am not allowed to perform magic except for my own amusement he told his visitors as he lighted a pipe with a crooked stem and began to smoke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0001.flac", "answer": "THE EDICT OF MILAN THE GREAT CHARTER OF TOLERATION HAD CONFIRMED TO EACH INDIVIDUAL OF THE ROMAN WORLD THE PRIVILEGE OF CHOOSING AND PROFESSING HIS OWN RELIGION", "subset": "test_clean", "task_type": "understanding", "prediction": "the edict of milan the great charter of toleration had confirmed to each individual of the roman world the privilege of choosing and professing his own religion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0003.flac", "answer": "CONSTANTINE EASILY BELIEVED THAT THE HERETICS WHO PRESUMED TO DISPUTE HIS OPINIONS OR TO OPPOSE HIS COMMANDS WERE GUILTY OF THE MOST ABSURD AND CRIMINAL OBSTINACY AND THAT A SEASONABLE APPLICATION OF MODERATE SEVERITIES MIGHT SAVE THOSE UNHAPPY MEN FROM THE DANGER OF AN EVERLASTING CONDEMNATION", "subset": "test_clean", "task_type": "understanding", "prediction": "constantine easily believed that the heretics who presumed to dispute his opinions or to oppose his commands were guilty of the most absurd and criminal obstinacy and that a seasonable application of moderate severities might save those unhappy men from the danger of an everlasting condemnation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0002.flac", "answer": "BUT THIS INESTIMABLE PRIVILEGE WAS SOON VIOLATED WITH THE KNOWLEDGE OF TRUTH THE EMPEROR IMBIBED THE MAXIMS OF PERSECUTION AND THE SECTS WHICH DISSENTED FROM THE CATHOLIC CHURCH WERE AFFLICTED AND OPPRESSED BY THE TRIUMPH OF CHRISTIANITY", "subset": "test_clean", "task_type": "understanding", "prediction": "but this inestimable privilege was soon violated with a knowledge of truth the emperor imbibed the maxims of persecution and the sects which dissented from the catholic church were afflicted and oppressed by the triumph of christianity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0004.flac", "answer": "SOME OF THE PENAL REGULATIONS WERE COPIED FROM THE EDICTS OF DIOCLETIAN AND THIS METHOD OF CONVERSION WAS APPLAUDED BY THE SAME BISHOPS WHO HAD FELT THE HAND OF OPPRESSION AND PLEADED FOR THE RIGHTS OF HUMANITY", "subset": "test_clean", "task_type": "understanding", "prediction": "some of the penal regulations were copied from the edicts of diocletian and this method of conversion was applauded by the same bishops who had felt the hand of oppression and pleaded for the rights of humanity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0005.flac", "answer": "THEY ASSERTED WITH CONFIDENCE AND ALMOST WITH EXULTATION THAT THE APOSTOLICAL SUCCESSION WAS INTERRUPTED THAT ALL THE BISHOPS OF EUROPE AND ASIA WERE INFECTED BY THE CONTAGION OF GUILT AND SCHISM AND THAT THE PREROGATIVES OF THE CATHOLIC CHURCH WERE CONFINED TO THE CHOSEN PORTION OF THE AFRICAN BELIEVERS WHO ALONE HAD PRESERVED INVIOLATE THE INTEGRITY OF THEIR FAITH AND DISCIPLINE", "subset": "test_clean", "task_type": "understanding", "prediction": "they asserted with confidence and almost with exultation that the apostolical succession was interrupted that all the bishops of europe and asia were infected by the contagion of guilt and schism and that the prerogatives of the catholic church were confined to the chosen portion of the african believers who alone had preserved inviolate the integrity of their faith and discipline", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0007.flac", "answer": "PROSCRIBED BY THE CIVIL AND ECCLESIASTICAL POWERS OF THE EMPIRE THE DONATISTS STILL MAINTAINED IN SOME PROVINCES PARTICULARLY IN NUMIDIA THEIR SUPERIOR NUMBERS AND FOUR HUNDRED BISHOPS ACKNOWLEDGED THE JURISDICTION OF THEIR PRIMATE", "subset": "test_clean", "task_type": "understanding", "prediction": "proscribed by the civil and ecclesiastical powers of the empire the donatists still maintained in some provinces particularly in numidia their superior numbers and four hundred bishops acknowledged the jurisdiction of their primate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0000.flac", "answer": "THE GRATEFUL APPLAUSE OF THE CLERGY HAS CONSECRATED THE MEMORY OF A PRINCE WHO INDULGED THEIR PASSIONS AND PROMOTED THEIR INTEREST", "subset": "test_clean", "task_type": "understanding", "prediction": "the grateful applause of the clergy has consecrated the memory of a prince who indulged their passions and promoted their interest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1284/134647/1284-134647-0006.flac", "answer": "BISHOPS VIRGINS AND EVEN SPOTLESS INFANTS WERE SUBJECTED TO THE DISGRACE OF A PUBLIC PENANCE BEFORE THEY COULD BE ADMITTED TO THE COMMUNION OF THE DONATISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "bishops virgins and even spotless infants were subjected to the disgrace of a public penance before they could be admitted to the communion of the donatists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36600/5142-36600-0000.flac", "answer": "CHAPTER SEVEN ON THE RACES OF MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "chapter seven on the races of man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36600/5142-36600-0001.flac", "answer": "IN DETERMINING WHETHER TWO OR MORE ALLIED FORMS OUGHT TO BE RANKED AS SPECIES OR VARIETIES NATURALISTS ARE PRACTICALLY GUIDED BY THE FOLLOWING CONSIDERATIONS NAMELY THE AMOUNT OF DIFFERENCE BETWEEN THEM AND WHETHER SUCH DIFFERENCES RELATE TO FEW OR MANY POINTS OF STRUCTURE AND WHETHER THEY ARE OF PHYSIOLOGICAL IMPORTANCE BUT MORE ESPECIALLY WHETHER THEY ARE CONSTANT", "subset": "test_clean", "task_type": "understanding", "prediction": "in determining whether two or more allied forms ought to be ranked as species or varieties naturalists are practically guided by the following considerations namely the amount of difference between them and whether such differences relate to few or many points of structure and whether they are of physiological importance but more especially whether they are constant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0062.flac", "answer": "NOW SHE PUT HER HAND ON HIS ARM AND SMILED AND SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "now she put her hand on his arm and smiled and said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0024.flac", "answer": "I STOOD WITH MY BACK TO THE WALL FOR I WANTED NO SWORD REACHING OUT OF THE DARK FOR ME", "subset": "test_clean", "task_type": "understanding", "prediction": "i stood with my back to the wall for i wanted no sword reaching out of the dark for me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0033.flac", "answer": "YOU WOULD NOT EAT WITH US YOU CANNOT SAY NO TO HALF OF MY ALE I DRINK THIS TO YOUR HEALTH", "subset": "test_clean", "task_type": "understanding", "prediction": "you would not eat with us you cannot say no to half of my ale i drink this to your health", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0051.flac", "answer": "AND WITH IT I LEAVE YOU A NAME SIF THE FRIENDLY I SHALL HOPE TO DRINK WITH YOU SOMETIME IN VALHALLA", "subset": "test_clean", "task_type": "understanding", "prediction": "and with it i leave you a name sith the friendly i shall hope to drink with you some time in valhalla", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0046.flac", "answer": "BY THE BEARD OF ODIN I CRIED YOU HAVE TAKEN OUR JOKE LIKE A MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "by the beard of odin i cried you have taken our joke like a man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0061.flac", "answer": "YOUR MOTHER THE QUEEN WAS STANDING BY", "subset": "test_clean", "task_type": "understanding", "prediction": "your mother the queen was standing by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0047.flac", "answer": "MY MEN POUNDED THE TABLE WITH THEIR FISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "my men pounded the table with their fists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0065.flac", "answer": "SOFT HEART HE SAID GENTLY TO HER THEN TO THORKEL WELL LET HIM GO THORKEL", "subset": "test_clean", "task_type": "understanding", "prediction": "soft heart he said gently to her then to torkel well let him go torkel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0056.flac", "answer": "HERE THEY SAID IS A RASCAL WHO HAS BEEN HARRYING OUR COASTS", "subset": "test_clean", "task_type": "understanding", "prediction": "here they said is a rascal who has been harrying our coasts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0068.flac", "answer": "SO I LIVED AND NOW AM YOUR TOOTH THRALL WELL IT IS THE LUCK OF WAR", "subset": "test_clean", "task_type": "understanding", "prediction": "so i lived and now i am your tooth thrall well it is the luck of war", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0040.flac", "answer": "AND THESE SHALL FOLLOW YOUR THRALLS IN THE SAME WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "and these shall follow your thralls in the same way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0050.flac", "answer": "MAY YOU DRINK HEART'S EASE FROM IT FOR MANY YEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "may you drink heartsease from it for many years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0032.flac", "answer": "THE FARMER SAT GLOOMILY ON THE BENCH AND WOULD NOT EAT AND YOU CANNOT WONDER FOR HE SAW US PUTTING POTFULS OF HIS GOOD BEEF AND BASKET LOADS OF BREAD INTO OUR BIG MOUTHS", "subset": "test_clean", "task_type": "understanding", "prediction": "the farmer sat gloomily on the bench and would not eat and you cannot wonder for he saw us putting potfuls of his good beef and baskiloads of bread into our big mouths", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0064.flac", "answer": "YOUR FATHER THOUGHT A MOMENT THEN LOOKED AT YOUR MOTHER AND SMILED", "subset": "test_clean", "task_type": "understanding", "prediction": "your father thought a moment then looked at your mother and smiled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0007.flac", "answer": "AT THE PROW I CARVED THE HEAD WITH OPEN MOUTH AND FORKED TONGUE THRUST OUT", "subset": "test_clean", "task_type": "understanding", "prediction": "at the prow i carve the head with open mouth and forked tongue thrust out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0044.flac", "answer": "I AM STIFF WITH LONG SITTING HE SAID I ITCH FOR A FIGHT I TURNED TO THE FARMER", "subset": "test_clean", "task_type": "understanding", "prediction": "i am stiff with long sitting he said i itch for a fight i turned to the farmer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0004.flac", "answer": "THESE HE GAVE TO THREE OF MY BROTHERS", "subset": "test_clean", "task_type": "understanding", "prediction": "these he gave to three of my brothers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0030.flac", "answer": "THE THRALLS WERE BRINGING IN A GREAT POT OF MEAT", "subset": "test_clean", "task_type": "understanding", "prediction": "the thralls were bringing in a great pot of meat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0008.flac", "answer": "I PAINTED THE EYES RED FOR ANGER", "subset": "test_clean", "task_type": "understanding", "prediction": "i painted the eyes red for anger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0052.flac", "answer": "HERE IS A RING FOR SIF THE FRIENDLY AND HERE IS A BRACELET A SWORD WOULD NOT BE ASHAMED TO HANG AT YOUR SIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "here is a ring for sif the friendly and here is a bracelet and a sword would not be ashamed to hang at your side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0063.flac", "answer": "AND WOULD HE NOT BE A GOOD GIFT FOR OUR BABY", "subset": "test_clean", "task_type": "understanding", "prediction": "and would he not be a good gift for our baby", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0066.flac", "answer": "THEN HE TURNED TO ME AGAIN FROWNING", "subset": "test_clean", "task_type": "understanding", "prediction": "then he turned to me again frowning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0028.flac", "answer": "ON A BENCH IN A FAR CORNER WERE A DOZEN PEOPLE HUDDLED TOGETHER", "subset": "test_clean", "task_type": "understanding", "prediction": "on a bench in a far corner were a dozen people huddled together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0055.flac", "answer": "THAT TIME IT POINTED US INTO YOUR FATHER'S SHIPS", "subset": "test_clean", "task_type": "understanding", "prediction": "that time it pointed us into your father ships", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0037.flac", "answer": "HAKON THERE SHALL BE YOUR CONSTANT COMPANION FRIEND FARMER", "subset": "test_clean", "task_type": "understanding", "prediction": "hawkin there shall be your constant companion friend farmer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0067.flac", "answer": "BUT YOUNG SHARP TONGUE NOW THAT WE HAVE CAUGHT YOU WE WILL PUT YOU INTO A TRAP THAT YOU CANNOT GET OUT OF", "subset": "test_clean", "task_type": "understanding", "prediction": "but young sharp tongue now that we have caught you we will put you into a trap that you cannot get out of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0038.flac", "answer": "HE SHALL NOT LEAVE YOU DAY OR NIGHT WHETHER YOU ARE WORKING OR PLAYING OR SLEEPING", "subset": "test_clean", "task_type": "understanding", "prediction": "he shall not leave you day or night whether you are working or playing or sleeping", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0048.flac", "answer": "BY THE HAMMER OF THOR SHOUTED GRIM HERE IS NO STINGY COWARD", "subset": "test_clean", "task_type": "understanding", "prediction": "by the hammer of thor shouted graham there is no stingy coward", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0041.flac", "answer": "SO I SET GUARDS OVER EVERY ONE IN THAT HOUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "so i set guards over every one in that house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0045.flac", "answer": "THIS IS OUR LAST FEAST WITH YOU I SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "this is our last feast with you i said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0021.flac", "answer": "UP AND DOWN THE WATER WE WENT TO GET MUCH WEALTH AND MUCH FROLIC", "subset": "test_clean", "task_type": "understanding", "prediction": "up and down the water we went to get much wealth and much frolic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0010.flac", "answer": "IN THE STERN I CURVED THE TAIL UP ALMOST AS HIGH AS THE HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "in the stern i carved the tail up almost as high as the head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0060.flac", "answer": "TAKE HIM OUT THORKEL AND LET HIM TASTE YOUR SWORD", "subset": "test_clean", "task_type": "understanding", "prediction": "take him out torkel and let him taste your sword", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0013.flac", "answer": "HE IS BUT A BOY THE MEN SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "he is but a boy the man said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0043.flac", "answer": "THEIR EYES DANCED BIG THORLEIF STOOD UP AND STRETCHED HIMSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "their eyes danced big torleif stood up and stretched himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0054.flac", "answer": "THAT IS THE BEST WAY TO DECIDE FOR THE SPEAR WILL ALWAYS POINT SOMEWHERE AND ONE THING IS AS GOOD AS ANOTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "that is the best way to decide for the spear will always point somewhere and one thing is as good as another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0012.flac", "answer": "THEN I WILL GET ME A FARM AND WILL WINTER IN THAT LAND NOW WHO WILL FOLLOW ME", "subset": "test_clean", "task_type": "understanding", "prediction": "then i will get me a farm and will win her in that land now who will follow me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0027.flac", "answer": "HE ACTS AS THOUGH HE HAD NOT EXPECTED US", "subset": "test_clean", "task_type": "understanding", "prediction": "he acts as though he had not expected us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0019.flac", "answer": "OH IT IS BETTER TO LIVE ON THE SEA AND LET OTHER MEN RAISE YOUR CROPS AND COOK YOUR MEALS", "subset": "test_clean", "task_type": "understanding", "prediction": "oh it is better to live on the sea and let other men raise your crops and cook your meals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0014.flac", "answer": "THIRTY MEN ONE AFTER ANOTHER RAISED THEIR HORNS AND SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "thirty men one after another raised their horns and said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0006.flac", "answer": "I MADE HER FOR ONLY TWENTY OARS BECAUSE I THOUGHT FEW MEN WOULD FOLLOW ME FOR I WAS YOUNG FIFTEEN YEARS OLD", "subset": "test_clean", "task_type": "understanding", "prediction": "i made her for only twenty ores because i thought few men would follow me for i was young fifteen years old", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0015.flac", "answer": "AS OUR BOAT FLASHED DOWN THE ROLLERS INTO THE WATER I MADE THIS SONG AND SANG IT", "subset": "test_clean", "task_type": "understanding", "prediction": "as our boat flashed down the rollers into the water i made this song and sang it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0005.flac", "answer": "BUT I STAYED THAT SPRING AND BUILT ME A BOAT", "subset": "test_clean", "task_type": "understanding", "prediction": "but i stayed that spring and built me a boat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0022.flac", "answer": "WHAT OF THE FARM OLAF NOT YET I ANSWERED VIKING IS BETTER FOR SUMMER", "subset": "test_clean", "task_type": "understanding", "prediction": "what of the farm olaf not yet i answered viking is better for summer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0011.flac", "answer": "THERE SHE SAT ON THE ROLLERS AS FAIR A SHIP AS I EVER SAW", "subset": "test_clean", "task_type": "understanding", "prediction": "there she sat on the rollers as fair a ship as i ever saw", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0025.flac", "answer": "COME COME I CALLED WHEN NO ONE OBEYED A FIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "come come i called when no one obeyed a fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0029.flac", "answer": "BRING IN THE TABLE WE ARE HUNGRY", "subset": "test_clean", "task_type": "understanding", "prediction": "bring in the table we are hungry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0017.flac", "answer": "WE ATE AT MANY MEN'S TABLES UNINVITED", "subset": "test_clean", "task_type": "understanding", "prediction": "we ate at many men s tables uninvited", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0042.flac", "answer": "SO NO TALES GOT OUT TO THE NEIGHBORS BESIDES IT WAS A LONELY PLACE AND BY GOOD LUCK NO ONE CAME THAT WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "so no tales got out to the neighbors besides it was a lonely place and by good luck no one came that way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0039.flac", "answer": "I NAMED NINE OTHERS AND SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "i named nine others and said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0026.flac", "answer": "MY MEN LAUGHED YES A STINGY HOST", "subset": "test_clean", "task_type": "understanding", "prediction": "my men laughed yes a stingy host", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0058.flac", "answer": "A ROBBER VIKING SAID THE KING AND SCOWLED AT ME", "subset": "test_clean", "task_type": "understanding", "prediction": "a robber viking said the king and he scowled at me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0016.flac", "answer": "SO WE HARRIED THE COAST OF NORWAY", "subset": "test_clean", "task_type": "understanding", "prediction": "so we harried the coast of norway", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0001.flac", "answer": "WHAT IS YOUR COUNTRY OLAF HAVE YOU ALWAYS BEEN A THRALL THE THRALL'S EYES FLASHED", "subset": "test_clean", "task_type": "understanding", "prediction": "what is your country olaf have you always been a thrall the thrall s eyes flashed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0020.flac", "answer": "A HOUSE SMELLS OF SMOKE A SHIP SMELLS OF FROLIC", "subset": "test_clean", "task_type": "understanding", "prediction": "a house smells of smoke a ship smells of frolic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0031.flac", "answer": "THEY SET UP A CRANE OVER THE FIRE AND HUNG THE POT UPON IT AND WE SAT AND WATCHED IT BOIL WHILE WE JOKED AT LAST THE SUPPER BEGAN", "subset": "test_clean", "task_type": "understanding", "prediction": "they set up a crane over the fire and hung the pot upon it and we sat and watched it boil while we joked at last the supper began", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0057.flac", "answer": "WE SUNK HIS SHIP AND MEN BUT HIM WE BROUGHT TO YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "we sunk his ship and men but him we brought to you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0003.flac", "answer": "THE REST OF YOU OFF A VIKING HE HAD THREE SHIPS", "subset": "test_clean", "task_type": "understanding", "prediction": "the rest of you off a viking he had three ships", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0000.flac", "answer": "AT ANOTHER TIME HARALD ASKED", "subset": "test_clean", "task_type": "understanding", "prediction": "at another time harold asked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0049.flac", "answer": "HERE FRIEND TAKE IT AND HE THRUST IT INTO THE FARMER'S HAND", "subset": "test_clean", "task_type": "understanding", "prediction": "here friend take it and he thrust it into the farmer s hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0034.flac", "answer": "THEN I DRANK HALF OF THE HORNFUL AND SENT THE REST ACROSS THE FIRE TO THE FARMER HE TOOK IT AND SMILED SAYING", "subset": "test_clean", "task_type": "understanding", "prediction": "then i drank half of the horn full and set the rest across the fire to the farmer he took it and smiled saying", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0035.flac", "answer": "DID YOU EVER HAVE SUCH A LORDLY GUEST BEFORE I WENT ON", "subset": "test_clean", "task_type": "understanding", "prediction": "did you ever have such a lordly guest before i went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0018.flac", "answer": "MY DRAGON'S BELLY IS NEVER FULL AND ON BOARD WENT THE GOLD", "subset": "test_clean", "task_type": "understanding", "prediction": "my dragon s belly is never full and on board went the gold", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0036.flac", "answer": "SO I WILL GIVE OUT THIS LAW THAT MY MEN SHALL NEVER LEAVE YOU ALONE", "subset": "test_clean", "task_type": "understanding", "prediction": "so i will give out this law that my men shall never leave you alone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0053.flac", "answer": "I TOOK FIVE GREAT BRACELETS OF GOLD FROM OUR TREASURE CHEST AND GAVE THEM TO HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "i took five great bracelets of gold from our treasure chest and gave them to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0059.flac", "answer": "YES AND WITH ALL YOUR FINGERS IT TOOK YOU A YEAR TO CATCH ME THE KING FROWNED MORE ANGRILY", "subset": "test_clean", "task_type": "understanding", "prediction": "yes and with all your fingers it took you a year to catch me the king frowned more angrily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0002.flac", "answer": "TWO HUNDRED WARRIORS FEASTED IN HIS HALL AND FOLLOWED HIM TO BATTLE", "subset": "test_clean", "task_type": "understanding", "prediction": "two hundred warriors feasted in his hall and followed him to battle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0009.flac", "answer": "THERE STAND SO I SAID AND GLARE AND HISS AT MY FOES", "subset": "test_clean", "task_type": "understanding", "prediction": "there stand so i said and glare and hiss at my foes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/33396/5142-33396-0023.flac", "answer": "IT WAS SO DARK THAT I COULD SEE NOTHING BUT A FEW SPARKS ON THE HEARTH", "subset": "test_clean", "task_type": "understanding", "prediction": "it was so dark that i could see nothing but a few sparks on the hearth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0012.flac", "answer": "MAKE ACQUAINTANCE WITH MISTER JAGO SIT TOGETHER", "subset": "test_clean", "task_type": "understanding", "prediction": "make acquaintance with miss giago sit together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0024.flac", "answer": "NAOMI SHOOK HER FOREFINGER REPROACHFULLY AT THEM AS IF THE TWO STURDY YOUNG FARMERS HAD BEEN TWO CHILDREN", "subset": "test_clean", "task_type": "understanding", "prediction": "naomi shook a forefinger reproachfully at them as if the two sturdy young farmers had been two children", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0018.flac", "answer": "HE LOOKED UP AT NAOMI DOUBTINGLY FROM HIS PLATE AND LOOKED DOWN AGAIN SLOWLY WITH A FROWN", "subset": "test_clean", "task_type": "understanding", "prediction": "he looked up at naomi doubtingly from his plate and looked down again slowly with a frown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0020.flac", "answer": "A MORE DREARY AND MORE DISUNITED FAMILY PARTY I NEVER SAT AT THE TABLE WITH", "subset": "test_clean", "task_type": "understanding", "prediction": "a more dreary and more disunited family party i never sat at the table with", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0004.flac", "answer": "SHE SIGNED TO ME WITH A GHOSTLY SOLEMNITY TO TAKE THE VACANT PLACE ON THE LEFT OF HER FATHER", "subset": "test_clean", "task_type": "understanding", "prediction": "she signed to me with a ghostly solemnity to take the vacant place on the left of her father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0010.flac", "answer": "HE IS NOT WELL HE HAS COME OVER THE OCEAN FOR REST AND CHANGE OF SCENE", "subset": "test_clean", "task_type": "understanding", "prediction": "he is not well he has come over the ocean for rest and change of scene", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0022.flac", "answer": "I WISH YOU GOOD NIGHT SHE LAID HER BONY HANDS ON THE BACK OF MISTER MEADOWCROFT'S INVALID CHAIR CUT HIM SHORT IN HIS FAREWELL SALUTATION TO ME AND WHEELED HIM OUT TO HIS BED AS IF SHE WERE WHEELING HIM OUT TO HIS GRAVE", "subset": "test_clean", "task_type": "understanding", "prediction": "i wish you good night she laid her bony hands on the back of mr medlicott s invalid chair cut him short in his farewell salutation to me and wheeled him out to his bed as if she were wheeling him out to his grave", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0001.flac", "answer": "IN FIVE MINUTES I WAS IN A NEW WORLD AND MY MELANCHOLY ROOM WAS FULL OF THE LIVELIEST FRENCH COMPANY", "subset": "test_clean", "task_type": "understanding", "prediction": "in five minutes i was in a new world and my melancholy room was full of the liveliest french company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0007.flac", "answer": "A LITTLE CRACKED THAT IN THE POPULAR PHRASE WAS MY IMPRESSION OF THE STRANGER WHO NOW MADE HIS APPEARANCE IN THE SUPPER ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "a little cracked that in the popular phrase was my impression of the stranger who now made his appearance in the supper room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0002.flac", "answer": "THE SOUND OF AN IMPERATIVE AND UNCOMPROMISING BELL RECALLED ME IN DUE TIME TO THE REGIONS OF REALITY", "subset": "test_clean", "task_type": "understanding", "prediction": "the sound of an imperative and uncompromising bell recalled me in due time to the regions of reality", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0025.flac", "answer": "SILAS SLUNK AWAY WITHOUT A WORD OF PROTEST AMBROSE STOOD HIS GROUND EVIDENTLY BENT ON MAKING HIS PEACE WITH NAOMI BEFORE HE LEFT HER SEEING THAT I WAS IN THE WAY I WALKED ASIDE TOWARD A GLASS DOOR AT THE LOWER END OF THE ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "silas slunk away without a word of protest ambrose stood his ground evidently bent on making his peace with naomi before he left her seeing that i was in the way i walked aside toward a glass door at the lower end of the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0009.flac", "answer": "PHILIP LEFRANK THIS IS MY OVERLOOKER MISTER JAGO SAID THE OLD MAN FORMALLY PRESENTING US", "subset": "test_clean", "task_type": "understanding", "prediction": "philip le frank this is my overlooker mr yago said the old man formally presenting us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0000.flac", "answer": "IT WAS ONE OF THE MASTERLY AND CHARMING STORIES OF DUMAS THE ELDER", "subset": "test_clean", "task_type": "understanding", "prediction": "it was one of the masterly and charming stories of dumah the elder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0021.flac", "answer": "ENVY HATRED MALICE AND UNCHARITABLENESS ARE NEVER SO ESSENTIALLY DETESTABLE TO MY MIND AS WHEN THEY ARE ANIMATED BY A SENSE OF PROPRIETY AND WORK UNDER THE SURFACE BUT FOR MY INTEREST IN NAOMI AND MY OTHER INTEREST IN THE LITTLE LOVE LOOKS WHICH I NOW AND THEN SURPRISED PASSING BETWEEN HER AND AMBROSE I SHOULD NEVER HAVE SAT THROUGH THAT SUPPER", "subset": "test_clean", "task_type": "understanding", "prediction": "envy hatred malice and uncharitableness are never so essentially detestable to my mind as when they are animated by the sense of propriety and work under the surface but for my interest in naomi and my other interest in the little love looks which i now and then surprised passing between her and ambrose i should never have sat through that supper", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0003.flac", "answer": "AMBROSE MET ME AT THE BOTTOM OF THE STAIRS AND SHOWED ME THE WAY TO THE SUPPER ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "ambrose met me at the bottom of the stairs and showed me the way to the supper room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0008.flac", "answer": "MISTER MEADOWCROFT THE ELDER HAVING NOT SPOKEN ONE WORD THUS FAR HIMSELF INTRODUCED THE NEWCOMER TO ME WITH A SIDE GLANCE AT HIS SONS WHICH HAD SOMETHING LIKE DEFIANCE IN IT A GLANCE WHICH AS I WAS SORRY TO NOTICE WAS RETURNED WITH THE DEFIANCE ON THEIR SIDE BY THE TWO YOUNG MEN", "subset": "test_clean", "task_type": "understanding", "prediction": "mr meddcroft the elder having not spoken one word thus far himself introduced the new comer to me with a side glance at his sons which had something like defiance in it a glance which as i was sorry to notice was returned with the defiance on their side by the two young men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0016.flac", "answer": "FOR ONCE IN A WAY I PROVED A TRUE PROPHET", "subset": "test_clean", "task_type": "understanding", "prediction": "for once in a way i proved a true prophet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0006.flac", "answer": "A NEW MEMBER OF THE FAMILY CIRCLE WHO INSTANTLY ATTRACTED MY ATTENTION ENTERED THE ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "a new member of the family circle who instantly attracted my attention entered the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0019.flac", "answer": "WHEN I ADDRESSED HIM HE ANSWERED CONSTRAINEDLY", "subset": "test_clean", "task_type": "understanding", "prediction": "when i addressed him he answered constrainedly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0005.flac", "answer": "THE DOOR OPENED AGAIN WHILE I WAS STILL STUDYING THE TWO BROTHERS WITHOUT I HONESTLY CONFESS BEING VERY FAVORABLY IMPRESSED BY EITHER OF THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "the door opened again while i was still studying the two brothers without i honestly confess being very favourably impressed by either of them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0015.flac", "answer": "OUR FIRST IMPRESSIONS OF PEOPLE ARE IN NINE CASES OUT OF TEN THE RIGHT IMPRESSIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "our first impressions of people are in nine cases out of ten the right impressions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0014.flac", "answer": "A PRETTY GIRL AND SO FAR AS I COULD JUDGE BY APPEARANCES A GOOD GIRL TOO DESCRIBING HER GENERALLY I MAY SAY THAT SHE HAD A SMALL HEAD WELL CARRIED AND WELL SET ON HER SHOULDERS BRIGHT GRAY EYES THAT LOOKED AT YOU HONESTLY AND MEANT WHAT THEY LOOKED A TRIM SLIGHT LITTLE FIGURE TOO SLIGHT FOR OUR ENGLISH NOTIONS OF BEAUTY A STRONG AMERICAN ACCENT AND A RARE THING IN AMERICA A PLEASANTLY TONED VOICE WHICH MADE THE ACCENT AGREEABLE TO ENGLISH EARS", "subset": "test_clean", "task_type": "understanding", "prediction": "a pretty girl and so far as i could judge by appearances a good girl too describing her generally i may say that she had a small head well carried and well set on her shoulders bright gray eyes that looked at you honestly and meant what they looked a trim slight little figure too slight for our english notions of beauty a strong american accent and a rare thing in america a pleasantly toned voice which made the accent agreeable to english ears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0017.flac", "answer": "THE ONLY CHEERFUL CONVERSATION WAS THE CONVERSATION ACROSS THE TABLE BETWEEN NAOMI AND ME", "subset": "test_clean", "task_type": "understanding", "prediction": "the only cheerful conversation was the conversation across the table between naomi and me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0011.flac", "answer": "MISTER JAGO IS AN AMERICAN PHILIP", "subset": "test_clean", "task_type": "understanding", "prediction": "mr yago is an american philip", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0023.flac", "answer": "YOU WERE QUITE RIGHT TO SAY NO AMBROSE BEGAN NEVER SMOKE WITH JOHN JAGO HIS CIGARS WILL POISON YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "you were quite right to say no ambrose began never smoke with johnny algo his cigars will poison you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36377/5142-36377-0013.flac", "answer": "THEY POINTEDLY DREW BACK FROM JOHN JAGO AS HE APPROACHED THE EMPTY CHAIR NEXT TO ME AND MOVED ROUND TO THE OPPOSITE SIDE OF THE TABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "they pointedly drew back from john yago as he approached the empty chair next to me and moved round to the opposite side of the table", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36586/5142-36586-0003.flac", "answer": "BUT THIS SUBJECT WILL BE MORE PROPERLY DISCUSSED WHEN WE TREAT OF THE DIFFERENT RACES OF MANKIND", "subset": "test_clean", "task_type": "understanding", "prediction": "but this subject will be more properly discussed when we treat of the different races of mankind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36586/5142-36586-0002.flac", "answer": "THE VARIABILITY OF MULTIPLE PARTS", "subset": "test_clean", "task_type": "understanding", "prediction": "the variability of multiple parts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36586/5142-36586-0004.flac", "answer": "EFFECTS OF THE INCREASED USE AND DISUSE OF PARTS", "subset": "test_clean", "task_type": "understanding", "prediction": "effects of the increased use and disuse of parts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36586/5142-36586-0001.flac", "answer": "SO IT IS WITH THE LOWER ANIMALS", "subset": "test_clean", "task_type": "understanding", "prediction": "so it is with the lower animals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5142/36586/5142-36586-0000.flac", "answer": "IT IS MANIFEST THAT MAN IS NOW SUBJECT TO MUCH VARIABILITY", "subset": "test_clean", "task_type": "understanding", "prediction": "it is manifest that man is now subject to much variability", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0069.flac", "answer": "IF YOU WILL GIVE US YOUR PROMISE TO MEET CAPTAIN BATTLEAX HERE AT THIS TIME TO MORROW WE WILL STRETCH A POINT AND DELAY THE DEPARTURE OF THE JOHN BRIGHT FOR TWENTY FOUR HOURS", "subset": "test_clean", "task_type": "understanding", "prediction": "if you will give us your promise to meet captain adalax here at this time to morrow we will stretch a point and delay the departure of the john bright for twenty four hours", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0048.flac", "answer": "WHAT WOULD BECOME OF YOUR GUN WERE I TO KIDNAP YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "what would become of your gun were i to kidnap you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0023.flac", "answer": "WE SAT WITH THE OFFICERS SOME LITTLE TIME AFTER DINNER AND THEN WENT ASHORE", "subset": "test_clean", "task_type": "understanding", "prediction": "we sat with the officer some little time after dinner and then went ashore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0061.flac", "answer": "YOU WILL CARRY OUT WITH YOU ONE HUNDRED MEN OF THE NORTH NORTH WEST BIRMINGHAM REGIMENT WHICH WILL PROBABLY SUFFICE FOR YOUR OWN SECURITY AS IT IS THOUGHT THAT IF MISTER NEVERBEND BE WITHDRAWN THE PEOPLE WILL REVERT EASILY TO THEIR OLD HABITS OF OBEDIENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "you will carry out with you one hundred men of the north north west birmingham regiment which will probably suffice for your own security as it is thought that if mr neverbend be withdrawn the people will revert easily to their old habits of obedience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0059.flac", "answer": "BUT IT IS SURMISED THAT YOU WILL FIND DIFFICULTIES IN THE WAY OF YOUR ENTERING AT ONCE UPON YOUR GOVERNMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "but it is surmised that you will find difficulties in the way of your entering at once upon your governor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0025.flac", "answer": "WHAT COULD I DO NOW BUT JUST LAY MYSELF DOWN AND DIE", "subset": "test_clean", "task_type": "understanding", "prediction": "what could i do now but just lay myself down and die", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0051.flac", "answer": "WHAT WORLD WIDE INIQUITY SUCH A SPEECH AS THAT DISCLOSES SAID I STILL TURNING MYSELF TO THE CAPTAIN FOR THOUGH I WOULD HAVE CRUSHED THEM BOTH BY MY WORDS HAD IT BEEN POSSIBLE MY DISLIKE CENTRED ITSELF ON SIR FERDINANDO", "subset": "test_clean", "task_type": "understanding", "prediction": "what world wide iniquity such a speech as that discloses said i still turning myself to the captain for though i would have crushed them both by my words had it been possible my dislike centered itself on sir ferdinando", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0003.flac", "answer": "AS I SPOKE I MADE HIM A GRACIOUS BOW AND I THINK I SHOWED HIM BY MY MODE OF ADDRESS THAT I DID NOT BEAR ANY GRUDGE AS TO MY INDIVIDUAL SELF", "subset": "test_clean", "task_type": "understanding", "prediction": "as i spoke i made him a gracious bow and i think i showed him by my mode of address that i did not bear any grudge as to my individual self", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0042.flac", "answer": "YOU HEAR WHAT SIR FERDINANDO BROWN HAS SAID REPLIED CAPTAIN BATTLEAX", "subset": "test_clean", "task_type": "understanding", "prediction": "you hear what sir ferdinando brown has said replied captain battleax", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0011.flac", "answer": "I DID NOT MEAN SAID CAPTAIN BATTLEAX TO TOUCH UPON PUBLIC SUBJECTS AT SUCH A MOMENT AS THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "i did not mean said captain battleax to touch upon public subjects at such a moment as this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0031.flac", "answer": "YOU HAVE RECEIVED US WITH ALL THAT COURTESY AND HOSPITALITY FOR WHICH YOUR CHARACTER IN ENGLAND STANDS SO HIGH", "subset": "test_clean", "task_type": "understanding", "prediction": "you have received us with all that courtesy and hospitality for which your character in england stands so high", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0028.flac", "answer": "JACK WOULD BECOME EVA'S HAPPY HUSBAND AND WOULD REMAIN AMIDST THE HURRIED DUTIES OF THE EAGER WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "jack would become eva s happy husband and would remain amidst the hurried duties of the eager world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0044.flac", "answer": "I WAS TO BE TAKEN AWAY AND CARRIED TO ENGLAND OR ELSEWHERE OR DROWNED UPON THE VOYAGE IT MATTERED NOT WHICH", "subset": "test_clean", "task_type": "understanding", "prediction": "i was to be taken away and carried to england or elsewhere or drowned upon the voyage it mattered not which", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0062.flac", "answer": "WHEN DO YOU INTEND THAT THE JOHN BRIGHT SHALL START", "subset": "test_clean", "task_type": "understanding", "prediction": "when do you intend that the john bright shall start", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0005.flac", "answer": "WE HAVE OUR LITTLE STRUGGLES HERE AS ELSEWHERE AND ALL THINGS CANNOT BE DONE BY ROSE WATER", "subset": "test_clean", "task_type": "understanding", "prediction": "we have our little struggles here as elsewhere and all things cannot be done by rosewater", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0035.flac", "answer": "THAT IS ALL QUITE TRUE MISTER NEVERBEND SAID SIR FERDINANDO BROWN", "subset": "test_clean", "task_type": "understanding", "prediction": "that is all quite true mr neverbend said sir ferdinando brown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0029.flac", "answer": "THINKING OF ALL THIS I WENT TO SLEEP", "subset": "test_clean", "task_type": "understanding", "prediction": "thinking of all this i went to sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0024.flac", "answer": "HOW MUCH OF EVIL OF REAL ACCOMPLISHED EVIL HAD THERE NOT OCCURRED TO ME DURING THE LAST FEW DAYS", "subset": "test_clean", "task_type": "understanding", "prediction": "how much of evil of real accomplished evil had there not occurred to me during the last few days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0020.flac", "answer": "OH YES SAID JACK AND I'M NOWHERE", "subset": "test_clean", "task_type": "understanding", "prediction": "oh yes said jack and i am nowhere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0047.flac", "answer": "YOU PROPOSE TO KIDNAP ME I SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "you propose to kidnap me i said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0041.flac", "answer": "THERE CAME UPON ME A SUDDEN SHOCK WHEN I HEARD THESE WORDS WHICH EXCEEDED ANYTHING WHICH I HAD YET FELT", "subset": "test_clean", "task_type": "understanding", "prediction": "there came upon me a sudden shock when i heard these words which exceeded anything which i had yet felt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0021.flac", "answer": "BUT I MEAN TO HAVE MY INNINGS BEFORE LONG", "subset": "test_clean", "task_type": "understanding", "prediction": "but i mean to have my innings before long", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0053.flac", "answer": "WERE I TO COMPLY WITH YOUR ORDERS WITHOUT EXPRESSING MY OWN OPINION I SHOULD SEEM TO HAVE DONE SO WILLINGLY HEREAFTER", "subset": "test_clean", "task_type": "understanding", "prediction": "were i to comply with your orders without expressing my own opinion i should seem to have done so willingly hereafter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0068.flac", "answer": "YOUR POWER IS SUFFICIENT I SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "your power is sufficient i said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0065.flac", "answer": "I SHALL BE HAPPY TO TAKE CHARGE OF THEM SAID SIR FERDINANDO", "subset": "test_clean", "task_type": "understanding", "prediction": "i shall be happy to take charge of them said sir ferdinando", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0015.flac", "answer": "I AND MY WIFE AND SON AND THE TWO CRASWELLERS AND THREE OR FOUR OTHERS AGREED TO DINE ON BOARD THE SHIP ON THE NEXT", "subset": "test_clean", "task_type": "understanding", "prediction": "i and my wife and son and the two cresswellers and three or four others agreed to dine on board the ship on the next", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0008.flac", "answer": "THE LADIES IN COMPLIANCE WITH THAT SOFTNESS OF HEART WHICH IS THEIR CHARACTERISTIC ARE ON ONE SIDE AND THE MEN BY WHOM THE WORLD HAS TO BE MANAGED ARE ON THE OTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "the ladies in compliance with that softness of heart which is their characteristic are on one side and the men by whom the world has to be managed are on the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0010.flac", "answer": "THEIR MASTERS SAID MISSUS NEVERBEND", "subset": "test_clean", "task_type": "understanding", "prediction": "their masters said mrs neverbend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0055.flac", "answer": "SIR I HAVE IT IN COMMAND TO INFORM YOUR EXCELLENCY THAT YOU HAVE BEEN APPOINTED GOVERNOR OF THE CROWN COLONY WHICH IS CALLED BRITANNULA", "subset": "test_clean", "task_type": "understanding", "prediction": "sir i have it in command to inform your excellency that you have been appointed governor of the crown colony which is called brittanula", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0045.flac", "answer": "THEN THE REPUBLIC OF BRITANNULA WAS TO BE DECLARED AS NON EXISTENT AND THE BRITISH FLAG WAS TO BE EXALTED AND A BRITISH GOVERNOR INSTALLED IN THE EXECUTIVE CHAMBERS", "subset": "test_clean", "task_type": "understanding", "prediction": "then the republic of britannula was to be declared as non existent and the british flag was to be exalted and a british governor installed in the executive chambers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0039.flac", "answer": "I CAN ASSURE YOU HE HAS NOT EVEN ALLOWED ME TO SEE THE TRIGGER SINCE I HAVE BEEN ON BOARD", "subset": "test_clean", "task_type": "understanding", "prediction": "i can assure you he has not even allowed me to see the trigger since i have been on board", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0036.flac", "answer": "I CAN AFFORD TO SMILE BECAUSE I AM ABSOLUTELY POWERLESS BEFORE YOU BUT I DO NOT THE LESS FEEL THAT IN A MATTER IN WHICH THE PROGRESS OF THE WORLD IS CONCERNED I OR RATHER WE HAVE BEEN PUT DOWN BY BRUTE FORCE", "subset": "test_clean", "task_type": "understanding", "prediction": "i can afford to smile because i am absolutely powerless before you but i do not the less feel that in a matter of which the progress of the world is concerned i or rather we have been put down by brute force", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0046.flac", "answer": "YOU MAY BE QUITE SURE IT'S THERE SAID CAPTAIN BATTLEAX AND THAT I CAN SO USE IT AS TO HALF OBLITERATE YOUR TOWN WITHIN TWO MINUTES OF MY RETURN ON BOARD", "subset": "test_clean", "task_type": "understanding", "prediction": "you may be quite sure it is there said captain battleax and that i can so use it as to half obliterate your town within two minutes of my return on board", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0040.flac", "answer": "THEN SAID SIR FERDINANDO THERE IS NOTHING FOR IT BUT THAT HE MUST TAKE YOU WITH HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "then said sir ferdinando there is nothing for it but that we must take you with him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0070.flac", "answer": "AND THIS PLAN WAS ADOPTED TOO IN ORDER TO EXTRACT FROM ME A PROMISE THAT I WOULD DEPART IN PEACE", "subset": "test_clean", "task_type": "understanding", "prediction": "and this plan was adopted too in order to extract from me a promise that i would depart in peace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0049.flac", "answer": "LIEUTENANT CROSSTREES IS A VERY GALLANT OFFICER", "subset": "test_clean", "task_type": "understanding", "prediction": "lieutenant crosstrees is a very gallant officer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0066.flac", "answer": "THEY OF COURSE MUST ALL BE ALTERED", "subset": "test_clean", "task_type": "understanding", "prediction": "they of course must all be otter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0058.flac", "answer": "IT IS FOUNDED ON THE ACKNOWLEDGED WEAKNESS OF THOSE WHO SURVIVE THAT PERIOD OF LIFE AT WHICH MEN CEASE TO WORK", "subset": "test_clean", "task_type": "understanding", "prediction": "it is founded on the acknowledged weakness of those who survive that period of life at which men cease to work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0026.flac", "answer": "AND THE DEATH OF WHICH I DREAMT COULD NOT ALAS", "subset": "test_clean", "task_type": "understanding", "prediction": "and the death of which i dreamt could not alas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0001.flac", "answer": "HAD EVA CRASWELLER NOT BEEN GOOD LOOKING HAD JACK BEEN STILL AT COLLEGE HAD SIR KENNINGTON OVAL REMAINED IN ENGLAND HAD MISTER BUNNIT AND THE BAR KEEPER NOT SUCCEEDED IN STOPPING MY CARRIAGE ON THE HILL SHOULD I HAVE SUCCEEDED IN ARRANGING FOR THE FINAL DEPARTURE OF MY OLD FRIEND", "subset": "test_clean", "task_type": "understanding", "prediction": "had eva cresswell or not been good looking had jack been still at college had sir kennington oval remained in england had mr bunnet and the barkeeper not succeeded in stopping my carriage on the hill should i have succeeded in arranging for the final departure of my old friend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0017.flac", "answer": "MY WIFE ON THE SPUR OF THE MOMENT MANAGED TO GIVE THE GENTLEMEN A VERY GOOD DINNER", "subset": "test_clean", "task_type": "understanding", "prediction": "my wife on the spur of the moment managed to give the gentlemen a very good dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0054.flac", "answer": "THE LETTER RAN AS FOLLOWS", "subset": "test_clean", "task_type": "understanding", "prediction": "the letter ran as follows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0002.flac", "answer": "ON ARRIVING AT HOME AT MY OWN RESIDENCE I FOUND THAT OUR SALON WAS FILLED WITH A BRILLIANT COMPANY", "subset": "test_clean", "task_type": "understanding", "prediction": "on arriving at home at my own residence i found that our salon was filled with a brilliant company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0033.flac", "answer": "BUT YOUR POWER IS SO SUPERIOR TO ANY THAT I CAN ADVANCE AS TO MAKE US HERE FEEL THAT THERE IS NO DISGRACE IN YIELDING TO IT", "subset": "test_clean", "task_type": "understanding", "prediction": "but your power is so superior to any that i can advance as to make us here feel that there is no disgrace in yielding to it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0034.flac", "answer": "NOT A DOUBT BUT HAD YOUR FORCE BEEN ONLY DOUBLE OR TREBLE OUR OWN I SHOULD HAVE FOUND IT MY DUTY TO STRUGGLE WITH YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "not a doubt but had your force been only double or treble our own i should have found it my duty to struggle with you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0067.flac", "answer": "OR OF THE HABITS OF OUR PEOPLE IT IS QUITE IMPOSSIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "or of the habits of our people it is quite impossible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0009.flac", "answer": "NO DOUBT IN PROCESS OF TIME THE LADIES WILL FOLLOW", "subset": "test_clean", "task_type": "understanding", "prediction": "no doubt in process of time the ladies will follow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0006.flac", "answer": "WE ARE QUITE SATISFIED NOW CAPTAIN BATTLEAX SAID MY WIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "we are quite satisfied now captain battleaxe said my wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0022.flac", "answer": "OF WHAT MISSUS NEVERBEND HAD GONE THROUGH IN PROVIDING BIRDS BEASTS AND FISHES NOT TO TALK OF TARTS AND JELLIES FOR THE DINNER OF THAT DAY NO ONE BUT MYSELF CAN HAVE ANY IDEA BUT IT MUST BE ADMITTED THAT SHE ACCOMPLISHED HER TASK WITH THOROUGH SUCCESS", "subset": "test_clean", "task_type": "understanding", "prediction": "of what mrs neverbend had gone through in providing birds beasts and fishes not to talk of tarts and jellies for the dinner of that day no one but myself can have any idea but it must be admitted that she accomplished her task with thorough success", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0014.flac", "answer": "SIR KENNINGTON OVAL IS A VERY FINE PLAYER SAID MY WIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "sir kennington oval is a very fine player said my wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0057.flac", "answer": "BUT IN THEIR SELECTION OF A CONSTITUTION THE BRITANNULISTS HAVE UNFORTUNATELY ALLOWED THEMSELVES BUT ONE DELIBERATIVE ASSEMBLY AND HENCE HAVE SPRUNG THEIR PRESENT DIFFICULTIES", "subset": "test_clean", "task_type": "understanding", "prediction": "but in their selection of a constitution the britannialists have unfortunately allowed themselves but one deliberate assembly and hence has sprung their present difficulties", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0030.flac", "answer": "MISTER NEVERBEND BEGAN THE CAPTAIN AND I OBSERVED THAT UP TO THAT MOMENT HE HAD GENERALLY ADDRESSED ME AS PRESIDENT IT CANNOT BE DENIED THAT WE HAVE COME HERE ON AN UNPLEASANT MISSION", "subset": "test_clean", "task_type": "understanding", "prediction": "mr neverbend began the captain and i observed that up to that moment he had generally addressed me as president it cannot be denied that we have come here on an unpleasant mission", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0038.flac", "answer": "THEREFORE I FEEL MYSELF QUITE ABLE AS PRESIDENT OF THIS REPUBLIC TO RECEIVE YOU WITH A COURTESY DUE TO THE SERVANTS OF A FRIENDLY ALLY", "subset": "test_clean", "task_type": "understanding", "prediction": "therefore i feel myself quite able as president of this republic to receive you with the courtesy due to the servants of a friendly ally", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0004.flac", "answer": "I HAVE COME TO YOUR SHORES MISTER PRESIDENT WITH THE PURPOSE OF SEEING HOW THINGS ARE PROGRESSING IN THIS DISTANT QUARTER OF THE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "i have come to your shores mr president with the purpose of seeing how things are progressing in this distant quarter of the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0050.flac", "answer": "ONE OF US ALWAYS REMAINS ON BOARD WHILE THE OTHER IS ON SHORE", "subset": "test_clean", "task_type": "understanding", "prediction": "one of us always remains on board while the other is on shore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0060.flac", "answer": "THE JOHN BRIGHT IS ARMED WITH A WEAPON OF GREAT POWER AGAINST WHICH IT IS IMPOSSIBLE THAT THE PEOPLE OF BRITANNULA SHOULD PREVAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "the john bright is armed with a weapon of great power against which it is impossible that the people of britain yule should prevail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0019.flac", "answer": "THEN THERE WERE THREE OR FOUR LEADING MEN OF THE COMMUNITY WITH THEIR WIVES WHO WERE FOR THE MOST PART THE FATHERS AND MOTHERS OF THE YOUNG LADIES", "subset": "test_clean", "task_type": "understanding", "prediction": "then there were three or four leading men of the community with their wives who were for the most part the fathers and mothers of the young ladies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0052.flac", "answer": "YOU WILL ALLOW ME TO SUGGEST SAID HE THAT THAT IS A MATTER OF OPINION", "subset": "test_clean", "task_type": "understanding", "prediction": "you will allow me to suggest said he that that is a matter of opinion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0027.flac", "answer": "WHEN THIS CAPTAIN SHOULD HAVE TAKEN HIMSELF AND HIS VESSEL BACK TO ENGLAND I WOULD RETIRE TO A SMALL FARM WHICH I POSSESSED AT THE FARTHEST SIDE OF THE ISLAND AND THERE IN SECLUSION WOULD I END MY DAYS", "subset": "test_clean", "task_type": "understanding", "prediction": "when this captain should have taken himself and his vessel back to england i would retire to a small farm which i possessed at the further side of the island and there in seclusion would i end my days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0007.flac", "answer": "QUITE SATISFIED SAID EVA", "subset": "test_clean", "task_type": "understanding", "prediction": "quite satisfied said eva", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0063.flac", "answer": "TO DAY I SHOUTED", "subset": "test_clean", "task_type": "understanding", "prediction": "to day i shouted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0018.flac", "answer": "THIS SHE SAID WAS TRUE HOSPITALITY AND I AM NOT SURE THAT I DID NOT AGREE WITH HER", "subset": "test_clean", "task_type": "understanding", "prediction": "this she said was true hospitality and i am not sure that i did not agree with her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0012.flac", "answer": "MISSUS NEVERBEND YOU MUST INDEED BE PROUD OF YOUR SON", "subset": "test_clean", "task_type": "understanding", "prediction": "mrs neverbend you must indeed be proud of your son", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0016.flac", "answer": "THIS I FELT WAS PAID TO ME AS BEING PRESIDENT OF THE REPUBLIC AND I ENDEAVOURED TO BEHAVE MYSELF WITH SUCH MINGLED HUMILITY AND DIGNITY AS MIGHT BEFIT THE OCCASION BUT I COULD NOT BUT FEEL THAT SOMETHING WAS WANTING TO THE SIMPLICITY OF MY ORDINARY LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "this i felt was paid to me as being president of the republic and i endeavored to behave myself with such mingled humility and dignity as might befit the occasion but i could not but feel that something was wanting to the simplicity of my ordinary life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0043.flac", "answer": "BUT WHAT IS THE DELICATE MISSION I ASKED", "subset": "test_clean", "task_type": "understanding", "prediction": "but what is the delicate mission i asked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0064.flac", "answer": "AND I HAVE NO ONE READY TO WHOM I CAN GIVE UP THE ARCHIVES OF THE GOVERNMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "and i have no one ready to whom i can give up the archives of the government", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0000.flac", "answer": "I REMAINED THERE ALONE FOR MANY HOURS BUT I MUST ACKNOWLEDGE THAT BEFORE I LEFT THE CHAMBERS I HAD GRADUALLY BROUGHT MYSELF TO LOOK AT THE MATTER IN ANOTHER LIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "i remained there alone for many hours but i must acknowledge that before i left the chambers i had gradually brought myself to look at the matter in another light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0032.flac", "answer": "IT IS A DUTY SAID I", "subset": "test_clean", "task_type": "understanding", "prediction": "it is a duty said i", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0013.flac", "answer": "JACK HAD BEEN STANDING IN THE FAR CORNER OF THE ROOM TALKING TO EVA AND WAS NOW REDUCED TO SILENCE BY HIS PRAISES", "subset": "test_clean", "task_type": "understanding", "prediction": "jack had been standing in the far corner of the room talking to eva and was now reduced to silence by his praises", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0037.flac", "answer": "YOU HAVE COME TO US THREATENING US WITH ABSOLUTE DESTRUCTION", "subset": "test_clean", "task_type": "understanding", "prediction": "you have come to us threatening us with absolute destruction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8455/210777/8455-210777-0056.flac", "answer": "THE PECULIAR CIRCUMSTANCES OF THE COLONY ARE WITHIN YOUR EXCELLENCY'S KNOWLEDGE", "subset": "test_clean", "task_type": "understanding", "prediction": "the peculiar circumstances of the colony are within your excellency s knowledge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0006.flac", "answer": "THEY ARE ALL SKETCHES MADE ABOUT THE VILLA D'ESTE YOU SEE", "subset": "test_clean", "task_type": "understanding", "prediction": "they are all sketches made about the villa d estes you see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0034.flac", "answer": "HE FELT A TREMOR RUN THROUGH THE SLENDER YELLOW FIGURE IN FRONT OF HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "he felt a tremor run through the slender yellow figure in front of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0004.flac", "answer": "I SHOULD NEVER HAVE ASKED YOU IF MOLLY HAD BEEN HERE FOR I REMEMBER YOU DON'T LIKE ENGLISH COOKERY", "subset": "test_clean", "task_type": "understanding", "prediction": "i should never have asked you if molly had been here for i remember you dont like english cookery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0026.flac", "answer": "HAVE I TOLD YOU ABOUT MY NEW PLAY", "subset": "test_clean", "task_type": "understanding", "prediction": "have i told you about my new play", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0023.flac", "answer": "THE STRANGE WOMAN AND HER PASSIONATE SENTENCE THAT RANG OUT SO SHARPLY HAD FRIGHTENED THEM BOTH", "subset": "test_clean", "task_type": "understanding", "prediction": "the strange woman and her passionate sentence that rang out so sharply had frightened them both", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0019.flac", "answer": "COME WE'LL HAVE OUR COFFEE IN THE OTHER ROOM AND YOU CAN SMOKE", "subset": "test_clean", "task_type": "understanding", "prediction": "come we ll have our coffee in the other room and you can smoke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0013.flac", "answer": "HAVE YOU BEEN IN PARIS MUCH THESE LATE YEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "have you been in paris much these late years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0016.flac", "answer": "HER HAIR IS STILL LIKE FLAX AND HER BLUE EYES ARE JUST LIKE A BABY'S AND SHE HAS THE SAME THREE FRECKLES ON HER LITTLE NOSE AND TALKS ABOUT GOING BACK TO HER BAINS DE MER", "subset": "test_clean", "task_type": "understanding", "prediction": "her hair is still like flax and her blue eyes are just like a baby s and she has the same three freckles on her little nose and talks about going back to urbana mare", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0032.flac", "answer": "HE STOOD A LITTLE BEHIND HER AND TRIED TO STEADY HIMSELF AS HE SAID IT'S SOFT AND MISTY SEE HOW WHITE THE STARS ARE", "subset": "test_clean", "task_type": "understanding", "prediction": "he stood a little behind her and tried to steady himself as he said it is soft and misty see how white the stars are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0018.flac", "answer": "DO YOU REMEMBER THAT FIRST WALK WE TOOK TOGETHER IN PARIS", "subset": "test_clean", "task_type": "understanding", "prediction": "do you remember that first walk we took together in paris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0014.flac", "answer": "THERE ARE FEW CHANGES IN THE OLD QUARTER", "subset": "test_clean", "task_type": "understanding", "prediction": "there are a few changes in the old quarter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0011.flac", "answer": "THERE IS NOTHING ELSE THAT LOOKS SO JOLLY", "subset": "test_clean", "task_type": "understanding", "prediction": "there is nothing else that looks so jolly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0024.flac", "answer": "BARTLEY STARTED WHEN HILDA RANG THE LITTLE BELL BESIDE HER DEAR ME WHY DID YOU DO THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "bartley started when hilda rang the little bell beside her dear me why did you do that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0021.flac", "answer": "WHAT SHE WANTED FROM US WAS NEITHER OUR FLOWERS NOR OUR FRANCS BUT JUST OUR YOUTH", "subset": "test_clean", "task_type": "understanding", "prediction": "what she wanted from us was neither our flowers nor our francs but just our youth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0033.flac", "answer": "FOR A LONG TIME NEITHER HILDA NOR BARTLEY SPOKE", "subset": "test_clean", "task_type": "understanding", "prediction": "for a long time neither hilda nor bartley spoke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0025.flac", "answer": "IT WAS VERY JOLLY HE MURMURED LAZILY AS MARIE CAME IN TO TAKE AWAY THE COFFEE", "subset": "test_clean", "task_type": "understanding", "prediction": "it was very jolly he murmured lazily as marie came in to take away the coffee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0008.flac", "answer": "I'VE MANAGED TO SAVE SOMETHING EVERY YEAR AND THAT WITH HELPING MY THREE SISTERS NOW AND THEN AND TIDING POOR COUSIN MIKE OVER BAD SEASONS", "subset": "test_clean", "task_type": "understanding", "prediction": "i have managed to save something every year and that with helping my three sisters now and then and tiding poor cousin mike over bad seasons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0027.flac", "answer": "WHEN SHE FINISHED ALEXANDER SHOOK HIMSELF OUT OF A REVERIE", "subset": "test_clean", "task_type": "understanding", "prediction": "when she finished alexander shook himself out of a reverie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0020.flac", "answer": "I THINK WE DID SHE ANSWERED DEMURELY", "subset": "test_clean", "task_type": "understanding", "prediction": "i think we did she answered demurely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0022.flac", "answer": "THEY WERE BOTH REMEMBERING WHAT THE WOMAN HAD SAID WHEN SHE TOOK THE MONEY GOD GIVE YOU A HAPPY LOVE", "subset": "test_clean", "task_type": "understanding", "prediction": "they were both remembering what the woman had said when she took the money god give you a happy love", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0000.flac", "answer": "HILDA WAS VERY NICE TO HIM AND HE SAT ON THE EDGE OF HIS CHAIR FLUSHED WITH HIS CONVERSATIONAL EFFORTS AND MOVING HIS CHIN ABOUT NERVOUSLY OVER HIS HIGH COLLAR", "subset": "test_clean", "task_type": "understanding", "prediction": "hilda was very nice to him and he sat on the edge of his chair flushed with his conversational efforts and moving his chin about nervously over his high collar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0030.flac", "answer": "ALEXANDER WENT OVER AND OPENED THE WINDOW FOR HER", "subset": "test_clean", "task_type": "understanding", "prediction": "alexander went over and opened the window for her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0003.flac", "answer": "WHEN BARTLEY ARRIVED AT BEDFORD SQUARE ON SUNDAY EVENING MARIE THE PRETTY LITTLE FRENCH GIRL MET HIM AT THE DOOR AND CONDUCTED HIM UPSTAIRS", "subset": "test_clean", "task_type": "understanding", "prediction": "when bartley arrived at bedford square on sunday evening marie the pretty little french girl met him at the door and conducted him upstairs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0015.flac", "answer": "DON'T I THOUGH I'M SO SORRY TO HEAR IT HOW DID HER SON TURN OUT", "subset": "test_clean", "task_type": "understanding", "prediction": "dont i though i am so sorry to hear it how did her son turn out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0010.flac", "answer": "THERE WAS WATERCRESS SOUP AND SOLE AND A DELIGHTFUL OMELETTE STUFFED WITH MUSHROOMS AND TRUFFLES AND TWO SMALL RARE DUCKLINGS AND ARTICHOKES AND A DRY YELLOW RHONE WINE OF WHICH BARTLEY HAD ALWAYS BEEN VERY FOND", "subset": "test_clean", "task_type": "understanding", "prediction": "there was watercress soup and sole and a delightful omelette stuffed with mushrooms and truffles and two small rare ducklings and artichokes and a dry yellow rhone wine of which bartley had always been very fond", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0001.flac", "answer": "THEY ASKED HIM TO COME TO SEE THEM IN CHELSEA AND THEY SPOKE VERY TENDERLY OF HILDA", "subset": "test_clean", "task_type": "understanding", "prediction": "they asked him to come to see them in chelsea and they spoke very tenderly of hilda", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0028.flac", "answer": "NONSENSE OF COURSE I CAN'T REALLY SING EXCEPT THE WAY MY MOTHER AND GRANDMOTHER DID BEFORE ME", "subset": "test_clean", "task_type": "understanding", "prediction": "nonsense of course i can t really sing except the way my mother and grandmother did before me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0029.flac", "answer": "IT'S REALLY TOO WARM IN THIS ROOM TO SING DON'T YOU FEEL IT", "subset": "test_clean", "task_type": "understanding", "prediction": "its really too warm in this room to sing dont you feel it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0002.flac", "answer": "LAMB WOULDN'T CARE A GREAT DEAL ABOUT MANY OF THEM I FANCY", "subset": "test_clean", "task_type": "understanding", "prediction": "lamb wouldnt care a great deal about many of them i fancy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0005.flac", "answer": "I HAVEN'T HAD A CHANCE YET TO TELL YOU WHAT A JOLLY LITTLE PLACE I THINK THIS IS", "subset": "test_clean", "task_type": "understanding", "prediction": "i haven t had a chance yet to tell you what a jolly little place i think this is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0035.flac", "answer": "BARTLEY LEANED OVER HER SHOULDER WITHOUT TOUCHING HER AND WHISPERED IN HER EAR YOU ARE GIVING ME A CHANCE YES", "subset": "test_clean", "task_type": "understanding", "prediction": "bartley leaned over her shoulder without touching her and whispered in her ear you are giving me a chance yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0031.flac", "answer": "THERE JUST IN FRONT", "subset": "test_clean", "task_type": "understanding", "prediction": "there just in front", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0007.flac", "answer": "THOSE FELLOWS ARE ALL VERY LOYAL EVEN MAINHALL", "subset": "test_clean", "task_type": "understanding", "prediction": "those fellows are all very loyal even main hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0012.flac", "answer": "THANK YOU BUT I DON'T LIKE IT SO WELL AS THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "thank you but i don t like it so well as this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0009.flac", "answer": "IT'S NOT PARTICULARLY RARE SHE SAID BUT SOME OF IT WAS MY MOTHER'S", "subset": "test_clean", "task_type": "understanding", "prediction": "its not particularly rare she said but some of it was my mothers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0017.flac", "answer": "HOW JOLLY IT WAS BEING YOUNG HILDA", "subset": "test_clean", "task_type": "understanding", "prediction": "how jolly it was being young hilda", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2273/4446-2273-0036.flac", "answer": "ALEXANDER UNCLENCHED THE TWO HANDS AT HIS SIDES", "subset": "test_clean", "task_type": "understanding", "prediction": "alexander clenched the two hands at his sides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0035.flac", "answer": "ALEXANDER ROSE AND SHOOK HIMSELF ANGRILY YES I KNOW I'M COWARDLY", "subset": "test_clean", "task_type": "understanding", "prediction": "alexander rose and shook himself angrily yes i know i am cowardly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0036.flac", "answer": "HE TOOK HER ROUGHLY IN HIS ARMS DO YOU KNOW WHAT I MEAN", "subset": "test_clean", "task_type": "understanding", "prediction": "he took her roughly in his arms do you know what i mean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0023.flac", "answer": "ALEXANDER GROANED I MEANT TO BUT SOMEHOW I COULDN'T", "subset": "test_clean", "task_type": "understanding", "prediction": "alexander groaned i meant to but somehow i couldnt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0024.flac", "answer": "SHE PRESSED HIS HAND GENTLY IN GRATITUDE", "subset": "test_clean", "task_type": "understanding", "prediction": "she pressed his hand gently in gratitude", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0039.flac", "answer": "I MUST KNOW ABOUT YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "i must know about you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0019.flac", "answer": "THE WORLD IS ALL THERE JUST AS IT USED TO BE BUT I CAN'T GET AT IT ANY MORE", "subset": "test_clean", "task_type": "understanding", "prediction": "the world is all there just as it used to be but i can t get at it any more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0033.flac", "answer": "WHAT I MEAN IS THAT I WANT YOU TO PROMISE NEVER TO SEE ME AGAIN NO MATTER HOW OFTEN I COME NO MATTER HOW HARD I BEG", "subset": "test_clean", "task_type": "understanding", "prediction": "what i mean is that i want you to promise never to see me again no matter how often i come no matter how hard i beg", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0015.flac", "answer": "HE PULLED UP A WINDOW AS IF THE AIR WERE HEAVY", "subset": "test_clean", "task_type": "understanding", "prediction": "he pulled up a window as if the air were heavy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0014.flac", "answer": "I CAN'T STAND SEEING YOU MISERABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "i can t stand seeing you miserable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0007.flac", "answer": "SHE PUSHED HIM TOWARD THE BIG CHAIR BY THE FIRE AND SAT DOWN ON A STOOL AT THE OPPOSITE SIDE OF THE HEARTH HER KNEES DRAWN UP TO HER CHIN LAUGHING LIKE A HAPPY LITTLE GIRL", "subset": "test_clean", "task_type": "understanding", "prediction": "she pushed him toward the big chair by the fire and sat down on a stool at the opposite side of the hearth her knees drawn up to her chin laughing like a happy little girl", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0012.flac", "answer": "SHE LOOKED AT HIS HEAVY SHOULDERS AND BIG DETERMINED HEAD THRUST FORWARD LIKE A CATAPULT IN LEASH", "subset": "test_clean", "task_type": "understanding", "prediction": "she looked at his heavy shoulders and big determined head thrust forward like a catapult in leash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0020.flac", "answer": "IT WAS MYSELF I WAS DEFYING HILDA", "subset": "test_clean", "task_type": "understanding", "prediction": "it was myself i was defying hilda", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0002.flac", "answer": "ALEXANDER PACED UP AND DOWN THE HALLWAY BUTTONING AND UNBUTTONING HIS OVERCOAT UNTIL SHE RETURNED AND TOOK HIM UP TO HILDA'S LIVING ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "alexander paced up and down the hallway buttoning and unbuttoning his overcoat until she returned and took him up to hilda s living room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0037.flac", "answer": "OH BARTLEY WHAT AM I TO DO", "subset": "test_clean", "task_type": "understanding", "prediction": "oh bartley what am i to do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0001.flac", "answer": "SHE BLUSHED AND SMILED AND FUMBLED HIS CARD IN HER CONFUSION BEFORE SHE RAN UPSTAIRS", "subset": "test_clean", "task_type": "understanding", "prediction": "she blushed and smiled and fumbled his card in her confusion before she ran upstairs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0016.flac", "answer": "HILDA WATCHED HIM FROM HER CORNER TREMBLING AND SCARCELY BREATHING DARK SHADOWS GROWING ABOUT HER EYES IT", "subset": "test_clean", "task_type": "understanding", "prediction": "hilda watched him from the corner trembling and scarcely breathing dark shadows growing about her eyes it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0022.flac", "answer": "BUT WHY DIDN'T YOU TELL ME WHEN YOU WERE HERE IN THE SUMMER", "subset": "test_clean", "task_type": "understanding", "prediction": "but why did n t you tell me when you were here in the summer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0010.flac", "answer": "ALEXANDER LEANED FORWARD AND WARMED HIS HANDS BEFORE THE BLAZE", "subset": "test_clean", "task_type": "understanding", "prediction": "alexander leaned forward and warmed his hands before the blaze", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0045.flac", "answer": "WE'VE TORTURED EACH OTHER ENOUGH FOR TONIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "weve tortured each other enough for tonight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0027.flac", "answer": "HE MOVED UNEASILY AND HIS CHAIR CREAKED", "subset": "test_clean", "task_type": "understanding", "prediction": "he moved uneasily and his chair creaked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0000.flac", "answer": "THE STOP AT QUEENSTOWN THE TEDIOUS PASSAGE UP THE MERSEY WERE THINGS THAT HE NOTED DIMLY THROUGH HIS GROWING IMPATIENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "the stop at queenstown the tedious passage up the mersey were things that he noted dimly through his growing impatience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0021.flac", "answer": "HILDA'S FACE QUIVERED BUT SHE WHISPERED YES I THINK IT MUST HAVE BEEN", "subset": "test_clean", "task_type": "understanding", "prediction": "hilda s face quivered but she whispered yes i think it must have been", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0018.flac", "answer": "I GET NOTHING BUT MISERY OUT OF EITHER", "subset": "test_clean", "task_type": "understanding", "prediction": "i get nothing but misery out of either", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0003.flac", "answer": "THE ROOM WAS EMPTY WHEN HE ENTERED", "subset": "test_clean", "task_type": "understanding", "prediction": "the room was empty when he entered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0026.flac", "answer": "SHE CLOSED HER EYES AND TOOK A DEEP BREATH AS IF TO DRAW IN AGAIN THE FRAGRANCE OF THOSE DAYS", "subset": "test_clean", "task_type": "understanding", "prediction": "she closed her eyes and took a deep breath as if to draw in again the fragrance of those days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0043.flac", "answer": "BARTLEY BENT OVER AND TOOK HER IN HIS ARMS KISSING HER MOUTH AND HER WET TIRED EYES", "subset": "test_clean", "task_type": "understanding", "prediction": "bartley bent over and took her in his arms kissing her mouth and her wet tired eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0013.flac", "answer": "I'LL DO ANYTHING YOU WISH ME TO BARTLEY SHE SAID TREMULOUSLY", "subset": "test_clean", "task_type": "understanding", "prediction": "ill do anything you wish me to bartley she said tremulously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0011.flac", "answer": "BARTLEY BENT LOWER OVER THE FIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "bartley bent lowered over the fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0017.flac", "answer": "BUT IT'S WORSE NOW IT'S UNBEARABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "but it is worse now it is unbearable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0006.flac", "answer": "I THOUGHT IT MIGHT BE SISTER KATE OR COUSIN MIKE WOULD BE HAPPENING ALONG", "subset": "test_clean", "task_type": "understanding", "prediction": "i thought it might be sister kate or cousin mike would be happening along", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0044.flac", "answer": "DON'T CRY DON'T CRY HE WHISPERED", "subset": "test_clean", "task_type": "understanding", "prediction": "ah dont cry dont cry he whispered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0032.flac", "answer": "BUT I DIDN'T KNOW YOU'VE ONLY TO TELL ME NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "but i didn t know you ve only to tell me now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0038.flac", "answer": "I WILL ASK THE LEAST IMAGINABLE BUT I MUST HAVE SOMETHING", "subset": "test_clean", "task_type": "understanding", "prediction": "i will ask the least imaginable but i must have something", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0031.flac", "answer": "I UNDERSTAND BARTLEY I WAS WRONG", "subset": "test_clean", "task_type": "understanding", "prediction": "i understand bartley i was wrong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0042.flac", "answer": "AND THEN YOU CAME BACK NOT CARING VERY MUCH BUT IT MADE NO DIFFERENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "and then you came back not caring very much but it made no difference", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0009.flac", "answer": "I GOT IN ABOUT TEN MINUTES AGO", "subset": "test_clean", "task_type": "understanding", "prediction": "i got in about ten minutes ago", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0028.flac", "answer": "YES YES SHE HURRIED PULLING HER HAND GENTLY AWAY FROM HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "yes yes she hurried pulling her hand gently away from him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0004.flac", "answer": "ALEXANDER DID NOT SIT DOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "alexander did not sit down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0025.flac", "answer": "WEREN'T YOU HAPPY THEN AT ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "weren t you happy then at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0040.flac", "answer": "THE SIGHT OF YOU BARTLEY TO SEE YOU LIVING AND HAPPY AND SUCCESSFUL CAN I NEVER MAKE YOU UNDERSTAND WHAT THAT MEANS TO ME", "subset": "test_clean", "task_type": "understanding", "prediction": "the sight of you bartley to see you living and happy and successful can i never make you understand what that means to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0005.flac", "answer": "I FELT IT IN MY BONES WHEN I WOKE THIS MORNING THAT SOMETHING SPLENDID WAS GOING TO TURN UP", "subset": "test_clean", "task_type": "understanding", "prediction": "i felt it in my bones when i woke this morning that something splendid was going to turn up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0030.flac", "answer": "YES HILDA I KNOW THAT HE SAID SIMPLY", "subset": "test_clean", "task_type": "understanding", "prediction": "yes hilda i know that he said simply", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0008.flac", "answer": "WHEN DID YOU COME BARTLEY AND HOW DID IT HAPPEN YOU HAVEN'T SPOKEN A WORD", "subset": "test_clean", "task_type": "understanding", "prediction": "when did you come bartley and how did it happen you have n t spoken a word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0034.flac", "answer": "KEEP AWAY IF YOU WISH WHEN HAVE I EVER FOLLOWED YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "keep away if you wish when have i ever followed you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0029.flac", "answer": "PLEASE TELL ME ONE THING BARTLEY AT LEAST TELL ME THAT YOU BELIEVE I THOUGHT I WAS MAKING YOU HAPPY", "subset": "test_clean", "task_type": "understanding", "prediction": "please tell me one thing bartley at least tell me that you believe i thought i was making you happy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2275/4446-2275-0041.flac", "answer": "YOU SEE LOVING SOME ONE AS I LOVE YOU MAKES THE WHOLE WORLD DIFFERENT", "subset": "test_clean", "task_type": "understanding", "prediction": "you see loving someone as i love you makes the whole world different", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0024.flac", "answer": "I SHOULDN'T WONDER IF SHE COULD LAUGH ABOUT IT WITH ME NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "i shouldn t wonder if she could laugh about it with me now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0007.flac", "answer": "SHE DOESN'T TAKE UP WITH ANYBODY YOU KNOW", "subset": "test_clean", "task_type": "understanding", "prediction": "she does n t take up with anybody you know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0013.flac", "answer": "DO YOU KNOW I THOUGHT THE DANCE A BIT CONSCIOUS TO NIGHT FOR THE FIRST TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "you know i thought the dance a bit conscious tonight for the first time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0014.flac", "answer": "WESTMERE AND I WERE BACK AFTER THE FIRST ACT AND WE THOUGHT SHE SEEMED QUITE UNCERTAIN OF HERSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "westmere and i were back after the first act and we thought she seemed quite uncertain of herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0003.flac", "answer": "IT'S BEEN ON ONLY TWO WEEKS AND I'VE BEEN HALF A DOZEN TIMES ALREADY", "subset": "test_clean", "task_type": "understanding", "prediction": "its been on only two weeks and i have been half a dozen times already", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0018.flac", "answer": "SHE CONSIDERED A MOMENT AND THEN SAID NO I THINK NOT THOUGH I AM GLAD YOU ASK ME", "subset": "test_clean", "task_type": "understanding", "prediction": "she considered for a moment and then said no i think not though i am glad you asked me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0023.flac", "answer": "AFTER ALL WE WERE AWFULLY YOUNG", "subset": "test_clean", "task_type": "understanding", "prediction": "after all we were awfully young", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0000.flac", "answer": "MAINHALL LIKED ALEXANDER BECAUSE HE WAS AN ENGINEER", "subset": "test_clean", "task_type": "understanding", "prediction": "main hall liked alexander because he was an engineer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0001.flac", "answer": "HE HAD PRECONCEIVED IDEAS ABOUT EVERYTHING AND HIS IDEA ABOUT AMERICANS WAS THAT THEY SHOULD BE ENGINEERS OR MECHANICS", "subset": "test_clean", "task_type": "understanding", "prediction": "he had preconceived ideas about everything and his idea about americans was that they should be engineers or mechanics", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0009.flac", "answer": "MAINHALL VOUCHED FOR HER CONSTANCY WITH A LOFTINESS THAT MADE ALEXANDER SMILE EVEN WHILE A KIND OF RAPID EXCITEMENT WAS TINGLING THROUGH HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "mainwaring vouched for her constancy with a loftiness that made alexander smile even while a kind of rapid excitement was tingling through him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0008.flac", "answer": "IRENE BURGOYNE ONE OF HER FAMILY TOLD ME IN CONFIDENCE THAT THERE WAS A ROMANCE SOMEWHERE BACK IN THE BEGINNING", "subset": "test_clean", "task_type": "understanding", "prediction": "irene bourgoign one of her family told me in confidence that there was a romance somewhere back in the beginning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0019.flac", "answer": "AFTER THAT IT WAS EASY TO FORGET ACTUALLY TO FORGET", "subset": "test_clean", "task_type": "understanding", "prediction": "after that it was easy to forget actually to forget", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0006.flac", "answer": "HE'S BEEN WANTING TO MARRY HILDA THESE THREE YEARS AND MORE", "subset": "test_clean", "task_type": "understanding", "prediction": "hes been wanting to marry hilda these three years and more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0004.flac", "answer": "DO YOU KNOW ALEXANDER MAINHALL LOOKED WITH PERPLEXITY UP INTO THE TOP OF THE HANSOM AND RUBBED HIS PINK CHEEK WITH HIS GLOVED FINGER DO YOU KNOW I SOMETIMES THINK OF TAKING TO CRITICISM SERIOUSLY MYSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "do you know alexander mainhall looked with perplexity up into the top of the hansom and rubbed his pink cheek with his gloved finger do you know i sometimes think of taking to criticism seriously myself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0012.flac", "answer": "I SAY SIR HARRY THE LITTLE GIRL'S GOING FAMOUSLY TO NIGHT ISN'T SHE", "subset": "test_clean", "task_type": "understanding", "prediction": "i say sir harry the little girl is going famously to night is n t she", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0022.flac", "answer": "I'M GLAD SHE'S HELD HER OWN SINCE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am glad she has held her own since", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0005.flac", "answer": "SHE SAVES HER HAND TOO SHE'S AT HER BEST IN THE SECOND ACT", "subset": "test_clean", "task_type": "understanding", "prediction": "she saves her hand too she sat her best in the second act", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0015.flac", "answer": "A LITTLE ATTACK OF NERVES POSSIBLY", "subset": "test_clean", "task_type": "understanding", "prediction": "a little attack of nerves possibly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0010.flac", "answer": "HE'S ANOTHER WHO'S AWFULLY KEEN ABOUT HER LET ME INTRODUCE YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "hes another whos awfully keen about her let me introduce you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0016.flac", "answer": "HE WAS BEGINNING TO FEEL A KEEN INTEREST IN THE SLENDER BAREFOOT DONKEY GIRL WHO SLIPPED IN AND OUT OF THE PLAY SINGING LIKE SOME ONE WINDING THROUGH A HILLY FIELD", "subset": "test_clean", "task_type": "understanding", "prediction": "he was beginning to feel a keen interest in the slender barefoot donkey girl who slipped in and out of the play singing like some one winding through a hilly field", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0017.flac", "answer": "ONE NIGHT WHEN HE AND WINIFRED WERE SITTING TOGETHER ON THE BRIDGE HE TOLD HER THAT THINGS HAD HAPPENED WHILE HE WAS STUDYING ABROAD THAT HE WAS SORRY FOR ONE THING IN PARTICULAR AND HE ASKED HER WHETHER SHE THOUGHT SHE OUGHT TO KNOW ABOUT THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "one night when he and winifred were sitting together on the bridge he told her that things had happened while he was studying abroad that he was sorry for one thing in particular and he asked her whether she thought she ought to know about them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0011.flac", "answer": "SIR HARRY TOWNE MISTER BARTLEY ALEXANDER THE AMERICAN ENGINEER", "subset": "test_clean", "task_type": "understanding", "prediction": "sir harry towne mr bartley alexander the american engineer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0020.flac", "answer": "OF COURSE HE REFLECTED SHE ALWAYS HAD THAT COMBINATION OF SOMETHING HOMELY AND SENSIBLE AND SOMETHING UTTERLY WILD AND DAFT", "subset": "test_clean", "task_type": "understanding", "prediction": "of course he reflected she always had that combination of something homely and sensible and something utterly wild and daft", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0021.flac", "answer": "SHE MUST CARE ABOUT THE THEATRE A GREAT DEAL MORE THAN SHE USED TO", "subset": "test_clean", "task_type": "understanding", "prediction": "she must care about the theatre a great deal more than she used to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4446/2271/4446-2271-0002.flac", "answer": "IT'S TREMENDOUSLY WELL PUT ON TOO", "subset": "test_clean", "task_type": "understanding", "prediction": "its tremendously well put on too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0014.flac", "answer": "PEARL SAW AND GAZED INTENTLY BUT NEVER SOUGHT TO MAKE ACQUAINTANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "pearl saw and gazed intently but never sought to make acquaintance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0000.flac", "answer": "HOW STRANGE IT SEEMED TO THE SAD WOMAN AS SHE WATCHED THE GROWTH AND THE BEAUTY THAT BECAME EVERY DAY MORE BRILLIANT AND THE INTELLIGENCE THAT THREW ITS QUIVERING SUNSHINE OVER THE TINY FEATURES OF THIS CHILD", "subset": "test_clean", "task_type": "understanding", "prediction": "how strange it seemed to the sad woman as she watched the growth and the beauty that became every day more brilliant and the intelligence that threw its quivering sunshine over the tiny features of this child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0010.flac", "answer": "IT WAS A LOOK SO INTELLIGENT YET INEXPLICABLE PERVERSE SOMETIMES SO MALICIOUS BUT GENERALLY ACCOMPANIED BY A WILD FLOW OF SPIRITS THAT HESTER COULD NOT HELP QUESTIONING AT SUCH MOMENTS WHETHER PEARL WAS A HUMAN CHILD", "subset": "test_clean", "task_type": "understanding", "prediction": "it was a look so intelligent yet inexplicable perverse sometimes so malicious but generally accompanied by a wild flow of spirits that hester could not help questioning at such moments whether pearl was a human child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0003.flac", "answer": "THE CHILD HAD A NATIVE GRACE WHICH DOES NOT INVARIABLY CO EXIST WITH FAULTLESS BEAUTY ITS ATTIRE HOWEVER SIMPLE ALWAYS IMPRESSED THE BEHOLDER AS IF IT WERE THE VERY GARB THAT PRECISELY BECAME IT BEST", "subset": "test_clean", "task_type": "understanding", "prediction": "the child had a native grace which does not invariably coexist with faultless beauty its attire however simple always impressed the beholder as if it were the very garb that precisely became it best", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0013.flac", "answer": "PEARL WAS A BORN OUTCAST OF THE INFANTILE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "pearl was a born outcast of the infantile world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0001.flac", "answer": "GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONOURED BOSOM TO CONNECT HER PARENT FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN", "subset": "test_clean", "task_type": "understanding", "prediction": "god as a direct consequence of the sin which man thus punished had given her a lovely child whose place was on that same dishonored bosom to connect her parent forever with the race and descent of mortals and to be finally a blessed soul in heaven", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0006.flac", "answer": "THEY WERE NOW ILLUMINATED BY THE MORNING RADIANCE OF A YOUNG CHILD'S DISPOSITION BUT LATER IN THE DAY OF EARTHLY EXISTENCE MIGHT BE PROLIFIC OF THE STORM AND WHIRLWIND", "subset": "test_clean", "task_type": "understanding", "prediction": "they were now illuminated by the morning radiance of a young child s disposition but later in the day of earthly existence might be prolific of the storm and whirlwind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0011.flac", "answer": "BEHOLDING IT HESTER WAS CONSTRAINED TO RUSH TOWARDS THE CHILD TO PURSUE THE LITTLE ELF IN THE FLIGHT WHICH SHE INVARIABLY BEGAN TO SNATCH HER TO HER BOSOM WITH A CLOSE PRESSURE AND EARNEST KISSES NOT SO MUCH FROM OVERFLOWING LOVE AS TO ASSURE HERSELF THAT PEARL WAS FLESH AND BLOOD AND NOT UTTERLY DELUSIVE", "subset": "test_clean", "task_type": "understanding", "prediction": "beholding it hester was constrained to rush towards the child to pursue the little elf in the flight which she invariably began to snatch her to her bosom with a close pressure and earnest kisses not so much from overflowing love as to assure herself that pearl was flesh and blood and not utterly delusive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0002.flac", "answer": "YET THESE THOUGHTS AFFECTED HESTER PRYNNE LESS WITH HOPE THAN APPREHENSION", "subset": "test_clean", "task_type": "understanding", "prediction": "yet these thoughts affected hester prynne less with hope than apprehension", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0007.flac", "answer": "HESTER PRYNNE NEVERTHELESS THE LOVING MOTHER OF THIS ONE CHILD RAN LITTLE RISK OF ERRING ON THE SIDE OF UNDUE SEVERITY", "subset": "test_clean", "task_type": "understanding", "prediction": "hester prynne nevertheless the loving mother of this one child ran little risk of erring on the side of undue severity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0004.flac", "answer": "THIS OUTWARD MUTABILITY INDICATED AND DID NOT MORE THAN FAIRLY EXPRESS THE VARIOUS PROPERTIES OF HER INNER LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "this outward mutability indicated and did not more than fairly express the various properties of her inner life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0009.flac", "answer": "AS TO ANY OTHER KIND OF DISCIPLINE WHETHER ADDRESSED TO HER MIND OR HEART LITTLE PEARL MIGHT OR MIGHT NOT BE WITHIN ITS REACH IN ACCORDANCE WITH THE CAPRICE THAT RULED THE MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "as to any other kind of discipline whether addressed to her mind or heart little pearl might or might not be within its reach in accordance with the caprice that ruled the moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0008.flac", "answer": "MINDFUL HOWEVER OF HER OWN ERRORS AND MISFORTUNES SHE EARLY SOUGHT TO IMPOSE A TENDER BUT STRICT CONTROL OVER THE INFANT IMMORTALITY THAT WAS COMMITTED TO HER CHARGE", "subset": "test_clean", "task_type": "understanding", "prediction": "mindful however of her own errors and misfortunes she early sought to impose a tender but strict control over the infant immortality that was committed to her charge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0012.flac", "answer": "BROODING OVER ALL THESE MATTERS THE MOTHER FELT LIKE ONE WHO HAS EVOKED A SPIRIT BUT BY SOME IRREGULARITY IN THE PROCESS OF CONJURATION HAS FAILED TO WIN THE MASTER WORD THAT SHOULD CONTROL THIS NEW AND INCOMPREHENSIBLE INTELLIGENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "brooding over all these matters the mother felt like one who has evoked a spirit but by some irregularity in the process of conjuration has failed to win the master word that should control this new and incomprehensible intelligence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0015.flac", "answer": "IF SPOKEN TO SHE WOULD NOT SPEAK AGAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "if spoken to she would not speak again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135766/1221-135766-0005.flac", "answer": "HESTER COULD ONLY ACCOUNT FOR THE CHILD'S CHARACTER AND EVEN THEN MOST VAGUELY AND IMPERFECTLY BY RECALLING WHAT SHE HERSELF HAD BEEN DURING THAT MOMENTOUS PERIOD WHILE PEARL WAS IMBIBING HER SOUL FROM THE SPIRITUAL WORLD AND HER BODILY FRAME FROM ITS MATERIAL OF EARTH", "subset": "test_clean", "task_type": "understanding", "prediction": "hester could only account for the child s character and even then most vaguely and imperfectly by recalling what she herself had been during that momentous period while pearl was imbibing her soul from the spiritual world and her bodily frame from its material of earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0022.flac", "answer": "BUT THE PROPRIETOR APPEARED ALREADY TO HAVE RELINQUISHED AS HOPELESS THE EFFORT TO PERPETUATE ON THIS SIDE OF THE ATLANTIC IN A HARD SOIL AND AMID THE CLOSE STRUGGLE FOR SUBSISTENCE THE NATIVE ENGLISH TASTE FOR ORNAMENTAL GARDENING", "subset": "test_clean", "task_type": "understanding", "prediction": "but the proprietor appeared already to have relinquished as hopeless the effort to perpetuate on this side of the atlantic in a hard soil and amid the close struggle for subsistence the native english taste for ornamental gardening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0002.flac", "answer": "AT THAT EPOCH OF PRISTINE SIMPLICITY HOWEVER MATTERS OF EVEN SLIGHTER PUBLIC INTEREST AND OF FAR LESS INTRINSIC WEIGHT THAN THE WELFARE OF HESTER AND HER CHILD WERE STRANGELY MIXED UP WITH THE DELIBERATIONS OF LEGISLATORS AND ACTS OF STATE", "subset": "test_clean", "task_type": "understanding", "prediction": "at that epoch of pristine simplicity however matters of even slighter public interest and of far less intrinsic weight than the welfare of hester and her child were strangely mixed up with the deliberations of legislators and acts of state", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0012.flac", "answer": "THEY APPROACHED THE DOOR WHICH WAS OF AN ARCHED FORM AND FLANKED ON EACH SIDE BY A NARROW TOWER OR PROJECTION OF THE EDIFICE IN BOTH OF WHICH WERE LATTICE WINDOWS THE WOODEN SHUTTERS TO CLOSE OVER THEM AT NEED", "subset": "test_clean", "task_type": "understanding", "prediction": "they approached the door which was of an arched form and flanked on each side by a narrow tower or projection of the edifice in both of which were lattice windows the wooden shutters to close over them at need", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0008.flac", "answer": "COME THEREFORE AND LET US FLING MUD AT THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "come therefore and let us fling mud at them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0011.flac", "answer": "IT WAS FURTHER DECORATED WITH STRANGE AND SEEMINGLY CABALISTIC FIGURES AND DIAGRAMS SUITABLE TO THE QUAINT TASTE OF THE AGE WHICH HAD BEEN DRAWN IN THE STUCCO WHEN NEWLY LAID ON AND HAD NOW GROWN HARD AND DURABLE FOR THE ADMIRATION OF AFTER TIMES", "subset": "test_clean", "task_type": "understanding", "prediction": "it was further decorated with strange and seemingly cabalistic figures and diagrams suitable to the quaint taste of the age which had been drawn in the stucco when newly laid on and had now grown hard and durable for the admiration of after times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0000.flac", "answer": "HESTER PRYNNE WENT ONE DAY TO THE MANSION OF GOVERNOR BELLINGHAM WITH A PAIR OF GLOVES WHICH SHE HAD FRINGED AND EMBROIDERED TO HIS ORDER AND WHICH WERE TO BE WORN ON SOME GREAT OCCASION OF STATE FOR THOUGH THE CHANCES OF A POPULAR ELECTION HAD CAUSED THIS FORMER RULER TO DESCEND A STEP OR TWO FROM THE HIGHEST RANK HE STILL HELD AN HONOURABLE AND INFLUENTIAL PLACE AMONG THE COLONIAL MAGISTRACY", "subset": "test_clean", "task_type": "understanding", "prediction": "hester prynne went one day to the mansion of governor bellingham with a pair of gloves which she had fringed and embroidered to his order and which were to be worn on some great occasion of state for though the chances of a popular election had caused this former ruler to descend a step or two from the highest rank he still held an honorable and influential place among the colonial magistracy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0019.flac", "answer": "MOTHER CRIED SHE I SEE YOU HERE LOOK LOOK", "subset": "test_clean", "task_type": "understanding", "prediction": "mother cried she i see you here look look", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0021.flac", "answer": "PEARL ACCORDINGLY RAN TO THE BOW WINDOW AT THE FURTHER END OF THE HALL AND LOOKED ALONG THE VISTA OF A GARDEN WALK CARPETED WITH CLOSELY SHAVEN GRASS AND BORDERED WITH SOME RUDE AND IMMATURE ATTEMPT AT SHRUBBERY", "subset": "test_clean", "task_type": "understanding", "prediction": "pearl accordingly ran to the bow window at the further end of the hall and looked along the vista of a garden walk carpeted with closely shaven grass and bordered with some rude and immature attempt at shrubbery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0023.flac", "answer": "THERE WERE A FEW ROSE BUSHES HOWEVER AND A NUMBER OF APPLE TREES PROBABLY THE DESCENDANTS OF THOSE PLANTED BY THE REVEREND MISTER BLACKSTONE THE FIRST SETTLER OF THE PENINSULA THAT HALF MYTHOLOGICAL PERSONAGE WHO RIDES THROUGH OUR EARLY ANNALS SEATED ON THE BACK OF A BULL", "subset": "test_clean", "task_type": "understanding", "prediction": "there were a few rose bushes however and a number of apple trees probably the descendants of those planted by the reverend mr blackstone the first settler of the peninsula that half mythological personage who rides through our early annals seated on the back of a bull", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0005.flac", "answer": "IT WAS THE SCARLET LETTER IN ANOTHER FORM THE SCARLET LETTER ENDOWED WITH LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "it was the scarlet letter in another form the scarlet letter endowed with life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0018.flac", "answer": "LITTLE PEARL WHO WAS AS GREATLY PLEASED WITH THE GLEAMING ARMOUR AS SHE HAD BEEN WITH THE GLITTERING FRONTISPIECE OF THE HOUSE SPENT SOME TIME LOOKING INTO THE POLISHED MIRROR OF THE BREASTPLATE", "subset": "test_clean", "task_type": "understanding", "prediction": "little pearl who was as greatly pleased with the gleaming armor as she had been with the glittering frontispiece of the house spent some time looking into the polished mirror of the breastplate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0016.flac", "answer": "WITH MANY VARIATIONS SUGGESTED BY THE NATURE OF HIS BUILDING MATERIALS DIVERSITY OF CLIMATE AND A DIFFERENT MODE OF SOCIAL LIFE GOVERNOR BELLINGHAM HAD PLANNED HIS NEW HABITATION AFTER THE RESIDENCES OF GENTLEMEN OF FAIR ESTATE IN HIS NATIVE LAND", "subset": "test_clean", "task_type": "understanding", "prediction": "with many variations suggested by the nature of his building materials diversity of climate and a different mode of social life governor bellingham had planned his new habitation after the residences of gentlemen of fair estate in his native land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0006.flac", "answer": "THE MOTHER HERSELF AS IF THE RED IGNOMINY WERE SO DEEPLY SCORCHED INTO HER BRAIN THAT ALL HER CONCEPTIONS ASSUMED ITS FORM HAD CAREFULLY WROUGHT OUT THE SIMILITUDE LAVISHING MANY HOURS OF MORBID INGENUITY TO CREATE AN ANALOGY BETWEEN THE OBJECT OF HER AFFECTION AND THE EMBLEM OF HER GUILT AND TORTURE", "subset": "test_clean", "task_type": "understanding", "prediction": "the mother herself as if the red ignominy were so deeply scorched into her brain that all her conceptions assumed its form had carefully wrought out the similitude lavishing many hours of morbid ingenuity to create an analogy between the object of her affection and the emblem of her guilt and torture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0009.flac", "answer": "BUT PEARL WHO WAS A DAUNTLESS CHILD AFTER FROWNING STAMPING HER FOOT AND SHAKING HER LITTLE HAND WITH A VARIETY OF THREATENING GESTURES SUDDENLY MADE A RUSH AT THE KNOT OF HER ENEMIES AND PUT THEM ALL TO FLIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "but pearl who was a dauntless child after frowning stamping her foot and shaking her little hand with a variety of threatening gestures suddenly made a rush at the knot of her enemies and put them all to flight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0015.flac", "answer": "YE MAY NOT SEE HIS WORSHIP NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "ye may not see his worship now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0004.flac", "answer": "WE HAVE SPOKEN OF PEARL'S RICH AND LUXURIANT BEAUTY A BEAUTY THAT SHONE WITH DEEP AND VIVID TINTS A BRIGHT COMPLEXION EYES POSSESSING INTENSITY BOTH OF DEPTH AND GLOW AND HAIR ALREADY OF A DEEP GLOSSY BROWN AND WHICH IN AFTER YEARS WOULD BE NEARLY AKIN TO BLACK", "subset": "test_clean", "task_type": "understanding", "prediction": "we have spoken of pearl's rich and luxuriant beauty a beauty that shone with deep and vivid tints a bright complexion eyes possessing intensity both of depth and glow and hair already of a deep glossy brown and which in after years would be nearly akin to black", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0014.flac", "answer": "YEA HIS HONOURABLE WORSHIP IS WITHIN BUT HE HATH A GODLY MINISTER OR TWO WITH HIM AND LIKEWISE A LEECH", "subset": "test_clean", "task_type": "understanding", "prediction": "yea his honourable worship is within but he hath a godly minister or two with him and likewise a leech", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0013.flac", "answer": "LIFTING THE IRON HAMMER THAT HUNG AT THE PORTAL HESTER PRYNNE GAVE A SUMMONS WHICH WAS ANSWERED BY ONE OF THE GOVERNOR'S BOND SERVANT A FREE BORN ENGLISHMAN BUT NOW A SEVEN YEARS SLAVE", "subset": "test_clean", "task_type": "understanding", "prediction": "lifting the iron hammer that hung at the portal hester prynne gave a summons which was answered by one of the governor s bond servants a freeborn englishman but now a seven years slave", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0003.flac", "answer": "THE PERIOD WAS HARDLY IF AT ALL EARLIER THAN THAT OF OUR STORY WHEN A DISPUTE CONCERNING THE RIGHT OF PROPERTY IN A PIG NOT ONLY CAUSED A FIERCE AND BITTER CONTEST IN THE LEGISLATIVE BODY OF THE COLONY BUT RESULTED IN AN IMPORTANT MODIFICATION OF THE FRAMEWORK ITSELF OF THE LEGISLATURE", "subset": "test_clean", "task_type": "understanding", "prediction": "the period was hardly if at all earlier than that of our story when a dispute concerning the right of property in a pig not only caused a fierce and bitter contest in the legislative body of the colony but resulted in an important modification of the framework itself of the legislature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0010.flac", "answer": "SHE SCREAMED AND SHOUTED TOO WITH A TERRIFIC VOLUME OF SOUND WHICH DOUBTLESS CAUSED THE HEARTS OF THE FUGITIVES TO QUAKE WITHIN THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "she screamed and shouted too with a terrific volume of sound which doubtless caused the hearts of the fugitives to quake within them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0017.flac", "answer": "ON THE TABLE IN TOKEN THAT THE SENTIMENT OF OLD ENGLISH HOSPITALITY HAD NOT BEEN LEFT BEHIND STOOD A LARGE PEWTER TANKARD AT THE BOTTOM OF WHICH HAD HESTER OR PEARL PEEPED INTO IT THEY MIGHT HAVE SEEN THE FROTHY REMNANT OF A RECENT DRAUGHT OF ALE", "subset": "test_clean", "task_type": "understanding", "prediction": "on the table in token that the sentiment of old english hospitality had not been left behind stood a large pewter tankard at the bottom of which had hester or pearl peeped into it they might have seen the frothy remnant of a recent draught of ale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0024.flac", "answer": "PEARL SEEING THE ROSE BUSHES BEGAN TO CRY FOR A RED ROSE AND WOULD NOT BE PACIFIED", "subset": "test_clean", "task_type": "understanding", "prediction": "pearl seeing the rose bushes began to cry for a red rose and would not be pacified", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0001.flac", "answer": "ANOTHER AND FAR MORE IMPORTANT REASON THAN THE DELIVERY OF A PAIR OF EMBROIDERED GLOVES IMPELLED HESTER AT THIS TIME TO SEEK AN INTERVIEW WITH A PERSONAGE OF SO MUCH POWER AND ACTIVITY IN THE AFFAIRS OF THE SETTLEMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "another and far more important reason than the delivery of a pair of embroidered gloves impelled hester at this time to seek an interview with a personage of so much power and activity in the affairs of the settlement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0007.flac", "answer": "BUT IN TRUTH PEARL WAS THE ONE AS WELL AS THE OTHER AND ONLY IN CONSEQUENCE OF THAT IDENTITY HAD HESTER CONTRIVED SO PERFECTLY TO REPRESENT THE SCARLET LETTER IN HER APPEARANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "but in truth pearl was the one as well as the other and only in consequence of that identity had hester contrived so perfectly to represent the scarlet letter in her appearance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1221/135767/1221-135767-0020.flac", "answer": "IN TRUTH SHE SEEMED ABSOLUTELY HIDDEN BEHIND IT", "subset": "test_clean", "task_type": "understanding", "prediction": "in truth she seemed absolutely hidden behind it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0018.flac", "answer": "AND FEAREST THOU BECAUSE I VANISH AND AM SEEN NO MORE", "subset": "test_clean", "task_type": "understanding", "prediction": "and fearest thou because i vanish and am seen no more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0020.flac", "answer": "TILL WE ARISE LINK'D IN A GOLDEN BAND AND NEVER PART BUT WALK UNITED BEARING FOOD TO ALL OUR TENDER FLOWERS", "subset": "test_clean", "task_type": "understanding", "prediction": "till we arise linked in a golden band and never part but walk united bearing food to all our tender flowers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0022.flac", "answer": "COME FORTH WORM AND THE SILENT VALLEY TO THY PENSIVE QUEEN", "subset": "test_clean", "task_type": "understanding", "prediction": "come forth worm in the silent valley to thy pensive queen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0015.flac", "answer": "O LITTLE CLOUD THE VIRGIN SAID I CHARGE THEE TO TELL ME WHY THOU COMPLAINEST NOW WHEN IN ONE HOUR THOU FADE AWAY THEN WE SHALL SEEK THEE BUT NOT FIND AH THEL IS LIKE TO THEE", "subset": "test_clean", "task_type": "understanding", "prediction": "o little cloud the virgin said i charge thee to tell me why thou complainest now when in one hour thou fade away then we shall seek thee but not find ah fell is like to thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0010.flac", "answer": "SHE CEASD AND SMILD IN TEARS THEN SAT DOWN IN HER SILVER SHRINE", "subset": "test_clean", "task_type": "understanding", "prediction": "she ceased and smiled in tears then sat down in her silver shrine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0001.flac", "answer": "O LIFE OF THIS OUR SPRING", "subset": "test_clean", "task_type": "understanding", "prediction": "o life of this our spring", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0007.flac", "answer": "THE LILLY OF THE VALLEY BREATHING IN THE HUMBLE GRASS ANSWERD THE LOVELY MAID AND SAID I AM A WATRY WEED AND I AM VERY SMALL AND LOVE TO DWELL IN LOWLY VALES SO WEAK THE GILDED BUTTERFLY SCARCE PERCHES ON MY HEAD YET I AM VISITED FROM HEAVEN AND HE THAT SMILES ON ALL WALKS IN THE VALLEY AND EACH MORN OVER ME SPREADS HIS HAND SAYING REJOICE THOU HUMBLE GRASS THOU NEW BORN LILY FLOWER", "subset": "test_clean", "task_type": "understanding", "prediction": "the lily of the valley breathing in the humble grass answered the lovely maiden said i am a watery weed and i am very small and love to dwell in lowly vales so weak the gilded butterfly scarce perches on my head yet i am visited from heaven and he that smiles on all walks in the valley and each morn over me spreads his hand saying rejoice thou humble grass thou new born lily flower", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0016.flac", "answer": "I PASS AWAY YET I COMPLAIN AND NO ONE HEARS MY VOICE", "subset": "test_clean", "task_type": "understanding", "prediction": "i pass away yet i complain and no one hears my voice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0027.flac", "answer": "AND LAY ME DOWN IN THY COLD BED AND LEAVE MY SHINING LOT", "subset": "test_clean", "task_type": "understanding", "prediction": "and lay me down in thy cold bed and leave my shining lot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0004.flac", "answer": "THEL IS LIKE A WATRY BOW AND LIKE A PARTING CLOUD LIKE A REFLECTION IN A GLASS LIKE SHADOWS IN THE WATER LIKE DREAMS OF INFANTS LIKE A SMILE UPON AN INFANTS FACE", "subset": "test_clean", "task_type": "understanding", "prediction": "thel is like a watery bow and like a parting cloud like a reflection in a glass like shadows in the water like dreams of infants like a smile upon an infant s face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0011.flac", "answer": "WHICH THOU DOST SCATTER ON EVERY LITTLE BLADE OF GRASS THAT SPRINGS REVIVES THE MILKED COW AND TAMES THE FIRE BREATHING STEED", "subset": "test_clean", "task_type": "understanding", "prediction": "which thou dost scatter on every little blade of grass that springs revives the milked cow and tames the fire breathing steed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0002.flac", "answer": "WHY FADES THE LOTUS OF THE WATER", "subset": "test_clean", "task_type": "understanding", "prediction": "why fades the lotus of the water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0021.flac", "answer": "LIVES NOT ALONE NOR OR ITSELF FEAR NOT AND I WILL CALL THE WEAK WORM FROM ITS LOWLY BED AND THOU SHALT HEAR ITS VOICE", "subset": "test_clean", "task_type": "understanding", "prediction": "lives not alone nor of itself fear not and i will call the weak worm from its lowly bed and thou shalt hear its voice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0024.flac", "answer": "IMAGE OF WEAKNESS ART THOU BUT A WORM", "subset": "test_clean", "task_type": "understanding", "prediction": "image of weakness art thou but a worm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0023.flac", "answer": "THE HELPLESS WORM AROSE AND SAT UPON THE LILLYS LEAF AND THE BRIGHT CLOUD SAILD ON TO FIND HIS PARTNER IN THE VALE", "subset": "test_clean", "task_type": "understanding", "prediction": "the helpless worm arose and sat upon the lily s leaf and the bright cloud sailed on to find his partner in the vale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0025.flac", "answer": "I SEE THEY LAY HELPLESS AND NAKED WEEPING AND NONE TO ANSWER NONE TO CHERISH THEE WITH MOTHERS SMILES", "subset": "test_clean", "task_type": "understanding", "prediction": "i see they lay helpless and naked weeping and none to answer none to cherish thee with mother s smiles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0013.flac", "answer": "AND WHY IT SCATTERS ITS BRIGHT BEAUTY THRO THE HUMID AIR", "subset": "test_clean", "task_type": "understanding", "prediction": "and why it scatters its bright beauty through the humid air", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0006.flac", "answer": "AND GENTLE SLEEP THE SLEEP OF DEATH AND GENTLY HEAR THE VOICE OF HIM THAT WALKETH IN THE GARDEN IN THE EVENING TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "and gentle sleep the sleep of death and gently hear the voice of him that walketh in the garden in the evening time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0009.flac", "answer": "WHY SHOULD THE MISTRESS OF THE VALES OF HAR UTTER A SIGH", "subset": "test_clean", "task_type": "understanding", "prediction": "why should the mistress of the vales of har utter a sigh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0019.flac", "answer": "IT IS TO TENFOLD LIFE TO LOVE TO PEACE AND RAPTURES HOLY UNSEEN DESCENDING WEIGH MY LIGHT WINGS UPON BALMY FLOWERS AND COURT THE FAIR EYED DEW TO TAKE ME TO HER SHINING TENT THE WEEPING VIRGIN TREMBLING KNEELS BEFORE THE RISEN SUN", "subset": "test_clean", "task_type": "understanding", "prediction": "it is to tenfold life to love to peace and raptures holy unseen descending weigh my light wings upon balmy flowers and court the fair eyed dew to take me to her shining tent the weeping virgin trembling kneels before the risen sun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0003.flac", "answer": "WHY FADE THESE CHILDREN OF THE SPRING", "subset": "test_clean", "task_type": "understanding", "prediction": "why fade these children of the spring", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0005.flac", "answer": "LIKE THE DOVES VOICE LIKE TRANSIENT DAY LIKE MUSIC IN THE AIR AH", "subset": "test_clean", "task_type": "understanding", "prediction": "like the dove s voice like transient day like music in the air ah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0008.flac", "answer": "THOU GENTLE MAID OF SILENT VALLEYS AND OF MODEST BROOKS FOR THOU SHALL BE CLOTHED IN LIGHT AND FED WITH MORNING MANNA TILL SUMMERS HEAT MELTS THEE BESIDE THE FOUNTAINS AND THE SPRINGS TO FLOURISH IN ETERNAL VALES THEY WHY SHOULD THEL COMPLAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "thou gentle maid of silent valleys and of modest brooks for thou shalt be clothed in light and fed with morning manna till summers heat melts thee beside the fountains and the springs to flourish in eternal vales they why shouldst thou complain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0028.flac", "answer": "OR AN EYE OF GIFTS AND GRACES SHOWRING FRUITS AND COINED GOLD", "subset": "test_clean", "task_type": "understanding", "prediction": "or an eye of gifts and graces showering fruits and coinage gold", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0030.flac", "answer": "WHY AN EAR A WHIRLPOOL FIERCE TO DRAW CREATIONS IN", "subset": "test_clean", "task_type": "understanding", "prediction": "why an ear a whirlpool fierce to draw creations in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0026.flac", "answer": "AND SAYS THOU MOTHER OF MY CHILDREN I HAVE LOVED THEE AND I HAVE GIVEN THEE A CROWN THAT NONE CAN TAKE AWAY", "subset": "test_clean", "task_type": "understanding", "prediction": "and says thou mother of my children i have loved thee and i have given thee a crown that none can take away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0017.flac", "answer": "THE CLOUD THEN SHEWD HIS GOLDEN HEAD AND HIS BRIGHT FORM EMERG'D", "subset": "test_clean", "task_type": "understanding", "prediction": "the cloud then showed his golden head and his bright form emerged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0029.flac", "answer": "WHY A TONGUE IMPRESS'D WITH HONEY FROM EVERY WIND", "subset": "test_clean", "task_type": "understanding", "prediction": "why a tongue impressed with honey from every wind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0000.flac", "answer": "TO FADE AWAY LIKE MORNING BEAUTY FROM HER MORTAL DAY DOWN BY THE RIVER OF ADONA HER SOFT VOICE IS HEARD AND THUS HER GENTLE LAMENTATION FALLS LIKE MORNING DEW", "subset": "test_clean", "task_type": "understanding", "prediction": "to fade away like morning beauty from her mortal day down by the river of adana her soft voice is heard and thus her gentle lamentation falls like morning dew", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0012.flac", "answer": "BUT THEL IS LIKE A FAINT CLOUD KINDLED AT THE RISING SUN I VANISH FROM MY PEARLY THRONE AND WHO SHALL FIND MY PLACE", "subset": "test_clean", "task_type": "understanding", "prediction": "but thou is like a faint cloud kindled at the rising sun i vanish from my pearly throne and who shall find my place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/157963/908-157963-0014.flac", "answer": "DESCEND O LITTLE CLOUD AND HOVER BEFORE THE EYES OF THEL", "subset": "test_clean", "task_type": "understanding", "prediction": "descend o little cloud and hover before the eyes of phel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0021.flac", "answer": "OH TO SHOOT MY SOUL'S FULL MEANING INTO FUTURE YEARS THAT THEY SHOULD LEND IT UTTERANCE AND SALUTE LOVE THAT ENDURES FROM LIFE THAT DISAPPEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "o to shoot my soul s full meaning into future years that they should lend it utterance and salute love that endures from life that disappears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0017.flac", "answer": "MUSSULMANS AND GIAOURS THROW KERCHIEFS AT A SMILE AND HAVE NO RUTH FOR ANY WEEPING", "subset": "test_clean", "task_type": "understanding", "prediction": "musulmans and gyors throw kerchiefs at a smile and have no ruth for any weeping", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0011.flac", "answer": "AND LOVE BE FALSE", "subset": "test_clean", "task_type": "understanding", "prediction": "and love be false", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 840, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0007.flac", "answer": "COULD IT MEAN TO LAST A LOVE SET PENDULOUS BETWEEN SORROW AND SORROW", "subset": "test_clean", "task_type": "understanding", "prediction": "could it mean to last a love set pendulous between sorrow and sorrow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 841, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0016.flac", "answer": "DEAREST TEACH ME SO TO POUR OUT GRATITUDE AS THOU DOST GOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "dearest teach me so to pour out gratitude as thou dost good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 842, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0018.flac", "answer": "BUT THOU ART NOT SUCH A LOVER MY BELOVED", "subset": "test_clean", "task_type": "understanding", "prediction": "but thou art not such a lover my beloved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 843, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0008.flac", "answer": "NAY I RATHER THRILLED DISTRUSTING EVERY LIGHT THAT SEEMED TO GILD THE ONWARD PATH AND FEARED TO OVERLEAN A FINGER EVEN", "subset": "test_clean", "task_type": "understanding", "prediction": "nay i rather thrilled distrusting every light that seemed to gild the onward path and feared to over lean a finger even", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 844, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0022.flac", "answer": "THEN I LONG TRIED BY NATURAL ILLS RECEIVED THE COMFORT FAST WHILE BUDDING AT THY SIGHT MY PILGRIM'S STAFF GAVE OUT GREEN LEAVES WITH MORNING DEWS IMPEARLED", "subset": "test_clean", "task_type": "understanding", "prediction": "then i long tried by natural ills received the comfort fast while budding at thy sight my pilgrim staff gave out green leaves with morning dews impearled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 845, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0002.flac", "answer": "I DID NOT WRONG MYSELF SO BUT I PLACED A WRONG ON THEE", "subset": "test_clean", "task_type": "understanding", "prediction": "i did not wrong myself so but i placed a wrong on thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 846, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0019.flac", "answer": "THOU CANST WAIT THROUGH SORROW AND SICKNESS TO BRING SOULS TO TOUCH AND THINK IT SOON WHEN OTHERS CRY TOO LATE", "subset": "test_clean", "task_type": "understanding", "prediction": "thou canst wait through sorrow and sickness to bring souls to touch and think it soon when others cry too late", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 847, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0025.flac", "answer": "I LOVE THEE WITH A LOVE I SEEMED TO LOSE WITH MY LOST SAINTS I LOVE THEE WITH THE BREATH SMILES TEARS OF ALL MY LIFE AND IF GOD CHOOSE I SHALL BUT LOVE THEE BETTER AFTER DEATH", "subset": "test_clean", "task_type": "understanding", "prediction": "i love thee with a love i seemed to lose with my lost saints i love thee with the breath smiles tears of all my life and if god choose i shall but love thee better after death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 848, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0001.flac", "answer": "I SIT BENEATH THY LOOKS AS CHILDREN DO IN THE NOON SUN WITH SOULS THAT TREMBLE THROUGH THEIR HAPPY EYELIDS FROM AN UNAVERRED YET PRODIGAL INWARD JOY", "subset": "test_clean", "task_type": "understanding", "prediction": "i sit beneath thy looks as children do in the noon sun with souls that tremble through their happy eyelids from an unavowed yet prodigal inward joy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 849, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0009.flac", "answer": "AND THOUGH I HAVE GROWN SERENE AND STRONG SINCE THEN I THINK THAT GOD HAS WILLED A STILL RENEWABLE FEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "and though i have grown serene and strong since then i think that god has willed a still renewable fear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 850, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0012.flac", "answer": "IF HE TO KEEP ONE OATH MUST LOSE ONE JOY BY HIS LIFE'S STAR FORETOLD", "subset": "test_clean", "task_type": "understanding", "prediction": "if he to keep one oath must lose one joy by his life s star foretold", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 851, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0013.flac", "answer": "SLOW TO WORLD GREETINGS QUICK WITH ITS O LIST WHEN THE ANGELS SPEAK", "subset": "test_clean", "task_type": "understanding", "prediction": "slow to world greetings quick with its o list when the angels speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 852, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0015.flac", "answer": "THAT WAS THE CHRISM OF LOVE WHICH LOVE'S OWN CROWN WITH SANCTIFYING SWEETNESS DID PRECEDE THE THIRD UPON MY LIPS WAS FOLDED DOWN IN PERFECT PURPLE STATE SINCE WHEN INDEED I HAVE BEEN PROUD AND SAID MY LOVE MY OWN", "subset": "test_clean", "task_type": "understanding", "prediction": "that was the chrism of love which love s own crown with sanctifying sweetness did proceed the third upon my lips was folded down in perfect purple state since when indeed i have been proud and said my love my own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 853, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0000.flac", "answer": "ALL IS SAID WITHOUT A WORD", "subset": "test_clean", "task_type": "understanding", "prediction": "all is said without a word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 854, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0003.flac", "answer": "WHEN CALLED BEFORE I TOLD HOW HASTILY I DROPPED MY FLOWERS OR BRAKE OFF FROM A GAME", "subset": "test_clean", "task_type": "understanding", "prediction": "when called before i told how hastily i dropped my flowers or brake off from a game", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 855, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0010.flac", "answer": "O LOVE O TROTH", "subset": "test_clean", "task_type": "understanding", "prediction": "o love o troth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 856, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0006.flac", "answer": "OPEN THY HEART WIDE AND FOLD WITHIN THE WET WINGS OF THY DOVE", "subset": "test_clean", "task_type": "understanding", "prediction": "open thy heart wide and fold within the wet wings of thy dove", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 857, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0023.flac", "answer": "I LOVE THEE FREELY AS MEN STRIVE FOR RIGHT I LOVE THEE PURELY AS THEY TURN FROM PRAISE", "subset": "test_clean", "task_type": "understanding", "prediction": "i love thee freely as men strive for right i love thee purely as they turn from praise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 858, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0004.flac", "answer": "SHALL I NEVER MISS HOME TALK AND BLESSING AND THE COMMON KISS THAT COMES TO EACH IN TURN NOR COUNT IT STRANGE WHEN I LOOK UP TO DROP ON A NEW RANGE OF WALLS AND FLOORS ANOTHER HOME THAN THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "shall i never miss home talk and blessing and the common kiss that comes to each in turn nor count it strange when i look up to drop on a new range of walls and floors another home than this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 859, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0024.flac", "answer": "I LOVE THEE WITH THE PASSION PUT TO USE IN MY OLD GRIEFS AND WITH MY CHILDHOOD'S FAITH", "subset": "test_clean", "task_type": "understanding", "prediction": "i love thee with the passion put to use in my old griefs in with my childhoods faith", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 860, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0020.flac", "answer": "I THANK ALL WHO HAVE LOVED ME IN THEIR HEARTS WITH THANKS AND LOVE FROM MINE", "subset": "test_clean", "task_type": "understanding", "prediction": "i thank all who have loved me in their hearts with thanks and love from mine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 861, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0005.flac", "answer": "ALAS I HAVE GRIEVED SO I AM HARD TO LOVE", "subset": "test_clean", "task_type": "understanding", "prediction": "alas i have grieved so i am hard to love", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 862, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/908/31957/908-31957-0014.flac", "answer": "A RING OF AMETHYST I COULD NOT WEAR HERE PLAINER TO MY SIGHT THAN THAT FIRST KISS", "subset": "test_clean", "task_type": "understanding", "prediction": "a ring of amethyst i could not wear here plainer to my sight than that first kiss", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 863, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0000.flac", "answer": "BUT ANDERS CARED NOTHING ABOUT THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "but anders cared nothing about that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 864, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0004.flac", "answer": "YES WHY NOT THOUGHT ANDERS", "subset": "test_clean", "task_type": "understanding", "prediction": "yes why not thought anders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 865, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0026.flac", "answer": "NO MY LITTLE SON SHE SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "no my little son she said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 866, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0017.flac", "answer": "SO IT IS SAID ANDERS", "subset": "test_clean", "task_type": "understanding", "prediction": "so it is said anders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 867, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0005.flac", "answer": "SEEING THAT I AM SO FINE I MAY AS WELL GO AND VISIT THE KING", "subset": "test_clean", "task_type": "understanding", "prediction": "seeing that i am so fine i may as well go and visit the king", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 868, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0012.flac", "answer": "BUT YOU MUST NOT EAT WITH YOUR CAP ON YOUR HEAD SHE SAID AND WAS GOING TO TAKE IT OFF", "subset": "test_clean", "task_type": "understanding", "prediction": "but you must not eat with your cap on your head she said and was going to take it off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 869, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0002.flac", "answer": "HE WAS SUCH A BIG BOY THAT HE WORE HIGH BOOTS AND CARRIED A JACK KNIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "he was such a big boy that he wore high boots and carried a jack knife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 870, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0006.flac", "answer": "I AM GOING TO THE COURT BALL ANSWERED ANDERS", "subset": "test_clean", "task_type": "understanding", "prediction": "i am going to the court ball answered anders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 871, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0015.flac", "answer": "WELL BUT NOW SAID THE PRINCESS AND SHE FILLED HIS POCKETS WITH CAKES AND PUT HER OWN HEAVY GOLD CHAIN AROUND HIS NECK AND BENT DOWN AND KISSED HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "well but now said the princess and she filled his pockets with cakes and put her own heavy gold chain around his neck and bent down and kissed him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 872, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0001.flac", "answer": "HE MADE A BOW SO DEEP THAT HIS BACK CAME NEAR BREAKING AND HE WAS DUMBFOUNDED I CAN TELL YOU WHEN HE SAW IT WAS NOBODY BUT ANDERS", "subset": "test_clean", "task_type": "understanding", "prediction": "he made a bow so deep that his back came near breaking and he was dumbfounded i can tell you when he saw it was nobody but anders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 873, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0008.flac", "answer": "FOR LIKE AS NOT THEY MUST HAVE THOUGHT HIM A PRINCE WHEN THEY SAW HIS FINE CAP", "subset": "test_clean", "task_type": "understanding", "prediction": "for like as not they must have thought him a prince when they saw his fine cap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 874, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0020.flac", "answer": "HE DARTED LIKE AN ARROW THROUGH ALL THE HALLS DOWN ALL THE STAIRS AND ACROSS THE YARD", "subset": "test_clean", "task_type": "understanding", "prediction": "he darted like an arrow through all the halls down all the stairs and across the yard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 875, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0022.flac", "answer": "AND ALL HIS BROTHERS AND SISTERS STOOD ROUND AND LISTENED WITH THEIR MOUTHS OPEN", "subset": "test_clean", "task_type": "understanding", "prediction": "and all his brothers and sisters stood round and listened with their mouths open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 876, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0025.flac", "answer": "BUT HIS MOTHER HUGGED HIM CLOSE", "subset": "test_clean", "task_type": "understanding", "prediction": "but his mother hugged him close", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 877, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0010.flac", "answer": "ON HUGE SILVER PLATTERS WERE PYRAMIDS OF TARTS AND CAKES AND RED WINE SPARKLED IN GLITTERING DECANTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "on huge silver platters were pyramids of tarts and cakes and red wine sparkled in glittering decanters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 878, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0009.flac", "answer": "AT THE FARTHER END OF THE LARGEST HALL A TABLE WAS SET WITH GOLDEN CUPS AND GOLDEN PLATES IN LONG ROWS", "subset": "test_clean", "task_type": "understanding", "prediction": "at the farther end of the largest hall a table was set with golden cups and golden plates in long rows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 879, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0027.flac", "answer": "IF YOU DRESSED IN SILK AND GOLD FROM TOP TO TOE YOU COULD NOT LOOK ANY NICER THAN IN YOUR LITTLE RED CAP", "subset": "test_clean", "task_type": "understanding", "prediction": "if you dressed in silk and gold from top to toe you could not look any nicer than in your little red cap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 880, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0013.flac", "answer": "THE PRINCESS CERTAINLY WAS BEAUTIFUL AND HE WOULD HAVE DEARLY LIKED TO BE KISSED BY HER BUT THE CAP WHICH HIS MOTHER HAD MADE HE WOULD NOT GIVE UP ON ANY CONDITION", "subset": "test_clean", "task_type": "understanding", "prediction": "the princess certainly was beautiful and he would have dearly liked to be kissed by her but the cap which his mother had made he would not give up on any condition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 881, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0003.flac", "answer": "NOW THIS KNIFE WAS A SPLENDID ONE THOUGH HALF THE BLADE WAS GONE AND THE HANDLE WAS A LITTLE CRACKED AND ANDERS KNEW THAT ONE IS ALMOST A MAN AS SOON AS ONE HAS A JACK KNIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "now this knife was a splendid one though half the blade was gone and the handle was a little cracked and anders knew that one is almost a man as soon as one has a jack knife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 882, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0021.flac", "answer": "HE STILL HELD ON TO IT WITH BOTH HANDS AS HE RUSHED INTO HIS MOTHER'S COTTAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "he still held on to it with both hands as he rushed into his mother s cottage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 883, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0007.flac", "answer": "AND SHE TOOK ANDERS HAND AND WALKED WITH HIM UP THE BROAD MARBLE STAIRS WHERE SOLDIERS WERE POSTED AT EVERY THIRD STEP AND THROUGH THE MAGNIFICENT HALLS WHERE COURTIERS IN SILK AND VELVET STOOD BOWING WHEREVER HE WENT", "subset": "test_clean", "task_type": "understanding", "prediction": "and she took anders hand and walked with him up the broad marble stairs where soldiers were posted at every third step and through the magnificent halls where courtiers in silk and velvet stood bowing wherever he went", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 884, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0011.flac", "answer": "THE PRINCESS SAT DOWN UNDER A BLUE CANOPY WITH BOUQUETS OF ROSES AND SHE LET ANDERS SIT IN A GOLDEN CHAIR BY HER SIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "the princess sat down under a blue canopy with bouquets of roses and she let anders sit in a golden chair by her side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 885, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0019.flac", "answer": "WITH ONE JUMP ANDERS GOT OUT OF HIS CHAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "with one jump anders got out of his chair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 886, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0014.flac", "answer": "HE ONLY SHOOK HIS HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "he only shook his head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 887, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0018.flac", "answer": "AND IT IS MADE OF MOTHER'S BEST YARN AND SHE KNITTED IT HERSELF AND EVERYBODY WANTS TO GET IT AWAY FROM ME", "subset": "test_clean", "task_type": "understanding", "prediction": "and it is made of mother s best yarn and she knitted it herself and everybody wants to get it away from me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 888, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0016.flac", "answer": "THAT IS A VERY FINE CAP YOU HAVE HE SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "that is a very fine cap you have he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 889, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0024.flac", "answer": "ANDERS FACE GREW RED", "subset": "test_clean", "task_type": "understanding", "prediction": "anders face grew red", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 890, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/85628/7021-85628-0023.flac", "answer": "BUT WHEN HIS BIG BROTHER HEARD THAT HE HAD REFUSED TO GIVE HIS CAP FOR A KING'S GOLDEN CROWN HE SAID THAT ANDERS WAS A STUPID", "subset": "test_clean", "task_type": "understanding", "prediction": "but when his big brother heard that he had refused to give his cap for a king s golden crown he said that anders was a stupid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 891, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79759/7021-79759-0003.flac", "answer": "VAST IMPORTANCE AND INFLUENCE OF THIS MENTAL FURNISHING", "subset": "test_clean", "task_type": "understanding", "prediction": "vast importance and influence of this mental furnishing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 892, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79759/7021-79759-0000.flac", "answer": "NATURE OF THE EFFECT PRODUCED BY EARLY IMPRESSIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "nature of the effect produced by early impressions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 893, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79759/7021-79759-0004.flac", "answer": "WITHOUT GOING TO ANY SUCH EXTREME AS THIS WE CAN EASILY SEE ON REFLECTION HOW VAST AN INFLUENCE ON THE IDEAS AND CONCEPTIONS AS WELL AS ON THE PRINCIPLES OF ACTION IN MATURE YEARS MUST BE EXERTED BY THE NATURE AND CHARACTER OF THE IMAGES WHICH THE PERIOD OF INFANCY AND CHILDHOOD IMPRESSES UPON THE MIND", "subset": "test_clean", "task_type": "understanding", "prediction": "without going to any such extreme as this we can easily see on reflection how vast an influence on the ideas and conceptions as well as on the principles of action in mature years must be exerted by the nature and character of the images which the period of infancy and childhood impress upon the mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 894, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79759/7021-79759-0005.flac", "answer": "THE PAIN PRODUCED BY AN ACT OF HASTY AND ANGRY VIOLENCE TO WHICH A FATHER SUBJECTS HIS SON MAY SOON PASS AWAY BUT THE MEMORY OF IT DOES NOT PASS AWAY WITH THE PAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "the pain produced by an act of hasty and angry violence to which a father subjects his son may soon pass away but the memory of it does not pass away with the pain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 895, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79759/7021-79759-0002.flac", "answer": "THEY ARE CHIEFLY FORMED FROM COMBINATIONS OF THE IMPRESSIONS MADE IN CHILDHOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "they are chiefly formed from combinations of the impressions made in childhood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 896, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79759/7021-79759-0001.flac", "answer": "THAT IS COMPARATIVELY NOTHING", "subset": "test_clean", "task_type": "understanding", "prediction": "that is comparatively nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 897, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0000.flac", "answer": "TO SUCH PERSONS THESE INDIRECT MODES OF TRAINING CHILDREN IN HABITS OF SUBORDINATION TO THEIR WILL OR RATHER OF YIELDING TO THEIR INFLUENCE ARE SPECIALLY USEFUL", "subset": "test_clean", "task_type": "understanding", "prediction": "to such persons these indirect modes of training children in habits of subordination to their will or rather of yielding to their influence are specially useful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 898, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0005.flac", "answer": "I AM VERY GLAD", "subset": "test_clean", "task_type": "understanding", "prediction": "i am very glad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 899, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0009.flac", "answer": "THEY WERE NOW PLAYING WITH THEIR DOLLS IN THE PARLOR", "subset": "test_clean", "task_type": "understanding", "prediction": "they were now playing with their dolls in the parlor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 900, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0010.flac", "answer": "DELIA CAME TO THE PARLOR AND WITH AN AIR OF GREAT MYSTERY BECKONED THE CHILDREN ASIDE AND SAID TO THEM IN A WHISPER LEAVE ANDELLA AND ROSALIE HERE AND DON'T SAY A WORD TO THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "delia came to the parlor and with an air of great mystery beckoned the children aside and said to them in a whisper leave andela and rosalie here and don t say a word to them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 901, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0008.flac", "answer": "FOR INSTANCE ONE DAY THE CHILDREN HAD BEEN PLAYING UPON THE PIAZZA WITH BLOCKS AND OTHER PLAYTHINGS AND FINALLY HAD GONE INTO THE HOUSE LEAVING ALL THE THINGS ON THE FLOOR OF THE PIAZZA INSTEAD OF PUTTING THEM AWAY IN THEIR PLACES AS THEY OUGHT TO HAVE DONE", "subset": "test_clean", "task_type": "understanding", "prediction": "for instance one day the children had been playing upon the piazza with blocks and other playthings and finally had gone into the house leaving all the things on the floor of the piazza instead of putting them away in their places as they ought to have done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 902, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0014.flac", "answer": "AND THIS METHOD OF TREATING THE CASE WAS MUCH MORE EFFECTUAL IN MAKING THEM DISPOSED TO AVOID COMMITTING A SIMILAR FAULT ANOTHER TIME THAN ANY DIRECT REBUKES OR EXPRESSIONS OF DISPLEASURE ADDRESSED PERSONALLY TO THEM WOULD HAVE BEEN", "subset": "test_clean", "task_type": "understanding", "prediction": "and this method of treating the case was much more effectual in making them disposed to avoid committing a similar fault another time than any direct rebukes or expressions of displeasure addressed personally to them would have been", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 903, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0007.flac", "answer": "THEN TURNING TO JANE SHE ASKED IN A SOMEWHAT ALTERED TONE HAS SHE BEEN A GOOD GIRL JANE", "subset": "test_clean", "task_type": "understanding", "prediction": "then turning to jane she asked in a somewhat altered tone has she been a good girl jane", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 904, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0001.flac", "answer": "DELLA HAD A YOUNG SISTER NAMED MARIA AND A COUSIN WHOSE NAME WAS JANE", "subset": "test_clean", "task_type": "understanding", "prediction": "della had a young sister named maria and a cousin whose name was jane", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 905, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0004.flac", "answer": "YOU HAVE COME ANDELLA ANDELLA WAS THE NAME OF JANE'S DOLL TO MAKE ROSALIE A VISIT", "subset": "test_clean", "task_type": "understanding", "prediction": "you have come andella andella was the name of jane s doll to make rosalie a visit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 906, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0011.flac", "answer": "SO SAYING SHE LED THE WAY ON TIPTOE FOLLOWED BY THE CHILDREN OUT OF THE ROOM AND ROUND BY A CIRCUITOUS ROUTE TO THE PIAZZA THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "so saying she led the way on tiptoe followed by the children out of the room and round by a circuitous route to the piazza there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 907, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0002.flac", "answer": "NOW DELIA CONTRIVED TO OBTAIN A GREAT INFLUENCE AND ASCENDENCY OVER THE MINDS OF THE CHILDREN BY MEANS OF THESE DOLLS", "subset": "test_clean", "task_type": "understanding", "prediction": "now delia contrived to obtain a great influence and ascendancy over the minds of the children by means of these dolls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 908, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0006.flac", "answer": "I EXPECT YOU HAVE BEEN A VERY GOOD GIRL ANDELLA SINCE YOU WERE HERE LAST", "subset": "test_clean", "task_type": "understanding", "prediction": "i expect you have been a very good girl andela since you were here last", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 909, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0012.flac", "answer": "SAID SHE POINTING TO THE PLAYTHINGS SEE", "subset": "test_clean", "task_type": "understanding", "prediction": "said she pointing to the playthings see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 910, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0013.flac", "answer": "PUT THESE PLAYTHINGS ALL AWAY QUICK AND CAREFULLY AND WE WILL NOT LET THEM KNOW ANY THING ABOUT YOUR LEAVING THEM OUT", "subset": "test_clean", "task_type": "understanding", "prediction": "put these playthings all away quick and carefully and we will not let them know anything about your leaving them out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 911, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79740/7021-79740-0003.flac", "answer": "TO GIVE AN IDEA OF THESE CONVERSATIONS I WILL REPORT ONE OF THEM IN FULL", "subset": "test_clean", "task_type": "understanding", "prediction": "to give an idea of these conversations i will report one of them in full", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 912, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0003.flac", "answer": "AS THE CHAISE DRIVES AWAY MARY STANDS BEWILDERED AND PERPLEXED ON THE DOOR STEP HER MIND IN A TUMULT OF EXCITEMENT IN WHICH HATRED OF THE DOCTOR DISTRUST AND SUSPICION OF HER MOTHER DISAPPOINTMENT VEXATION AND ILL HUMOR SURGE AND SWELL AMONG THOSE DELICATE ORGANIZATIONS ON WHICH THE STRUCTURE AND DEVELOPMENT OF THE SOUL SO CLOSELY DEPEND DOING PERHAPS AN IRREPARABLE INJURY", "subset": "test_clean", "task_type": "understanding", "prediction": "as the chaise drives away mary stands bewildered and perplexed on the door step her mind in a tumult of excitement in which hatred of the doctor distrust and suspicion of her mother disappointment vexation and ill humour surge and swell among those delicate organisations on which the structure and development of the soul so closely depend doing perhaps an irreparable injury", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 913, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0007.flac", "answer": "IF YOU SHOULD NOT BE A GOOD GIRL BUT SHOULD SHOW SIGNS OF MAKING US ANY TROUBLE I SHALL HAVE TO SEND YOU OUT SOMEWHERE TO THE BACK PART OF THE HOUSE UNTIL WE ARE GONE", "subset": "test_clean", "task_type": "understanding", "prediction": "if you should not be a good girl but should show signs of making us any trouble i shall have to send you out somewhere to the back part of the house until we are gone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 914, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0000.flac", "answer": "THE THREE MODES OF MANAGEMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "the three modes of management", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 915, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0001.flac", "answer": "TO SUPPOSE THAT THE OBJECT OF THIS WORK IS TO AID IN EFFECTING SUCH A SUBSTITUTION AS THAT IS ENTIRELY TO MISTAKE ITS NATURE AND DESIGN", "subset": "test_clean", "task_type": "understanding", "prediction": "to suppose that the object of this work is to aid in effecting such a substitution as that is entirely to mistake its nature and design", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 916, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0008.flac", "answer": "BUT THIS LAST SUPPOSITION IS ALMOST ALWAYS UNNECESSARY FOR IF MARY HAS BEEN HABITUALLY MANAGED ON THIS PRINCIPLE SHE WILL NOT MAKE ANY TROUBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "but this last supposition is almost always unnecessary for if mary has been habitually managed on this principle she will not make any trouble", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 917, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0004.flac", "answer": "THE MOTHER AS SOON AS THE CHAISE IS SO FAR TURNED THAT MARY CAN NO LONGER WATCH THE EXPRESSION OF HER COUNTENANCE GOES AWAY FROM THE DOOR WITH A SMILE OF COMPLACENCY AND SATISFACTION UPON HER FACE AT THE INGENUITY AND SUCCESS OF HER LITTLE ARTIFICE", "subset": "test_clean", "task_type": "understanding", "prediction": "the mother as soon as the chaise is so far turned that mary can no longer watch the expression of her countenance goes away from the door with a smile of complacency and satisfaction on her face at the ingenuity and success of her little artifice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 918, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0005.flac", "answer": "SO YOU WILL BE A GOOD GIRL I KNOW AND NOT MAKE ANY TROUBLE BUT WILL STAY AT HOME CONTENTEDLY WON'T YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "so you will be a good girl i know and not make any trouble but will stay at home contentedly won t you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 919, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0009.flac", "answer": "IT IS INDEED TRUE THAT THE IMPORTANCE OF TACT AND SKILL IN THE TRAINING OF THE YOUNG AND OF CULTIVATING THEIR REASON AND SECURING THEIR AFFECTION CAN NOT BE OVERRATED", "subset": "test_clean", "task_type": "understanding", "prediction": "it is indeed true that the importance of tact and skill in the training of the young and of cultivating their reason and securing their affection cannot be overrated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 920, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0002.flac", "answer": "BY REASON AND AFFECTION", "subset": "test_clean", "task_type": "understanding", "prediction": "by reason and affection", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 921, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7021/79730/7021-79730-0006.flac", "answer": "THE MOTHER IN MANAGING THE CASE IN THIS WAY RELIES PARTLY ON CONVINCING THE REASON OF THE CHILD AND PARTLY ON AN APPEAL TO HER AFFECTION", "subset": "test_clean", "task_type": "understanding", "prediction": "the mother in managing the case in this way relies partly on convincing the reason of the child and partly on an appeal to her affection", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 922, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0004.flac", "answer": "IN WINTER WHEN THE SNOW LAY GLITTERING ON THE GROUND A HARE WOULD OFTEN COME LEAPING ALONG AND JUMP RIGHT OVER THE LITTLE TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "in winter when the snow lay glittering on the ground a hare would often come leaping along and jump right over the little tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 923, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0010.flac", "answer": "REJOICE IN THY GROWTH SAID THE SUNBEAMS", "subset": "test_clean", "task_type": "understanding", "prediction": "rejoice in thy growth said the sunbeams", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 924, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0039.flac", "answer": "I WON'T TREMBLE TO MORROW THOUGHT THE FIR TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "i won t tremble to morrow thought the fir tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 925, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0051.flac", "answer": "I AM BY NO MEANS OLD SAID THE FIR TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am by no means old said the fir tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 926, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0014.flac", "answer": "WERE I BUT ALREADY ON THE CART", "subset": "test_clean", "task_type": "understanding", "prediction": "were i but already on the cards", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 927, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0052.flac", "answer": "THERE'S MANY A ONE CONSIDERABLY OLDER THAN I AM", "subset": "test_clean", "task_type": "understanding", "prediction": "there is many a one considerably older than i am", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 928, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0000.flac", "answer": "OUT IN THE WOODS STOOD A NICE LITTLE FIR TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "out in the wood stood a nice little fir tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 929, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0025.flac", "answer": "THE TREE ONLY CAME TO HIMSELF WHEN HE WAS UNLOADED IN A COURT YARD WITH THE OTHER TREES AND HEARD A MAN SAY THAT ONE IS SPLENDID WE DON'T WANT THE OTHERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the tree only came to himself when he was unloaded in a courtyard with the other trees and heard a man say that one is splendid we don t want the others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 930, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0017.flac", "answer": "SOMETHING BETTER SOMETHING STILL GRANDER MUST FOLLOW BUT WHAT", "subset": "test_clean", "task_type": "understanding", "prediction": "something better something still grander must follow but what", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 931, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0026.flac", "answer": "THERE TOO WERE LARGE EASY CHAIRS SILKEN SOFAS LARGE TABLES FULL OF PICTURE BOOKS AND FULL OF TOYS WORTH HUNDREDS AND HUNDREDS OF CROWNS AT LEAST THE CHILDREN SAID SO", "subset": "test_clean", "task_type": "understanding", "prediction": "there too were large easy chairs silken sofas large tables full of picture books and full of toys worth hundreds and hundreds of crowns at least the children said so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 932, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0048.flac", "answer": "IF IT ONLY WERE NOT SO DARK HERE AND SO TERRIBLY LONELY", "subset": "test_clean", "task_type": "understanding", "prediction": "if it only were not so dark here and so terribly lonely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 933, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0053.flac", "answer": "THEY WERE SO EXTREMELY CURIOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "they were so extremely curious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 934, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0060.flac", "answer": "IT IS A VERY STUPID STORY", "subset": "test_clean", "task_type": "understanding", "prediction": "it is a very stupid story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 935, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0058.flac", "answer": "WHO IS HUMPY DUMPY ASKED THE MICE", "subset": "test_clean", "task_type": "understanding", "prediction": "who is humpty dumpty asked the mice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 936, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0068.flac", "answer": "BUT IT WAS NOT THE FIR TREE THAT THEY MEANT", "subset": "test_clean", "task_type": "understanding", "prediction": "but it was not the fir tree that they meant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 937, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0050.flac", "answer": "THEY SNUFFED ABOUT THE FIR TREE AND RUSTLED AMONG THE BRANCHES", "subset": "test_clean", "task_type": "understanding", "prediction": "they snuffed about the fir tree and rustled among the branches", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 938, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0030.flac", "answer": "PERHAPS THE OTHER TREES FROM THE FOREST WILL COME TO LOOK AT ME", "subset": "test_clean", "task_type": "understanding", "prediction": "perhaps the other trees from the forest will come to look at me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 939, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0032.flac", "answer": "CRIED THE YOUNG LADIES AND THEY QUICKLY PUT OUT THE FIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "cried the young ladies and they quickly put out the fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 940, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0073.flac", "answer": "THE WOOD FLAMED UP SPLENDIDLY UNDER THE LARGE BREWING COPPER AND IT SIGHED SO DEEPLY", "subset": "test_clean", "task_type": "understanding", "prediction": "the wood flamed up splendidly under the large brewing copper and it sighed so deeply", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 941, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0071.flac", "answer": "IN THE COURT YARD SOME OF THE MERRY CHILDREN WERE PLAYING WHO HAD DANCED AT CHRISTMAS ROUND THE FIR TREE AND WERE SO GLAD AT THE SIGHT OF HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "in the courtyard some of the married children were playing who had danced at christmas round the fir tree and were so glad at the sight of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 942, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0044.flac", "answer": "AND HE LEANED AGAINST THE WALL LOST IN REVERIE", "subset": "test_clean", "task_type": "understanding", "prediction": "and he leaned against the wall lost in reverie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 943, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0007.flac", "answer": "IN AUTUMN THE WOOD CUTTERS ALWAYS CAME AND FELLED SOME OF THE LARGEST TREES", "subset": "test_clean", "task_type": "understanding", "prediction": "in autumn the woodcutters always came and felled some of the largest trees", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 944, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0020.flac", "answer": "BUT THE TREE DID NOT REJOICE AT ALL HE GREW AND GREW AND WAS GREEN BOTH WINTER AND SUMMER", "subset": "test_clean", "task_type": "understanding", "prediction": "but the tree did not rejoice at all he grew and grew and was green both winter and summer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 945, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0064.flac", "answer": "AT LAST THE LITTLE MICE STAYED AWAY ALSO AND THE TREE SIGHED AFTER ALL IT WAS VERY PLEASANT WHEN THE SLEEK LITTLE MICE SAT ROUND ME AND LISTENED TO WHAT I TOLD THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "at last the little mice stayed away also and the tree sighed after all it was very pleasant when the sleek little mice sat round me and listened to what i told them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 946, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0067.flac", "answer": "THE TRUNKS WERE MOVED THE TREE WAS PULLED OUT AND THROWN RATHER HARD IT IS TRUE DOWN ON THE FLOOR BUT A MAN DREW HIM TOWARDS THE STAIRS WHERE THE DAYLIGHT SHONE", "subset": "test_clean", "task_type": "understanding", "prediction": "the trunks were moved the tree was pulled out and thrown rather hard it is true down on the floor but a man drew him towards the stairs where the daylight shone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 947, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0057.flac", "answer": "YES IN REALITY THOSE WERE HAPPY TIMES", "subset": "test_clean", "task_type": "understanding", "prediction": "yes in reality those were happy times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 948, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0015.flac", "answer": "WERE I IN THE WARM ROOM WITH ALL THE SPLENDOR AND MAGNIFICENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "were i in the warm room with all the splendor and magnificence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 949, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0069.flac", "answer": "IT WAS IN A CORNER THAT HE LAY AMONG WEEDS AND NETTLES", "subset": "test_clean", "task_type": "understanding", "prediction": "it was in a corner that he lay among weeds and nettles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 950, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0070.flac", "answer": "THE GOLDEN STAR OF TINSEL WAS STILL ON THE TOP OF THE TREE AND GLITTERED IN THE SUNSHINE", "subset": "test_clean", "task_type": "understanding", "prediction": "the golden star of tinsel was still on the top of the tree and glittered in the sunshine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 951, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0034.flac", "answer": "A STORY CRIED THE CHILDREN DRAWING A LITTLE FAT MAN TOWARDS THE TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "a story cried the children drawing a little fat man towards the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 952, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0035.flac", "answer": "BUT I SHALL TELL ONLY ONE STORY", "subset": "test_clean", "task_type": "understanding", "prediction": "but i shall tell only one story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 953, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0043.flac", "answer": "WHAT'S THE MEANING OF THIS THOUGHT THE TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "what is the meaning of this thought the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 954, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0024.flac", "answer": "THE DEPARTURE WAS NOT AT ALL AGREEABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "the departure was not at all agreeable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 955, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0040.flac", "answer": "AND THE WHOLE NIGHT THE TREE STOOD STILL AND IN DEEP THOUGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "and the whole night the tree stood still and in deep thought", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 956, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0046.flac", "answer": "TIS NOW WINTER OUT OF DOORS THOUGHT THE TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "tis now winter out of doors thought the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 957, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0037.flac", "answer": "THAT'S THE WAY OF THE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "that is the way of the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 958, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0012.flac", "answer": "I WOULD FAIN KNOW IF I AM DESTINED FOR SO GLORIOUS A CAREER CRIED THE TREE REJOICING", "subset": "test_clean", "task_type": "understanding", "prediction": "i would fain know if i am destined for so glorious a career cried the tree rejoicing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 959, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0031.flac", "answer": "IT BLAZED UP FAMOUSLY HELP HELP", "subset": "test_clean", "task_type": "understanding", "prediction": "it blazed up famously help help", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 960, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0049.flac", "answer": "SQUEAK SQUEAK", "subset": "test_clean", "task_type": "understanding", "prediction": "squeak squeak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 961, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0023.flac", "answer": "HE WELL KNEW THAT HE SHOULD NEVER SEE HIS DEAR OLD COMRADES THE LITTLE BUSHES AND FLOWERS AROUND HIM ANYMORE PERHAPS NOT EVEN THE BIRDS", "subset": "test_clean", "task_type": "understanding", "prediction": "he well knew that he should never see his dear old comrades the little bushes and flowers around him any more perhaps not even the birds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 962, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0011.flac", "answer": "AND THEN WHAT HAPPENS THEN", "subset": "test_clean", "task_type": "understanding", "prediction": "and then what happens then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 963, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0002.flac", "answer": "HE DID NOT THINK OF THE WARM SUN AND OF THE FRESH AIR HE DID NOT CARE FOR THE LITTLE COTTAGE CHILDREN THAT RAN ABOUT AND PRATTLED WHEN THEY WERE IN THE WOODS LOOKING FOR WILD STRAWBERRIES", "subset": "test_clean", "task_type": "understanding", "prediction": "he did not think of the warm sun and of the fresh air he did not care for the little cottage children that ran about and prattled when they were in the woods looking for wild strawberries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 964, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0029.flac", "answer": "HOW IT WILL SHINE THIS EVENING", "subset": "test_clean", "task_type": "understanding", "prediction": "how it will shine this evening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 965, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0038.flac", "answer": "THOUGHT THE FIR TREE AND BELIEVED IT ALL BECAUSE THE MAN WHO TOLD THE STORY WAS SO GOOD LOOKING WELL WELL", "subset": "test_clean", "task_type": "understanding", "prediction": "thought the fir tree and believed it all because the man who told the story was so good looking well well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 966, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0018.flac", "answer": "REJOICE IN OUR PRESENCE SAID THE AIR AND THE SUNLIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "rejoice in our presence said the air and the sunlight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 967, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0021.flac", "answer": "AND TOWARDS CHRISTMAS HE WAS ONE OF THE FIRST THAT WAS CUT DOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "and towards christmas he was one of the first that was cut down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 968, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0066.flac", "answer": "WHY ONE MORNING THERE CAME A QUANTITY OF PEOPLE AND SET TO WORK IN THE LOFT", "subset": "test_clean", "task_type": "understanding", "prediction": "why one morning there came a quantity of people and set to work in the loft", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 969, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0036.flac", "answer": "HUMPY DUMPY FELL DOWNSTAIRS AND YET HE MARRIED THE PRINCESS", "subset": "test_clean", "task_type": "understanding", "prediction": "humpty dumpty fell down stairs and yet he married the princess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 970, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0045.flac", "answer": "TIME ENOUGH HAD HE TOO FOR HIS REFLECTIONS FOR DAYS AND NIGHTS PASSED ON AND NOBODY CAME UP AND WHEN AT LAST SOMEBODY DID COME IT WAS ONLY TO PUT SOME GREAT TRUNKS IN A CORNER OUT OF THE WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "time enough had he too for his reflections for days and nights passed on and nobody came up and when at last somebody did come it was only to put some great trunks in a corner out of the way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 971, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0061.flac", "answer": "DON'T YOU KNOW ONE ABOUT BACON AND TALLOW CANDLES CAN'T YOU TELL ANY LARDER STORIES", "subset": "test_clean", "task_type": "understanding", "prediction": "dont you know one about bacon and tallow candles canst you tell any louder stories", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 972, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0001.flac", "answer": "THE PLACE HE HAD WAS A VERY GOOD ONE THE SUN SHONE ON HIM AS TO FRESH AIR THERE WAS ENOUGH OF THAT AND ROUND HIM GREW MANY LARGE SIZED COMRADES PINES AS WELL AS FIRS", "subset": "test_clean", "task_type": "understanding", "prediction": "the place he had was a very good one the sun shone on him as to fresh air there was enough of that and round him grew many large sized comrades pines as well as firs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 973, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0074.flac", "answer": "HOWEVER THAT WAS OVER NOW THE TREE GONE THE STORY AT AN END", "subset": "test_clean", "task_type": "understanding", "prediction": "however that was over now the tree gone the story at an end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 974, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0056.flac", "answer": "SAID THE FIR TREE THINKING OVER WHAT HE HAD HIMSELF RELATED", "subset": "test_clean", "task_type": "understanding", "prediction": "said the fir tree thinking over what he had himself related", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 975, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0022.flac", "answer": "THE AXE STRUCK DEEP INTO THE VERY PITH THE TREE FELL TO THE EARTH WITH A SIGH HE FELT A PANG IT WAS LIKE A SWOON HE COULD NOT THINK OF HAPPINESS FOR HE WAS SORROWFUL AT BEING SEPARATED FROM HIS HOME FROM THE PLACE WHERE HE HAD SPRUNG UP", "subset": "test_clean", "task_type": "understanding", "prediction": "the axe struck deep into the very pith the tree fell to the earth with a sigh he felt a pang it was like a swoon he could not think of happiness for he was sorrowful at being separated from his home from the place where he had sprung up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 976, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0008.flac", "answer": "THIS HAPPENED EVERY YEAR AND THE YOUNG FIR TREE THAT HAD NOW GROWN TO A VERY COMELY SIZE TREMBLED AT THE SIGHT FOR THE MAGNIFICENT GREAT TREES FELL TO THE EARTH WITH NOISE AND CRACKING THE BRANCHES WERE LOPPED OFF AND THE TREES LOOKED LONG AND BARE THEY WERE HARDLY TO BE RECOGNISED AND THEN THEY WERE LAID IN CARTS AND THE HORSES DRAGGED THEM OUT OF THE WOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "this happened every year and the young fir tree that had now grown to a very comely size trembled at the sight for the magnificent great trees fell to the earth with noise and cracking the branches were lopped off and the trees looked long and bare they were hardly to be recognized and then they were laid in carts and the horses dragged them out of the wood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 977, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0065.flac", "answer": "NOW THAT TOO IS OVER", "subset": "test_clean", "task_type": "understanding", "prediction": "now that too is over", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 978, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0054.flac", "answer": "I KNOW NO SUCH PLACE SAID THE TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "i know no such place said the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 979, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0003.flac", "answer": "BUT THIS WAS WHAT THE TREE COULD NOT BEAR TO HEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "but this was what the tree could not bear to hear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 980, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0027.flac", "answer": "THE SERVANTS AS WELL AS THE YOUNG LADIES DECORATED IT", "subset": "test_clean", "task_type": "understanding", "prediction": "the servants as well as the young ladies decorated it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 981, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0063.flac", "answer": "THEN GOOD BYE SAID THE RATS AND THEY WENT HOME", "subset": "test_clean", "task_type": "understanding", "prediction": "then good bye said the rats and they went home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 982, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0028.flac", "answer": "THIS EVENING THEY ALL SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "this evening they all said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 983, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0047.flac", "answer": "HOW KIND MAN IS AFTER ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "how kind man is after all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 984, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0016.flac", "answer": "YES THEN SOMETHING BETTER SOMETHING STILL GRANDER WILL SURELY FOLLOW OR WHEREFORE SHOULD THEY THUS ORNAMENT ME", "subset": "test_clean", "task_type": "understanding", "prediction": "yes and something better something still grander will surely follow or wherefore should they thus ornament me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 985, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0059.flac", "answer": "ONLY THAT ONE ANSWERED THE TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "only that one answered the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 986, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0006.flac", "answer": "TO GROW AND GROW TO GET OLDER AND BE TALL THOUGHT THE TREE THAT AFTER ALL IS THE MOST DELIGHTFUL THING IN THE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "to grow and grow to get older and be tall thought the tree that after all is the most delightful thing in the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 987, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0072.flac", "answer": "AND THE GARDENER'S BOY CHOPPED THE TREE INTO SMALL PIECES THERE WAS A WHOLE HEAP LYING THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "and the gardener s boy chopped the tree into small pieces there was a whole heap lying there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 988, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0055.flac", "answer": "AND THEN HE TOLD ALL ABOUT HIS YOUTH AND THE LITTLE MICE HAD NEVER HEARD THE LIKE BEFORE AND THEY LISTENED AND SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "and then he told all about his youth and the little mice had never heard the like before and they listened and said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 989, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0042.flac", "answer": "BUT THEY DRAGGED HIM OUT OF THE ROOM AND UP THE STAIRS INTO THE LOFT AND HERE IN A DARK CORNER WHERE NO DAYLIGHT COULD ENTER THEY LEFT HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "but they dragged him out of the room and up the stairs into the loft and here in a dark corner where no daylight could enter they left him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 990, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0009.flac", "answer": "HAVE YOU NOT MET THEM ANYWHERE", "subset": "test_clean", "task_type": "understanding", "prediction": "have you not met them anywhere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 991, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0005.flac", "answer": "OH THAT MADE HIM SO ANGRY", "subset": "test_clean", "task_type": "understanding", "prediction": "oh that made him so angry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 992, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0013.flac", "answer": "I AM NOW TALL AND MY BRANCHES SPREAD LIKE THE OTHERS THAT WERE CARRIED OFF LAST YEAR OH", "subset": "test_clean", "task_type": "understanding", "prediction": "i am now tall and my branches spread like the others that were carried off last year oh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 993, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0019.flac", "answer": "REJOICE IN THY OWN FRESH YOUTH", "subset": "test_clean", "task_type": "understanding", "prediction": "rejoice in thy own fresh youth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 994, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0041.flac", "answer": "IN THE MORNING THE SERVANT AND THE HOUSEMAID CAME IN", "subset": "test_clean", "task_type": "understanding", "prediction": "in the morning the servant and the housemaid came in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 995, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0062.flac", "answer": "NO SAID THE TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "no said the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 996, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/672/122797/672-122797-0033.flac", "answer": "A STORY", "subset": "test_clean", "task_type": "understanding", "prediction": "a story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 997, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0019.flac", "answer": "THE LARGE LETTER CONTAINS INDEED ENTIRELY FEEBLE AND ILL DRAWN FIGURES THAT IS MERELY CHILDISH AND FAILING WORK OF AN INFERIOR HAND IT IS NOT CHARACTERISTIC OF GOTHIC OR ANY OTHER SCHOOL", "subset": "test_clean", "task_type": "understanding", "prediction": "the large letter contains indeed entirely feeble and ill drawn figures that is merely childish and failing work of an inferior hand it is not characteristic of gothic or any other school", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 998, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0043.flac", "answer": "SEE THAT YOUR LIVES BE IN NOTHING WORSE THAN A BOY'S CLIMBING FOR HIS ENTANGLED KITE", "subset": "test_clean", "task_type": "understanding", "prediction": "see that your lies be in nothing worse than a boy s climbing for his entangled kite", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 999, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0001.flac", "answer": "THEY UNITE EVERY QUALITY AND SOMETIMES YOU WILL FIND ME REFERRING TO THEM AS COLORISTS SOMETIMES AS CHIAROSCURISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "they unite every quality and sometimes you will find me referring to them as colourists sometimes as chiaroscuroists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1000, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0033.flac", "answer": "EVERY PLANT IN THE GRASS IS SET FORMALLY GROWS PERFECTLY AND MAY BE REALIZED COMPLETELY", "subset": "test_clean", "task_type": "understanding", "prediction": "every plant in the grass is set formally grows perfectly and may be realized completely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1001, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0031.flac", "answer": "THERE'S ONE AND THERE'S ANOTHER THE DUDLEY AND THE FLINT", "subset": "test_clean", "task_type": "understanding", "prediction": "there is one and there is another the dudley and the flint", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1002, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0042.flac", "answer": "THE SCENE IS ABSOLUTELY ARCADIAN", "subset": "test_clean", "task_type": "understanding", "prediction": "the scene is absolutely arcadian", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1003, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0013.flac", "answer": "IT MUST REMEMBER BE ONE OR THE OTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "it must remember be one or the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1004, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0032.flac", "answer": "IT IS ONLY A PENCIL OUTLINE BY EDWARD BURNE JONES IN ILLUSTRATION OF THE STORY OF PSYCHE IT IS THE INTRODUCTION OF PSYCHE AFTER ALL HER TROUBLES INTO HEAVEN", "subset": "test_clean", "task_type": "understanding", "prediction": "it is only a pencil outline by edward byrne jones in illustration of the story of psyche it is the introduction of psyche after all her troubles into heaven", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1005, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0040.flac", "answer": "THE CRAMPNESS AND THE POVERTY ARE ALL INTENDED", "subset": "test_clean", "task_type": "understanding", "prediction": "the crampness and the poverty are all intended", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1006, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0016.flac", "answer": "THIS AT ONCE COMPELS YOU TO UNDERSTAND THAT THE WORK IS TO BE IMAGINATIVE AND DECORATIVE THAT IT REPRESENTS BEAUTIFUL THINGS IN THE CLEAREST WAY BUT NOT UNDER EXISTING CONDITIONS AND THAT IN FACT YOU ARE PRODUCING JEWELER'S WORK RATHER THAN PICTURES", "subset": "test_clean", "task_type": "understanding", "prediction": "this at once compels you to understand that the work is to be imaginative and decorative that it represents beautiful things in the clearest way but not under existing conditions and that in fact you are producing jewellers work rather than pictures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1007, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0000.flac", "answer": "YOU WILL FIND ME CONTINUALLY SPEAKING OF FOUR MEN TITIAN HOLBEIN TURNER AND TINTORET IN ALMOST THE SAME TERMS", "subset": "test_clean", "task_type": "understanding", "prediction": "you will find me continually speaking of four men titian holbein turner and tintoret in almost the same terms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1008, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0044.flac", "answer": "IT WILL BE WELL FOR YOU IF YOU JOIN NOT WITH THOSE WHO INSTEAD OF KITES FLY FALCONS WHO INSTEAD OF OBEYING THE LAST WORDS OF THE GREAT CLOUD SHEPHERD TO FEED HIS SHEEP LIVE THE LIVES HOW MUCH LESS THAN VANITY OF THE WAR WOLF AND THE GIER EAGLE", "subset": "test_clean", "task_type": "understanding", "prediction": "it will be well for you if you join not with those who instead of kites fly falcons who instead of obeying the last words of the great cloud shepherd to feed his sheep live the lives how much less than vanity of the war wolf and the geer eagle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1009, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0020.flac", "answer": "BUT OBSERVE YOU CAN ONLY DO THIS ON ONE CONDITION THAT OF STRIVING ALSO TO CREATE IN REALITY THE BEAUTY WHICH YOU SEEK IN IMAGINATION", "subset": "test_clean", "task_type": "understanding", "prediction": "but observe you can only do this on one condition that of striving also to create in reality the beauty which you seek in imagination", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1010, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0030.flac", "answer": "HE KNOWS THEM BOTH", "subset": "test_clean", "task_type": "understanding", "prediction": "he knows them both", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1011, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0035.flac", "answer": "THUS IN CHAUCER'S DREAM", "subset": "test_clean", "task_type": "understanding", "prediction": "thus in chaucer s dream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1012, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0023.flac", "answer": "THE COLORIST SAYS FIRST OF ALL AS MY DELICIOUS PAROQUET WAS RUBY SO THIS NASTY VIPER SHALL BE BLACK AND THEN IS THE QUESTION CAN I ROUND HIM OFF EVEN THOUGH HE IS BLACK AND MAKE HIM SLIMY AND YET SPRINGY AND CLOSE DOWN CLOTTED LIKE A POOL OF BLACK BLOOD ON THE EARTH ALL THE SAME", "subset": "test_clean", "task_type": "understanding", "prediction": "the colorist says first of all as my delicious paroquet was ruby so this nasty viper shall be black and then is the question can i round him off even though he is black and make him slimy and yet springy and close down clotted like a pool of black blood on the earth all the same", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1013, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0002.flac", "answer": "BY BEING STUDIOUS OF COLOR THEY ARE STUDIOUS OF DIVISION AND WHILE THE CHIAROSCURIST DEVOTES HIMSELF TO THE REPRESENTATION OF DEGREES OF FORCE IN ONE THING UNSEPARATED LIGHT THE COLORISTS HAVE FOR THEIR FUNCTION THE ATTAINMENT OF BEAUTY BY ARRANGEMENT OF THE DIVISIONS OF LIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "by being studious of colour they are studious of division and while the chiaroscuroist devotes himself to the representation of degrees of force in one thing unseparated light the colourists have for their function the attainment of beauty by arrangement of the divisions of light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1014, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0039.flac", "answer": "IT HAS NO BEAUTY WHATSOEVER NO SPECIALTY OF PICTURESQUENESS AND ALL ITS LINES ARE CRAMPED AND POOR", "subset": "test_clean", "task_type": "understanding", "prediction": "it has no beauty whatsoever no specialty of picturesqueness and all its lines are cramped and poor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1015, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0021.flac", "answer": "IT WILL BE WHOLLY IMPOSSIBLE FOR YOU TO RETAIN THE TRANQUILLITY OF TEMPER AND FELICITY OF FAITH NECESSARY FOR NOBLE PURIST PAINTING UNLESS YOU ARE ACTIVELY ENGAGED IN PROMOTING THE FELICITY AND PEACE OF PRACTICAL LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "it will be wholly impossible for you to retain the tranquillity of temper and felicity of faith necessary for noble purest painting unless you are actively engaged in promoting the felicity and peace of practical life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1016, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0022.flac", "answer": "YOU MUST LOOK AT HIM IN THE FACE FIGHT HIM CONQUER HIM WITH WHAT SCATHE YOU MAY YOU NEED NOT THINK TO KEEP OUT OF THE WAY OF HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "you must look him in the face fight him conquer him with what scathe you may you need not think to keep out of the way of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1017, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0010.flac", "answer": "BUT IN THIS VIGNETTE COPIED FROM TURNER YOU HAVE THE TWO PRINCIPLES BROUGHT OUT PERFECTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "but in this vignette copied from turner you have the two principles brought out perfectly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1018, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0025.flac", "answer": "YOU KNOW I HAVE JUST BEEN TELLING YOU HOW THIS SCHOOL OF MATERIALISM AND CLAY INVOLVED ITSELF AT LAST IN CLOUD AND FIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "you know i have just been telling you how this school of materialism in clay involved itself at last in cloud and fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1019, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0014.flac", "answer": "DO NOT THEREFORE THINK THAT THE GOTHIC SCHOOL IS AN EASY ONE", "subset": "test_clean", "task_type": "understanding", "prediction": "do not therefore think that the gothic school is an easy one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1020, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0036.flac", "answer": "IN BOTH THESE HIGH MYTHICAL SUBJECTS THE SURROUNDING NATURE THOUGH SUFFERING IS STILL DIGNIFIED AND BEAUTIFUL", "subset": "test_clean", "task_type": "understanding", "prediction": "in both these high mythical subjects the surrounding nature though suffering is still dignified and beautiful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1021, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0038.flac", "answer": "BUT NOW HERE IS A SUBJECT OF WHICH YOU WILL WONDER AT FIRST WHY TURNER DREW IT AT ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "but now here is a subject of which you will wonder at first why turner drew it at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1022, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0034.flac", "answer": "EXQUISITE ORDER AND UNIVERSAL WITH ETERNAL LIFE AND LIGHT THIS IS THE FAITH AND EFFORT OF THE SCHOOLS OF CRYSTAL AND YOU MAY DESCRIBE AND COMPLETE THEIR WORK QUITE LITERALLY BY TAKING ANY VERSES OF CHAUCER IN HIS TENDER MOOD AND OBSERVING HOW HE INSISTS ON THE CLEARNESS AND BRIGHTNESS FIRST AND THEN ON THE ORDER", "subset": "test_clean", "task_type": "understanding", "prediction": "exquisite order and universal with eternal life and light this is the faith and effort of the schools of crystal and you may describe and complete their work quite literally by taking any verses of chaucer in his tender mood and observing how he insists on the clearness and brightness first and then on the order", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1023, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0005.flac", "answer": "IT IS THE HEAD OF A PARROT WITH A LITTLE FLOWER IN HIS BEAK FROM A PICTURE OF CARPACCIO'S ONE OF HIS SERIES OF THE LIFE OF SAINT GEORGE", "subset": "test_clean", "task_type": "understanding", "prediction": "it is the head of a parrot with a little flower in his beak from a picture of carpaccio s one of his series of the life of st george", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1024, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0017.flac", "answer": "THAT A STYLE IS RESTRAINED OR SEVERE DOES NOT MEAN THAT IT IS ALSO ERRONEOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "that a style is restrained or severe does not mean that it is also erroneous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1025, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0012.flac", "answer": "IT MAY BE THAT A GREAT COLORIST WILL USE HIS UTMOST FORCE OF COLOR AS A SINGER HIS FULL POWER OF VOICE BUT LOUD OR LOW THE VIRTUE IS IN BOTH CASES ALWAYS IN REFINEMENT NEVER IN LOUDNESS", "subset": "test_clean", "task_type": "understanding", "prediction": "it may be that a great colorist will use his utmost force of color as a singer his full power of voice but loud or low the virtue is in both cases always in refinement never in loudness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1026, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0018.flac", "answer": "IN ALL EARLY GOTHIC ART INDEED YOU WILL FIND FAILURE OF THIS KIND ESPECIALLY DISTORTION AND RIGIDITY WHICH ARE IN MANY RESPECTS PAINFULLY TO BE COMPARED WITH THE SPLENDID REPOSE OF CLASSIC ART", "subset": "test_clean", "task_type": "understanding", "prediction": "in all early gothic art indeed you will find failure of this kind especially distortion and rigidity which are in many respects painfully to be compared with the splendid repose of classic art", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1027, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0006.flac", "answer": "THEN HE COMES TO THE BEAK OF IT", "subset": "test_clean", "task_type": "understanding", "prediction": "then he comes to the beak of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1028, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0015.flac", "answer": "THE LAW OF THAT SCHOOL IS THAT EVERYTHING SHALL BE SEEN CLEARLY OR AT LEAST ONLY IN SUCH MIST OR FAINTNESS AS SHALL BE DELIGHTFUL AND I HAVE NO DOUBT THAT THE BEST INTRODUCTION TO IT WOULD BE THE ELEMENTARY PRACTICE OF PAINTING EVERY STUDY ON A GOLDEN GROUND", "subset": "test_clean", "task_type": "understanding", "prediction": "the law of that school is that everything shall be seen clearly or at least only in such mist or faintness as shall be delightful and i have no doubt that the best introduction to it would be the elementary practice of painting every study on a golden ground", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1029, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0007.flac", "answer": "THE BROWN GROUND BENEATH IS LEFT FOR THE MOST PART ONE TOUCH OF BLACK IS PUT FOR THE HOLLOW TWO DELICATE LINES OF DARK GRAY DEFINE THE OUTER CURVE AND ONE LITTLE QUIVERING TOUCH OF WHITE DRAWS THE INNER EDGE OF THE MANDIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "the brown ground beneath is left for the most part one touch of black is put for the hollow two delicate lines of dark gray define the outer curve and one little quivering touch of white draws the inner edge of the mandible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1030, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0003.flac", "answer": "MY FIRST AND PRINCIPAL REASON WAS THAT THEY ENFORCED BEYOND ALL RESISTANCE ON ANY STUDENT WHO MIGHT ATTEMPT TO COPY THEM THIS METHOD OF LAYING PORTIONS OF DISTINCT HUE SIDE BY SIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "my first and principal reason was that they enforced beyond all resistance on any student who might attempt to copy them this method of laying portions of distinct hue side by side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1031, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0028.flac", "answer": "WELL THEN LAST HERE IS TURNER'S GREEK SCHOOL OF THE HIGHEST CLASS AND YOU DEFINE HIS ART ABSOLUTELY AS FIRST THE DISPLAYING INTENSELY AND WITH THE STERNEST INTELLECT OF NATURAL FORM AS IT IS AND THEN THE ENVELOPMENT OF IT WITH CLOUD AND FIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "well then last here is turner s greek school of the highest class and you define his art absolutely as first the displaying intensely and with the sternest intellect of natural form as it is and then the envelopment of it with cloud and fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1032, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0008.flac", "answer": "FOR BELIEVE ME THE FINAL PHILOSOPHY OF ART CAN ONLY RATIFY THEIR OPINION THAT THE BEAUTY OF A COCK ROBIN IS TO BE RED AND OF A GRASS PLOT TO BE GREEN AND THE BEST SKILL OF ART IS IN INSTANTLY SEIZING ON THE MANIFOLD DELICIOUSNESS OF LIGHT WHICH YOU CAN ONLY SEIZE BY PRECISION OF INSTANTANEOUS TOUCH", "subset": "test_clean", "task_type": "understanding", "prediction": "for believe me the final philosophy of art can only ratify their opinion that the beauty of a cock robin is to be red and of a grass plot to be green and the best skill of art is an instantly seizing on the manifold deliciousness of light which you can only seize by precision of instantaneous touch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1033, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0029.flac", "answer": "ONLY THERE ARE TWO SORTS OF CLOUD AND FIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "only there are two sorts of cloud and fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1034, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0026.flac", "answer": "HERE IS AN EQUALLY TYPICAL GREEK SCHOOL LANDSCAPE BY WILSON LOST WHOLLY IN GOLDEN MIST THE TREES SO SLIGHTLY DRAWN THAT YOU DON'T KNOW IF THEY ARE TREES OR TOWERS AND NO CARE FOR COLOR WHATEVER PERFECTLY DECEPTIVE AND MARVELOUS EFFECT OF SUNSHINE THROUGH THE MIST APOLLO AND THE PYTHON", "subset": "test_clean", "task_type": "understanding", "prediction": "here is an equally typical greek school landscape by wilson lost wholly in golden mist the trees so slightly drawn that you do not know if they are trees or towers and no care for color whatsoever perfectly deceptive and marvelous effect of sunshine through the mist apollo and the python", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1035, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0004.flac", "answer": "SOME OF THE TOUCHES INDEED WHEN THE TINT HAS BEEN MIXED WITH MUCH WATER HAVE BEEN LAID IN LITTLE DROPS OR PONDS SO THAT THE PIGMENT MIGHT CRYSTALLIZE HARD AT THE EDGE", "subset": "test_clean", "task_type": "understanding", "prediction": "some of the touches indeed when the tint has been mixed with much water have been laid in little drops or ponds so that the pigment might crystallize hard at the edge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1036, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0009.flac", "answer": "NOW YOU WILL SEE IN THESE STUDIES THAT THE MOMENT THE WHITE IS INCLOSED PROPERLY AND HARMONIZED WITH THE OTHER HUES IT BECOMES SOMEHOW MORE PRECIOUS AND PEARLY THAN THE WHITE PAPER AND THAT I AM NOT AFRAID TO LEAVE A WHOLE FIELD OF UNTREATED WHITE PAPER ALL ROUND IT BEING SURE THAT EVEN THE LITTLE DIAMONDS IN THE ROUND WINDOW WILL TELL AS JEWELS IF THEY ARE GRADATED JUSTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "now you will see in these studies that the moment the white is enclosed properly and harmonized with the other hues it becomes somehow more precious and pearly than the white paper and that i am not afraid to leave a whole field of untreated white paper all round it being sure that even the little diamonds in the round window will tell as jewels if they are gradated justly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1037, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0024.flac", "answer": "NOTHING WILL BE MORE PRECIOUS TO YOU I THINK IN THE PRACTICAL STUDY OF ART THAN THE CONVICTION WHICH WILL FORCE ITSELF ON YOU MORE AND MORE EVERY HOUR OF THE WAY ALL THINGS ARE BOUND TOGETHER LITTLE AND GREAT IN SPIRIT AND IN MATTER", "subset": "test_clean", "task_type": "understanding", "prediction": "nothing will be more precious to you i think in the practical study of art than the conviction which will force itself on you more and more every hour of the way all things are bound together little and great in spirit and in matter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1038, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0037.flac", "answer": "EVERY LINE IN WHICH THE MASTER TRACES IT EVEN WHERE SEEMINGLY NEGLIGENT IS LOVELY AND SET DOWN WITH A MEDITATIVE CALMNESS WHICH MAKES THESE TWO ETCHINGS CAPABLE OF BEING PLACED BESIDE THE MOST TRANQUIL WORK OF HOLBEIN OR DUERER", "subset": "test_clean", "task_type": "understanding", "prediction": "every line in which the master traces it even where seemingly negligent is lovely and set down with a meditative calmness which makes these two etchings capable of being placed beside the most tranquil work of holbein or doure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1039, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0041.flac", "answer": "IT IS A GLEANER BRINGING DOWN HER ONE SHEAF OF CORN TO AN OLD WATERMILL ITSELF MOSSY AND RENT SCARCELY ABLE TO GET ITS STONES TO TURN", "subset": "test_clean", "task_type": "understanding", "prediction": "it is a gleaner bringing down her one sheaf of corn to an old water mill itself mossy and rent scarcely able to get its stones to turn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1040, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0027.flac", "answer": "NOW HERE IS RAPHAEL EXACTLY BETWEEN THE TWO TREES STILL DRAWN LEAF BY LEAF WHOLLY FORMAL BUT BEAUTIFUL MIST COMING GRADUALLY INTO THE DISTANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "now here is raphael exactly between the two trees still drawn leaf by leaf wholly formal but beautiful mist coming gradually into the distance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1041, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1188/133604/1188-133604-0011.flac", "answer": "THEY ARE BEYOND ALL OTHER WORKS THAT I KNOW EXISTING DEPENDENT FOR THEIR EFFECT ON LOW SUBDUED TONES THEIR FAVORITE CHOICE IN TIME OF DAY BEING EITHER DAWN OR TWILIGHT AND EVEN THEIR BRIGHTEST SUNSETS PRODUCED CHIEFLY OUT OF GRAY PAPER", "subset": "test_clean", "task_type": "understanding", "prediction": "they are beyond all other works that i know existing dependent for their effect on low subdued tones their favourite choice in time of day being either dawn or twilight and even their brightest sunsets produced chiefly out of grey paper", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1042, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0018.flac", "answer": "HE SOON FORESAW THAT STILL GREATER ECONOMY WOULD BE NECESSARY FOR COMMERCIAL SUCCESS NOT ALONE FOR THE LARGER TERRITORY OPENING BUT FOR THE COMPACT DISTRICTS OF LARGE CITIES", "subset": "test_clean", "task_type": "understanding", "prediction": "he soon foresaw that still greater economy would be necessary for commercial success not alone for the larger territory opening but for the compact district of large cities", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1043, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0036.flac", "answer": "THE METER CONTINUED IN GENERAL SERVICE DURING EIGHTEEN NINETY NINE AND PROBABLY UP TO THE CLOSE OF THE CENTURY", "subset": "test_clean", "task_type": "understanding", "prediction": "the meter continued in general service during eighteen ninety nine and probably up to the close of the century", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1044, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0019.flac", "answer": "THE STRONG POSITION HELD BY THE EDISON SYSTEM UNDER THE STRENUOUS COMPETITION THAT WAS ALREADY SPRINGING UP WAS ENORMOUSLY IMPROVED BY THE INTRODUCTION OF THE THREE WIRE SYSTEM AND IT GAVE AN IMMEDIATE IMPETUS TO INCANDESCENT LIGHTING", "subset": "test_clean", "task_type": "understanding", "prediction": "the strong position held by the edison system under the strenuous competition that was already springing up was enormously improved by the introduction of the three wire system and it gave an immediate impetus to incandescent lighting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1045, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0021.flac", "answer": "THE STREET CONDUCTORS WERE OF THE OVERHEAD POLE LINE CONSTRUCTION AND WERE INSTALLED BY THE CONSTRUCTION COMPANY THAT HAD BEEN ORGANIZED BY EDISON TO BUILD AND EQUIP CENTRAL STATIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "the street conductors were of the overhead pole line construction and were installed by the construction company that had been organized by edison to build and equip central stations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1046, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0016.flac", "answer": "THEN AGAIN THERE WAS NO KNOWN WAY TO LUBRICATE AN ENGINE FOR CONTINUOUS RUNNING AND MISTER EDISON INFORMED ME THAT AS A MARINE ENGINE STARTED BEFORE THE SHIP LEFT NEW YORK AND CONTINUED RUNNING UNTIL IT REACHED ITS HOME PORT SO AN ENGINE FOR HIS PURPOSES MUST PRODUCE LIGHT AT ALL TIMES", "subset": "test_clean", "task_type": "understanding", "prediction": "then again there was no known way to lubricate an engine for continuous running and mr edison informed me that as a marine engine started before the ship left new york and continued running until it reached its home port so an engine for his purposes must produce light at all times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1047, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0015.flac", "answer": "HE OBTAINED THE DESIRED SPEED AND LOAD WITH A FRICTION BRAKE ALSO REGULATOR OF SPEED BUT WAITED FOR AN INDICATOR TO VERIFY IT", "subset": "test_clean", "task_type": "understanding", "prediction": "he obtained the desired speed and load with a friction brake also regulator of speed but waited for an indicator to verify it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1048, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0008.flac", "answer": "EVERYTHING HE HAS DONE HAS BEEN AIMED AT THE CONSERVATION OF ENERGY THE CONTRACTION OF SPACE THE INTENSIFICATION OF CULTURE", "subset": "test_clean", "task_type": "understanding", "prediction": "everything he has done has been aimed at the conservation of energy the contraction of space the intensification of culture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1049, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0022.flac", "answer": "MEANWHILE HE HAD CALLED UPON ME TO MAKE A REPORT OF THE THREE WIRE SYSTEM KNOWN IN ENGLAND AS THE HOPKINSON BOTH DOCTOR JOHN HOPKINSON AND MISTER EDISON BEING INDEPENDENT INVENTORS AT PRACTICALLY THE SAME TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "meanwhile he had called upon me to make a report of the three wire system known in england as the hopkinson both dr john hopkinson and mr edison being independent inventors at practically the same time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1050, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0003.flac", "answer": "THE DYNAMO ELECTRIC MACHINE THOUGH SMALL WAS ROBUST FOR UNDER ALL THE VARYING SPEEDS OF WATER POWER AND THE VICISSITUDES OF THE PLANT TO WHICH IT BELONGED IT CONTINUED IN ACTIVE USE UNTIL EIGHTEEN NINETY NINE SEVENTEEN YEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "the dynamo electric machine though small was robust for under all the varying speeds of water power and the vicissitudes of the plant to which it belonged it continued in active use until eighteen ninety nine seventeen years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1051, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0002.flac", "answer": "THERE MESSRS JOHNSON AND HAMMER PUT INTO PRACTICE MANY OF THE IDEAS NOW STANDARD IN THE ART AND SECURED MUCH USEFUL DATA FOR THE WORK IN NEW YORK OF WHICH THE STORY HAS JUST BEEN TOLD", "subset": "test_clean", "task_type": "understanding", "prediction": "there messrs johnson and hammer put into practice many of the ideas now standard in the art and secured much useful data for the work in new york of which the story has just been told", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1052, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0028.flac", "answer": "THERE WAS INFINITE SCEPTICISM AROUND HIM ON THE SUBJECT AND WHILE OTHER INVENTORS WERE ALSO GIVING THE SUBJECT THEIR THOUGHT THE PUBLIC TOOK IT FOR GRANTED THAT ANYTHING SO UTTERLY INTANGIBLE AS ELECTRICITY THAT COULD NOT BE SEEN OR WEIGHED AND ONLY GAVE SECONDARY EVIDENCE OF ITSELF AT THE EXACT POINT OF USE COULD NOT BE BROUGHT TO ACCURATE REGISTRATION", "subset": "test_clean", "task_type": "understanding", "prediction": "there was infinite skepticism around him on the subject and while other inventors were also giving the subject their thought the public took it for granted that anything so utterly intangible as electricity that could not be seen or weighed and only gave secondary evidence of itself at the exact point of use could not be brought to accurate registration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1053, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0034.flac", "answer": "THE OTHERS HAVING BEEN IN OPERATION TOO SHORT A TIME TO SHOW DEFINITE RESULTS ALTHOUGH THEY ALSO WENT QUICKLY TO A DIVIDEND BASIS", "subset": "test_clean", "task_type": "understanding", "prediction": "the others having been in operation too short a time to show definite results although they also went quickly to a dividend basis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1054, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0031.flac", "answer": "ASSOCIATED WITH THIS SIMPLE FORM OF APPARATUS WERE VARIOUS INGENIOUS DETAILS AND REFINEMENTS TO SECURE REGULARITY OF OPERATION FREEDOM FROM INACCURACY AND IMMUNITY FROM SUCH TAMPERING AS WOULD PERMIT THEFT OF CURRENT OR DAMAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "associated with this simple form of apparatus were various ingenious details and refinements to secure regularity of operation freedom from inaccuracy and immunity from such tampering as would permit theft of current or damage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1055, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0035.flac", "answer": "IN THIS CONNECTION IT SHOULD BE MENTIONED THAT THE ASSOCIATION OF EDISON ILLUMINATING COMPANIES IN THE SAME YEAR ADOPTED RESOLUTIONS UNANIMOUSLY TO THE EFFECT THAT THE EDISON METER WAS ACCURATE AND THAT ITS USE WAS NOT EXPENSIVE FOR STATIONS ABOVE ONE THOUSAND LIGHTS AND THAT THE BEST FINANCIAL RESULTS WERE INVARIABLY SECURED IN A STATION SELLING CURRENT BY METER", "subset": "test_clean", "task_type": "understanding", "prediction": "in this connection it should be mentioned that the association of edison illuminating companies in the same year adopted resolutions unanimously to the effect that the edison meter was accurate and that its use was not expensive for stations above one thousand lights and that the best financial results were invariably secured in a station selling current by meter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1056, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0040.flac", "answer": "WE WERE MORE INTERESTED IN THE TECHNICAL CONDITION OF THE STATION THAN IN THE COMMERCIAL PART", "subset": "test_clean", "task_type": "understanding", "prediction": "we were more interested in the technical condition of the station than in the commercial part", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1057, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0032.flac", "answer": "THE STANDARD EDISON METER PRACTICE WAS TO REMOVE THE CELLS ONCE A MONTH TO THE METER ROOM OF THE CENTRAL STATION COMPANY FOR EXAMINATION ANOTHER SET BEING SUBSTITUTED", "subset": "test_clean", "task_type": "understanding", "prediction": "the standard edison meter practice was to remove the cells once a month to the meter room of the central station company for examination another set being substituted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1058, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0033.flac", "answer": "IN DECEMBER EIGHTEEN EIGHTY EIGHT MISTER W J JENKS READ AN INTERESTING PAPER BEFORE THE AMERICAN INSTITUTE OF ELECTRICAL ENGINEERS ON THE SIX YEARS OF PRACTICAL EXPERIENCE HAD UP TO THAT TIME WITH THE METER THEN MORE GENERALLY IN USE THAN ANY OTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "in december eighteen eighty eight mister w j jenks read an interesting paper before the american institute of electrical engineers on the six years of practical experience had up to that time with the meter then more generally in use than any other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1059, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0039.flac", "answer": "THE PROBLEM WAS SOLVED", "subset": "test_clean", "task_type": "understanding", "prediction": "the problem was solved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1060, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0024.flac", "answer": "BUT THE PLANT RAN AND IT WAS THE FIRST THREE WIRE STATION IN THIS COUNTRY", "subset": "test_clean", "task_type": "understanding", "prediction": "but the plant ran and it was the first three wire station in this country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1061, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0023.flac", "answer": "I THINK HE WAS PERHAPS MORE APPRECIATIVE THAN I WAS OF THE DISCIPLINE OF THE EDISON CONSTRUCTION DEPARTMENT AND THOUGHT IT WOULD BE WELL FOR US TO WAIT UNTIL THE MORNING OF THE FOURTH BEFORE WE STARTED UP", "subset": "test_clean", "task_type": "understanding", "prediction": "i think he was perhaps more appreciative that i was of the discipline of the edison construction department and thought it would be well for us to wait until the morning of the fourth before we started up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1062, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0038.flac", "answer": "HE FELT HE WAS UP AGAINST IT AND THAT PERHAPS ANOTHER KIND OF A JOB WOULD SUIT HIM BETTER", "subset": "test_clean", "task_type": "understanding", "prediction": "he felt he was up against it and that perhaps another kind of a job would suit him better", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1063, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0037.flac", "answer": "HE WEIGHED AND REWEIGHED THE METER PLATES AND PURSUED EVERY LINE OF INVESTIGATION IMAGINABLE BUT ALL IN VAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "he weighed and reweighed the meter plates and pursued every line of investigation imaginable but all in vain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1064, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0020.flac", "answer": "IT WAS SPECIALLY SUITED FOR A TRIAL PLANT ALSO IN THE EARLY DAYS WHEN A YIELD OF SIX OR EIGHT LAMPS TO THE HORSE POWER WAS CONSIDERED SUBJECT FOR CONGRATULATION", "subset": "test_clean", "task_type": "understanding", "prediction": "it was specially suited for a trial plant also in the early days when a yield of six or eight lamps to the horse power was considered subject for congratulation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1065, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0000.flac", "answer": "THE PARIS PLANT LIKE THAT AT THE CRYSTAL PALACE WAS A TEMPORARY EXHIBIT", "subset": "test_clean", "task_type": "understanding", "prediction": "the paris plant like that of the crystal palace was a temporary exhibit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1066, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0041.flac", "answer": "WE HAD METERS IN WHICH THERE WERE TWO BOTTLES OF LIQUID", "subset": "test_clean", "task_type": "understanding", "prediction": "we had meters in which there were two bottles of liquid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1067, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0001.flac", "answer": "THE LONDON PLANT WAS LESS TEMPORARY BUT NOT PERMANENT SUPPLYING BEFORE IT WAS TORN OUT NO FEWER THAN THREE THOUSAND LAMPS IN HOTELS CHURCHES STORES AND DWELLINGS IN THE VICINITY OF HOLBORN VIADUCT", "subset": "test_clean", "task_type": "understanding", "prediction": "the london plant was less temporary but not permanent supplying before it was torn out no fewer than three thousand lamps in hotels churches stores and dwellings in the vicinity of holborn viaduct", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1068, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0029.flac", "answer": "HENCE THE EDISON ELECTROLYTIC METER IS NO LONGER USED DESPITE ITS EXCELLENT QUALITIES", "subset": "test_clean", "task_type": "understanding", "prediction": "hence the addison electrolytic meter is no longer used despite its excellent qualities", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1069, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0026.flac", "answer": "THE ARC LAMP INSTALLED OUTSIDE A CUSTOMER'S PREMISES OR IN A CIRCUIT FOR PUBLIC STREET LIGHTING BURNED SO MANY HOURS NIGHTLY SO MANY NIGHTS IN THE MONTH AND WAS PAID FOR AT THAT RATE SUBJECT TO REBATE FOR HOURS WHEN THE LAMP MIGHT BE OUT THROUGH ACCIDENT", "subset": "test_clean", "task_type": "understanding", "prediction": "the arc lamp installed outside a customer s premises or in a circuit for public street lighting burned so many hours nightly so many nights in the month and was paid for at that rate subject to rebate for hours when the lamp might be out through accident", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1070, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0027.flac", "answer": "EDISON HELD THAT THE ELECTRICITY SOLD MUST BE MEASURED JUST LIKE GAS OR WATER AND HE PROCEEDED TO DEVELOP A METER", "subset": "test_clean", "task_type": "understanding", "prediction": "edison held that the electricity sold must be measured just like gas or water and he proceeded to develop a meter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1071, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0025.flac", "answer": "THEY WERE LATER USED AS RESERVE MACHINES AND FINALLY WITH THE ENGINE RETIRED FROM SERVICE AS PART OF THE COLLECTION OF EDISONIA BUT THEY REMAIN IN PRACTICALLY AS GOOD CONDITION AS WHEN INSTALLED IN EIGHTEEN EIGHTY THREE", "subset": "test_clean", "task_type": "understanding", "prediction": "they were later used as reserve machines and finally with the engine retired from service as part of the collection of edisonia but they remain in practically as good condition as when installed in eighteen eighty three", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1072, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0010.flac", "answer": "IT COULD NOT BE USED FOR ELECTROPLATING OR DEPOSITION NOR COULD IT CHARGE STORAGE BATTERIES ALL OF WHICH ARE EASILY WITHIN THE ABILITY OF THE DIRECT CURRENT", "subset": "test_clean", "task_type": "understanding", "prediction": "it could not be used for electroplating or deposition nor could it charge storage batteries all of which are easily within the ability of the direct current", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1073, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0009.flac", "answer": "FOR SOME YEARS IT WAS NOT FOUND FEASIBLE TO OPERATE MOTORS ON ALTERNATING CURRENT CIRCUITS AND THAT REASON WAS OFTEN URGED AGAINST IT SERIOUSLY", "subset": "test_clean", "task_type": "understanding", "prediction": "for some years it was not found feasible to operate motors on alternating current circuits and that reason was often urged against it seriously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1074, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0011.flac", "answer": "BUT WHEN IT CAME TO BE A QUESTION OF LIGHTING A SCATTERED SUBURB A GROUP OF DWELLINGS ON THE OUTSKIRTS A REMOTE COUNTRY RESIDENCE OR A FARM HOUSE THE ALTERNATING CURRENT IN ALL ELEMENTS SAVE ITS DANGER WAS AND IS IDEAL", "subset": "test_clean", "task_type": "understanding", "prediction": "but when it came to be a question of lighting a scattered suburb a group of dwellings on the outskirts a remote country residence or a farm house the alternating current in all elements save its danger was and is ideal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1075, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0013.flac", "answer": "UNLESS HE COULD SECURE AN ENGINE OF SMOOTHER RUNNING AND MORE EXACTLY GOVERNED AND REGULATED THAN THOSE AVAILABLE FOR HIS DYNAMO AND LAMP EDISON REALIZED THAT HE WOULD FIND IT ALMOST IMPOSSIBLE TO GIVE A STEADY LIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "unless he could secure an engine of smoother running and more exactly governed and regulated than those available for his dynamo and lamp edison realized that he would find it almost impossible to give a steady light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1076, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0030.flac", "answer": "THE PRINCIPLE EMPLOYED IN THE EDISON ELECTROLYTIC METER IS THAT WHICH EXEMPLIFIES THE POWER OF ELECTRICITY TO DECOMPOSE A CHEMICAL SUBSTANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "the principle employed in the addison electrolytic meter is that which exemplifies the power of electricity to decompose a chemical substance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1077, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0017.flac", "answer": "EDISON HAD INSTALLED HIS HISTORIC FIRST GREAT CENTRAL STATION SYSTEM IN NEW YORK ON THE MULTIPLE ARC SYSTEM COVERED BY HIS FEEDER AND MAIN INVENTION WHICH RESULTED IN A NOTABLE SAVING IN THE COST OF CONDUCTORS AS AGAINST A STRAIGHT TWO WIRE SYSTEM THROUGHOUT OF THE TREE KIND", "subset": "test_clean", "task_type": "understanding", "prediction": "edison had installed his historic first great central station system in new york on the multiple arc system covered by his feeder and main invention which resulted in a notable saving in the cost of conductors as against a straight two wire system throughout of the tree kind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1078, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0012.flac", "answer": "EDISON WAS INTOLERANT OF SHAM AND SHODDY AND NOTHING WOULD SATISFY HIM THAT COULD NOT STAND CROSS EXAMINATION BY MICROSCOPE TEST TUBE AND GALVANOMETER", "subset": "test_clean", "task_type": "understanding", "prediction": "edison was intolerant of sham and shoddy and nothing would satisfy him that could not stand cross examination by microscope test tube and galvanometer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1079, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0014.flac", "answer": "MISTER EDISON WAS A LEADER FAR AHEAD OF THE TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "mr edison was a leader far ahead of the time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1080, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0006.flac", "answer": "THERE SEEMS NO GOOD REASON FOR BELIEVING THAT IT WILL CHANGE", "subset": "test_clean", "task_type": "understanding", "prediction": "there seems no good reason for believing that it will change", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1081, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0007.flac", "answer": "BROAD AS THE PRAIRIES AND FREE IN THOUGHT AS THE WINDS THAT SWEEP THEM HE IS IDIOSYNCRATICALLY OPPOSED TO LOOSE AND WASTEFUL METHODS TO PLANS OF EMPIRE THAT NEGLECT THE POOR AT THE GATE", "subset": "test_clean", "task_type": "understanding", "prediction": "broad as the prairies and free in thought as the winds that swept them he is idiosyncratically opposed to loose and wasteful methods to plans of empire that neglect the poor at the gate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1082, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0004.flac", "answer": "OWING TO HIS INSISTENCE ON LOW PRESSURE DIRECT CURRENT FOR USE IN DENSELY POPULATED DISTRICTS AS THE ONLY SAFE AND TRULY UNIVERSAL PROFITABLE WAY OF DELIVERING ELECTRICAL ENERGY TO THE CONSUMERS EDISON HAS BEEN FREQUENTLY SPOKEN OF AS AN OPPONENT OF THE ALTERNATING CURRENT", "subset": "test_clean", "task_type": "understanding", "prediction": "owing to his insistence on low pressure direct current for use in densely populated districts as the only safe and truly universal profitable way of delivering electrical energy to the consumers edison has been frequently spoken of as an opponent of the alternating current", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1083, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2300/131720/2300-131720-0005.flac", "answer": "WHY IF WE ERECT A STATION AT THE FALLS IT IS A GREAT ECONOMY TO GET IT UP TO THE CITY", "subset": "test_clean", "task_type": "understanding", "prediction": "why if we erect a station at the falls it is a great economy to get it up to the city", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1084, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0020.flac", "answer": "THERE CERTAINLY WAS NO END TO IT AND EVEN RUTH WAS PHILADELPHIAN ENOUGH TO BELIEVE THAT A STREET OUGHT NOT TO HAVE ANY END OR ARCHITECTURAL POINT UPON WHICH THE WEARY EYE COULD REST", "subset": "test_clean", "task_type": "understanding", "prediction": "there certainly was no end to it and even ruth was philadelphian enough to believe that a street ought not to have any end or architectural point upon which the weary eye could rest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1085, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0034.flac", "answer": "WHY SHOULD I RUST AND BE STUPID AND SIT IN INACTION BECAUSE I AM A GIRL", "subset": "test_clean", "task_type": "understanding", "prediction": "why should i rust and be stupid and sit in inaction because i am a girl", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1086, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0012.flac", "answer": "AND BESIDES SUPPOSE THEE DOES LEARN MEDICINE", "subset": "test_clean", "task_type": "understanding", "prediction": "and besides suppose he does learn medicine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1087, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0004.flac", "answer": "I HEARD FATHER TELL COUSIN ABNER THAT HE WAS WHIPPED SO OFTEN FOR WHISTLING WHEN HE WAS A BOY THAT HE WAS DETERMINED TO HAVE WHAT COMPENSATION HE COULD GET NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "i heard father tell cousin abner that he was whipped so often for whistling when he was a boy that he was determined to have what compensation he could get now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1088, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0013.flac", "answer": "I WILL PRACTICE IT", "subset": "test_clean", "task_type": "understanding", "prediction": "i will practice it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1089, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0033.flac", "answer": "WHAT A BOX WOMEN ARE PUT INTO MEASURED FOR IT AND PUT IN YOUNG IF WE GO ANYWHERE IT'S IN A BOX VEILED AND PINIONED AND SHUT IN BY DISABILITIES", "subset": "test_clean", "task_type": "understanding", "prediction": "what a box women are put into measured for it and put in young if we go anywhere it is in a box veiled and pinioned and shut in by disabilities", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1090, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0010.flac", "answer": "THEE STUDY MEDICINE", "subset": "test_clean", "task_type": "understanding", "prediction": "thee study medicine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1091, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0037.flac", "answer": "BUT THAT WISE AND PLACID WOMAN UNDERSTOOD THE SWEET REBEL A GREAT DEAL BETTER THAN RUTH UNDERSTOOD HERSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "but that wise and placid woman understood the sweet rebel a great deal better than ruth understood herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1092, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0008.flac", "answer": "MOTHER I'M GOING TO STUDY MEDICINE", "subset": "test_clean", "task_type": "understanding", "prediction": "mother i am going to study medicine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1093, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0009.flac", "answer": "MARGARET BOLTON ALMOST LOST FOR A MOMENT HER HABITUAL PLACIDITY", "subset": "test_clean", "task_type": "understanding", "prediction": "margaret bolton almost lost for a moment her habitual placidity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1094, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0030.flac", "answer": "FATHER THEE'S UNJUST TO PHILIP HE'S GOING INTO BUSINESS", "subset": "test_clean", "task_type": "understanding", "prediction": "father these are unjust of philip he is going into business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1095, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0002.flac", "answer": "WELL MOTHER SAID THE YOUNG STUDENT LOOKING UP WITH A SHADE OF IMPATIENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "well mother said the young student looking up with a shade of impatience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1096, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0028.flac", "answer": "HE DOESN'T SAY BUT IT'S ON THE FRONTIER AND ON THE MAP EVERYTHING BEYOND IT IS MARKED INDIANS AND DESERT AND LOOKS AS DESOLATE AS A WEDNESDAY MEETING HUMPH IT WAS TIME FOR HIM TO DO SOMETHING", "subset": "test_clean", "task_type": "understanding", "prediction": "he doesn t say but it s on the frontier and on the map everything beyond it is marked indians and desert and looks as desolate as a wednesday meeting humph it was time for him to do something", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1097, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0017.flac", "answer": "THE SIGHT SEERS RETURNED IN HIGH SPIRITS FROM THE CITY", "subset": "test_clean", "task_type": "understanding", "prediction": "the sightseers returned in high spirits from the city", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1098, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0016.flac", "answer": "RUTH SAT QUITE STILL FOR A TIME WITH FACE INTENT AND FLUSHED IT WAS OUT NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "ruth sat quite still for a time with face intent and flushed it was out now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1099, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0014.flac", "answer": "WHERE THEE AND THY FAMILY ARE KNOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "where thee and thy family are known", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0015.flac", "answer": "IF I CAN GET PATIENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "if i can get patients", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0038.flac", "answer": "RUTH WAS GLAD TO HEAR THAT PHILIP HAD MADE A PUSH INTO THE WORLD AND SHE WAS SURE THAT HIS TALENT AND COURAGE WOULD MAKE A WAY FOR HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "ruth was glad to hear that philip had made a push into the world and she was sure that his talent and courage would make a way for him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0005.flac", "answer": "THY WAYS GREATLY TRY ME RUTH AND ALL THY RELATIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "thy ways greatly try me ruth and all thy relations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0021.flac", "answer": "BUT NEITHER SAINT GIRARD NOR BROAD STREET NEITHER WONDERS OF THE MINT NOR THE GLORIES OF THE HALL WHERE THE GHOSTS OF OUR FATHERS SIT ALWAYS SIGNING THE DECLARATION IMPRESSED THE VISITORS SO MUCH AS THE SPLENDORS OF THE CHESTNUT STREET WINDOWS AND THE BARGAINS ON EIGHTH STREET", "subset": "test_clean", "task_type": "understanding", "prediction": "but neither st gerard nor broad street neither wonders of the mint nor the glories of the hall where the ghosts of our fathers sit always signing the declaration impress the visitor so much as the splendors of the chestnut street windows and the bargains on eighth street", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0023.flac", "answer": "I HAVE NOTHING TO WEAR REPLIED THAT DEMURE PERSON", "subset": "test_clean", "task_type": "understanding", "prediction": "i have nothing to wear replied that demure person", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0000.flac", "answer": "SHE WAS TIRED OF OTHER THINGS", "subset": "test_clean", "task_type": "understanding", "prediction": "she was tired of other things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0019.flac", "answer": "AND THEN THERE WAS BROAD STREET", "subset": "test_clean", "task_type": "understanding", "prediction": "and then there was broad street", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0006.flac", "answer": "IS THY FATHER WILLING THEE SHOULD GO AWAY TO A SCHOOL OF THE WORLD'S PEOPLE", "subset": "test_clean", "task_type": "understanding", "prediction": "is thy father willing thee should go away to a school of the world s people", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0027.flac", "answer": "IT'S SUCH A CRUSH AT THE YEARLY MEETING AT ARCH STREET AND THEN THERE'S THE ROW OF SLEEK LOOKING YOUNG MEN WHO LINE THE CURBSTONE AND STARE AT US AS WE COME OUT", "subset": "test_clean", "task_type": "understanding", "prediction": "its such a crush at the yearly meeting at arch street and then there is the row of sleek looking young men who lie on the curbstone and stare at us as we come out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0026.flac", "answer": "IF I GO TO MEETING AT ALL I LIKE BEST TO SIT IN THE QUIET OLD HOUSE IN GERMANTOWN WHERE THE WINDOWS ARE ALL OPEN AND I CAN SEE THE TREES AND HEAR THE STIR OF THE LEAVES", "subset": "test_clean", "task_type": "understanding", "prediction": "if i go to meeting at all i like best to sit in the quiet old house in germantown where the windows are all open and i can see the trees and hear the stir of the leaves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0001.flac", "answer": "SHE TRIED THIS MORNING AN AIR OR TWO UPON THE PIANO SANG A SIMPLE SONG IN A SWEET BUT SLIGHTLY METALLIC VOICE AND THEN SEATING HERSELF BY THE OPEN WINDOW READ PHILIP'S LETTER", "subset": "test_clean", "task_type": "understanding", "prediction": "she tried this morning an air or two upon the piano sang a simple song in a sweet but slightly metallic voice and then seating herself by the open window read philip s letter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0018.flac", "answer": "RUTH ASKED THE ENTHUSIASTS IF THEY WOULD LIKE TO LIVE IN SUCH A SOUNDING MAUSOLEUM WITH ITS GREAT HALLS AND ECHOING ROOMS AND NO COMFORTABLE PLACE IN IT FOR THE ACCOMMODATION OF ANY BODY", "subset": "test_clean", "task_type": "understanding", "prediction": "ruth asked the enthusiasts if they would like to live in such a sounding mausoleum with its great halls and echoing rooms and no comfortable place in it for the accommodation of any body", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0036.flac", "answer": "HAS THEE CONSULTED THY MOTHER ABOUT A CAREER I SUPPOSE IT IS A CAREER THEE WANTS", "subset": "test_clean", "task_type": "understanding", "prediction": "has thee consulted thy mother about a career i suppose it is a career thee wants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0031.flac", "answer": "HE DOESN'T SAY EXACTLY WHAT IT IS SAID RUTH A LITTLE DUBIOUSLY BUT IT'S SOMETHING ABOUT LAND AND RAILROADS AND THEE KNOWS FATHER THAT FORTUNES ARE MADE NOBODY KNOWS EXACTLY HOW IN A NEW COUNTRY", "subset": "test_clean", "task_type": "understanding", "prediction": "he doesn t say exactly what it is said ruth a little dubiously but it is something about land and railroads and thee knows father that fortunes are made nobody knows exactly how in a new country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0032.flac", "answer": "BUT PHILIP IS HONEST AND HE HAS TALENT ENOUGH IF HE WILL STOP SCRIBBLING TO MAKE HIS WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "that philip is honest and he has talent enough if he will stop scribbling to make his way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0022.flac", "answer": "IS THEE GOING TO THE YEARLY MEETING RUTH ASKED ONE OF THE GIRLS", "subset": "test_clean", "task_type": "understanding", "prediction": "is thee going to the yearly meeting ruth asked one of the girls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0011.flac", "answer": "DOES THEE THINK THEE COULD STAND IT SIX MONTHS", "subset": "test_clean", "task_type": "understanding", "prediction": "does thee think thee could stand it six months", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0035.flac", "answer": "AND IF I HAD A FORTUNE WOULD THEE WANT ME TO LEAD A USELESS LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "and if i had a fortune would thee want me to lead a useless life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0007.flac", "answer": "I HAVE NOT ASKED HIM RUTH REPLIED WITH A LOOK THAT MIGHT IMPLY THAT SHE WAS ONE OF THOSE DETERMINED LITTLE BODIES WHO FIRST MADE UP HER OWN MIND AND THEN COMPELLED OTHERS TO MAKE UP THEIRS IN ACCORDANCE WITH HERS", "subset": "test_clean", "task_type": "understanding", "prediction": "i have not asked him ruth replied with a look that might imply that she was one of those determined little bodies who first made up her own mind and then compelled others to make up theirs in accordance with hers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0024.flac", "answer": "IT HAS OCCUPIED MOTHER A LONG TIME TO FIND AT THE SHOPS THE EXACT SHADE FOR HER NEW BONNET", "subset": "test_clean", "task_type": "understanding", "prediction": "it has occupied mother a long time to find at the shops the exact shade for her new bonnet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0025.flac", "answer": "AND THEE WON'T GO WHY SHOULD I", "subset": "test_clean", "task_type": "understanding", "prediction": "and thee won t go why should i", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0029.flac", "answer": "IS HE GOING TO START A DAILY NEWSPAPER AMONG THE KICK A POOS", "subset": "test_clean", "task_type": "understanding", "prediction": "is he going to start a daily newspaper among the kickapoos", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29095/4970-29095-0003.flac", "answer": "I HOPE THEE TOLD THE ELDERS THAT FATHER AND I ARE RESPONSIBLE FOR THE PIANO AND THAT MUCH AS THEE LOVES MUSIC THEE IS NEVER IN THE ROOM WHEN IT IS PLAYED", "subset": "test_clean", "task_type": "understanding", "prediction": "i hope thee told the elders that father and i are responsible for the piano and that much as thee loves music thee is never in the room when it is played", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0009.flac", "answer": "PHILIP THEREFORE READ DILIGENTLY IN THE ASTOR LIBRARY PLANNED LITERARY WORKS THAT SHOULD COMPEL ATTENTION AND NURSED HIS GENIUS", "subset": "test_clean", "task_type": "understanding", "prediction": "philip therefore read diligently in the astor library planned literary works that should compel attention and nursed his genius", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0021.flac", "answer": "I WAS AFRAID IT WAS NEARER HOME", "subset": "test_clean", "task_type": "understanding", "prediction": "i was afraid it was nearer home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0017.flac", "answer": "I'VE BEEN READY TO GO ANYWHERE FOR SIX MONTHS", "subset": "test_clean", "task_type": "understanding", "prediction": "i been ready to go anywhere for six months", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0016.flac", "answer": "NO ITS NOT TOO SOON", "subset": "test_clean", "task_type": "understanding", "prediction": "no it is not too soon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0012.flac", "answer": "BUT PHILIP DID AFFORD IT AND HE WROTE THANKING HIS FRIENDS AND DECLINING BECAUSE HE SAID THE POLITICAL SCHEME WOULD FAIL AND OUGHT TO FAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "what philip did afford it and he wrote thanking his friends and declining because he said the political scheme would fail and ought to fail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0013.flac", "answer": "AND HE WENT BACK TO HIS BOOKS AND TO HIS WAITING FOR AN OPENING LARGE ENOUGH FOR HIS DIGNIFIED ENTRANCE INTO THE LITERARY WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "and he went back to his books and to his waiting for an opening large enough for his dignified entrance into the literary world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0023.flac", "answer": "HE WELL KNEW THE PERILS OF THE FRONTIER THE SAVAGE STATE OF SOCIETY THE LURKING INDIANS AND THE DANGERS OF FEVER", "subset": "test_clean", "task_type": "understanding", "prediction": "he well knew the perils of the frontier the savage state of society the lurking indians and the dangers of fever", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0007.flac", "answer": "IT IS SUCH A NOBLE AMBITION THAT IT IS A PITY IT HAS USUALLY SUCH A SHALLOW FOUNDATION", "subset": "test_clean", "task_type": "understanding", "prediction": "it is such a noble ambition that it is a pity it has usually such a shallow foundation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0022.flac", "answer": "HE KNEW HIS UNCLE WOULD BE GLAD TO HEAR THAT HE HAD AT LAST TURNED HIS THOUGHTS TO A PRACTICAL MATTER", "subset": "test_clean", "task_type": "understanding", "prediction": "he knew his uncle would be glad to hear that he had at last turned his thoughts to a practical matter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0001.flac", "answer": "TO THE YOUNG AMERICAN HERE OR ELSEWHERE THE PATHS TO FORTUNE ARE INNUMERABLE AND ALL OPEN THERE IS INVITATION IN THE AIR AND SUCCESS IN ALL HIS WIDE HORIZON", "subset": "test_clean", "task_type": "understanding", "prediction": "to the young american here or elsewhere the paths to fortune are innumerable and all open there is invitation in the air and success in all his wide horizon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0008.flac", "answer": "HE WANTED TO BEGIN AT THE TOP OF THE LADDER", "subset": "test_clean", "task_type": "understanding", "prediction": "he wanted to begin at the top of the ladder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0006.flac", "answer": "LAW SEEMED TO HIM WELL ENOUGH AS A SCIENCE BUT HE NEVER COULD DISCOVER A PRACTICAL CASE WHERE IT APPEARED TO HIM WORTH WHILE TO GO TO LAW AND ALL THE CLIENTS WHO STOPPED WITH THIS NEW CLERK IN THE ANTE ROOM OF THE LAW OFFICE WHERE HE WAS WRITING PHILIP INVARIABLY ADVISED TO SETTLE NO MATTER HOW BUT SETTLE GREATLY TO THE DISGUST OF HIS EMPLOYER WHO KNEW THAT JUSTICE BETWEEN MAN AND MAN COULD ONLY BE ATTAINED BY THE RECOGNIZED PROCESSES WITH THE ATTENDANT FEES", "subset": "test_clean", "task_type": "understanding", "prediction": "law seemed to him well enough as a science but he never could discover a practical case where it appeared to him worth while to go to law and all the clients who stopped with this new clerk in the ante room of the law office where he was writing philip invariably advised to settle no matter how but settle greatly to the disgust of his employer who knew that justice between man and man could only be attained by the recognized processes with the attendant fees", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0011.flac", "answer": "O VERY WELL SAID GRINGO TURNING AWAY WITH A SHADE OF CONTEMPT YOU'LL FIND IF YOU ARE GOING INTO LITERATURE AND NEWSPAPER WORK THAT YOU CAN'T AFFORD A CONSCIENCE LIKE THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "oh very well said gringo turning away with a shade of contempt you will find if you are going into literature and newspaper work that you can not afford a conscience like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0019.flac", "answer": "THE NIGHT WAS SPENT IN PACKING UP AND WRITING LETTERS FOR PHILIP WOULD NOT TAKE SUCH AN IMPORTANT STEP WITHOUT INFORMING HIS FRIENDS", "subset": "test_clean", "task_type": "understanding", "prediction": "the night was spent in packing up and writing letters for philip would not take such an important step without informing his friends", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0002.flac", "answer": "HE HAS NO TRADITIONS TO BIND HIM OR GUIDE HIM AND HIS IMPULSE IS TO BREAK AWAY FROM THE OCCUPATION HIS FATHER HAS FOLLOWED AND MAKE A NEW WAY FOR HIMSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "he has no traditions to bind him or guide him and his impulse is to break away from the occupation his father has followed and make a new way for himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0014.flac", "answer": "WELL I'M GOING AS AN ENGINEER YOU CAN GO AS ONE", "subset": "test_clean", "task_type": "understanding", "prediction": "well i am going as an engineer you could go as one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0015.flac", "answer": "YOU CAN BEGIN BY CARRYING A ROD AND PUTTING DOWN THE FIGURES", "subset": "test_clean", "task_type": "understanding", "prediction": "you can begin by carrying a rod and putting down the figures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0003.flac", "answer": "THE MODEST FELLOW WOULD HAVE LIKED FAME THRUST UPON HIM FOR SOME WORTHY ACHIEVEMENT IT MIGHT BE FOR A BOOK OR FOR THE SKILLFUL MANAGEMENT OF SOME GREAT NEWSPAPER OR FOR SOME DARING EXPEDITION LIKE THAT OF LIEUTENANT STRAIN OR DOCTOR KANE", "subset": "test_clean", "task_type": "understanding", "prediction": "the modest fellow would have liked fame thrust upon him for some worthy achievement it might be for a book or for the skilful management of some great newspaper or for some daring expedition like that of lieutenant strane or doctor kane", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0000.flac", "answer": "YOU'LL NEVER DIG IT OUT OF THE ASTOR LIBRARY", "subset": "test_clean", "task_type": "understanding", "prediction": "you will never dig it out of the astor library", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0005.flac", "answer": "SOMETIMES HE THOUGHT HE WOULD LIKE TO STAND IN A CONSPICUOUS PULPIT AND HUMBLY PREACH THE GOSPEL OF REPENTANCE AND IT EVEN CROSSED HIS MIND THAT IT WOULD BE NOBLE TO GIVE HIMSELF TO A MISSIONARY LIFE TO SOME BENIGHTED REGION WHERE THE DATE PALM GROWS AND THE NIGHTINGALE'S VOICE IS IN TUNE AND THE BUL BUL SINGS ON THE OFF NIGHTS", "subset": "test_clean", "task_type": "understanding", "prediction": "sometimes he thought he would like to stand in a conspicuous pulpit and humbly preach the gospel of repentance and it even crossed his mind that it would be noble to give himself to a missionary life to some benighted region where the date palm grows and the nightingale s voice is in tune and the bulbul sings on the off nights", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0010.flac", "answer": "HE HAD NO FRIEND WISE ENOUGH TO TELL HIM TO STEP INTO THE DORKING CONVENTION THEN IN SESSION MAKE A SKETCH OF THE MEN AND WOMEN ON THE PLATFORM AND TAKE IT TO THE EDITOR OF THE DAILY GRAPEVINE AND SEE WHAT HE COULD GET A LINE FOR IT", "subset": "test_clean", "task_type": "understanding", "prediction": "he had no friend wise enough to tell him to step into the dorking convention then in session make a sketch of the men and women on the platform and take it to the editor of the daily grapevine and see what he could get a line for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0004.flac", "answer": "HE WAS UNABLE TO DECIDE EXACTLY WHAT IT SHOULD BE", "subset": "test_clean", "task_type": "understanding", "prediction": "he was unable to decide exactly what it should be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0020.flac", "answer": "WHY IT'S IN MISSOURI SOMEWHERE ON THE FRONTIER I THINK WE'LL GET A MAP", "subset": "test_clean", "task_type": "understanding", "prediction": "why it is in missouri somewhere on the frontier i think we will get a map", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4970/29093/4970-29093-0018.flac", "answer": "THE TWO YOUNG MEN WHO WERE BY THIS TIME FULL OF THE ADVENTURE WENT DOWN TO THE WALL STREET OFFICE OF HENRY'S UNCLE AND HAD A TALK WITH THAT WILY OPERATOR", "subset": "test_clean", "task_type": "understanding", "prediction": "the two young men who were by this time full of the adventure went down to the wall street office of henry s uncle and had a talk with that wily operator", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0001.flac", "answer": "WELL AS I SAY IT'S AN AWFUL QUEER WORLD THEY CLAP ALL THE BURGLARS INTO JAIL AND THE MURDERERS AND THE WIFE BEATERS I'VE ALLERS THOUGHT A GENTLE REPROOF WOULD BE ENOUGH PUNISHMENT FOR A WIFE BEATER CAUSE HE PROBABLY HAS A LOT O PROVOCATION THAT NOBODY KNOWS AND THE FIREBUGS CAN'T THINK O THE RIGHT NAME SOMETHING LIKE CENDENARIES AN THE BREAKERS O THE PEACE AN WHAT NOT AN YET THE LAW HAS NOTHIN TO SAY TO A MAN LIKE HEN LORD", "subset": "test_clean", "task_type": "understanding", "prediction": "well as i say it is an awful queer world they clap all the burglars in jail and the murderers and the wife beaters i allers thought a gentle reproof would be enough punishment for a wife beater cause he probably has a lot of provocation that nobody knows and the fire bugs cant think of the right name something like scendiaries and the breakers of the peace and what not and yet the law has nothing to say to a man like han lord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0020.flac", "answer": "NANCY'S CURLY CHESTNUT CROP SHONE IN THE SUN AND OLIVE'S THICK BLACK PLAITS LOOKED BLACKER BY CONTRAST", "subset": "test_clean", "task_type": "understanding", "prediction": "nancy s curly chestnut crop shone in the sun and olive s thick black plaits looked blacker by contrast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0007.flac", "answer": "HE GIVE UP HIS POSITION AND SHUT THE FAMILY UP IN THAT TOMB OF A HOUSE SO T HE COULD STUDY HIS BOOKS", "subset": "test_clean", "task_type": "understanding", "prediction": "he gave up his position and shut the family up in that tomb of a house so that he could study his books", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0004.flac", "answer": "I SWAN TO MAN HE EJACULATED IF YOU DON'T WORK HARD YOU CAN'T KEEP UP WITH THE TIMES DOCTOR OF LAWS", "subset": "test_clean", "task_type": "understanding", "prediction": "i swain to man he ejaculated if you dont work hard you cant keep up with the times doctor of laws", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0014.flac", "answer": "WHEN SHE COULD NOT MAKE A RABBIT OR A BIRD LOOK REAL ON PAPER SHE SEARCHED IN HER FATHER'S BOOKS FOR PICTURES OF ITS BONES", "subset": "test_clean", "task_type": "understanding", "prediction": "when she could not make a rabbit or a bird look real on paper she searched in her father s books for pictures of its bones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0021.flac", "answer": "SHE'S WONDERFUL MORE WONDERFUL THAN ANYBODY WE'VE EVER SEEN ANYWHERE AND SHE DRAWS BETTER THAN THE TEACHER IN CHARLESTOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "she is wonderful more wonderful than anybody we have ever seen anywhere and she draws better than the teacher in charlestown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0016.flac", "answer": "THEY COULDN'T RUN NOR MOVE THEY'RE JUST PASTEBOARD", "subset": "test_clean", "task_type": "understanding", "prediction": "they couldnt run or move they are just pasteboard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0018.flac", "answer": "THERE IN THE CEDAR HOLLOW THEN LIVED OLIVE LORD AN ANGRY RESENTFUL LITTLE CREATURE WEIGHED DOWN BY A FIERCE SENSE OF INJURY", "subset": "test_clean", "task_type": "understanding", "prediction": "there in the cedar hollow then lived olive lord an angry resentful little creature weighed down by a fierce sense of injury", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0011.flac", "answer": "WHATEVER APPEALED TO HER SENSE OF BEAUTY WAS STRAIGHTWAY TRANSFERRED TO PAPER OR CANVAS", "subset": "test_clean", "task_type": "understanding", "prediction": "whatever appealed to her sense of beauty was straightway transferred to paper or canvas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0013.flac", "answer": "SHE MAKES EFFORT AFTER EFFORT TREMBLING WITH EAGERNESS AND WHEN SHE FAILS TO REPRODUCE WHAT SHE SEES SHE WORKS HERSELF INTO A FRENZY OF GRIEF AND DISAPPOINTMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "she makes effort after effort trembling with eagerness and when she fails to reproduce what she sees she works herself into a frenzy of grief and disappointment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0012.flac", "answer": "SHE IS WILD TO KNOW HOW TO DO THINGS", "subset": "test_clean", "task_type": "understanding", "prediction": "she is wild to know how to do things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0000.flac", "answer": "YES DEAD THESE FOUR YEARS AN A GOOD JOB FOR HER TOO", "subset": "test_clean", "task_type": "understanding", "prediction": "yas dead these four years and a good job for her too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0010.flac", "answer": "ALWAYS IRRITABLE COLD INDIFFERENT HE HAD GROWN RAPIDLY MORE SO AS YEARS WENT ON", "subset": "test_clean", "task_type": "understanding", "prediction": "always irritable cold indifferent he had grown rapidly more so as the years went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0009.flac", "answer": "HENRY LORD WITH THE DEGREE OF PH D TO HIS CREDIT HAD BEEN PROFESSOR OF ZOOLOGY AT A NEW ENGLAND COLLEGE BUT HAD RESIGNED HIS POST IN ORDER TO WRITE A SERIES OF SCIENTIFIC TEXT BOOKS", "subset": "test_clean", "task_type": "understanding", "prediction": "henry lord with a degree of ph d to his credit had been professor of zoology at a new england college but had resigned his post in order to write a series of scientific text books", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0002.flac", "answer": "GRANDFATHER WAS ALEXANDER CAREY L L D DOCTOR OF LAWS THAT IS", "subset": "test_clean", "task_type": "understanding", "prediction": "grandfather was alexander cary ll d doctor of laws that is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0003.flac", "answer": "MISTER POPHAM LAID DOWN HIS BRUSH", "subset": "test_clean", "task_type": "understanding", "prediction": "mr popham laid down his brush", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0015.flac", "answer": "CYRIL THERE MUST BE SOME BETTER WAY OF DOING I JUST DRAW THE OUTLINE OF AN ANIMAL AND THEN I PUT HAIRS OR FEATHERS ON IT THEY HAVE NO BODIES", "subset": "test_clean", "task_type": "understanding", "prediction": "cyril there must be some better way of doing i just draw the outline of an animal and then i put hairs or feathers on it they have no bodies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0017.flac", "answer": "HE WOULDN'T SEARCH SO DON'T WORRY REPLIED CYRIL QUIETLY AND THE TWO LOOKED AT EACH OTHER AND KNEW THAT IT WAS SO", "subset": "test_clean", "task_type": "understanding", "prediction": "he wouldn search so dont worry replied cyril quietly and the two looked at each other and knew that it was so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0019.flac", "answer": "OLIVE'S MOURNFUL BLACK EYES MET NANCY'S SPARKLING BROWN ONES", "subset": "test_clean", "task_type": "understanding", "prediction": "olive s mournful black eyes met nancy s sparkling brown ones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0005.flac", "answer": "DONE HE AIN'T DONE A THING HE'D OUGHTER SENCE HE WAS BORN", "subset": "test_clean", "task_type": "understanding", "prediction": "done he ain t done a thing he orter since he was born", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0006.flac", "answer": "HE KEEPS THE THOU SHALT NOT COMMANDMENTS FIRST RATE HEN LORD DOES", "subset": "test_clean", "task_type": "understanding", "prediction": "he keeps the thou shalt not commandments first rate hen lord does", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0022.flac", "answer": "SHE'S OLDER THAN I AM BUT SO TINY AND SAD AND SHY THAT SHE SEEMS LIKE A CHILD", "subset": "test_clean", "task_type": "understanding", "prediction": "she is older than i am but so tiny and sad and shy that she seems like a child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41797/4992-41797-0008.flac", "answer": "MISTER POPHAM EXAGGERATED NOTHING BUT ON THE CONTRARY LEFT MUCH UNSAID IN HIS NARRATIVE OF THE FAMILY AT THE HOUSE OF LORDS", "subset": "test_clean", "task_type": "understanding", "prediction": "mr popham exaggerated nothing but on the contrary left much unsaid in his narrative of the family at the house of lords", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0013.flac", "answer": "MY LORD MISS MILNER'S TASTE IS NOT A DEPRAVED ONE IT IS BUT TOO REFINED", "subset": "test_clean", "task_type": "understanding", "prediction": "my lord miss milner s taste is not a depraved one it is but too refined", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0005.flac", "answer": "NOT THAT I KNOW OF NOT ONE MORE THAT I KNOW OF HE REPLIED WITH ASTONISHMENT AT WHAT SHE HAD INSINUATED AND YET WITH A PERFECT ASSURANCE THAT SHE WAS IN THE WRONG", "subset": "test_clean", "task_type": "understanding", "prediction": "not that i know of not one more that i know of he replied with astonishment at what she had insinuated and yet with a perfect assurance that she was in the wrong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0004.flac", "answer": "AND YET YOU MUST OWN HER BEHAVIOUR HAS WARRANTED THEM HAS IT NOT BEEN IN THIS PARTICULAR INCOHERENT AND UNACCOUNTABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "and yet you must own her behaviour has warranted them has it not been in this particular incoherent and unaccountable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0017.flac", "answer": "MISS WOODLEY WAS TOO LITTLE VERSED IN THE SUBJECT TO KNOW THIS WOULD HAVE BEEN NOT TO LOVE AT ALL AT LEAST NOT TO THE EXTENT OF BREAKING THROUGH ENGAGEMENTS AND ALL THE VARIOUS OBSTACLES THAT STILL MILITATED AGAINST THEIR UNION", "subset": "test_clean", "task_type": "understanding", "prediction": "miss woodley was too little versed in the subject to know this would have been not to love at all at least not to the extent of breaking through engagements and all the various obstacles that still mitigated against their union", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0011.flac", "answer": "IF SHE DOES NOT KNOW HOW TO ESTIMATE HER OWN VALUE I DO", "subset": "test_clean", "task_type": "understanding", "prediction": "if she does not know how to estimate her own value i do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0007.flac", "answer": "TO ASK ANY MORE QUESTIONS OF YOU I BELIEVE WOULD BE UNFAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "to ask any more questions of you i believe would be unfair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0006.flac", "answer": "PERHAPS I AM MISTAKEN ANSWERED SHE", "subset": "test_clean", "task_type": "understanding", "prediction": "perhaps i am mistaken answered she", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0008.flac", "answer": "HE SEEMED TO WAIT FOR HER REPLY BUT AS SHE MADE NONE HE PROCEEDED", "subset": "test_clean", "task_type": "understanding", "prediction": "he seemed to wait for her reply but as she made none he proceeded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0000.flac", "answer": "BUT THE MORE FORGETFULNESS HAD THEN PREVAILED THE MORE POWERFUL WAS THE FORCE OF REMEMBRANCE WHEN SHE AWOKE", "subset": "test_clean", "task_type": "understanding", "prediction": "but the more forgetfulness had then prevailed the more powerful was the force of remembrance when she awoke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0014.flac", "answer": "WHAT CAN YOU MEAN BY THAT MISS WOODLEY YOU TALK MYSTERIOUSLY", "subset": "test_clean", "task_type": "understanding", "prediction": "what can you mean by that miss woodley you talk mysteriously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0020.flac", "answer": "I HAVE NEVER YET HOWEVER BEEN VANQUISHED BY THEM AND EVEN UPON THIS OCCASION MY REASON SHALL COMBAT THEM TO THE LAST AND MY REASON SHALL FAIL ME BEFORE I DO WRONG", "subset": "test_clean", "task_type": "understanding", "prediction": "i have never yet however been vanquished by them and even upon this occasion my reason shall combat them to the last and my reason shall fail me before i do wrong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0003.flac", "answer": "SO THERE IS TO ME ADDED SANDFORD WITH A SARCASTIC SNEER", "subset": "test_clean", "task_type": "understanding", "prediction": "so there is to me added sanford with a sarcastic sneer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0009.flac", "answer": "OH MY LORD CRIED MISS WOODLEY WITH A MOST FORCIBLE ACCENT YOU ARE THE LAST PERSON ON EARTH SHE WOULD PARDON ME FOR ENTRUSTING", "subset": "test_clean", "task_type": "understanding", "prediction": "o my lord cried miss woodley with a most forcible accent you are the last person on earth she would pardon me for entrusting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0012.flac", "answer": "INDEPENDENT OF HER FORTUNE SHE HAS BEAUTY TO CAPTIVATE THE HEART OF ANY MAN AND WITH ALL HER FOLLIES SHE HAS A FRANKNESS IN HER MANNER AN UNAFFECTED WISDOM IN HER THOUGHTS A VIVACITY IN HER CONVERSATION AND WITHAL A SOFTNESS IN HER DEMEANOUR THAT MIGHT ALONE ENGAGE THE AFFECTIONS OF A MAN OF THE NICEST SENTIMENTS AND THE STRONGEST UNDERSTANDING", "subset": "test_clean", "task_type": "understanding", "prediction": "independent of her fortune she has beauty to captivate the heart of any man and with all her follies she has a frankness in her manner an unaffected wisdom in her thoughts a vivacity in her conversation and withal a softness in her demeanor that might alone engage the affections of a man of the nicest sentiments and the strongest understanding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0002.flac", "answer": "SAID MISSUS HORTON A FEW MINUTES AFTER", "subset": "test_clean", "task_type": "understanding", "prediction": "said mrs horton a few minutes after", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0019.flac", "answer": "I WILL MAKE NO UNJUST USE OF WHAT I KNOW HE REPLIED WITH FIRMNESS I BELIEVE YOU MY LORD", "subset": "test_clean", "task_type": "understanding", "prediction": "i will make no unjust use of what i know he replied with firmness i believe you my lord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0015.flac", "answer": "IS SHE NOT AFRAID THAT I WILL THWART HER INCLINATIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "is she not afraid that i will thwart her inclinations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0018.flac", "answer": "TO RELIEVE HER FROM BOTH HE LAID HIS HAND WITH FORCE UPON HIS HEART AND SAID DO YOU BELIEVE ME", "subset": "test_clean", "task_type": "understanding", "prediction": "to relieve her from both he laid his hand with force upon his heart and said do you believe me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0010.flac", "answer": "BUT IN SUCH A CASE MISS MILNER'S ELECTION OF A HUSBAND SHALL NOT DIRECT MINE", "subset": "test_clean", "task_type": "understanding", "prediction": "but in such a case miss milner s election of a husband shall not direct mine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0016.flac", "answer": "AGAIN HE SEARCHED HIS OWN THOUGHTS NOR INEFFECTUALLY AS BEFORE", "subset": "test_clean", "task_type": "understanding", "prediction": "again he searched his own thoughts nor ineffectually as before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/23283/4992-23283-0001.flac", "answer": "MISS MILNER'S HEALTH IS NOT GOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "miss milner s health is not good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0005.flac", "answer": "NEXT CAME OLIVE'S TURN TO HELP IN THE CEREMONIES", "subset": "test_clean", "task_type": "understanding", "prediction": "next came olive s turn to help in the ceremonies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0001.flac", "answer": "TO NIGHT THERE WAS NO NEED OF EXTRA HEAT AND THERE WERE GREAT CEREMONIES TO BE OBSERVED IN LIGHTING THE FIRES ON THE HEARTHSTONES", "subset": "test_clean", "task_type": "understanding", "prediction": "to night there was no need of extra heat and there were great ceremonies to be observed in lighting the fires on the hearthstones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0000.flac", "answer": "NATTY HARMON TRIED THE KITCHEN PUMP SECRETLY SEVERAL TIMES DURING THE EVENING FOR THE WATER HAD TO RUN UP HILL ALL THE WAY FROM THE WELL TO THE KITCHEN SINK AND HE BELIEVED THIS TO BE A CONTINUAL MIRACLE THAT MIGHT GIVE OUT AT ANY MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "natty harmon tried the kitchen pump secretly several times during the evening for the water had to run up hill all the way from the well to the kitchen sink and he believed this to be a continual miracle that might give out at any moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0013.flac", "answer": "APPROACHING THE DINING TABLE HE CAREFULLY PLACED THE ARTICLE IN THE CENTRE AND REMOVED THE CLOTH", "subset": "test_clean", "task_type": "understanding", "prediction": "approaching the dining table he carefully placed the article in the center and removed the cloth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0011.flac", "answer": "MOTHER CAREY POURED COFFEE NANCY CHOCOLATE AND THE OTHERS HELPED SERVE THE SANDWICHES AND CAKE DOUGHNUTS AND TARTS", "subset": "test_clean", "task_type": "understanding", "prediction": "mother carey poured coffee nancy chocolate and the others helped serve the sandwiches and cake doughnuts and tarts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0002.flac", "answer": "THEY BEGAN WITH THE ONE IN THE FAMILY SITTING ROOM COLONEL WHEELER RALPH THURSTON MISTER AND MISSUS BILL HARMON WITH NATTY AND RUFUS MISTER AND MISSUS POPHAM WITH DIGBY AND LALLIE JOY ALL STANDING IN ADMIRING GROUPS AND THRILLING WITH DELIGHT AT THE ORDER OF EVENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "they began with the one in the family sitting room colonel wheeler ralph thurston mr and mrs bill harmon with natty and rufus mr and mrs popham with digby and lally joy all standing in admiring groups and thrilling with delight at the order of events", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0003.flac", "answer": "KATHLEEN WAVED THE TORCH TO AND FRO AS SHE RECITED SOME BEAUTIFUL LINES WRITTEN FOR SOME SUCH PURPOSE AS THAT WHICH CALLED THEM TOGETHER TO NIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "kathleen waved the torch to and fro as she recited some beautiful lines written for some such purpose as that which called them together to night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0012.flac", "answer": "AT THAT MOMENT THE GENTLEMAN ENTERED BEARING A HUGE OBJECT CONCEALED BY A PIECE OF GREEN FELT", "subset": "test_clean", "task_type": "understanding", "prediction": "at that moment the gentleman entered bearing a huge object concealed by a piece of green felt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0015.flac", "answer": "MISSUS HARMON THOUGHT HE SANG TOO MUCH AND TOLD HER HUSBAND PRIVATELY THAT IF HE WAS A CANARY BIRD SHE SHOULD WANT TO KEEP A TABLE COVER OVER HIS HEAD MOST OF THE TIME BUT HE WAS IMMENSELY POPULAR WITH THE REST OF HIS AUDIENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "mrs harmon thought he sang too much and told her husband privately that if he was a canary bird she should want to keep a table cover over his head most of the time but he was immensely popular with the rest of his audience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0014.flac", "answer": "THINKS I TO MYSELF I NEVER SEEN ANYTHING OSH POPHAM COULDN'T MEND IF HE TOOK TIME ENOUGH AND GLUE ENOUGH SO I CARRIED THIS LITTLE FELLER HOME IN A BUSHEL BASKET ONE NIGHT LAST MONTH AN I'VE SPENT ELEVEN EVENIN'S PUTTIN HIM TOGETHER", "subset": "test_clean", "task_type": "understanding", "prediction": "thinks i to myself i never seen anything osh popham couldn t mend if he took time enough and glue enough so i carried this little feller home in a bushel basket one night last month and i ve spent eleven evenings putting him together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0004.flac", "answer": "BURN FIRE BURN FLICKER FLICKER FLAME", "subset": "test_clean", "task_type": "understanding", "prediction": "burn fire burn flicker flicker flame", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0006.flac", "answer": "RALPH THURSTON HAD FOUND A LINE OF LATIN FOR THEM IN HIS BELOVED HORACE TIBI SPLENDET FOCUS FOR YOU THE HEARTH FIRE SHINES", "subset": "test_clean", "task_type": "understanding", "prediction": "ralph thurston had found a line of latin for them in his beloved horace tibi splendet focus for you the hearth fire shines", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0008.flac", "answer": "OLIVE HAS ANOTHER LOVELY GIFT FOR THE YELLOW HOUSE SAID MOTHER CAREY RISING AND TO CARRY OUT THE NEXT PART OF THE PROGRAMME WE SHALL HAVE TO GO IN PROCESSION UPSTAIRS TO MY BEDROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "olive has another lovely gift for the yellow house said mother carey rising and to carry out the next part of the programme we shall have to go in procession upstairs to my bedroom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0010.flac", "answer": "AIN'T THEY THE GREATEST", "subset": "test_clean", "task_type": "understanding", "prediction": "aint they the greatest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0016.flac", "answer": "THE FACE OF THE MAHOGANY SHONE WITH DELIGHT AND WHY NOT WHEN IT WAS DOING EVERYTHING ALMOST EVERYTHING WITHIN THE SCOPE OF A PIANO AND YET THE FAMILY HAD ENJOYED WEEKS OF GOOD NOURISHING MEALS ON WHAT HAD BEEN SAVED BY ITS EXERTIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "the face of the mahogany shone with delight and why not when it was doing everything almost everything within the scope of a piano and yet the family had enjoyed weeks of good nourishing meals on what had been saved by its exertions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0009.flac", "answer": "EXCLAIMED BILL HARMON TO HIS WIFE AS THEY WENT THROUGH THE LIGHTED HALL", "subset": "test_clean", "task_type": "understanding", "prediction": "exclaimed bill harman to his wife as they went through the lighted hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0017.flac", "answer": "WE SHUT OUR EYES THE FLOWERS BLOOM ON WE MURMUR BUT THE CORN EARS FILL WE CHOOSE THE SHADOW BUT THE SUN THAT CASTS IT SHINES BEHIND US STILL", "subset": "test_clean", "task_type": "understanding", "prediction": "we shut our eyes the flowers bloom on we murmur but the corn ears fill we choose the shadow but the sun that cast it shines behind us still", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4992/41806/4992-41806-0007.flac", "answer": "OLIVE HAD PAINTED THE MOTTO ON A LONG NARROW PANEL OF CANVAS AND GIVING IT TO MISTER POPHAM STOOD BY THE FIRESIDE WHILE HE DEFTLY FITTED IT INTO THE PLACE PREPARED FOR IT", "subset": "test_clean", "task_type": "understanding", "prediction": "olive had painted the motto on a long narrow panel of canvas and giving it to mr popham stood by the fireside while he deftly fitted it into the place prepared for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0014.flac", "answer": "AND EMIL MOWED HIS WAY SLOWLY DOWN TOWARD THE CHERRY TREES", "subset": "test_clean", "task_type": "understanding", "prediction": "and emil mowed his way slowly down toward the cherry trees", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0003.flac", "answer": "THE ORCHARD WAS SPARKLING AND RIPPLING IN THE SUN", "subset": "test_clean", "task_type": "understanding", "prediction": "the orchard was sparkling and rippling in the sun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0027.flac", "answer": "MARIE'S FACE FELL UNDER HIS BROODING GAZE", "subset": "test_clean", "task_type": "understanding", "prediction": "marie s face fell under his brooding gaze", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0020.flac", "answer": "YES DON'T YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "yes dont you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0029.flac", "answer": "I DON'T WANT TO STAND AROUND AND LOOK ON", "subset": "test_clean", "task_type": "understanding", "prediction": "i dont want to stand around and look on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0019.flac", "answer": "HE DROPPED A HANDFUL INTO HER LAP", "subset": "test_clean", "task_type": "understanding", "prediction": "he dropped a handful into her lap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0038.flac", "answer": "AND ANYHOW THERE'S NOTHING TO UNDERSTAND", "subset": "test_clean", "task_type": "understanding", "prediction": "and anyhow there is nothing to understand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0028.flac", "answer": "I'M SURE ALEXANDRA HOPES YOU WILL STAY ON HERE SHE MURMURED", "subset": "test_clean", "task_type": "understanding", "prediction": "i am sure alexandra helps you will stay on here she murmured", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0015.flac", "answer": "THAT SUMMER THE RAINS HAD BEEN SO MANY AND OPPORTUNE THAT IT WAS ALMOST MORE THAN SHABATA AND HIS MAN COULD DO TO KEEP UP WITH THE CORN THE ORCHARD WAS A NEGLECTED WILDERNESS", "subset": "test_clean", "task_type": "understanding", "prediction": "that summer the rains had been so many and opportune that it was almost more than shabata and his man could do to keep up with the corn the orchard was a neglected wilderness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0030.flac", "answer": "I WANT TO BE DOING SOMETHING ON MY OWN ACCOUNT", "subset": "test_clean", "task_type": "understanding", "prediction": "i want to be doing something on my own account", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0009.flac", "answer": "I SUPPOSE THAT'S THE WET SEASON TOO THEN", "subset": "test_clean", "task_type": "understanding", "prediction": "i suppose that is the wet season too then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0041.flac", "answer": "I CAN'T PRAY TO HAVE THE THINGS I WANT HE SAID SLOWLY AND I WON'T PRAY NOT TO HAVE THEM NOT IF I'M DAMNED FOR IT", "subset": "test_clean", "task_type": "understanding", "prediction": "i can t pray to have the things i want he said slowly and i won t pray not to have them not if i m damned for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0039.flac", "answer": "THAT WON'T LAST IT WILL GO AWAY AND THINGS WILL BE JUST AS THEY USED TO", "subset": "test_clean", "task_type": "understanding", "prediction": "that wont last it will go away and things will be just as they used to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0021.flac", "answer": "OH EVER SO MUCH ONLY HE SEEMS KIND OF STAID AND SCHOOL TEACHERY", "subset": "test_clean", "task_type": "understanding", "prediction": "oh ever so much only he seems kind of staid and school teacherie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0024.flac", "answer": "I LIKE TO TALK TO CARL ABOUT NEW YORK AND WHAT A FELLOW CAN DO THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "i like to talk to carl about new york and what a fellow can do there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0004.flac", "answer": "THAT INVITATION DECIDED HER", "subset": "test_clean", "task_type": "understanding", "prediction": "that invitation decided her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0034.flac", "answer": "THANK YOU HE RETURNED SHORTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "thank you he returned shortly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0010.flac", "answer": "IT'S EXCITING TO SEE EVERYTHING GROWING SO FAST AND TO GET THE GRASS CUT", "subset": "test_clean", "task_type": "understanding", "prediction": "its exciting to see everything growing so fast and to get the grass cut", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0008.flac", "answer": "I SUPPOSE IT'S THE WET SEASON WILL YOU HAVE TO CUT THEM TOO", "subset": "test_clean", "task_type": "understanding", "prediction": "i suppose it is the wet season will you have to cut them too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0011.flac", "answer": "AREN'T YOU SPLASHED LOOK AT THE SPIDER WEBS ALL OVER THE GRASS", "subset": "test_clean", "task_type": "understanding", "prediction": "arent you splashed look at the spider webs all over the grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0031.flac", "answer": "SOMETIMES I DON'T WANT TO DO ANYTHING AT ALL AND SOMETIMES I WANT TO PULL THE FOUR CORNERS OF THE DIVIDE TOGETHER HE THREW OUT HIS ARM AND BROUGHT IT BACK WITH A JERK SO LIKE A TABLE CLOTH", "subset": "test_clean", "task_type": "understanding", "prediction": "sometimes i don't want to do anything at all and sometimes i want to pull the four corners of the divide together he threw out his arm and brought it back with a jerk so like a tablecloth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0017.flac", "answer": "IF I FEEL THAT WAY I FEEL THAT WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "if i feel that way i feel that way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0042.flac", "answer": "THEN ALL OUR GOOD TIMES ARE OVER", "subset": "test_clean", "task_type": "understanding", "prediction": "then all our good times are over", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0018.flac", "answer": "HE REACHED UP AMONG THE BRANCHES AND BEGAN TO PICK THE SWEET INSIPID FRUIT LONG IVORY COLORED BERRIES TIPPED WITH FAINT PINK LIKE WHITE CORAL THAT FALL TO THE GROUND UNHEEDED ALL SUMMER THROUGH", "subset": "test_clean", "task_type": "understanding", "prediction": "he reached up among the branches and began to pick the sweet insipid fruit long ivory colored berries tipped with faint pink like white coral that fall to the ground unheeded all summer through", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0012.flac", "answer": "IN A FEW MOMENTS HE HEARD THE CHERRIES DROPPING SMARTLY INTO THE PAIL AND HE BEGAN TO SWING HIS SCYTHE WITH THAT LONG EVEN STROKE THAT FEW AMERICAN BOYS EVER LEARN", "subset": "test_clean", "task_type": "understanding", "prediction": "in a few moments he heard the cherries dropping smartly into the pail and he began to swing his scythe with that long even stroke that few american boys ever learn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0040.flac", "answer": "I PRAY FOR YOU BUT THAT'S NOT THE SAME AS IF YOU PRAYED YOURSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "i pray for you but that is not the same as if you prayed yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0002.flac", "answer": "A BRISK WIND HAD COME UP AND WAS DRIVING PUFFY WHITE CLOUDS ACROSS THE SKY", "subset": "test_clean", "task_type": "understanding", "prediction": "a brisk wind had come up and was driving puffy white clouds across the sky", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0006.flac", "answer": "JUST SMELL THE WILD ROSES THEY ARE ALWAYS SO SPICY AFTER A RAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "just smell the wild roses they are always so spicy after a rain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0035.flac", "answer": "AND YOU NEVER USED TO BE CROSS TO ME", "subset": "test_clean", "task_type": "understanding", "prediction": "and you never used to be cross to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0007.flac", "answer": "WE NEVER HAD SO MANY OF THEM IN HERE BEFORE", "subset": "test_clean", "task_type": "understanding", "prediction": "we never had so many of them in here before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0016.flac", "answer": "I DON'T KNOW ALL OF THEM BUT I KNOW LINDENS ARE", "subset": "test_clean", "task_type": "understanding", "prediction": "i do not know all of them but i know lindens are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0013.flac", "answer": "MARIE PICKED CHERRIES AND SANG SOFTLY TO HERSELF STRIPPING ONE GLITTERING BRANCH AFTER ANOTHER SHIVERING WHEN SHE CAUGHT A SHOWER OF RAINDROPS ON HER NECK AND HAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "marie picked cherries and sang softly to herself stripping one glittering branch after another shivering when she caught a shower of raindrops on her neck and hair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0001.flac", "answer": "MARIE SIGHED", "subset": "test_clean", "task_type": "understanding", "prediction": "marie sighed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0000.flac", "answer": "FRANK READ ENGLISH SLOWLY AND THE MORE HE READ ABOUT THIS DIVORCE CASE THE ANGRIER HE GREW", "subset": "test_clean", "task_type": "understanding", "prediction": "frank read english slowly and the more he read about this divorce case the angrier he grew", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0026.flac", "answer": "SURELY YOU ARE NOT THINKING OF GOING OFF THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "surely you are not thinking of going off there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0037.flac", "answer": "BUT EMIL IF I UNDERSTAND THEN ALL OUR GOOD TIMES ARE OVER WE CAN NEVER DO NICE THINGS TOGETHER ANY MORE", "subset": "test_clean", "task_type": "understanding", "prediction": "but emil if i understand then all our good times are over we can never do nice things together any more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0022.flac", "answer": "WHEN SHE USED TO TELL ME ABOUT HIM I ALWAYS WONDERED WHETHER SHE WASN'T A LITTLE IN LOVE WITH HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "when she used to tell me about him i always wondered whether she wasnt a little in love with him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0032.flac", "answer": "I GET TIRED OF SEEING MEN AND HORSES GOING UP AND DOWN UP AND DOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "i get tired of seeing men and horses going up and down up and down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0023.flac", "answer": "IT WOULD SERVE YOU ALL RIGHT IF SHE WALKED OFF WITH CARL", "subset": "test_clean", "task_type": "understanding", "prediction": "it would serve you all right if she walked off with carl", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0005.flac", "answer": "OH BUT I'M GLAD TO GET THIS PLACE MOWED", "subset": "test_clean", "task_type": "understanding", "prediction": "oh but i am glad to get this place muldo", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0025.flac", "answer": "OH EMIL", "subset": "test_clean", "task_type": "understanding", "prediction": "oh emil", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0036.flac", "answer": "I CAN'T PLAY WITH YOU LIKE A LITTLE BOY ANY MORE HE SAID SLOWLY THAT'S WHAT YOU MISS MARIE", "subset": "test_clean", "task_type": "understanding", "prediction": "i can not play with you like a little boy any more he said slowly that is what you miss marie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134500/237-134500-0033.flac", "answer": "I WISH YOU WEREN'T SO RESTLESS AND DIDN'T GET SO WORKED UP OVER THINGS SHE SAID SADLY", "subset": "test_clean", "task_type": "understanding", "prediction": "i wish you weren t so restless and didn t get so worked up over things she said sadly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0008.flac", "answer": "SHE GATHERED UP HER REINS", "subset": "test_clean", "task_type": "understanding", "prediction": "she gathered up her reins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0017.flac", "answer": "ANY ONE THEREABOUTS WOULD HAVE TOLD YOU THAT THIS WAS ONE OF THE RICHEST FARMS ON THE DIVIDE AND THAT THE FARMER WAS A WOMAN ALEXANDRA BERGSON", "subset": "test_clean", "task_type": "understanding", "prediction": "any one thereabouts would have told you that this was one of the richest farms on the divide and that the farmer was a woman alexandra bergson", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0009.flac", "answer": "PLEASE WAIT FOR ME MARIE EMIL COAXED", "subset": "test_clean", "task_type": "understanding", "prediction": "please wait for me marie emil coaxed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0003.flac", "answer": "FROM THE GRAVEYARD GATE ONE CAN COUNT A DOZEN GAYLY PAINTED FARMHOUSES THE GILDED WEATHER VANES ON THE BIG RED BARNS WINK AT EACH OTHER ACROSS THE GREEN AND BROWN AND YELLOW FIELDS", "subset": "test_clean", "task_type": "understanding", "prediction": "from the graveyard gate one can count a dozen gayly painted farmhouses the gilded weather vanes on the big red barns wink at each other across the green and brown and yellow fields", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0014.flac", "answer": "THEY THINK YOU'RE PROUD BECAUSE YOU'VE BEEN AWAY TO SCHOOL OR SOMETHING", "subset": "test_clean", "task_type": "understanding", "prediction": "they think you are proud because you have been away to school or something", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0016.flac", "answer": "ON EITHER SIDE OF THE ROAD FOR A MILE BEFORE YOU REACHED THE FOOT OF THE HILL STOOD TALL OSAGE ORANGE HEDGES THEIR GLOSSY GREEN MARKING OFF THE YELLOW FIELDS", "subset": "test_clean", "task_type": "understanding", "prediction": "on either side of the road for a mile before you reached the foot of the hill stood tall osage orange hedges their glossy green marking off the yellow fields", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0000.flac", "answer": "IT IS SIXTEEN YEARS SINCE JOHN BERGSON DIED", "subset": "test_clean", "task_type": "understanding", "prediction": "it is sixteen years since john birks and died", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0004.flac", "answer": "THE AIR AND THE EARTH ARE CURIOUSLY MATED AND INTERMINGLED AS IF THE ONE WERE THE BREATH OF THE OTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "the air and the earth are curiously mated and intermingled as if the one were the breath of the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0006.flac", "answer": "THAT'S NOT MUCH OF A JOB FOR AN ATHLETE HERE I'VE BEEN TO TOWN AND BACK", "subset": "test_clean", "task_type": "understanding", "prediction": "thats not much of a job for an athlete here i have been to town and back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0007.flac", "answer": "ALEXANDRA LETS YOU SLEEP LATE", "subset": "test_clean", "task_type": "understanding", "prediction": "alexandra lets you sleep late", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0005.flac", "answer": "HE WAS A SPLENDID FIGURE OF A BOY TALL AND STRAIGHT AS A YOUNG PINE TREE WITH A HANDSOME HEAD AND STORMY GRAY EYES DEEPLY SET UNDER A SERIOUS BROW", "subset": "test_clean", "task_type": "understanding", "prediction": "he was a splendid figure of a boy tall and straight as a young pine tree with a handsome head and stormy gray eyes deeply set under a serious brow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0002.flac", "answer": "FROM THE NORWEGIAN GRAVEYARD ONE LOOKS OUT OVER A VAST CHECKER BOARD MARKED OFF IN SQUARES OF WHEAT AND CORN LIGHT AND DARK DARK AND LIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "from the norwegian graveyard one looks out over a vast checkerboard marked off in squares of wheat and corn light and dark dark and light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0011.flac", "answer": "HOW BROWN YOU'VE GOT SINCE YOU CAME HOME I WISH I HAD AN ATHLETE TO MOW MY ORCHARD", "subset": "test_clean", "task_type": "understanding", "prediction": "how brown you have got since you came home i wish i had an athlete to mow my orchard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0015.flac", "answer": "THERE WAS SOMETHING INDIVIDUAL ABOUT THE GREAT FARM A MOST UNUSUAL TRIMNESS AND CARE FOR DETAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "there was something individual about the great farm a most unusual trimness and care for detail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0010.flac", "answer": "I NEVER SEE LOU'S SCYTHE OVER HERE", "subset": "test_clean", "task_type": "understanding", "prediction": "i never see lou sigh though over here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0018.flac", "answer": "THERE IS EVEN A WHITE ROW OF BEEHIVES IN THE ORCHARD UNDER THE WALNUT TREES", "subset": "test_clean", "task_type": "understanding", "prediction": "there is even a white row of bee hives in the orchard under the walnut trees", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0013.flac", "answer": "INDEED HE HAD LOOKED AWAY WITH THE PURPOSE OF NOT SEEING IT", "subset": "test_clean", "task_type": "understanding", "prediction": "indeed he had looked away with the purpose of not seeing it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0012.flac", "answer": "I GET WET TO MY KNEES WHEN I GO DOWN TO PICK CHERRIES", "subset": "test_clean", "task_type": "understanding", "prediction": "i get wet to my knees when i go down to pick cherries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/134493/237-134493-0001.flac", "answer": "HIS WIFE NOW LIES BESIDE HIM AND THE WHITE SHAFT THAT MARKS THEIR GRAVES GLEAMS ACROSS THE WHEAT FIELDS", "subset": "test_clean", "task_type": "understanding", "prediction": "his wife now lies beside him and the white shaft that marks their graves gleams across the wheat fields", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0018.flac", "answer": "DON'T MIND IT POLLY WHISPERED JASPER TWASN'T HER FAULT", "subset": "test_clean", "task_type": "understanding", "prediction": "dont mind it polly whispered jasper twasnt her fault", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0002.flac", "answer": "THEN DEAR SAID MISSUS WHITNEY YOU MUST BE KINDER TO HER THAN EVER THINK WHAT IT WOULD BE FOR ONE OF YOU TO BE AWAY FROM HOME EVEN AMONG FRIENDS", "subset": "test_clean", "task_type": "understanding", "prediction": "then dear said mrs whitney you must be kinder to her than ever think what it would be for one of you to be away from home even among friends", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0015.flac", "answer": "YES ALL ALONE BY HIMSELF ASSERTED JASPER VEHEMENTLY AND WINKING FURIOUSLY TO THE OTHERS TO STOP THEIR LAUGHING HE DID NOW TRULY PHRONSIE", "subset": "test_clean", "task_type": "understanding", "prediction": "yes all alone by himself asserted jasper vehemently and winking furiously to the others to stop their laughing he did now truly phronsie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0007.flac", "answer": "BUT POLLY COULDN'T SPEAK AND IF JASPER HADN'T CAUGHT HER JUST IN TIME SHE WOULD HAVE TUMBLED OVER BACKWARD FROM THE STOOL PHRONSIE AND ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "but polly couldn't speak and if jasper hadn t caught her just in time she would have tumbled over backward from the stool phronsie and all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0023.flac", "answer": "HE CRIED IN HIGH DUDGEON JUST AS IF HE OWNED THE WHOLE OF THE PEPPERS AND COULD DISPOSE OF THEM ALL TO SUIT HIS FANCY", "subset": "test_clean", "task_type": "understanding", "prediction": "he cried in high dudgeon just as if he owned the whole of the peppers and could dispose of them all to suit his fancy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0014.flac", "answer": "ASKED PHRONSIE IN INTENSE INTEREST SLIPPING DOWN OUT OF POLLY'S ARMS AND CROWDING UP CLOSE TO JASPER'S SIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "asked phronsie in intense interest slipping down out of polly's arms and crowding up close to jasper side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0021.flac", "answer": "SHE ASKED IMPULSIVELY I DIDN'T BELIEVE YOU COULD PERSUADE HER FATHER", "subset": "test_clean", "task_type": "understanding", "prediction": "she asked impulsively i didn t believe you could persuade her father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0016.flac", "answer": "OH NO JASPER I MUST GO BY MY VERY OWN SELF", "subset": "test_clean", "task_type": "understanding", "prediction": "oh no japsir i must go by my very own self", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0005.flac", "answer": "OH SHE'S ALWAYS AT THE PIANO SAID VAN SHE MUST BE THERE NOW SOMEWHERE AND THEN SOMEBODY LAUGHED", "subset": "test_clean", "task_type": "understanding", "prediction": "oh she is always at the piano said van she must be there now somewhere and then somebody laughed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0011.flac", "answer": "ISN'T HE SPLENDID CRIED JASPER IN INTENSE PRIDE SWELLING UP FATHER KNEW HOW TO DO IT", "subset": "test_clean", "task_type": "understanding", "prediction": "isn t he splendid cried jasper in intense pride swelling up father knew how to do it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0008.flac", "answer": "ASKED PHRONSIE WITH HER LITTLE FACE CLOSE TO POLLY'S OWN", "subset": "test_clean", "task_type": "understanding", "prediction": "asked phronsie with her little face close to polly s own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0012.flac", "answer": "THERE THERE HE SAID SOOTHINGLY PATTING HER BROWN FUZZY HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "there there he said soothingly patting her brown fuzzy head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0017.flac", "answer": "THERE JAP YOU'VE CAUGHT IT LAUGHED PERCY WHILE THE OTHERS SCREAMED AT THE SIGHT OF JASPER'S FACE", "subset": "test_clean", "task_type": "understanding", "prediction": "there jap youve caught it laughed percy while the others screamed at the sight of jasper s face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0013.flac", "answer": "I KNOW GASPED POLLY CONTROLLING HER SOBS I WON'T ONLY I CAN'T THANK YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "i know gasped polly controlling her sobs i won't only i can not thank you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0004.flac", "answer": "IF SHE COULD ONLY SEE PHRONSIE FOR JUST ONE MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "if she could only see phronsie for just one moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0003.flac", "answer": "SOMEHOW OF ALL THE DAYS WHEN THE HOME FEELING WAS THE STRONGEST THIS DAY IT SEEMED AS IF SHE COULD BEAR IT NO LONGER", "subset": "test_clean", "task_type": "understanding", "prediction": "somehow of all the days when the home feeling was the strongest this day it seemed as if she could bear it no longer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0009.flac", "answer": "NOW YOU'LL STAY CRIED VAN SAY POLLY WON'T YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "now you ll stay cried van say polly won t you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0020.flac", "answer": "HOW DID HER MOTHER EVER LET HER GO", "subset": "test_clean", "task_type": "understanding", "prediction": "how did her mother ever let her go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0024.flac", "answer": "AND THE OLD GENTLEMAN WAS SO DELIGHTED WITH HIS SUCCESS THAT HE HAD TO BURST OUT INTO A SERIES OF SHORT HAPPY BITS OF LAUGHTER THAT OCCUPIED QUITE A SPACE OF TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "and the old gentleman was so delighted with his success that he had to burst out into a series of short happy bits of laughter that occupied quite a space of time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0010.flac", "answer": "OH YOU ARE THE DEAREST AND BEST MISTER KING I EVER SAW BUT HOW DID YOU MAKE MAMMY LET HER COME", "subset": "test_clean", "task_type": "understanding", "prediction": "oh you are the dearest and best mr king i ever saw but how did you make mammy let her come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0022.flac", "answer": "I DIDN'T HAVE ANY FEARS IF I WORKED IT RIGHTLY SAID THE OLD GENTLEMAN COMPLACENTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "i didn t have any fears if i worked it rightly said the old gentleman complacently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0025.flac", "answer": "AT LAST HE CAME OUT OF THEM AND WIPED HIS FACE VIGOROUSLY", "subset": "test_clean", "task_type": "understanding", "prediction": "at last he came out of them and wiped his face vigorously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0019.flac", "answer": "DEAR ME EJACULATED THE OLD GENTLEMAN IN THE UTMOST AMAZEMENT AND SUCH A TIME AS I'VE HAD TO GET HER HERE TOO", "subset": "test_clean", "task_type": "understanding", "prediction": "dear me ejaculated the old gentleman in the utmost amazement and such a time as i have had to get her here too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0006.flac", "answer": "AT THIS THE BUNDLE OPENED SUDDENLY AND OUT POPPED PHRONSIE", "subset": "test_clean", "task_type": "understanding", "prediction": "at this the bundle opened suddenly and out popped phronsie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0001.flac", "answer": "EVERY CHANCE SHE COULD STEAL AFTER PRACTICE HOURS WERE OVER AND AFTER THE CLAMOROUS DEMANDS OF THE BOYS UPON HER TIME WERE FULLY SATISFIED WAS SEIZED TO FLY ON THE WINGS OF THE WIND TO THE FLOWERS", "subset": "test_clean", "task_type": "understanding", "prediction": "every chance she could steal after practice hours were over and after the clamorous demands of the boys upon her time were fully satisfied was seized to fly on the wings of the wind to the flowers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/237/126133/237-126133-0000.flac", "answer": "HERE SHE WOULD STAY COMFORTED AND SOOTHED AMONG THE LOVELY PLANTS AND RICH EXOTICS REJOICING THE HEART OF OLD TURNER THE GARDENER WHO SINCE POLLY'S FIRST RAPTUROUS ENTRANCE HAD TAKEN HER INTO HIS GOOD GRACES FOR ALL TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "here she would stay comforted and soothed among the lovely plants and rich exotics rejoicing the heart of old turner the gardener who since polly s first rapturous entrance had taken her into his good graces for all time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0002.flac", "answer": "HE HAD HIS HAND UPON LAKE'S SHOULDER", "subset": "test_clean", "task_type": "understanding", "prediction": "he had his hand upon lake s shoulder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0001.flac", "answer": "SAID LORD CHELFORD ADDRESSING ME", "subset": "test_clean", "task_type": "understanding", "prediction": "said lord shelford addressing me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0005.flac", "answer": "BUT HER GREETING TO CAPTAIN LAKE WAS MORE THAN USUALLY HAUGHTY AND FROZEN AND HER FEATURES I FANCIED PARTICULARLY PROUD AND PALE", "subset": "test_clean", "task_type": "understanding", "prediction": "but her greeting to captain lake was more than usually haughty and frozen and her features i fancied particularly proud and pale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0014.flac", "answer": "HE'S NOT A MAN FOR COUNTRY QUARTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "hes not a man for country quarters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0015.flac", "answer": "I HAD A HORRID DREAM ABOUT HIM LAST NIGHT THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "i had a horrid dream about him last night that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0008.flac", "answer": "I BELIEVE I HAVE A LITTLE TASTE THAT WAY THOSE ARE ALL REAL YOU KNOW THOSE JEWELS", "subset": "test_clean", "task_type": "understanding", "prediction": "i believe i have a little taste that way those are all real you know those jewels", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0011.flac", "answer": "WHEREUPON LAKE LAUGHED QUIETLY STILL LOOKING ON THE ACE OF HEARTS WITH HIS SLY EYES", "subset": "test_clean", "task_type": "understanding", "prediction": "whereupon lake laughed quietly still looking on the ace of hearts with his sly eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0010.flac", "answer": "I WAS THINKING IT'S VERY LIKE THE ACE OF HEARTS ANSWERED THE CAPTAIN SOFTLY SMILING ON", "subset": "test_clean", "task_type": "understanding", "prediction": "i was thinking it is very like the ace of hearts answered the captain softly smiling on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0006.flac", "answer": "AT DINNER LAKE WAS EASY AND AMUSING", "subset": "test_clean", "task_type": "understanding", "prediction": "at dinner lake was easy and amusing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0016.flac", "answer": "OH I KNOW THAT'S LORNE BRANDON", "subset": "test_clean", "task_type": "understanding", "prediction": "oh i know that is lorne brandon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0007.flac", "answer": "I'M GLAD YOU LIKE IT SAYS WYLDER CHUCKLING BENIGNANTLY ON IT OVER HIS SHOULDER", "subset": "test_clean", "task_type": "understanding", "prediction": "i am glad you like it says wilder chuckling benignantly on it over his shoulder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0017.flac", "answer": "ALL THE TIME HE WAS TALKING TO ME HIS ANGRY LITTLE EYES WERE FOLLOWING LAKE", "subset": "test_clean", "task_type": "understanding", "prediction": "all the time he was talking to me his angry little eyes were following lake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0012.flac", "answer": "AND WYLDER LAUGHED TOO MORE SUDDENLY AND NOISILY THAN THE HUMOUR OF THE JOKE SEEMED QUITE TO CALL FOR AND GLANCED A GRIM LOOK FROM THE CORNERS OF HIS EYES ON LAKE BUT THE GALLANT CAPTAIN DID NOT SEEM TO PERCEIVE IT AND AFTER A FEW SECONDS MORE HE HANDED IT VERY INNOCENTLY BACK TO MISSUS DOROTHY ONLY REMARKING", "subset": "test_clean", "task_type": "understanding", "prediction": "and wilder laughed too more suddenly and noisily than the humor of the joke seemed quite to call for and glanced a grim look from the corners of his eyes on lake but the gallant captain did not seem to perceive it and after a few seconds more he handed it very innocently back to mrs dorothy only remarking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0013.flac", "answer": "DO YOU KNOW LAKE OH I REALLY CAN'T TELL BUT HE'LL SOON TIRE OF COUNTRY LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "do you know lake oh i really can t tell but he ll soon tire of country life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0003.flac", "answer": "THEY ARE COUSINS YOU KNOW WE ARE ALL COUSINS", "subset": "test_clean", "task_type": "understanding", "prediction": "they are cousins you know we are all cousins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0004.flac", "answer": "WHATEVER LORD CHELFORD SAID MISS BRANDON RECEIVED IT VERY GRACIOUSLY AND EVEN WITH A MOMENTARY SMILE", "subset": "test_clean", "task_type": "understanding", "prediction": "whatever lord chelford said miss brandon received it very graciously and even with a momentary smile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0000.flac", "answer": "YOU KNOW CAPTAIN LAKE", "subset": "test_clean", "task_type": "understanding", "prediction": "you know captain lake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32865/5683-32865-0009.flac", "answer": "AND HE PLACED IT IN THAT GENTLEMAN'S FINGERS WHO NOW TOOK HIS TURN AT THE LAMP AND CONTEMPLATED THE LITTLE PARALLELOGRAM WITH A GLEAM OF SLY AMUSEMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "and he placed it in that gentleman s fingers who now took his turn at the lamp and contemplated the little parallelogram with a gleam of sly amusement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0018.flac", "answer": "IT IS AN ANTIPATHY AN ANTIPATHY I CANNOT GET OVER DEAR DORCAS YOU MAY THINK IT A MADNESS BUT DON'T BLAME ME", "subset": "test_clean", "task_type": "understanding", "prediction": "it is an antipathy an antipathy i cannot get over dear dorcas you may think it a madness but dont blame me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0005.flac", "answer": "THIS TRANSIENT SPRING AND LIGHTING UP ARE BEAUTIFUL A GLAMOUR BEGUILING OUR SENSES", "subset": "test_clean", "task_type": "understanding", "prediction": "this transient spring and lighting up are beautiful a glamour beguiling our senses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0009.flac", "answer": "ILL AND TROUBLED DEAR TROUBLED IN MIND AND MISERABLY NERVOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "ill and troubled dear troubled in mind and miserably nervous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0012.flac", "answer": "THANK YOU RACHEL MY COUSIN RACHEL MY ONLY FRIEND", "subset": "test_clean", "task_type": "understanding", "prediction": "think you rachel my cousin rachel my only friend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0015.flac", "answer": "YES SAID RACHEL", "subset": "test_clean", "task_type": "understanding", "prediction": "yes said rachel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0016.flac", "answer": "AND THE WAN ORACLE HAVING SPOKEN SHE SATE DOWN IN THE SAME SORT OF ABSTRACTION AGAIN BESIDE DORCAS AND SHE LOOKED FULL IN HER COUSIN'S EYES", "subset": "test_clean", "task_type": "understanding", "prediction": "and the wan oracle having spoken she sat down in the same sort of abstraction again beside dorcas and she looked full in her cousin s eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0021.flac", "answer": "DORCAS IN HER STRANGE WAY WAS MOVED", "subset": "test_clean", "task_type": "understanding", "prediction": "dorcas in her strange way was moved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0010.flac", "answer": "POOR RACHEL HER NATURE RECOILED FROM DECEIT AND SHE TOLD AT ALL EVENTS AS MUCH OF THE TRUTH AS SHE DARED", "subset": "test_clean", "task_type": "understanding", "prediction": "poor rachel her nature recoiled from deceit and she told at all events as much of the truth as she dared", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0006.flac", "answer": "THERE WAS SOMETHING OF SWEETNESS AND FONDNESS IN HER TONES AND MANNER WHICH WAS NEW TO RACHEL AND COMFORTING AND SHE RETURNED THE GREETING AS KINDLY AND FELT MORE LIKE HER FORMER SELF", "subset": "test_clean", "task_type": "understanding", "prediction": "there was something of sweetness and fondness in her tones and manner which was new to rachel and comforting and she returned the greeting as kindly and felt more like her former self", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0001.flac", "answer": "WELL SHE WAS BETTER THOUGH SHE HAD HAD A BAD NIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "well she was better though she had had a bad night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0022.flac", "answer": "I LIKE YOU STILL RACHEL I'M SURE I'LL ALWAYS LIKE YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "i like you still rachel i am sure i will always like you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0019.flac", "answer": "I HAVE VERY FEW TO LOVE ME NOW AND I THOUGHT YOU MIGHT LOVE ME AS I HAVE BEGUN TO LOVE YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "i have very few to love me now and i thought you might love me as i have begun to love you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0004.flac", "answer": "BUT POOR RACHEL LAKE HAD MORE THAN THAT STOICAL HYPOCRISY WHICH ENABLES THE TORTURED SPIRITS OF HER SEX TO LIFT A PALE FACE THROUGH THE FLAMES AND SMILE", "subset": "test_clean", "task_type": "understanding", "prediction": "but poor rachel lake had more than that stoical hypocrisy which enables the tortured spirits of her sex to lift a pale face through the flames and smile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0007.flac", "answer": "RACHEL'S PALE AND SHARPENED FEATURES AND DILATED EYE STRUCK HER WITH A PAINFUL SURPRISE", "subset": "test_clean", "task_type": "understanding", "prediction": "rachels pale and sharpened features and dilated eye struck her with a painful surprise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0000.flac", "answer": "IT WAS NOT VERY MUCH PAST ELEVEN THAT MORNING WHEN THE PONY CARRIAGE FROM BRANDON DREW UP BEFORE THE LITTLE GARDEN WICKET OF REDMAN'S FARM", "subset": "test_clean", "task_type": "understanding", "prediction": "it was not very much past eleven that morning when the pony carriage from brandon drew up before the little garden wicket of redmond s farm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0023.flac", "answer": "YOU RESEMBLE ME RACHEL YOU ARE FEARLESS AND INFLEXIBLE AND GENEROUS", "subset": "test_clean", "task_type": "understanding", "prediction": "you resemble me rachel you are fearless and inflexible and generous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0020.flac", "answer": "AND SHE THREW HER ARMS ROUND HER COUSIN'S NECK AND BRAVE RACHEL AT LAST BURST INTO TEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "and she threw her arms round her cousin s neck and brave rachel at last burst into tears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0017.flac", "answer": "OF MARK WYLDER I SAY THIS HIS NAME HAS BEEN FOR YEARS HATEFUL TO ME AND RECENTLY IT HAS BECOME FRIGHTFUL AND YOU WILL PROMISE ME SIMPLY THIS THAT YOU WILL NEVER ASK ME TO SPEAK AGAIN ABOUT HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "of mark wylder i say this his name has been for years hateful to me and recently it has become frightful and you will promise me simply this that you will never ask me to speak again about him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0013.flac", "answer": "CHELFORD HAD A NOTE FROM MISTER WYLDER THIS MORNING ANOTHER NOTE HIS COMING DELAYED AND SOMETHING OF HIS HAVING TO SEE SOME PERSON WHO IS ABROAD CONTINUED DORCAS AFTER A LITTLE PAUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "chelford had a note from mr wylder this morning another note his coming delayed and something of his having to see some person who was abroad continued dorcas after a little pause", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0002.flac", "answer": "SO THERE CAME A STEP AND A LITTLE RUSTLING OF FEMININE DRAPERIES THE SMALL DOOR OPENED AND RACHEL ENTERED WITH HER HAND EXTENDED AND A PALE SMILE OF WELCOME", "subset": "test_clean", "task_type": "understanding", "prediction": "so there came a step and a little rustling of feminine draperies the small door opened and rachel entered with her hand extended and a pale smile of welcome", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0003.flac", "answer": "WOMEN CAN HIDE THEIR PAIN BETTER THAN WE MEN AND BEAR IT BETTER TOO EXCEPT WHEN SHAME DROPS FIRE INTO THE DREADFUL CHALICE", "subset": "test_clean", "task_type": "understanding", "prediction": "women can hide their pain better than we men and bear it better too except when shame drops fire into the dreadful chalice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0008.flac", "answer": "YOU HAVE BEEN SO ILL MY POOR RACHEL", "subset": "test_clean", "task_type": "understanding", "prediction": "you have been so ill my poor rachel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0024.flac", "answer": "YES RACHEL I DO LOVE YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "yes rachel i do love you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0014.flac", "answer": "YES SOMETHING EVERYTHING SAID RACHEL HURRIEDLY LOOKING FROWNINGLY AT A FLOWER WHICH SHE WAS TWIRLING IN HER FINGERS", "subset": "test_clean", "task_type": "understanding", "prediction": "yes something everything said rachel hurriedly looking frowningly at a flower which she was twirling in her fingers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0025.flac", "answer": "THANK YOU DORCAS DEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "thank you dorcas dear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32879/5683-32879-0011.flac", "answer": "SHE SPOKE WITH A SUDDEN ENERGY WHICH PARTOOK OF FEAR AND PASSION AND FLUSHED HER THIN CHEEK AND MADE HER LANGUID EYES FLASH", "subset": "test_clean", "task_type": "understanding", "prediction": "she spoke with a sudden energy which partook of fear and passion and flushed her thin cheek and made her languid eyes flash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0010.flac", "answer": "WELL YOU KNOW RADIE WOMEN LIKE WICKED FELLOWS IT IS CONTRAST I SUPPOSE BUT THEY DO AND I'M SURE FROM WHAT BRACTON HAS SAID TO ME I KNOW HIM INTIMATELY THAT DORCAS LIKES HIM AND I CAN'T CONCEIVE WHY THEY ARE NOT MARRIED", "subset": "test_clean", "task_type": "understanding", "prediction": "well you know rady women like wicked fellows it is contrast i suppose but they do and i am sure from what brackton has said to me i know him intimately that dorcas likes him and i can t conceive why they are not married", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0027.flac", "answer": "A COLD BRIGHT MOON WAS SHINING WITH CLEAR SHARP LIGHTS AND SHADOWS", "subset": "test_clean", "task_type": "understanding", "prediction": "a cold bright moon was shining with clear sharp lights and shadows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0003.flac", "answer": "IN THE MEANTIME I HAD FORMED A NEW IDEA OF HER", "subset": "test_clean", "task_type": "understanding", "prediction": "in the meantime i had formed a new idea of her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0023.flac", "answer": "ALL THE FURNITURE BELONGED TO OTHER TIMES", "subset": "test_clean", "task_type": "understanding", "prediction": "all the furniture belonged to other times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0017.flac", "answer": "I AM VERY UNEASY ABOUT IT WHATEVER IT IS I CAN'T HELP IT", "subset": "test_clean", "task_type": "understanding", "prediction": "i am very uneasy about it whatever it is i can help it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0029.flac", "answer": "SOMEHOW I HAD GROWN NERVOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "somehow i had grown nervous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0004.flac", "answer": "BY THIS TIME LORD CHELFORD AND WYLDER RETURNED AND DISGUSTED RATHER WITH MYSELF I RUMINATED ON MY WANT OF GENERAL SHIP", "subset": "test_clean", "task_type": "understanding", "prediction": "by this time lord chelford and wilder returned and disgusted rather with myself i ruminated on my want of generalship", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0009.flac", "answer": "I DON'T KNOW AND CAN'T SAY HOW YOU FINE GENTLEMEN DEFINE WICKEDNESS ONLY AS AN OBSCURE FEMALE I SPEAK ACCORDING TO MY LIGHTS AND HE IS GENERALLY THOUGHT THE WICKEDEST MAN IN THIS COUNTY", "subset": "test_clean", "task_type": "understanding", "prediction": "i don know and can t say how you fine gentlemen define wickedness only as an obscure female i speak according to my lights and he is generally thought the wickedest man in this county", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0030.flac", "answer": "A LITTLE BIT OF PLASTER TUMBLED DOWN THE CHIMNEY AND STARTLED ME CONFOUNDEDLY", "subset": "test_clean", "task_type": "understanding", "prediction": "a little bit of plaster tumbled down the chimney and startled me confoundedly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0008.flac", "answer": "BRACTON'S A VERY GOOD FELLOW I CAN ASSURE YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "brackton is a very good fellow i can assure you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0025.flac", "answer": "I DID NOT EVEN TAKE THE PRECAUTION OF SMOKING UP THE CHIMNEY", "subset": "test_clean", "task_type": "understanding", "prediction": "i did not even take the precaution of smoking up the chimney", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0012.flac", "answer": "NOW THAT'S IMPOSSIBLE RADIE FOR I REALLY DON'T THINK I ONCE THOUGHT OF HIM ALL THIS EVENING EXCEPT JUST WHILE WE WERE TALKING", "subset": "test_clean", "task_type": "understanding", "prediction": "now that is impossible rady for i really don think i once thought of him all this evening except just while we were talking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0028.flac", "answer": "THE SOMBRE OLD TREES LIKE GIGANTIC HEARSE PLUMES BLACK AND AWFUL", "subset": "test_clean", "task_type": "understanding", "prediction": "the sombre old trees like gigantic hearse plumes black and awful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0016.flac", "answer": "MARK MY WORDS YOU'LL FIND HIM TOO STRONG FOR YOU AYE AND TOO DEEP", "subset": "test_clean", "task_type": "understanding", "prediction": "mark my words you will find him too strong for you ay and too deep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0013.flac", "answer": "THERE WAS A BRIGHT MOONLIGHT BROKEN BY THE SHADOWS OF OVERHANGING BOUGHS AND WITHERED LEAVES AND THE MOTTLED LIGHTS AND SHADOWS GLIDED ODDLY ACROSS HIS PALE FEATURES", "subset": "test_clean", "task_type": "understanding", "prediction": "there was a bright moonlight broken by the shadows of overhanging boughs and withered leaves and the mottled lights and shadows glided oddly across his pale features", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0024.flac", "answer": "I SHAN'T TROUBLE YOU ABOUT MY TRAIN OF THOUGHTS OR FANCIES BUT I BEGAN TO FEEL VERY LIKE A GENTLEMAN IN A GHOST STORY WATCHING EXPERIMENTALLY IN A HAUNTED CHAMBER", "subset": "test_clean", "task_type": "understanding", "prediction": "i shan t trouble you about my train of thoughts or fancies but i began to feel very like a gentleman in a ghost story watching experimentally in a haunted chamber", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0011.flac", "answer": "THEIR WALK CONTINUED SILENT FOR THE GREATER PART NEITHER WAS QUITE SATISFIED WITH THE OTHER BUT RACHEL AT LAST SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "their walk continued silent for the greater part neither was quite satisfied with the other but rachel at last said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0022.flac", "answer": "ITS CURTAINS WERE OF THICK AND FADED TAPESTRY", "subset": "test_clean", "task_type": "understanding", "prediction": "its curtains were of thick and faded tapestry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0002.flac", "answer": "BUT DON'T THESE VERY WISE THINGS SOMETIMES TURN OUT VERY FOOLISHLY", "subset": "test_clean", "task_type": "understanding", "prediction": "but dont these very wise things sometimes turn out very foolishly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0000.flac", "answer": "MISS LAKE DECLINED THE CARRIAGE TO NIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "miss lake declined the carriage to night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0026.flac", "answer": "I BOLDLY LIGHTED MY CHEROOT", "subset": "test_clean", "task_type": "understanding", "prediction": "i boldly lighted my cheroot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0007.flac", "answer": "IF A FELLOW'S BEEN A LITTLE BIT WILD HE'S BEELZEBUB AT ONCE", "subset": "test_clean", "task_type": "understanding", "prediction": "if a fellow has been a little bit wild he is beelzebub at once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0006.flac", "answer": "YES SO THEY SAID BUT THAT WOULD I THINK HAVE BEEN WORSE", "subset": "test_clean", "task_type": "understanding", "prediction": "yes so they said but that would i think have been worse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0019.flac", "answer": "THE MYSTERY OF THEIR ORIGIN THEIR CAPACITY FOR EVOLVING LATENT FACULTIES OF CRIME AND THE STEADY VITALITY WITH WHICH THEY SURVIVE THE HEARSE AND SPEAK THEIR DEEP MOUTHED MALIGNITIES IN EVERY NEW BORN GENERATION HAVE ASSOCIATED THEM SOMEHOW IN MY MIND WITH A SPELL OF LIFE EXCEEDING AND DISTINCT FROM HUMAN AND A SPECIAL SATANIC ACTION", "subset": "test_clean", "task_type": "understanding", "prediction": "the mystery of their origin their capacity for evolving latent faculties of crime and the steady vitality with which they survive the hearse and speak their deep mouthed malignities in every new born generation have associated them somehow in my mind with a spell of life exceeding and distinct from human and especial satanic action", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0021.flac", "answer": "MY BED WAS UNEXCEPTIONABLY COMFORTABLE BUT IN MY THEN MOOD I COULD HAVE WISHED IT A GREAT DEAL MORE MODERN", "subset": "test_clean", "task_type": "understanding", "prediction": "my bed was unexceptionably comfortable but in my then mood i could have wished it a great deal more modern", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0018.flac", "answer": "TO MY MIND THERE HAS ALWAYS BEEN SOMETHING INEXPRESSIBLY AWFUL IN FAMILY FEUDS", "subset": "test_clean", "task_type": "understanding", "prediction": "to my mind there has always been something inexpressibly awful in family feuds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0014.flac", "answer": "DON'T INSULT ME STANLEY BY TALKING AGAIN AS YOU DID THIS MORNING", "subset": "test_clean", "task_type": "understanding", "prediction": "dont insult me stanley by talking again as you did this morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0001.flac", "answer": "AND HE ADDED SOMETHING STILL LESS COMPLIMENTARY", "subset": "test_clean", "task_type": "understanding", "prediction": "and he added something still less complimentary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0005.flac", "answer": "AND HE MADE A LITTLE DIP OF HIS CANE TOWARDS BRANDON HALL OVER HIS SHOULDER", "subset": "test_clean", "task_type": "understanding", "prediction": "and he made a little dip of his cane towards brandon hall over his shoulder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0020.flac", "answer": "THE FLOOR MORE THAN ANYTHING ELSE SHOWED THE GREAT AGE OF THE ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "the floor more than anything else showed the great age of the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5683/32866/5683-32866-0015.flac", "answer": "WHAT I SAY IS ALTOGETHER ON YOUR OWN ACCOUNT", "subset": "test_clean", "task_type": "understanding", "prediction": "what i say is altogether on your own account", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0015.flac", "answer": "THUS IT IS THAT THE HONOR OF THREE IS SAVED OUR COUNTRY'S OUR MASTER'S AND OUR OWN", "subset": "test_clean", "task_type": "understanding", "prediction": "thus it is that the honour of three is saved our country our masters and our own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0010.flac", "answer": "I CAN PERCEIVE LOVE CLEARLY ENOUGH", "subset": "test_clean", "task_type": "understanding", "prediction": "i can perceive love clearly enough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0018.flac", "answer": "THE NIGHT WAS CLEAR STARLIT AND SPLENDID THE TEMPEST HAD PASSED AWAY AND THE SWEET INFLUENCES OF THE EVENING HAD RESTORED LIFE PEACE AND SECURITY EVERYWHERE", "subset": "test_clean", "task_type": "understanding", "prediction": "the night was clear starlit and splendid the tempest had passed away and the sweet influences of the evening had restored life peace and security everywhere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0008.flac", "answer": "CAN YOU IMAGINE WHY BUCKINGHAM HAS BEEN SO VIOLENT I SUSPECT", "subset": "test_clean", "task_type": "understanding", "prediction": "can you imagine why buckingham has been so violent i suspect", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0013.flac", "answer": "IN THOSE VERY TERMS I EVEN ADDED MORE", "subset": "test_clean", "task_type": "understanding", "prediction": "in those very terms i even added more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0019.flac", "answer": "UPON THE LARGE SQUARE IN FRONT OF THE HOTEL THE SHADOWS OF THE TENTS INTERSECTED BY THE GOLDEN MOONBEAMS FORMED AS IT WERE A HUGE MOSAIC OF JET AND YELLOW FLAGSTONES", "subset": "test_clean", "task_type": "understanding", "prediction": "upon the large square in front of the hotel the shadows of the tents intersected by the golden moonbeams formed as it were a huge mosaic of jet and yellow flagstones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0009.flac", "answer": "IT IS YOU WHO ARE MISTAKEN RAOUL I HAVE READ HIS DISTRESS IN HIS EYES IN HIS EVERY GESTURE AND ACTION THE WHOLE DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "it is you who are mistaken raoul i have read his distress in his eyes in his every gesture and action the whole day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0020.flac", "answer": "BRAGELONNE WATCHED FOR SOME TIME THE CONDUCT OF THE TWO LOVERS LISTENED TO THE LOUD AND UNCIVIL SLUMBERS OF MANICAMP WHO SNORED AS IMPERIOUSLY AS THOUGH HE WAS WEARING HIS BLUE AND GOLD INSTEAD OF HIS VIOLET SUIT", "subset": "test_clean", "task_type": "understanding", "prediction": "bragelonne watched for some time the conduct of the two lovers listened to the loud and uncivil slumbers of manicamp who snored as imperiously as though he was wearing his blue and gold instead of his violet suit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0000.flac", "answer": "CONCORD RETURNED TO ITS PLACE AMIDST THE TENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "concord returned to its place amidst the tents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0007.flac", "answer": "YOU WILL BE FRANK WITH ME I ALWAYS AM", "subset": "test_clean", "task_type": "understanding", "prediction": "you will be frank with me i always am", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0006.flac", "answer": "THIS HAS INDEED BEEN A HARASSING DAY CONTINUED THE YOUNG MAN HIS EYES FIXED UPON HIS FRIEND", "subset": "test_clean", "task_type": "understanding", "prediction": "this has indeed been a harassing day continued the young man his eyes fixed upon his friend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0005.flac", "answer": "THE COUNT HAD THROWN HIMSELF BACK ON HIS SEAT LEANING HIS SHOULDERS AGAINST THE PARTITION OF THE TENT AND REMAINED THUS HIS FACE BURIED IN HIS HANDS WITH HEAVING CHEST AND RESTLESS LIMBS", "subset": "test_clean", "task_type": "understanding", "prediction": "the count had thrown himself back on his seat leaning his shoulders against the partition of the tent and remained thus his face buried in his hands with heaving chest and restless limbs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0004.flac", "answer": "SHE TAUGHT HER DAUGHTER THEN BY HER OWN AFFECTION FOR IT THAT LOVE FOR A COUNTRY WHERE THEY HAD BOTH BEEN HOSPITABLY RECEIVED AND WHERE A BRILLIANT FUTURE OPENED BEFORE THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "she taught her daughter then by her own affection for it that love for a country where they had both been hospitably received and where a brilliant future opened for them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0002.flac", "answer": "CONGRATULATIONS WERE POURED IN UPON THE PRINCESS EVERYWHERE DURING HER JOURNEY", "subset": "test_clean", "task_type": "understanding", "prediction": "congratulations were poured in upon the princess everywhere during her journey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0011.flac", "answer": "I AM CONVINCED OF WHAT I SAY SAID THE COUNT", "subset": "test_clean", "task_type": "understanding", "prediction": "i am convinced of what i say said the count", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0003.flac", "answer": "FROM THE RESPECT PAID HER ON ALL SIDES SHE SEEMED LIKE A QUEEN AND FROM THE ADORATION WITH WHICH SHE WAS TREATED BY TWO OR THREE SHE APPEARED AN OBJECT OF WORSHIP THE QUEEN MOTHER GAVE THE FRENCH THE MOST AFFECTIONATE RECEPTION FRANCE WAS HER NATIVE COUNTRY AND SHE HAD SUFFERED TOO MUCH UNHAPPINESS IN ENGLAND FOR ENGLAND TO HAVE MADE HER FORGET FRANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "from the respect paid her on all sides she seemed like a queen and from the adoration with which she was treated by two or three she appeared an object of worship the queen mother gave the french the most affectionate reception france was her native country and she had suffered too much unhappiness in england for england to have made her forget france", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0001.flac", "answer": "THE ENGLISH FORWARDED TO THE FRENCH BASKETS OF FLOWERS OF WHICH THEY HAD MADE A PLENTIFUL PROVISION TO GREET THE ARRIVAL OF THE YOUNG PRINCESS THE FRENCH IN RETURN INVITED THE ENGLISH TO A SUPPER WHICH WAS TO BE GIVEN THE NEXT DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "the english forwarded to the french baskets of flowers of which they had made a plentiful provision to greet the arrival of the young princess the french in return invited the english to a supper which was to be given the next day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0017.flac", "answer": "BUT IN THIS FRIENDLY PRESSURE RAOUL COULD DETECT THE NERVOUS AGITATION OF A GREAT INTERNAL CONFLICT", "subset": "test_clean", "task_type": "understanding", "prediction": "but in this friendly pressure rao could detect the nervous agitation of a great internal conflict", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0016.flac", "answer": "YES I NEED REPOSE MANY THINGS HAVE AGITATED ME TO DAY BOTH IN MIND AND BODY WHEN YOU RETURN TO MORROW I SHALL NO LONGER BE THE SAME MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "yes i need repose many things have agitated me to day both in mind and body when you return to morrow i shall no longer be the same man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0014.flac", "answer": "BUT CONTINUED RAOUL NOT INTERRUPTED BY THIS MOVEMENT OF HIS FRIEND HEAVEN BE PRAISED THE FRENCH WHO ARE PRONOUNCED TO BE THOUGHTLESS AND INDISCREET RECKLESS EVEN ARE CAPABLE OF BRINGING A CALM AND SOUND JUDGMENT TO BEAR ON MATTERS OF SUCH HIGH IMPORTANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "but continued raoul not interrupted by this movement of his friend heaven be praised the french who are pronounced to be thoughtless and indiscreet reckless even are capable of bringing a calm and sound judgment to bear on matters of such high importance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/75918/6930-75918-0012.flac", "answer": "IT IS ANNOYANCE THEN", "subset": "test_clean", "task_type": "understanding", "prediction": "it is annoyance then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0021.flac", "answer": "A TERRIBLE THOUGHT FLASHED INTO MY MIND", "subset": "test_clean", "task_type": "understanding", "prediction": "a terrible thought flashed into my mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0001.flac", "answer": "I HEARD A NOISE BEHIND I TURNED AND SAW KAFFAR HIS BLACK EYES SHINING WHILE IN HIS HAND HE HELD A GLEAMING KNIFE HE LIFTED IT ABOVE HIS HEAD AS IF TO STRIKE BUT I HAD THE STRENGTH OF TEN MEN AND I HURLED HIM FROM ME", "subset": "test_clean", "task_type": "understanding", "prediction": "i heard a noise behind i turned and saw kaffir his black eyes shining while in his hand he held a gleaming knife he lifted it above his head as if to strike but i had the strength of ten men and i hurled him from me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0002.flac", "answer": "ONWARD SAID A DISTANT VOICE", "subset": "test_clean", "task_type": "understanding", "prediction": "onward said a distant voice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0000.flac", "answer": "NO WORDS WERE SPOKEN NO LANGUAGE WAS UTTERED SAVE THAT OF WAILING AND HISSING AND THAT SOMEHOW WAS INDISTINCT AS IF IT EXISTED IN FANCY AND NOT IN REALITY", "subset": "test_clean", "task_type": "understanding", "prediction": "no words were spoken no language was uttered save that of wailing and hissing and that somehow was indistinct as if it existed in fancy and not in reality", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0023.flac", "answer": "PERCHANCE TOO KAFFAR'S DEATH MIGHT SERVE HIM IN GOOD STEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "perchance too kaffir s death might serve him in good stead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0003.flac", "answer": "NO SOUND BROKE THE STILLNESS OF THE NIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "no sound broke the stillness of the night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0011.flac", "answer": "A FEELING OF FREEDOM AND I WAS AWAKE WHERE", "subset": "test_clean", "task_type": "understanding", "prediction": "a feeling of freedom and i was awake where", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0016.flac", "answer": "BUT THAT IS KAFFAR'S KNIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "but that is kaffir s knife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0024.flac", "answer": "MY TONGUE REFUSED TO ARTICULATE MY POWER OF SPEECH LEFT ME", "subset": "test_clean", "task_type": "understanding", "prediction": "my tongue refused to articulate my power of speech left me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0014.flac", "answer": "IN THE LIGHT OF THE MOON I SAW A KNIFE RED WITH BLOOD AND MY HAND TOO WAS ALSO DISCOLOURED", "subset": "test_clean", "task_type": "understanding", "prediction": "in the light of the moon i saw a knife red with blood and my hand too was also discolored", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0027.flac", "answer": "FOR SOME TIME AFTER THAT I REMEMBERED NOTHING DISTINCTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "for some time after that i remembered nothing distinctly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0018.flac", "answer": "I REMEMBER SAYING HAVE WE BEEN TOGETHER", "subset": "test_clean", "task_type": "understanding", "prediction": "i remembered saying have we been together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0017.flac", "answer": "I KNOW HE HAD IT THIS VERY EVENING", "subset": "test_clean", "task_type": "understanding", "prediction": "i know he had it this very evening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0007.flac", "answer": "NOTHING MORE NOT EVEN THE WRIST TO WHICH IT MIGHT BE ATTACHED", "subset": "test_clean", "task_type": "understanding", "prediction": "nothing more not even the wrist to which it might be attached", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0005.flac", "answer": "WHAT WAS THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "what was that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0020.flac", "answer": "I SAY YOU DO KNOW WHAT THIS MEANS AND YOU MUST TELL US", "subset": "test_clean", "task_type": "understanding", "prediction": "i say you do know what this means and you must tell us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0004.flac", "answer": "THE STORY OF ITS EVIL INFLUENCE CAME BACK TO ME AND IN MY BEWILDERED CONDITION I WONDERED WHETHER THERE WAS NOT SOME TRUTH IN WHAT HAD BEEN SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "the story of its evil influence came back to me and in my bewildered condition i wondered whether there was not some truth in what had been said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0022.flac", "answer": "I HAD AGAIN BEEN ACTING UNDER THE INFLUENCE OF THIS MAN'S POWER", "subset": "test_clean", "task_type": "understanding", "prediction": "i had again been acting under the influence of this man s power", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0019.flac", "answer": "VOLTAIRE PICKED UP SOMETHING FROM THE GROUND AND LOOKED AT IT", "subset": "test_clean", "task_type": "understanding", "prediction": "voltaire picked up something from the ground and looked at it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0008.flac", "answer": "IT DID NOT BECKON OR INDEED MOVE AT ALL IT WAS AS STILL AS THE HAND OF DEATH", "subset": "test_clean", "task_type": "understanding", "prediction": "it did not beckon or indeed move at all it was as still as the hand of death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0009.flac", "answer": "I AWOKE TO CONSCIOUSNESS FIGHTING AT FIRST IT SEEMED AS IF I WAS FIGHTING WITH A PHANTOM BUT GRADUALLY MY OPPONENT BECAME MORE REAL TO ME IT WAS KAFFAR", "subset": "test_clean", "task_type": "understanding", "prediction": "i awoke to consciousness fighting at first it seemed as if i was fighting with a phantom but gradually my opponent became more real to me it was kaffir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0012.flac", "answer": "SAID ANOTHER VOICE WHICH I RECOGNIZED AS VOLTAIRE'S KAFFAR", "subset": "test_clean", "task_type": "understanding", "prediction": "said another voice which i recognized as voltaire s caffer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0010.flac", "answer": "A SOUND OF VOICES A FLASH OF LIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "a sound of voices a flash of light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0026.flac", "answer": "MY OVERWROUGHT NERVES YIELDED AT LAST", "subset": "test_clean", "task_type": "understanding", "prediction": "my overwrought nerves yielded at last", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0013.flac", "answer": "I HAD SCARCELY KNOWN WHAT I HAD BEEN SAYING OR DOING UP TO THIS TIME BUT AS HE SPOKE I LOOKED AT MY HAND", "subset": "test_clean", "task_type": "understanding", "prediction": "i had scarcely known what i had been saying or doing up to this time but as he spoke i looked at my hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0025.flac", "answer": "MY POSITION WAS TOO TERRIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "my position was too terrible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0006.flac", "answer": "WHAT THEN A HUMAN HAND LARGE AND SHAPELY APPEARED DISTINCTLY ON THE SURFACE OF THE POND", "subset": "test_clean", "task_type": "understanding", "prediction": "what then a human hand large and shapely appeared distinctly on the surface of the pond", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/81414/6930-81414-0015.flac", "answer": "I DO NOT KNOW I AM DAZED BEWILDERED", "subset": "test_clean", "task_type": "understanding", "prediction": "i do not know i am dazed bewildered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0015.flac", "answer": "SMUGGLING THE HOUSE CLEANING PARAPHERNALIA INTO THE CELLAR WINDOW UNOBSERVED THAT AFTERNOON PROVED NO EASY TASK FOR CYNTHIA HAD ADDED A WHISK BROOM AND DUST PAN TO THE OUTFIT", "subset": "test_clean", "task_type": "understanding", "prediction": "smuggling the house cleaning paraphernalia into the cellar window unobserved that afternoon proved no easy task for cynthia had added a whisk broom and dust pan to the outfit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0003.flac", "answer": "NOW WHAT WAS THE SENSE OF IT TWO INNOCENT BABIES LIKE THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "now what is the sense of it two innocent babies like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0011.flac", "answer": "THEY WORRY ME TERRIBLY AND BESIDES I'D LIKE TO SEE WHAT THIS LOVELY FURNITURE LOOKS LIKE WITHOUT SUCH QUANTITIES OF DUST ALL OVER IT GOOD SCHEME CYN", "subset": "test_clean", "task_type": "understanding", "prediction": "they worry me terribly and besides i d like to see what this lovely furniture looks like without such quantities of dust all over it good scheme sim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0001.flac", "answer": "THEY WERE CERTAINLY NO NEARER THE SOLUTION OF THEIR PROBLEM", "subset": "test_clean", "task_type": "understanding", "prediction": "there were certainly no near the solution of their problem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0014.flac", "answer": "THIS THOUGHT HOWEVER DID NOT ENTER THE HEADS OF THE ENTHUSIASTIC PAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "this thought however did not enter the heads of the enthusiastic pair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0019.flac", "answer": "NOW LET'S DUST THE FURNITURE AND PICTURES", "subset": "test_clean", "task_type": "understanding", "prediction": "now lets dust the furniture and pictures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0009.flac", "answer": "DO YOU SUPPOSE THE MINIATURE WAS A COPY OF THE SAME THING", "subset": "test_clean", "task_type": "understanding", "prediction": "do you suppose the miniature was a copy of the same thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0008.flac", "answer": "I THOUGHT WE WERE STUMPED AGAIN WHEN I FIRST SAW THAT PICTURE BUT IT'S BEEN OF SOME USE AFTER ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "i thought we were stumped again when i first saw that picture but it has been of some use after all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0010.flac", "answer": "WHAT IN THE WORLD IS THAT QUERIED JOYCE", "subset": "test_clean", "task_type": "understanding", "prediction": "what in the world is it queried joyce", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0006.flac", "answer": "HERS HAPPENED TO BE IN THE SAME FRAME TOO BUT SHE EVIDENTLY DIDN'T CARE ABOUT THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "hers happened to be on the same frame too but she evidently did n t care about it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0026.flac", "answer": "ISN'T HE THE GREATEST FOR GETTING INTO ODD CORNERS", "subset": "test_clean", "task_type": "understanding", "prediction": "isn t he the greatest for getting into odd corners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0024.flac", "answer": "THEY SAY ILLUMINATION BY CANDLE LIGHT IS THE PRETTIEST IN THE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "they say illumination by candlelight is the prettiest in the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0007.flac", "answer": "NOW WHAT HAVE YOU TO SAY CYNTHIA SPRAGUE", "subset": "test_clean", "task_type": "understanding", "prediction": "now what have you to say cynthia sprague", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0013.flac", "answer": "IT CAN'T HURT ANYTHING I'M SURE FOR WE WON'T DISTURB THINGS AT ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "it can t hurt anything i m sure for we won t disturb things at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0012.flac", "answer": "WE'LL COME IN HERE THIS AFTERNOON WITH OLD CLOTHES ON AND HAVE A REGULAR HOUSE CLEANING", "subset": "test_clean", "task_type": "understanding", "prediction": "well come in here this afternoon with old clothes on and have a regular house cleaning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0005.flac", "answer": "THE TWIN BROTHER DID SOMETHING SHE DIDN'T LIKE AND SHE TURNED HIS PICTURE TO THE WALL", "subset": "test_clean", "task_type": "understanding", "prediction": "the twin brother did something she didn like and she turned his picture to the wall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0025.flac", "answer": "WHY IT'S GOLIATH AS USUAL THEY BOTH CRIED PEERING IN", "subset": "test_clean", "task_type": "understanding", "prediction": "why it is goliath as usual they both cried peering in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0028.flac", "answer": "WELL I'M CONVINCED THAT THE BOARDED UP HOUSE MYSTERY HAPPENED NOT EARLIER THAN APRIL SIXTEENTH EIGHTEEN SIXTY ONE AND PROBABLY NOT MUCH LATER", "subset": "test_clean", "task_type": "understanding", "prediction": "well i am convinced that the boarded up house mystery happened not earlier than april sixteenth eighteen sixty one and probably not much later", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0021.flac", "answer": "SURFACE DUST AT LEAST HAD BEEN REMOVED AND THE FINE OLD FURNITURE GAVE A HINT OF ITS REAL ELEGANCE AND POLISH", "subset": "test_clean", "task_type": "understanding", "prediction": "surface dust at least had been removed and the fine old furniture gave a hint of its real elegance and polish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0002.flac", "answer": "THE POOR LITTLE THINGS CRIED CYNTHIA THINK OF THEM HAVING BEEN TURNED TO THE WALL ALL THESE YEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "the poor little things cried cynthia think of them having been turned to the wall all these years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0022.flac", "answer": "THEN SHE SUDDENLY REMARKED", "subset": "test_clean", "task_type": "understanding", "prediction": "then she suddenly remarked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0000.flac", "answer": "GOLIATH MAKES ANOTHER DISCOVERY", "subset": "test_clean", "task_type": "understanding", "prediction": "goliath makes another discovery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0004.flac", "answer": "BUT JOYCE HAD NOT BEEN LISTENING ALL AT ONCE SHE PUT DOWN HER CANDLE ON THE TABLE AND FACED HER COMPANION", "subset": "test_clean", "task_type": "understanding", "prediction": "but joyce had not been listening all at once she put down her candle on the table and faced her companion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0023.flac", "answer": "AND MY POCKET MONEY IS GETTING LOW AGAIN AND YOU HAVEN'T ANY LEFT AS USUAL", "subset": "test_clean", "task_type": "understanding", "prediction": "and my pocket money is getting low again and you havent any left as usual", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0020.flac", "answer": "YET LITTLE AS IT WAS IT HAD ALREADY MADE A VAST DIFFERENCE IN THE ASPECT OF THE ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "yet little as it was it had already made a vast difference in the aspect of the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0018.flac", "answer": "HE MAKES IT SORT OF COZIER", "subset": "test_clean", "task_type": "understanding", "prediction": "he makes it sort of cosier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0016.flac", "answer": "THE LURE PROVED TOO MUCH FOR HIM AND HE CAME SPORTING AFTER IT AS FRISKILY AS A YOUNG KITTEN MUCH TO CYNTHIA'S DELIGHT WHEN SHE CAUGHT SIGHT OF HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "the lure proved too much for him and he came sporting after it as friskily as a young kitten much to cynthia s delight when she caught sight of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0017.flac", "answer": "OH LET HIM COME ALONG SHE URGED I DO LOVE TO SEE HIM ABOUT THAT OLD HOUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "oh let him come along she urged i do love to see him about that old house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6930/76324/6930-76324-0027.flac", "answer": "FORGETTING ALL THEIR WEARINESS THEY SEIZED THEIR CANDLES AND SCURRIED THROUGH THE HOUSE FINDING AN OCCASIONAL PAPER TUCKED AWAY IN SOME ODD CORNER", "subset": "test_clean", "task_type": "understanding", "prediction": "forgetting all their weariness they seized their candles and scurried through the house finding on occasional paper tucked away in some odd corner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0002.flac", "answer": "RODOLFO AND HIS COMPANIONS WITH THEIR FACES MUFFLED IN THEIR CLOAKS STARED RUDELY AND INSOLENTLY AT THE MOTHER THE DAUGHTER AND THE SERVANT MAID", "subset": "test_clean", "task_type": "understanding", "prediction": "rodolfo and his companions with their faces muffled in their cloaks stared rudely and insolently at the mother the daughter and the servant maid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0011.flac", "answer": "SHE FOUND THE DOOR BUT IT WAS LOCKED OUTSIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "she found the door but it was locked outside", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0038.flac", "answer": "JUST AT THE MOMENT WHEN THE TEARS OF THE PITYING BEHOLDERS FLOWED FASTEST AND THEIR EJACULATIONS WERE MOST EXPRESSIVE OF DESPAIR LEOCADIA GAVE SIGNS OF RECOVERY AND BROUGHT BACK GLADNESS TO THE HEARTS OF ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "just at the moment when the tears of the pitying beholders flowed fastest and their ejaculations were most expressive of despair leocadia gave signs of recovery and brought back gladness to the hearts of all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0014.flac", "answer": "AMONG OTHER THINGS ON WHICH SHE CAST HER EYES WAS A SMALL CRUCIFIX OF SOLID SILVER STANDING ON A CABINET NEAR THE WINDOW", "subset": "test_clean", "task_type": "understanding", "prediction": "among other things on which she cast her eyes was a small crucifix of solid silver standing on a cabinet near the window", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0009.flac", "answer": "MOTHER DEAR FATHER DO YOU HEAR ME", "subset": "test_clean", "task_type": "understanding", "prediction": "mother dear father do you hear me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0006.flac", "answer": "RODOLFO ARRIVED AT HIS OWN HOUSE WITHOUT ANY IMPEDIMENT AND LEOCADIA'S PARENTS REACHED THEIRS HEART BROKEN AND DESPAIRING", "subset": "test_clean", "task_type": "understanding", "prediction": "rodolpho arrived at his own house without any impediment and leocadia s parents reached theirs heart broken and despairing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0003.flac", "answer": "IN A MOMENT HE COMMUNICATED HIS THOUGHTS TO HIS COMPANIONS AND IN THE NEXT MOMENT THEY RESOLVED TO TURN BACK AND CARRY HER OFF TO PLEASE RODOLFO FOR THE RICH WHO ARE OPEN HANDED ALWAYS FIND PARASITES READY TO ENCOURAGE THEIR BAD PROPENSITIES AND THUS TO CONCEIVE THIS WICKED DESIGN TO COMMUNICATE IT APPROVE IT RESOLVE ON RAVISHING LEOCADIA AND TO CARRY THAT DESIGN INTO EFFECT WAS THE WORK OF A MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "in a moment he communicated his thoughts to his companions and in the next moment they resolved to turn back and carry her off to please rudolpho for the rich who are open handed always find parasites ready to encourage their bad propensities and thus to conceive this wicked design to communicate it approve it resolve on ravishing leocadia and to carry that design into effect was the work of a moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0004.flac", "answer": "THEY DREW THEIR SWORDS HID THEIR FACES IN THE FLAPS OF THEIR CLOAKS TURNED BACK AND SOON CAME IN FRONT OF THE LITTLE PARTY WHO HAD NOT YET DONE GIVING THANKS TO GOD FOR THEIR ESCAPE FROM THOSE AUDACIOUS MEN", "subset": "test_clean", "task_type": "understanding", "prediction": "they drew their swords hid their faces in the flaps of their cloaks turned back and soon came in front of the little party who had not yet done giving thanks to god for their escape from those audacious men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0024.flac", "answer": "ONE DAY WHEN THE BOY WAS SENT BY HIS GRANDFATHER WITH A MESSAGE TO A RELATION HE PASSED ALONG A STREET IN WHICH THERE WAS A GREAT CONCOURSE OF HORSEMEN", "subset": "test_clean", "task_type": "understanding", "prediction": "one day when the boy was sent by his grandfather with a message to a relation he passed along a street in which there was a great concourse of horsemen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0007.flac", "answer": "MEANWHILE RODOLFO HAD LEOCADIA SAFE IN HIS CUSTODY AND IN HIS OWN APARTMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "meanwhile rudolpho had leocadia safe in his custody and in his own apartment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0000.flac", "answer": "ELEVEN O'CLOCK HAD STRUCK IT WAS A FINE CLEAR NIGHT THEY WERE THE ONLY PERSONS ON THE ROAD AND THEY SAUNTERED LEISURELY ALONG TO AVOID PAYING THE PRICE OF FATIGUE FOR THE RECREATION PROVIDED FOR THE TOLEDANS IN THEIR VALLEY OR ON THE BANKS OF THEIR RIVER", "subset": "test_clean", "task_type": "understanding", "prediction": "eleven o clock had struck it was a fine clear night they were the only persons on the road and they sauntered leisurely along to avoid paying the price of fatigue for the recreation provided for the toledans in the valley or on the banks of their river", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0028.flac", "answer": "I HAVE GREAT THINGS TO TELL YOU SENOR SAID DONA ESTAFANIA TO HER HUSBAND THE CREAM AND SUBSTANCE OF WHICH IS THIS THE FAINTING GIRL BEFORE YOU IS YOUR DAUGHTER AND THAT BOY IS YOUR GRANDSON", "subset": "test_clean", "task_type": "understanding", "prediction": "i have great things to tell you senor said donna estafania to her husband the cream and substance of which is this the fainting girl before you is your daughter and the boy is your grandson", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0005.flac", "answer": "FINALLY THE ONE PARTY WENT OFF EXULTING AND THE OTHER WAS LEFT IN DESOLATION AND WOE", "subset": "test_clean", "task_type": "understanding", "prediction": "finally the one party went off exulting and the other was left in desolation and woe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0008.flac", "answer": "WHO TOUCHES ME AM I IN BED", "subset": "test_clean", "task_type": "understanding", "prediction": "who touches me am i in bed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0016.flac", "answer": "ON THE CONTRARY HE RESOLVED TO TELL THEM THAT REPENTING OF HIS VIOLENCE AND MOVED BY HER TEARS HE HAD ONLY CARRIED HER HALF WAY TOWARDS HIS HOUSE AND THEN LET HER GO", "subset": "test_clean", "task_type": "understanding", "prediction": "on the contrary he resolved to tell them that repenting of his violence and moved by her tears he had only carried her half way towards his house and then let her go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0040.flac", "answer": "THIS WAS DONE FOR THE EVENT TOOK PLACE AT A TIME WHEN THE CONSENT OF THE PARTIES WAS SUFFICIENT FOR THE CELEBRATION OF A MARRIAGE WITHOUT ANY OF THE PRELIMINARY FORMALITIES WHICH ARE NOW SO PROPERLY REQUIRED", "subset": "test_clean", "task_type": "understanding", "prediction": "this was done for the event took place at a time when the consent of the parties was sufficient for the celebration of a marriage without any of the preliminary formalities which are now so properly required", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0018.flac", "answer": "THAT WOULD BE VERY WELL MY CHILD REPLIED HER FATHER IF YOUR PLAN WERE NOT LIABLE TO BE FRUSTRATED BY ORDINARY CUNNING BUT NO DOUBT THIS IMAGE HAS BEEN ALREADY MISSED BY ITS OWNER AND HE WILL HAVE SET IT DOWN FOR CERTAIN THAT IT WAS TAKEN OUT OF THE ROOM BY THE PERSON HE LOCKED UP THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "that would be very well my child replied her father if your plan were not liable to be frustrated by ordinary cunning but no doubt this image had been already missed by its owner and he will have set it down for certain that it was taken out of the room by the person he locked up there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0032.flac", "answer": "FOR GOD'S SAKE MY LADY MOTHER GIVE ME A WIFE WHO WOULD BE AN AGREEABLE COMPANION NOT ONE WHO WILL DISGUST ME SO THAT WE MAY BOTH BEAR EVENLY AND WITH MUTUAL GOOD WILL THE YOKE IMPOSED ON US BY HEAVEN INSTEAD OF PULLING THIS WAY AND THAT WAY AND FRETTING EACH OTHER TO DEATH", "subset": "test_clean", "task_type": "understanding", "prediction": "for god sake my lady mother give me a wife who would be an agreeable companion not one who will disgust me so that we may both bear evenly and with mutual good will the yoke imposed on us by heaven instead of pulling this way and that way and fretting each other to death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0030.flac", "answer": "JUST THEN LEOCADIA CAME TO HERSELF AND EMBRACING THE CROSS SEEMED CHANGED INTO A SEA OF TEARS AND THE GENTLEMAN REMAINED IN UTTER BEWILDERMENT UNTIL HIS WIFE HAD REPEATED TO HIM FROM BEGINNING TO END LEOCADIA'S WHOLE STORY AND HE BELIEVED IT THROUGH THE BLESSED DISPENSATION OF HEAVEN WHICH HAD CONFIRMED IT BY SO MANY CONVINCING TESTIMONIES", "subset": "test_clean", "task_type": "understanding", "prediction": "just then leocadia came to herself and embracing the cross seemed changed into a sea of tears and the gentleman remaining in utter bewilderment until his wife had repeated to him from beginning to end leocadia s whole story and he believed it through the blessed dispensation of heaven which had confirmed it by so many convincing testimonies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0033.flac", "answer": "HER BEARING WAS GRACEFUL AND ANIMATED SHE LED HER SON BY THE HAND AND BEFORE HER WALKED TWO MAIDS WITH WAX LIGHTS AND SILVER CANDLESTICKS", "subset": "test_clean", "task_type": "understanding", "prediction": "her bearing was graceful and animated she led her son by the hand and before her walked two maids with wax lights in silver candlesticks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0023.flac", "answer": "WHEN THE BOY WALKED THROUGH THE STREETS BLESSINGS WERE SHOWERED UPON HIM BY ALL WHO SAW HIM BLESSINGS UPON HIS BEAUTY UPON THE MOTHER THAT BORE HIM UPON THE FATHER THAT BEGOT HIM UPON THOSE WHO BROUGHT HIM UP SO WELL", "subset": "test_clean", "task_type": "understanding", "prediction": "when the boy walked through the streets blessings were showered upon him by all who saw him blessing upon his beauty upon the mother that bore him upon the father that begot him upon those who brought him up so well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0001.flac", "answer": "SECURE AS HE THOUGHT IN THE CAREFUL ADMINISTRATION OF JUSTICE IN THAT CITY AND THE CHARACTER OF ITS WELL DISPOSED INHABITANTS THE GOOD HIDALGO WAS FAR FROM THINKING THAT ANY DISASTER COULD BEFAL HIS FAMILY", "subset": "test_clean", "task_type": "understanding", "prediction": "secure as he thought in the careful administration of justice in that city and the character of its well disposed inhabitants the good hidalgo was far from thinking that any disaster could befall his family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0034.flac", "answer": "ALL ROSE TO DO HER REVERENCE AS IF SOMETHING FROM HEAVEN HAD MIRACULOUSLY APPEARED BEFORE THEM BUT GAZING ON HER ENTRANCED WITH ADMIRATION NOT ONE OF THEM WAS ABLE TO ADDRESS A SINGLE WORD TO HER", "subset": "test_clean", "task_type": "understanding", "prediction": "all rose to do her reverence as if something from heaven had miraculously appeared before them but gazing on her entranced with admiration not one of them was able to address a single word to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0035.flac", "answer": "SHE REFLECTED HOW NEAR SHE STOOD TO THE CRISIS WHICH WAS TO DETERMINE WHETHER SHE WAS TO BE BLESSED OR UNHAPPY FOR EVER AND RACKED BY THE INTENSITY OF HER EMOTIONS SHE SUDDENLY CHANGED COLOUR HER HEAD DROPPED AND SHE FELL FORWARD IN A SWOON INTO THE ARMS OF THE DISMAYED ESTAFANIA", "subset": "test_clean", "task_type": "understanding", "prediction": "she reflected how near she stood to the crisis which was to determine whether she was to be blessed or unhappy for ever and racked by the intensity of her emotions she suddenly changed colour her head dropped and she fell forward in a swoon into the arms of the dismayed estephania", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0010.flac", "answer": "IT IS THE ONLY AMENDS I ASK OF YOU FOR THE WRONG YOU HAVE DONE ME", "subset": "test_clean", "task_type": "understanding", "prediction": "it is the only amends i ask of you for the wrong you have done me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0021.flac", "answer": "SHE MEANWHILE PASSED HER LIFE WITH HER PARENTS IN THE STRICTEST RETIREMENT NEVER LETTING HERSELF BE SEEN BUT SHUNNING EVERY EYE LEST IT SHOULD READ HER MISFORTUNE IN HER FACE", "subset": "test_clean", "task_type": "understanding", "prediction": "she meanwhile passed her life with her parents in the strictest retirement never letting herself be seen but shunning every eye lest it should read her misfortune in her face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0022.flac", "answer": "TIME ROLLED ON THE HOUR OF HER DELIVERY ARRIVED IT TOOK PLACE IN THE UTMOST SECRECY HER MOTHER TAKING UPON HER THE OFFICE OF MIDWIFE AND SHE GAVE BIRTH TO A SON ONE OF THE MOST BEAUTIFUL EVER SEEN", "subset": "test_clean", "task_type": "understanding", "prediction": "time rolled on the hour of her delivery arrived it took place in the utmost secrecy her mother taking upon her the office of midwife as she gave birth to a son one of the most beautiful ever seen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0013.flac", "answer": "SHE SAW THAT THE BED WAS GILDED AND SO RICH THAT IT SEEMED THAT OF A PRINCE RATHER THAN OF A PRIVATE GENTLEMAN", "subset": "test_clean", "task_type": "understanding", "prediction": "she saw that the bed was gilded and so rich that it seemed that of a prince rather than of a private gentleman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0012.flac", "answer": "SHE SUCCEEDED IN OPENING THE WINDOW AND THE MOONLIGHT SHONE IN SO BRIGHTLY THAT SHE COULD DISTINGUISH THE COLOUR OF SOME DAMASK HANGINGS IN THE ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "she succeeded in opening the window and the moonlight shone in so brightly that she could distinguish the colour of some damask hanging in the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0019.flac", "answer": "WHAT YOU HAD BEST DO MY CHILD IS TO KEEP IT AND PRAY TO IT THAT SINCE IT WAS A WITNESS TO YOUR UNDOING IT WILL DEIGN TO VINDICATE YOUR CAUSE BY ITS RIGHTEOUS JUDGMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "what you had best do my child is to keep it and pray to it that since it was a witness to your undoing it will deign to vindicate your cause by its righteous judgment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0027.flac", "answer": "THUS SAYING AND PRESSING THE CRUCIFIX TO HER BREAST SHE FELL FAINTING INTO THE ARMS OF DONA ESTAFANIA WHO AS A GENTLEWOMAN TO WHOSE SEX PITY IS AS NATURAL AS CRUELTY IS TO MAN INSTANTLY PRESSED HER LIPS TO THOSE OF THE FAINTING GIRL SHEDDING OVER HER SO MANY TEARS THAT THERE NEEDED NO OTHER SPRINKLING OF WATER TO RECOVER LEOCADIA FROM HER SWOON", "subset": "test_clean", "task_type": "understanding", "prediction": "thus saying and pressing the crucifix to her breast she fell fainting into the arms of donna estefania who as a gentler woman to whose sex pity is as natural as cruelty is to man instantly pressed her lips to those of the fainting girl shedding over her so many tears that there needed no other sprinkling of water to recover leocadia from her swoon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0017.flac", "answer": "CHOKING WITH EMOTION LEOCADI MADE A SIGN TO HER PARENTS THAT SHE WISHED TO BE ALONE WITH THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "choking with emotion leocadia made a sign to her parents that she wished to be alone with them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0039.flac", "answer": "WHEN SHE CAME TO HER SENSES AND BLUSHING TO FIND HERSELF IN RODOLFO'S ARMS WOULD HAVE DISENGAGED HERSELF NO SENORA HE SAID THAT MUST NOT BE STRIVE NOT TO WITHDRAW FROM THE ARMS OF HIM WHO HOLDS YOU IN HIS SOUL", "subset": "test_clean", "task_type": "understanding", "prediction": "when she came to her senses and blushing to find herself in rodolphos arms would have disengaged herself no signora he said that must not be strive not to withdraw from the arms of him who holds you in his soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0025.flac", "answer": "THE BED SHE TOO WELL REMEMBERED WAS THERE AND ABOVE ALL THE CABINET ON WHICH HAD STOOD THE IMAGE SHE HAD TAKEN AWAY WAS STILL ON THE SAME SPOT", "subset": "test_clean", "task_type": "understanding", "prediction": "the bed sheet too well remembered was there and above all the cabinet on which had stood the image she had taken away was still on the same spot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0036.flac", "answer": "HIS MOTHER HAD LEFT HER TO HIM AS BEING HER DESTINED PROTECTOR BUT WHEN SHE SAW THAT HE TOO WAS INSENSIBLE SHE WAS NEAR MAKING A THIRD AND WOULD HAVE DONE SO HAD HE NOT COME TO HIMSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "his mother had left her to him as being her destined protector but when she saw that he too was insensible she was near making a third and would have done so had he not come to himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0037.flac", "answer": "KNOW THEN SON OF MY HEART THAT THIS FAINTING LADY IS YOUR REAL BRIDE I SAY REAL BECAUSE SHE IS THE ONE WHOM YOUR FATHER AND I HAVE CHOSEN FOR YOU AND THE PORTRAIT WAS A PRETENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "know then son of my heart that this fainting lady is your real bride i say real because she is the one whom your father and i have chosen for you and the portrait was a pretense", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0029.flac", "answer": "THIS TRUTH WHICH I HAVE LEARNED FROM HER LIPS IS CONFIRMED BY HIS FACE IN WHICH WE HAVE BOTH BEHELD THAT OF OUR SON", "subset": "test_clean", "task_type": "understanding", "prediction": "this truth which i have learned from her lips is confirmed by his face in which we have both beheld that of our son", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0020.flac", "answer": "THUS DID THIS HUMANE AND RIGHT MINDED FATHER COMFORT HIS UNHAPPY DAUGHTER AND HER MOTHER EMBRACING HER AGAIN DID ALL SHE COULD TO SOOTHE HER FEELINGS", "subset": "test_clean", "task_type": "understanding", "prediction": "thus did the humane and right minded father comfort his unhappy daughter and her mother embracing her again did all she could to soothe the feelings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0015.flac", "answer": "THIS PERSON WAS RODOLFO WHO THOUGH HE HAD GONE TO LOOK FOR HIS FRIENDS HAD CHANGED HIS MIND IN THAT RESPECT NOT THINKING IT ADVISABLE TO ACQUAINT THEM WITH WHAT HAD PASSED BETWEEN HIM AND THE GIRL", "subset": "test_clean", "task_type": "understanding", "prediction": "this person was rodolfo who though he had gone to look for his friends had changed his mind in that respect not thinking it advisable to acquaint them with what had passed between him and the girl", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0026.flac", "answer": "LUIS WAS OUT OF DANGER IN A FORTNIGHT IN A MONTH HE ROSE FROM HIS BED AND DURING ALL THAT TIME HE WAS VISITED DAILY BY HIS MOTHER AND GRANDMOTHER AND TREATED BY THE MASTER AND MISTRESS OF THE HOUSE AS IF HE WAS THEIR OWN CHILD", "subset": "test_clean", "task_type": "understanding", "prediction": "lewis was out of danger in a fortnight in a month he rose from his bed and during all that time he was visited daily by his mother and grandmother and treated by the master and mistress of the house as if he was their own child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0031.flac", "answer": "SO PERSUASIVE WERE HER ENTREATIES AND SO STRONG HER ASSURANCES THAT NO HARM WHATEVER COULD RESULT TO THEM FROM THE INFORMATION SHE SOUGHT THEY WERE INDUCED TO CONFESS THAT ONE SUMMER'S NIGHT THE SAME SHE HAD MENTIONED THEMSELVES AND ANOTHER FRIEND BEING OUT ON A STROLL WITH RODOLFO THEY HAD BEEN CONCERNED IN THE ABDUCTION OF A GIRL WHOM RODOLFO CARRIED OFF WHILST THE REST OF THEM DETAINED HER FAMILY WHO MADE A GREAT OUTCRY AND WOULD HAVE DEFENDED HER IF THEY COULD", "subset": "test_clean", "task_type": "understanding", "prediction": "so persuasive were her entreaties and so strong her assurances that no harm whatever could result to them from the information she sought they were induced to confess that one summer's night the same she had mentioned themselves and another friend being out on a stroll with rodolpho they had been concerned in the abduction of a girl whom rodolpho carried off whilst the rest of them detained her family who made a great outcry and would have defended her if they could", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5639/40744/5639-40744-0041.flac", "answer": "NOR WAS RODOLFO LESS SURPRISED THAN THEY AND THE BETTER TO ASSURE HIMSELF OF SO WONDERFUL A FACT HE BEGGED LEOCADIA TO GIVE HIM SOME TOKEN WHICH SHOULD MAKE PERFECTLY CLEAR TO HIM THAT WHICH INDEED HE DID NOT DOUBT SINCE IT WAS AUTHENTICATED BY HIS PARENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "nor was rodolph less surprised than they and the better to assure himself of so wonderful a fact he begged lochelia to give him some token which should make perfectly clear to him that which indeed he did not doubt since it was authenticated by his parents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0017.flac", "answer": "OBSERVE AGAIN WHAT CARE THE LAW TOOK IN THE PURSUIT OF WISDOM SEARCHING OUT THE DEEP THINGS OF THE WORLD AND APPLYING THEM TO THE USE OF MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "observe again what care the law took in the pursuit of wisdom searching out the deep things of the world and applying them to the use of men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0013.flac", "answer": "SOLON MARVELLED AND DESIRED TO BE INFORMED OF THE PARTICULARS", "subset": "test_clean", "task_type": "understanding", "prediction": "solon marveled and desired to be informed of the particulars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0020.flac", "answer": "THIS IS THE EXPLANATION OF THE SHALLOWS WHICH ARE FOUND IN THAT PART OF THE ATLANTIC OCEAN", "subset": "test_clean", "task_type": "understanding", "prediction": "this is the explanation of the shallows which are found in that part of the atlantic ocean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0009.flac", "answer": "TELL US SAID THE OTHER THE WHOLE STORY AND WHERE SOLON HEARD THE STORY", "subset": "test_clean", "task_type": "understanding", "prediction": "tell us said the other the whole story and where solon heard this story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0012.flac", "answer": "FOR IN THE TIMES BEFORE THE GREAT FLOOD ATHENS WAS THE GREATEST AND BEST OF CITIES AND DID THE NOBLEST DEEDS AND HAD THE BEST CONSTITUTION OF ANY UNDER THE FACE OF HEAVEN", "subset": "test_clean", "task_type": "understanding", "prediction": "for in the times before the great flood athens was the greatest and best of cities and did the noblest deeds and had the best constitution of any under the face of heaven", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0021.flac", "answer": "BUT I WOULD NOT SPEAK AT THE TIME BECAUSE I WANTED TO REFRESH MY MEMORY", "subset": "test_clean", "task_type": "understanding", "prediction": "but i would not speak at the time because i wanted to refresh my memory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0011.flac", "answer": "THE GENEALOGIES WHICH YOU HAVE RECITED TO US OUT OF YOUR OWN ANNALS SOLON ARE A MERE CHILDREN'S STORY", "subset": "test_clean", "task_type": "understanding", "prediction": "the genealogies which you have recited to us out of your own annals solon are a mere childrens story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0010.flac", "answer": "BUT IN EGYPT THE TRADITIONS OF OUR OWN AND OTHER LANDS ARE BY US REGISTERED FOR EVER IN OUR TEMPLES", "subset": "test_clean", "task_type": "understanding", "prediction": "but in egypt the traditions of our own and other lands are by us registered forever in our temples", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0000.flac", "answer": "SOCRATES BEGINS THE TIMAEUS WITH A SUMMARY OF THE REPUBLIC", "subset": "test_clean", "task_type": "understanding", "prediction": "socrates begins the timaeus with a summary of the republic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0005.flac", "answer": "SOME POEMS OF SOLON WERE RECITED BY THE BOYS", "subset": "test_clean", "task_type": "understanding", "prediction": "some poems of saloon were recited by the boys", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0016.flac", "answer": "I WILL BRIEFLY DESCRIBE THEM TO YOU AND YOU SHALL READ THE ACCOUNT OF THEM AT YOUR LEISURE IN THE SACRED REGISTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "i will briefly describe them to you and you shall read the account of them at your leisure in the sacred registers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0001.flac", "answer": "AND NOW HE DESIRES TO SEE THE IDEAL STATE SET IN MOTION HE WOULD LIKE TO KNOW HOW SHE BEHAVED IN SOME GREAT STRUGGLE", "subset": "test_clean", "task_type": "understanding", "prediction": "and now he desires to see the ideal state set in motion he would like to know how she behaved in some great struggle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0015.flac", "answer": "MANY LAWS EXIST AMONG US WHICH ARE THE COUNTERPART OF YOURS AS THEY WERE IN THE OLDEN TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "many laws exist among us which are the counterpart of yours as they were in the olden time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0004.flac", "answer": "LISTEN THEN SOCRATES TO A TALE OF SOLON'S WHO BEING THE FRIEND OF DROPIDAS MY GREAT GRANDFATHER TOLD IT TO MY GRANDFATHER CRITIAS AND HE TOLD ME", "subset": "test_clean", "task_type": "understanding", "prediction": "listen then socrates to a tale of solons who being the friend of drobidas my great grandfather told it to my grandfather critias and he told me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0014.flac", "answer": "NINE THOUSAND YEARS HAVE ELAPSED SINCE SHE FOUNDED YOURS AND EIGHT THOUSAND SINCE SHE FOUNDED OURS AS OUR ANNALS RECORD", "subset": "test_clean", "task_type": "understanding", "prediction": "nine thousand years have elapsed since she found it yours and eight thousand since she found it ours as our annals record", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0007.flac", "answer": "THE SUBJECT WAS A VERY NOBLE ONE HE DESCRIBED THE MOST FAMOUS ACTION IN WHICH THE ATHENIAN PEOPLE WERE EVER ENGAGED", "subset": "test_clean", "task_type": "understanding", "prediction": "the subject was a very noble one he described the most famous action in which the athenian people were ever engaged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0019.flac", "answer": "FOR AT THE PERIL OF HER OWN EXISTENCE AND WHEN THE OTHER HELLENES HAD DESERTED HER SHE REPELLED THE INVADER AND OF HER OWN ACCORD GAVE LIBERTY TO ALL THE NATIONS WITHIN THE PILLARS", "subset": "test_clean", "task_type": "understanding", "prediction": "for at the peril of her own existence and when the other hellenes had deserted her she repelled the invader and of her own accord gave liberty to all the nations within the pillars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0006.flac", "answer": "AND WHAT WAS THE SUBJECT OF THE POEM SAID THE PERSON WHO MADE THE REMARK", "subset": "test_clean", "task_type": "understanding", "prediction": "and what was the subject of the poem said the person who made the remark", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0008.flac", "answer": "BUT THE MEMORY OF THEIR EXPLOITS HAS PASSED AWAY OWING TO THE LAPSE OF TIME AND THE EXTINCTION OF THE ACTORS", "subset": "test_clean", "task_type": "understanding", "prediction": "but the memory of their exploits had passed away owing to the lapse of time and the extinction of the actors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0003.flac", "answer": "I WILL IF TIMAEUS APPROVES I APPROVE", "subset": "test_clean", "task_type": "understanding", "prediction": "i will if timmy oz approves i approve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0002.flac", "answer": "AND THEREFORE TO YOU I TURN TIMAEUS CITIZEN OF LOCRIS WHO ARE AT ONCE A PHILOSOPHER AND A STATESMAN AND TO YOU CRITIAS WHOM ALL ATHENIANS KNOW TO BE SIMILARLY ACCOMPLISHED AND TO HERMOCRATES WHO IS ALSO FITTED BY NATURE AND EDUCATION TO SHARE IN OUR DISCOURSE", "subset": "test_clean", "task_type": "understanding", "prediction": "and therefore to you i turn timaeus citizen of locris who are at once a philosopher and a statesman and to you critias whom all athenians know to be similarly accomplished and to hermocrates who is also fitted by nature and education to share in our discourse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0022.flac", "answer": "THEN NOW LET ME EXPLAIN TO YOU THE ORDER OF OUR ENTERTAINMENT FIRST TIMAEUS WHO IS A NATURAL PHILOSOPHER WILL SPEAK OF THE ORIGIN OF THE WORLD GOING DOWN TO THE CREATION OF MAN AND THEN I SHALL RECEIVE THE MEN WHOM HE HAS CREATED AND SOME OF WHOM WILL HAVE BEEN EDUCATED BY YOU AND INTRODUCE THEM TO YOU AS THE LOST ATHENIAN CITIZENS OF WHOM THE EGYPTIAN RECORD SPOKE", "subset": "test_clean", "task_type": "understanding", "prediction": "then now let me explain to you the order of our entertainment first timaeus who is a natural philosopher will speak of the origin of the world going down to the creation of men and then i shall receive the men whom he has created and some of whom will have been educated by you and introduce them to you as the lost athenian citizens of whom the egyptian records spoke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/961/2961-961-0018.flac", "answer": "THE MOST FAMOUS OF THEM ALL WAS THE OVERTHROW OF THE ISLAND OF ATLANTIS", "subset": "test_clean", "task_type": "understanding", "prediction": "the most famous of them all was the overthrow of the island of atlantis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0022.flac", "answer": "PLATO HAD NOT THE COMMAND OF HIS MATERIALS WHICH WOULD HAVE ENABLED HIM TO PRODUCE A PERFECT WORK OF ART", "subset": "test_clean", "task_type": "understanding", "prediction": "plato had not the command of his materials which would have enabled him to produce a perfect work of art", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0005.flac", "answer": "IN THE PRESENT DAY WE ARE WELL AWARE THAT AN ANCIENT PHILOSOPHER IS TO BE INTERPRETED FROM HIMSELF AND BY THE CONTEMPORARY HISTORY OF THOUGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "in the present day we are well aware that an ancient philosopher is to be interpreted from himself and by the contemporary history of thought", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0018.flac", "answer": "BUT IN THE REST OF THE WORK THE POWER OF LANGUAGE SEEMS TO FAIL HIM AND THE DRAMATIC FORM IS WHOLLY GIVEN UP", "subset": "test_clean", "task_type": "understanding", "prediction": "but in the rest of the work the power of language seems to fail him and the dramatic form is wholly given up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0013.flac", "answer": "IT IS PROBABLE THAT THE RELATION OF THE IDEAS TO GOD OR OF GOD TO THE WORLD WAS DIFFERENTLY CONCEIVED BY HIM AT DIFFERENT TIMES OF HIS LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "it is probable that the relation of the ideas to god or of god to the world was differently conceived by him at different times of his life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0014.flac", "answer": "THE IDEAS ALSO REMAIN BUT THEY HAVE BECOME TYPES IN NATURE FORMS OF MEN ANIMALS BIRDS FISHES", "subset": "test_clean", "task_type": "understanding", "prediction": "the ideas also remain but they have become types in nature forms of men animals birds fishes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0008.flac", "answer": "WE DO NOT KNOW HOW PLATO WOULD HAVE ARRANGED HIS OWN DIALOGUES OR WHETHER THE THOUGHT OF ARRANGING ANY OF THEM BESIDES THE TWO TRILOGIES WHICH HE HAS EXPRESSLY CONNECTED WAS EVER PRESENT TO HIS MIND", "subset": "test_clean", "task_type": "understanding", "prediction": "we do not know how plato would have arranged his own dialogues or whether the thought of arranging any of them besides the two trilogies which he has expressly connected was ever present to his mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0007.flac", "answer": "BUT THEY HAVE NOTHING TO DO WITH THE INTERPRETATION OF PLATO AND IN SPIRIT THEY ARE OPPOSED TO HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "but they have nothing to do with the interpretation of plato and in spirit they are opposed to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0019.flac", "answer": "HE COULD WRITE IN ONE STYLE BUT NOT IN ANOTHER AND THE GREEK LANGUAGE HAD NOT AS YET BEEN FASHIONED BY ANY POET OR PHILOSOPHER TO DESCRIBE PHYSICAL PHENOMENA", "subset": "test_clean", "task_type": "understanding", "prediction": "he could write in one style but not in another and the greek language had not as yet been fashioned by any poet or philosopher to describe physical phenomena", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0000.flac", "answer": "HE PASSES ABRUPTLY FROM PERSONS TO IDEAS AND NUMBERS AND FROM IDEAS AND NUMBERS TO PERSONS FROM THE HEAVENS TO MAN FROM ASTRONOMY TO PHYSIOLOGY HE CONFUSES OR RATHER DOES NOT DISTINGUISH SUBJECT AND OBJECT FIRST AND FINAL CAUSES AND IS DREAMING OF GEOMETRICAL FIGURES LOST IN A FLUX OF SENSE", "subset": "test_clean", "task_type": "understanding", "prediction": "he passes abruptly from persons to ideas and numbers and from ideas and numbers to persons from the heavens to man from astronomy to physiology he confuses or rather does not distinguish subject and object first and final causes and is dreaming of geometrical figures lost in a flux of sense", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0012.flac", "answer": "MANY IF NOT ALL THE ELEMENTS OF THE PRE SOCRATIC PHILOSOPHY ARE INCLUDED IN THE TIMAEUS", "subset": "test_clean", "task_type": "understanding", "prediction": "many if not all the elements of the pre socratic philosophy are included in the timaeus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0006.flac", "answer": "THE FANCIES OF THE NEO PLATONISTS ARE ONLY INTERESTING TO US BECAUSE THEY EXHIBIT A PHASE OF THE HUMAN MIND WHICH PREVAILED WIDELY IN THE FIRST CENTURIES OF THE CHRISTIAN ERA AND IS NOT WHOLLY EXTINCT IN OUR OWN DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "the fancies of the neo platonists are only interesting to us because they exhibit a phase of the human mind which prevailed widely in the first centuries of the christian era and is not wholly extinct in our own day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0015.flac", "answer": "THE STYLE AND PLAN OF THE TIMAEUS DIFFER GREATLY FROM THAT OF ANY OTHER OF THE PLATONIC DIALOGUES", "subset": "test_clean", "task_type": "understanding", "prediction": "the style and plan of the timaeus differ greatly from that of any other of the platonic dialogues", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0003.flac", "answer": "THEY WERE ABSORBED IN HIS THEOLOGY AND WERE UNDER THE DOMINION OF HIS NAME WHILE THAT WHICH WAS TRULY GREAT AND TRULY CHARACTERISTIC IN HIM HIS EFFORT TO REALIZE AND CONNECT ABSTRACTIONS WAS NOT UNDERSTOOD BY THEM AT ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "they were absorbed in his theology and were under the dominion of his name while that which was truly great and truly characteristic in him his effort to realise and connect abstractions was not understood by them at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0016.flac", "answer": "BUT PLATO HAS NOT THE SAME MASTERY OVER HIS INSTRUMENT WHICH HE EXHIBITS IN THE PHAEDRUS OR SYMPOSIUM", "subset": "test_clean", "task_type": "understanding", "prediction": "but plato has not the same mastery over his instrument which he exhibits in the phaedrus or symposium", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0004.flac", "answer": "THERE IS NO DANGER OF THE MODERN COMMENTATORS ON THE TIMAEUS FALLING INTO THE ABSURDITIES OF THE NEO PLATONISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "there is no danger of the modern commentators on the timaeus falling into the absurdities of the neoplatonists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0009.flac", "answer": "THE DIALOGUE IS PRIMARILY CONCERNED WITH THE ANIMAL CREATION INCLUDING UNDER THIS TERM THE HEAVENLY BODIES AND WITH MAN ONLY AS ONE AMONG THE ANIMALS", "subset": "test_clean", "task_type": "understanding", "prediction": "the dialogue is primarily concerned with the animal creation including under this term the heavenly bodies and with man only as one among the animals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0021.flac", "answer": "THERE IS A WANT OF FLOW AND OFTEN A DEFECT OF RHYTHM THE MEANING IS SOMETIMES OBSCURE AND THERE IS A GREATER USE OF APPOSITION AND MORE OF REPETITION THAN OCCURS IN PLATO'S EARLIER WRITINGS", "subset": "test_clean", "task_type": "understanding", "prediction": "there is a want of flow and often a defect of rhythm the meaning is sometimes obscure and there is a greater use of apposition and more of repetition than occurs in plato s earlier writings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0020.flac", "answer": "AND HENCE WE FIND THE SAME SORT OF CLUMSINESS IN THE TIMAEUS OF PLATO WHICH CHARACTERIZES THE PHILOSOPHICAL POEM OF LUCRETIUS", "subset": "test_clean", "task_type": "understanding", "prediction": "and hence we find the same sort of clumsiness in the timaeus of plato which characterizes the philosophical poem of lucretius", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0002.flac", "answer": "IN THE SUPPOSED DEPTHS OF THIS DIALOGUE THE NEO PLATONISTS FOUND HIDDEN MEANINGS AND CONNECTIONS WITH THE JEWISH AND CHRISTIAN SCRIPTURES AND OUT OF THEM THEY ELICITED DOCTRINES QUITE AT VARIANCE WITH THE SPIRIT OF PLATO", "subset": "test_clean", "task_type": "understanding", "prediction": "in the supposed depths of this dialogue the neoplatonists found hidden meanings and connections with the jewish and christian scriptures and out of them they elicited doctrines quite at variance with the spirit of plato", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0010.flac", "answer": "BUT HE HAS NOT AS YET DEFINED THIS INTERMEDIATE TERRITORY WHICH LIES SOMEWHERE BETWEEN MEDICINE AND MATHEMATICS AND HE WOULD HAVE FELT THAT THERE WAS AS GREAT AN IMPIETY IN RANKING THEORIES OF PHYSICS FIRST IN THE ORDER OF KNOWLEDGE AS IN PLACING THE BODY BEFORE THE SOUL", "subset": "test_clean", "task_type": "understanding", "prediction": "but he has not as yet defined this intermediate territory which lies somewhere between medicine and mathematics and he would have felt that there was as great an impiety in ranking theories of physics first in the order of knowledge as in placing the body before the soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0011.flac", "answer": "WITH HERACLEITUS HE ACKNOWLEDGES THE PERPETUAL FLUX LIKE ANAXAGORAS HE ASSERTS THE PREDOMINANCE OF MIND ALTHOUGH ADMITTING AN ELEMENT OF NECESSITY WHICH REASON IS INCAPABLE OF SUBDUING LIKE THE PYTHAGOREANS HE SUPPOSES THE MYSTERY OF THE WORLD TO BE CONTAINED IN NUMBER", "subset": "test_clean", "task_type": "understanding", "prediction": "with heraclitus he acknowledges the perpetual flux like anaxagoras he asserts the predominance of mind although admitting an element of necessity which reason is incapable of subduing like the pythagoreans he supposes the mystery of the world to be contained in number", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0017.flac", "answer": "NOTHING CAN EXCEED THE BEAUTY OR ART OF THE INTRODUCTION IN WHICH HE IS USING WORDS AFTER HIS ACCUSTOMED MANNER", "subset": "test_clean", "task_type": "understanding", "prediction": "nothing can exceed the beauty or art of the introduction in which he is using words after his accustomed manner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2961/960/2961-960-0001.flac", "answer": "THE INFLUENCE WITH THE TIMAEUS HAS EXERCISED UPON POSTERITY IS DUE PARTLY TO A MISUNDERSTANDING", "subset": "test_clean", "task_type": "understanding", "prediction": "the influence which the timaeus has exercised upon posterity is due partly to a misunderstanding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0010.flac", "answer": "HE WORKED ME VERY HARD HE WANTED TO BE BEATING ME ALL THE TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "he worked me very hard he wanted to be beating me all the time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0003.flac", "answer": "OF THIS PARTY EDWARD A BOY OF SEVENTEEN CALLED FORTH MUCH SYMPATHY HE TOO WAS CLAIMED BY HOLLAN", "subset": "test_clean", "task_type": "understanding", "prediction": "of this party edward a boy of seventeen called forth much sympathy he too was claimed by holland", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0006.flac", "answer": "THE DOCTOR WHO ATTENDED THE INJURED CREATURE IN THIS CASE WAS SIMPLY TOLD THAT SHE SLIPPED AND FELL DOWN STAIRS AS SHE WAS COMING DOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "the doctor who attended the injured creature in this case was simply told that she slipped and fell down the stairs as she was coming down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0001.flac", "answer": "IT IS HARDLY NECESSARY TO SAY MORE OF THEM HERE", "subset": "test_clean", "task_type": "understanding", "prediction": "it is hardly necessary to say more of them here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0014.flac", "answer": "OF STARTING I DIDN'T KNOW THE WAY TO COME", "subset": "test_clean", "task_type": "understanding", "prediction": "of starting i did n t know the way to come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0002.flac", "answer": "FROM THE MANNER IN WHICH HE EXPRESSED HIMSELF WITH REGARD TO ROBERT HOLLAN NO MAN IN THE WHOLE RANGE OF HIS RECOLLECTIONS WILL BE LONGER REMEMBERED THAN HE HIS ENTHRALMENT WHILE UNDER HOLLAN WILL HARDLY EVER BE FORGOTTEN", "subset": "test_clean", "task_type": "understanding", "prediction": "from the manner in which he expressed himself with regard to robert holland no man in the whole range of his recollections will be longer remembered than he his enthralment while under holland will hardly ever be forgotten", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0005.flac", "answer": "A FEW YEARS BACK ONE OF THEIR SLAVES A COACHMAN WAS KEPT ON THE COACH BOX ONE COLD NIGHT WHEN THEY WERE OUT AT A BALL UNTIL HE BECAME ALMOST FROZEN TO DEATH IN FACT HE DID DIE IN THE INFIRMARY FROM THE EFFECTS OF THE FROST ABOUT ONE WEEK AFTERWARDS", "subset": "test_clean", "task_type": "understanding", "prediction": "a few years back one of their slaves a coachman was kept on the coach box one cold night when they were out at a ball until he became almost frozen to death in fact he did die in the infirmary from the effects of the frost about one week afterwards", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0013.flac", "answer": "AS TO HIS AGE AND ALSO THE NAME OF HIS MASTER JACOB'S STATEMENT VARIED SOMEWHAT FROM THE ADVERTISEMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "as to his age and also the name of his master jacob s statement varied somewhat from the advertisement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0008.flac", "answer": "AS USUAL NOTHING WAS DONE IN THE WAY OF PUNISHMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "as usual nothing was done in the way of punishment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0007.flac", "answer": "ANOTHER CASE SAID JOHN WESLEY WAS A LITTLE GIRL HALF GROWN WHO WAS WASHING WINDOWS UP STAIRS ONE DAY AND UNLUCKILY FELL ASLEEP IN THE WINDOW AND IN THIS POSITION WAS FOUND BY HER MISTRESS IN A RAGE THE MISTRESS HIT HER A HEAVY SLAP KNOCKED HER OUT OF THE WINDOW AND SHE FELL TO THE PAVEMENT AND DIED IN A FEW HOURS FROM THE EFFECTS THEREOF", "subset": "test_clean", "task_type": "understanding", "prediction": "another case said john wesley was a little girl half grown who was washing windows upstairs one day and unluckily fell asleep in the window and in this position was found by her mistress in a rage the mistress hit her a heavy slap knocked her out of the window and she fell to the pavement and died in a few hours from the effects thereof", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0000.flac", "answer": "THIS WAS WHAT DID THE MISCHIEF SO FAR AS THE RUNNING AWAY WAS CONCERNED", "subset": "test_clean", "task_type": "understanding", "prediction": "this was what did the mischief so far as the running away was concerned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0012.flac", "answer": "SUBSTANTIALLY THIS WAS JACOB'S UNVARNISHED DESCRIPTION OF HIS MASTER AND MISTRESS", "subset": "test_clean", "task_type": "understanding", "prediction": "substantially this was jacob s unvarnished description of his master and mistress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0009.flac", "answer": "I NEVER KNEW OF BUT ONE MAN WHO COULD EVER PLEASE HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "i never knew of but one man who could ever please him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0011.flac", "answer": "SHE WAS A LARGE HOMELY WOMAN THEY WERE COMMON WHITE PEOPLE WITH NO REPUTATION IN THE COMMUNITY", "subset": "test_clean", "task_type": "understanding", "prediction": "she was a large homely woman they were common white people with no reputation in the community", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/287645/8463-287645-0004.flac", "answer": "JOHN WESLEY COMBASH JACOB TAYLOR AND THOMAS EDWARD SKINNER", "subset": "test_clean", "task_type": "understanding", "prediction": "john wesley combash jacob taylor and thomas edward skinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0035.flac", "answer": "AND SO IF I'D BEEN DELAYED BY A QUARTER OF AN HOUR OR EVEN LESS THE FRIGATE WOULD HAVE GONE WITHOUT ME AND I WOULD HAVE MISSED OUT ON THIS UNEARTHLY EXTRAORDINARY AND INCONCEIVABLE EXPEDITION WHOSE TRUE STORY MIGHT WELL MEET WITH SOME SKEPTICISM", "subset": "test_clean", "task_type": "understanding", "prediction": "and so if i had been delayed by a quarter of an hour or even less the frigate would have gone without me and i would have missed out on this unearthly extraordinary and inconceivable expedition whose true story might well meet with some scepticism", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0037.flac", "answer": "DEPARTING FROM FIVE HUNDRED THOUSAND THROATS THREE CHEERS BURST FORTH IN SUCCESSION", "subset": "test_clean", "task_type": "understanding", "prediction": "departing from five hundred thousand throats three cheers burst forth in succession", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0014.flac", "answer": "THERE WAS GOOD REASON TO STOP AND THINK EVEN FOR THE WORLD'S MOST EMOTIONLESS MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "there was good reason to stop and think even for the world s most emotionless man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0036.flac", "answer": "THE WHARVES OF BROOKLYN AND EVERY PART OF NEW YORK BORDERING THE EAST RIVER WERE CROWDED WITH CURIOSITY SEEKERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the wharves of brooklyn and every part of new york bordering the east river were crowded with curiosity seekers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0015.flac", "answer": "CONSEIL I CALLED A THIRD TIME CONSEIL APPEARED", "subset": "test_clean", "task_type": "understanding", "prediction": "conseil i called a third time conseil appeared", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0027.flac", "answer": "I LEFT INSTRUCTIONS FOR SHIPPING MY CONTAINERS OF STUFFED ANIMALS AND DRIED PLANTS TO PARIS FRANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "i left instructions for shipping my containers of stuffed animals and dried plants to paris france", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0038.flac", "answer": "THOUSANDS OF HANDKERCHIEFS WERE WAVING ABOVE THESE TIGHTLY PACKED MASSES HAILING THE ABRAHAM LINCOLN UNTIL IT REACHED THE WATERS OF THE HUDSON RIVER AT THE TIP OF THE LONG PENINSULA THAT FORMS NEW YORK CITY", "subset": "test_clean", "task_type": "understanding", "prediction": "thousands of handkerchiefs were waving above these tightly packed masses hailing the abraham lincoln until it reached the waters of the hudson river at the tip of the long peninsula that forms new york city", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0029.flac", "answer": "OUR BAGGAGE WAS IMMEDIATELY CARRIED TO THE DECK OF THE FRIGATE I RUSHED ABOARD", "subset": "test_clean", "task_type": "understanding", "prediction": "our baggage was immediately carried to the deck of the frigate i rushed aboard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0000.flac", "answer": "CHAPTER THREE AS MASTER WISHES", "subset": "test_clean", "task_type": "understanding", "prediction": "chapter three as master wishes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0007.flac", "answer": "CLASSIFYING WAS EVERYTHING TO HIM SO HE KNEW NOTHING ELSE WELL VERSED IN THE THEORY OF CLASSIFICATION HE WAS POORLY VERSED IN ITS PRACTICAL APPLICATION AND I DOUBT THAT HE COULD TELL A SPERM WHALE FROM A BALEEN WHALE", "subset": "test_clean", "task_type": "understanding", "prediction": "classifying was everything to him so he knew nothing else well versed in the theory of classification he was poorly versed in its practical application and i doubt that he could tell a sperm whale from a baleen whale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0008.flac", "answer": "AND YET WHAT A FINE GALLANT LAD", "subset": "test_clean", "task_type": "understanding", "prediction": "and yet what a fine gallant lad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0020.flac", "answer": "YES WE ARE CERTAINLY I REPLIED EVASIVELY BUT AFTER WE MAKE A DETOUR", "subset": "test_clean", "task_type": "understanding", "prediction": "yes we are certainly i replied evasively but after we make a detour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0001.flac", "answer": "THREE SECONDS BEFORE THE ARRIVAL OF J B HOBSON'S LETTER I NO MORE DREAMED OF CHASING THE UNICORN THAN OF TRYING FOR THE NORTHWEST PASSAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "three seconds before the arrival of j b hobson s letter i no more dreamed of chasing the unicorn than of trying for the northwest passage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0021.flac", "answer": "A ROUTE SLIGHTLY LESS DIRECT THAT'S ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "a route slightly less direct that is all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0026.flac", "answer": "WE HAVE A COMMANDER WHO'S GAME FOR ANYTHING", "subset": "test_clean", "task_type": "understanding", "prediction": "we have a commander who is game for anything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0009.flac", "answer": "NOT ONCE DID HE COMMENT ON THE LENGTH OR THE HARDSHIPS OF A JOURNEY", "subset": "test_clean", "task_type": "understanding", "prediction": "not once did he comment on the length or the hardships of the journey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0034.flac", "answer": "WE'LL BE QUITE COMFORTABLE HERE I TOLD CONSEIL", "subset": "test_clean", "task_type": "understanding", "prediction": "will be quite comfortable here i told conseil", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0017.flac", "answer": "PACK AS MUCH INTO MY TRUNK AS YOU CAN MY TRAVELING KIT MY SUITS SHIRTS AND SOCKS DON'T BOTHER COUNTING JUST SQUEEZE IT ALL IN AND HURRY", "subset": "test_clean", "task_type": "understanding", "prediction": "pack as much into my trunk as you can my traveling kit my suits shirts and socks dont bother counting just squeeze it all in and hurry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0005.flac", "answer": "CONSEIL WAS MY MANSERVANT", "subset": "test_clean", "task_type": "understanding", "prediction": "conseil was my manservant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0033.flac", "answer": "I WAS WELL SATISFIED WITH MY CABIN WHICH WAS LOCATED IN THE STERN AND OPENED INTO THE OFFICERS MESS", "subset": "test_clean", "task_type": "understanding", "prediction": "i was well satisfied with my cabin which was located in the stern and opened into the officers mess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0025.flac", "answer": "BUT WE'RE GOING JUST THE SAME", "subset": "test_clean", "task_type": "understanding", "prediction": "but were going just the same", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0031.flac", "answer": "ONE OF THE SAILORS LED ME TO THE AFTERDECK WHERE I STOOD IN THE PRESENCE OF A SMART LOOKING OFFICER WHO EXTENDED HIS HAND TO ME", "subset": "test_clean", "task_type": "understanding", "prediction": "one of the sailors led me to the after deck where i stood in the presence of a smart looking officer who extended his hand to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0016.flac", "answer": "DID MASTER SUMMON ME HE SAID ENTERING", "subset": "test_clean", "task_type": "understanding", "prediction": "did master summon me he said entering", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0019.flac", "answer": "ANYHOW WE'LL LEAVE INSTRUCTIONS TO SHIP THE WHOLE MENAGERIE TO FRANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "anyhow we will leave instructions to ship the whole menagerie to france", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0011.flac", "answer": "HE WENT HERE THERE AND EVERYWHERE IN PERFECT CONTENTMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "he went here there and everywhere in perfect contentment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0028.flac", "answer": "I OPENED A LINE OF CREDIT SUFFICIENT TO COVER THE BABIRUSA AND CONSEIL AT MY HEELS I JUMPED INTO A CARRIAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "i opened a line of credit sufficient to cover the barbarossa and conseil at my heels i jumped into a carriage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0018.flac", "answer": "WE'LL DEAL WITH THEM LATER WHAT", "subset": "test_clean", "task_type": "understanding", "prediction": "well deal with them later what", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0003.flac", "answer": "I WANTED NOTHING MORE THAN TO SEE MY COUNTRY AGAIN MY FRIENDS MY MODEST QUARTERS BY THE BOTANICAL GARDENS MY DEARLY BELOVED COLLECTIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "i wanted nothing more than to see my country again my friends my modest quarters by the botanical gardens my dearly beloved collections", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0004.flac", "answer": "BUT NOW NOTHING COULD HOLD ME BACK", "subset": "test_clean", "task_type": "understanding", "prediction": "but now nothing could hold me back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0012.flac", "answer": "PLEASE FORGIVE ME FOR THIS UNDERHANDED WAY OF ADMITTING I HAD TURNED FORTY", "subset": "test_clean", "task_type": "understanding", "prediction": "please forgive me for this underhanded way of admitting that i had turned forty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0022.flac", "answer": "WE'RE LEAVING ON THE ABRAHAM LINCOLN", "subset": "test_clean", "task_type": "understanding", "prediction": "we are leaving on the abraham lincoln", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0032.flac", "answer": "IN PERSON WELCOME ABOARD PROFESSOR YOUR CABIN IS WAITING FOR YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "in person welcome aboard professor your cabin is waiting for you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0030.flac", "answer": "I ASKED FOR COMMANDER FARRAGUT", "subset": "test_clean", "task_type": "understanding", "prediction": "i asked for commander farragut", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0010.flac", "answer": "NEVER DID HE OBJECT TO BUCKLING UP HIS SUITCASE FOR ANY COUNTRY WHATEVER CHINA OR THE CONGO NO MATTER HOW FAR OFF IT WAS", "subset": "test_clean", "task_type": "understanding", "prediction": "never did he object to buckling up his suitcase for any country whatever china or the congo no matter how far off it was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0023.flac", "answer": "YOU SEE MY FRIEND IT'S AN ISSUE OF THE MONSTER THE NOTORIOUS NARWHALE", "subset": "test_clean", "task_type": "understanding", "prediction": "you see my friend it is an issue of the monster the notorious narwhal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0006.flac", "answer": "FROM RUBBING SHOULDERS WITH SCIENTISTS IN OUR LITTLE UNIVERSE BY THE BOTANICAL GARDENS THE BOY HAD COME TO KNOW A THING OR TWO", "subset": "test_clean", "task_type": "understanding", "prediction": "from rubbing shoulders with scientists in our little universe by the botanical gardens the boy had come to know a thing or two", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0024.flac", "answer": "WE DON'T KNOW WHERE IT WILL TAKE US", "subset": "test_clean", "task_type": "understanding", "prediction": "we don t know where it will take us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0013.flac", "answer": "HE WAS A FANATIC ON FORMALITY AND HE ONLY ADDRESSED ME IN THE THIRD PERSON TO THE POINT WHERE IT GOT TIRESOME", "subset": "test_clean", "task_type": "understanding", "prediction": "he was a fanatic on formality and he only addressed me in the third person to the point where it got tiresome", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294828/8463-294828-0002.flac", "answer": "EVEN SO I HAD JUST RETURNED FROM AN ARDUOUS JOURNEY EXHAUSTED AND BADLY NEEDING A REST", "subset": "test_clean", "task_type": "understanding", "prediction": "even so i had just returned from an arduous journey exhausted and badly needing a rest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0007.flac", "answer": "EVEN THE SUPPORTING CAST IS SHREWDLY DRAWN PROFESSOR ARONNAX THE CAREER SCIENTIST CAUGHT IN AN ETHICAL CONFLICT CONSEIL THE COMPULSIVE CLASSIFIER WHO SUPPLIES HUMOROUS TAG LINES FOR VERNE'S FAST FACTS THE HARPOONER NED LAND A CREATURE OF CONSTANT APPETITES MAN AS HEROIC ANIMAL", "subset": "test_clean", "task_type": "understanding", "prediction": "even the supporting cast is shrewdly drawn professor aronnax the career scientist caught in an ethical conflict conseil the compulsive classifier who supplies humorous taglines for verne s fast facts the harpooner ned land a creature of constant appetites man as heroic animal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0003.flac", "answer": "NEMO BUILDS A FABULOUS FUTURISTIC SUBMARINE THE NAUTILUS THEN CONDUCTS AN UNDERWATER CAMPAIGN OF VENGEANCE AGAINST HIS IMPERIALIST OPPRESSOR", "subset": "test_clean", "task_type": "understanding", "prediction": "nemo builds a fabulous futuristic submarine the nautilus then conducts an underwater campaign of vengeance against his imperialist oppressor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0010.flac", "answer": "AND IN THIS LAST ACTION HE FALLS INTO THE CLASSIC SIN OF PRIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "and in this last action he falls into the classic sin of pride", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0006.flac", "answer": "HIS SPECIFICATIONS FOR AN OPEN SEA SUBMARINE AND A SELF CONTAINED DIVING SUIT WERE DECADES BEFORE THEIR TIME YET MODERN TECHNOLOGY BEARS THEM OUT TRIUMPHANTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "his specifications for an open sea submarine and a self containing diving suit were decades before their time yet modern technology bears them out triumphantly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0014.flac", "answer": "FATHOM SIX FEET", "subset": "test_clean", "task_type": "understanding", "prediction": "fathom six feet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0017.flac", "answer": "LITER ROUGHLY ONE QUART", "subset": "test_clean", "task_type": "understanding", "prediction": "leader roughly one quart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0000.flac", "answer": "IT'S ALMOST BEYOND CONJECTURE", "subset": "test_clean", "task_type": "understanding", "prediction": "its almost beyond conjecture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0012.flac", "answer": "THE NAUTILUS NEARLY PERISHES IN THE ANTARCTIC AND NEMO SINKS INTO A GROWING DEPRESSION", "subset": "test_clean", "task_type": "understanding", "prediction": "the nautilus nearly perishes in the antarctic and nemo sinks into a growing depression", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0008.flac", "answer": "BUT MUCH OF THE NOVEL'S BROODING POWER COMES FROM CAPTAIN NEMO", "subset": "test_clean", "task_type": "understanding", "prediction": "but much of the novel s brooding power comes from captain nemo", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0002.flac", "answer": "FIRST AS A PARIS STOCKBROKER LATER AS A CELEBRATED AUTHOR AND YACHTSMAN HE WENT ON FREQUENT VOYAGES TO BRITAIN AMERICA THE MEDITERRANEAN", "subset": "test_clean", "task_type": "understanding", "prediction": "first as a paris stockbroker later as a celebrated author and yachtsman he went on frequent voyages to britain america the mediterranean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0011.flac", "answer": "HE'S SWIFTLY PUNISHED", "subset": "test_clean", "task_type": "understanding", "prediction": "he is swiftly punished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0019.flac", "answer": "MILLIMETER ROUGHLY ONE TWENTY FIFTH OF AN INCH", "subset": "test_clean", "task_type": "understanding", "prediction": "millimeter roughly one twenty fifth of an inch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0018.flac", "answer": "METER ROUGHLY ONE YARD THREE INCHES", "subset": "test_clean", "task_type": "understanding", "prediction": "meter roughly one yard three inches", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0001.flac", "answer": "THIS REALITY BEGINS TO EXPLAIN THE DARK POWER AND OTHERWORLDLY FASCINATION OF TWENTY THOUSAND LEAGUES UNDER THE SEAS", "subset": "test_clean", "task_type": "understanding", "prediction": "this reality begins to explain the dark power and otherworldly fascination of twenty thousand leagues under the sea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0005.flac", "answer": "OTHER SUBTLETIES OCCUR INSIDE EACH EPISODE THE TEXTURES SPARKLING WITH WIT INFORMATION AND INSIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "other subtleties occur inside each episode the textures sparkling with wit information and insight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0004.flac", "answer": "IN ALL THE NOVEL HAD A DIFFICULT GESTATION", "subset": "test_clean", "task_type": "understanding", "prediction": "in all the novel had a difficult gestation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0009.flac", "answer": "THIS COMPULSION LEADS NEMO INTO UGLY CONTRADICTIONS HE'S A FIGHTER FOR FREEDOM YET ALL WHO BOARD HIS SHIP ARE IMPRISONED THERE FOR GOOD HE WORKS TO SAVE LIVES BOTH HUMAN AND ANIMAL YET HE HIMSELF CREATES A HOLOCAUST HE DETESTS IMPERIALISM YET HE LAYS PERSONAL CLAIM TO THE SOUTH POLE", "subset": "test_clean", "task_type": "understanding", "prediction": "this compulsion leads nemo into ugly contradictions he is a fighter for freedom yet all who board his ship are imprisoned there for good he works to save lives both human and animal yet he himself creates a holocaust he detests imperialism yet he lays personal claim to the south pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0016.flac", "answer": "MILLIGRAM ROUGHLY ONE TWENTY EIGHT THOUSAND OF AN OUNCE", "subset": "test_clean", "task_type": "understanding", "prediction": "milligram roughly one twenty eight thousandth of an ounce", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0013.flac", "answer": "FOR MANY THEN THIS BOOK HAS BEEN A SOURCE OF FASCINATION SURELY ONE OF THE MOST INFLUENTIAL NOVELS EVER WRITTEN AN INSPIRATION FOR SUCH SCIENTISTS AND DISCOVERERS AS ENGINEER SIMON LAKE OCEANOGRAPHER WILLIAM BEEBE POLAR TRAVELER SIR ERNEST SHACKLETON", "subset": "test_clean", "task_type": "understanding", "prediction": "for many then this book has been a source of fascination surely one of the most influential novels ever written an inspiration for such scientists and discoverers as engineer simon lake oceanographer william bebey polar traveller sir ernest shackleton", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8463/294825/8463-294825-0015.flac", "answer": "GRAM ROUGHLY ONE TWENTY EIGHTH OF AN OUNCE", "subset": "test_clean", "task_type": "understanding", "prediction": "graham roughly one twenty eighth of an ounce", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0022.flac", "answer": "THE HAWK EMBITTERED BY THE LOSS OF HIS FIRST QUARRY HAD BECOME AS DOGGED IN PURSUIT AS A WEASEL NOT TO BE SHAKEN OFF OR EVADED OR DECEIVED", "subset": "test_clean", "task_type": "understanding", "prediction": "the hawk embittered by the loss of his first quarry had become as dogged in pursuit as a weasel not to be shaken off or evaded or deceived", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0024.flac", "answer": "THE LAST DROP FLY AS LUCK WOULD HAVE IT CAUGHT JUST IN THE CORNER OF THE HAWK'S ANGRILY OPEN BEAK HOOKING ITSELF FIRMLY", "subset": "test_clean", "task_type": "understanding", "prediction": "the last drop fly as luck would have it caught just in the corner of the hawk s angrily open beak hooking itself firmly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0025.flac", "answer": "AT THE SUDDEN SHARP STING OF IT THE GREAT BIRD TURNED HIS HEAD AND NOTICED FOR THE FIRST TIME THE FISHERMAN STANDING ON THE BANK", "subset": "test_clean", "task_type": "understanding", "prediction": "at the sudden sharp sting of it the great bird turned his head and noticed for the first time the fisherman standing on the bank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0004.flac", "answer": "BUT SUDDENLY STRAIGHT AND SWIFT AS A DIVING CORMORANT HE SHOT DOWN INTO THE TORRENT AND DISAPPEARED BENEATH THE SURFACE", "subset": "test_clean", "task_type": "understanding", "prediction": "but suddenly straight and swift as a diving cormorant he shot down into the torrent and disappeared beneath the surface", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0005.flac", "answer": "ONCE FAIRLY A WING HOWEVER HE WHEELED AND MADE BACK HURRIEDLY FOR HIS PERCH", "subset": "test_clean", "task_type": "understanding", "prediction": "once fairly a wing however he wheeled and made back hurriedly for his perch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0019.flac", "answer": "AS HE FLEW HIS DOWN REACHING CLUTCHING TALONS WERE NOT HALF A YARD ABOVE THE FUGITIVE'S HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "as he flew his down reaching clutching talons were not half a yard above the fugitives head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0002.flac", "answer": "HIS FEET WERE RED HIS LONG NARROW BEAK WITH ITS SAW TOOTHED EDGES AND SHARP HOOKED TIP WAS BRIGHT RED", "subset": "test_clean", "task_type": "understanding", "prediction": "his feet were red his long narrow beak with its saw toothed edges and sharp hooked tip was bright red", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0023.flac", "answer": "HE HAD A LOT OF LINE OUT AND THE PLACE WAS NONE TOO FREE FOR A LONG CAST BUT HE WAS IMPATIENT TO DROP HIS FLIES AGAIN ON THE SPOT WHERE THE BIG FISH WAS FEEDING", "subset": "test_clean", "task_type": "understanding", "prediction": "he had a lot of line out and the place was none too free for a long cast but he was impatient to drop his flies again on the spot where the big fish was feeding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0003.flac", "answer": "BUT HERE HE WAS AT A TERRIBLE DISADVANTAGE AS COMPARED WITH THE OWLS HAWKS AND EAGLES HE HAD NO RENDING CLAWS", "subset": "test_clean", "task_type": "understanding", "prediction": "but here he was at a terrible disadvantage as compared with the owls hawks and eagles he had no rending claws", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0021.flac", "answer": "BUT AS BEFORE THE LEAPING WAVES OF THE RAPIDS WERE TOO MUCH FOR HIS PURSUER AND HE WAS ABLE TO FLAP HIS WAY ONWARD IN A CLOUD OF FOAM WHILE DOOM HUNG LOW ABOVE HIS HEAD YET HESITATED TO STRIKE", "subset": "test_clean", "task_type": "understanding", "prediction": "but as before the leaping waves of the rapids were too much for his pursuer and he was able to flap his way onward in a cloud of foam while doom hung low above his head yet hesitated to strike", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0015.flac", "answer": "ALMOST INSTANTLY HE WAS FORCED TO THE TOP", "subset": "test_clean", "task_type": "understanding", "prediction": "almost instantly he was forced to the top", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0027.flac", "answer": "THEN THE LEADER PARTED FROM THE LINE", "subset": "test_clean", "task_type": "understanding", "prediction": "then the leader parted from the line", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0006.flac", "answer": "IT MIGHT HAVE SEEMED THAT A TROUT OF THIS SIZE WAS A FAIRLY SUBSTANTIAL MEAL", "subset": "test_clean", "task_type": "understanding", "prediction": "it might have seemed that a trout of this size was a fairly substantial meal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0026.flac", "answer": "THE DRAG UPON HIS BEAK AND THE LIGHT CHECK UPON HIS WINGS WERE INEXPLICABLE TO HIM AND APPALLING", "subset": "test_clean", "task_type": "understanding", "prediction": "the drag upon his beak and the light check upon his wings were inexplicable to him and appalling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0017.flac", "answer": "BUT AT THIS POINT IN THE RAPIDS IT WAS IMPOSSIBLE FOR HIM TO STAY DOWN", "subset": "test_clean", "task_type": "understanding", "prediction": "but at this point in the rapids it was impossible for him to stay down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0016.flac", "answer": "STRAIGHTWAY THE HAWK GLIDED FROM HIS PERCH AND DARTED AFTER HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "straightway the hawk glided from his perch and darted after him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0009.flac", "answer": "THE GREAT HAWK FOLLOWED HURRIEDLY TO RETRIEVE HIS PREY FROM THE GROUND", "subset": "test_clean", "task_type": "understanding", "prediction": "the great hawk followed hurriedly to retrieve his prey from the ground", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0018.flac", "answer": "BUT THIS FREQUENTER OF THE HEIGHTS OF AIR FOR ALL HIS SAVAGE VALOR WAS TROUBLED AT THE LEAPING WAVES AND THE TOSSING FOAM OF THESE MAD RAPIDS HE DID NOT UNDERSTAND THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "but this frequenter of the heights of air for all his savage valor was troubled at the leaping waves and the tossing foam of these mad rapids he did not understand them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0011.flac", "answer": "IN FACT HE HAD JUST FINISHED IT THE LAST OF THE TROUT'S TAIL HAD JUST VANISHED WITH A SPASM DOWN HIS STRAINED GULLET WHEN THE BAFFLED HAWK CAUGHT SIGHT OF HIM AND SWOOPED", "subset": "test_clean", "task_type": "understanding", "prediction": "in fact he had just finished it the last of the trout s tail had just vanished with a spasm down his strained gullet when the baffled hawk caught sight of him and swooped", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0001.flac", "answer": "THE MERGANSER HAD A CRESTED HEAD OF IRIDESCENT GREEN BLACK A BROAD COLLAR OF LUSTROUS WHITE BLACK BACK BLACK AND WHITE WINGS WHITE BELLY SIDES FINELY PENCILLED IN BLACK AND WHITE AND A BREAST OF RICH CHESTNUT RED STREAKED WITH BLACK", "subset": "test_clean", "task_type": "understanding", "prediction": "the merganser had a crested head of iridescent green black a broad collar of lustrous white black back black and white wings white belly sides finely penciled in black and white and a breast of rich chestnut red streaked with black", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0012.flac", "answer": "THE HAWK ALIGHTED ON THE DEAD BRANCH AND SAT UPRIGHT MOTIONLESS AS IF SURPRISED", "subset": "test_clean", "task_type": "understanding", "prediction": "the hawk alighted on the dead branch and sat upright motionless as if surprised", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0007.flac", "answer": "BUT SUCH WAS HIS KEENNESS THAT EVEN WHILE THE WIDE FLUKES OF HIS ENGORGED VICTIM WERE STILL STICKING OUT AT THE CORNERS OF HIS BEAK HIS FIERCE RED EYES WERE ONCE MORE PEERING DOWNWARD INTO THE TORRENT IN SEARCH OF FRESH PREY", "subset": "test_clean", "task_type": "understanding", "prediction": "but such was his keenness that even while the wide flukes of his engorged victim were still sticking out at the corners of his beak his fierce red eyes were once more peering downward into the torrent in search of fresh prey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0013.flac", "answer": "LIKE HIS UNFORTUNATE LITTLE COUSIN THE TEAL HE TOO HAD FELT THE FEAR OF DEATH SMITTEN INTO HIS HEART AND WAS HEADING DESPERATELY FOR THE REFUGE OF SOME DARK OVERHANGING BANK DEEP FRINGED WITH WEEDS WHERE THE DREADFUL EYE OF THE HAWK SHOULD NOT DISCERN HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "like his unfortunate little cousin the teal he too had felt the fear of death smitten into his heart and was heading desperately for the refuge of some dark overhanging bank deep fringed with weeds where the dreadful eye of the hawk should not discern him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0014.flac", "answer": "THE HAWK SAT UPON THE BRANCH AND WATCHED HIS QUARRY SWIMMING BENEATH THE SURFACE", "subset": "test_clean", "task_type": "understanding", "prediction": "the hawk sat upon the branch and watched his quarry swimming beneath the surface", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0000.flac", "answer": "ALL ABOUT HIM WAS A TUMULT OF BRIGHT AND BROKEN COLOR SCATTERED IN BROAD SPLASHES", "subset": "test_clean", "task_type": "understanding", "prediction": "all about him was a tumult of bright and broken color scattered in broad splashes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0010.flac", "answer": "THE CAT GROWLED SOFTLY PICKED UP THE PRIZE IN HER JAWS AND TROTTED INTO THE BUSHES TO DEVOUR IT", "subset": "test_clean", "task_type": "understanding", "prediction": "the cat growled softly picked up the prize in her jaws and trotted into the bushes to devour it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0020.flac", "answer": "WHERE THE WAVES FOR AN INSTANT SANK THEY CAME CLOSER BUT NOT QUITE WITHIN GRASPING REACH", "subset": "test_clean", "task_type": "understanding", "prediction": "where the waves for an instant sank they came closer but not quite within grasping reach", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/88083/7176-88083-0008.flac", "answer": "IN DESPAIR HE HURLED HIMSELF DOWNWARD TOO SOON", "subset": "test_clean", "task_type": "understanding", "prediction": "in despair he hurled himself downward too soon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0018.flac", "answer": "IN THE MODERN WELL CONSTRUCTED PLAY HE SIMPLY RINGS UP AN IMAGINARY CONFEDERATE AND TELLS HIM WHAT HE IS GOING TO DO COULD ANYTHING BE MORE NATURAL", "subset": "test_clean", "task_type": "understanding", "prediction": "in the modern well constructed play he simply rings up an imaginary confederate and tells him what he is going to do could anything be more natural", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0024.flac", "answer": "TO BE OR NOT TO BE THAT IS THE QUESTION WHETHER TIS NOBLER", "subset": "test_clean", "task_type": "understanding", "prediction": "to be or not to be that is the question whether tis nobler", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0026.flac", "answer": "ENTER HAMLET WITH HIS FAVOURITE BOAR HOUND", "subset": "test_clean", "task_type": "understanding", "prediction": "enter hamlet with his favourite boarhound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0023.flac", "answer": "YOU GAVE ME DOUBLE FIVE I WANT DOUBLE NINE HALLO IS THAT YOU HORATIO HAMLET SPEAKING", "subset": "test_clean", "task_type": "understanding", "prediction": "you gave me double five i want double nine hello is that you horatio hamlet speaking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0008.flac", "answer": "LEND ME YOUR EAR FOR TEN MINUTES AND YOU SHALL LEARN JUST WHAT STAGECRAFT IS", "subset": "test_clean", "task_type": "understanding", "prediction": "lend me your ear for ten minutes and you shall learn just what stagecraft is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0044.flac", "answer": "BUT IT IS THE CIGARETTE WHICH CHIEFLY HAS BROUGHT THE MODERN DRAMA TO ITS PRESENT STATE OF PERFECTION", "subset": "test_clean", "task_type": "understanding", "prediction": "but it is the cigarette which chiefly has brought the modern drama to its present state of perfection", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0033.flac", "answer": "RELAPSES INTO SILENCE FOR THE REST OF THE EVENING", "subset": "test_clean", "task_type": "understanding", "prediction": "relapses into silence for the rest of the evening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0032.flac", "answer": "HOW YOU MAY BE WONDERING ARE YOU TO BEGIN YOUR MASTERPIECE", "subset": "test_clean", "task_type": "understanding", "prediction": "how you may be wondering are you to begin your masterpiece", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0003.flac", "answer": "YOUR PLAY MUST BE NOT MERELY A GOOD PLAY BUT A SUCCESSFUL ONE", "subset": "test_clean", "task_type": "understanding", "prediction": "your play must be not merely a good play but a successful one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0010.flac", "answer": "HAM TO BE OR NOT TO BE", "subset": "test_clean", "task_type": "understanding", "prediction": "ham to be or not to be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0028.flac", "answer": "LARKSPUR BIT ME AGAIN THIS MORNING FOR THE THIRD TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "larkspur bit me again this morning for the third time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0005.flac", "answer": "BUT SUPPOSE YOU SAID I'M FOND OF WRITING MY PEOPLE ALWAYS SAY MY LETTERS HOME ARE GOOD ENOUGH FOR PUNCH", "subset": "test_clean", "task_type": "understanding", "prediction": "but suppose you said i am fond of writing my people always say my letters home are good enough for punch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0014.flac", "answer": "IF IT BE GRANTED FIRST THAT THE THOUGHTS OF A CERTAIN CHARACTER SHOULD BE KNOWN TO THE AUDIENCE AND SECONDLY THAT SOLILOQUY OR THE HABIT OF THINKING ALOUD IS IN OPPOSITION TO MODERN STAGE TECHNIQUE HOW SHALL A SOLILOQUY BE AVOIDED WITHOUT DAMAGE TO THE PLAY", "subset": "test_clean", "task_type": "understanding", "prediction": "if it be granted first that the thoughts of a certain character should be known to the audience and secondly that soliloquy or the habit of thinking aloud is in opposition to modern stage technique how shall a soliloquy be avoided without damage to the play", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0036.flac", "answer": "THE CROWD DRIFTS OFF LEAVING THE HERO AND HEROINE ALONE IN THE MIDDLE OF THE STAGE AND THEN YOU CAN BEGIN", "subset": "test_clean", "task_type": "understanding", "prediction": "the crowd drifts off leaving the hero and heroine alone in the middle of the stage and then you can begin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0019.flac", "answer": "I WANT DOUBLE NINE HAL LO", "subset": "test_clean", "task_type": "understanding", "prediction": "i want double nine hello", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0001.flac", "answer": "IN SHORT HE BECOMES A PROMINENT FIGURE IN LONDON SOCIETY AND IF HE IS NOT CAREFUL SOMEBODY WILL SAY SO", "subset": "test_clean", "task_type": "understanding", "prediction": "in short he becomes a prominent figure in london society and if he is not careful somebody will say so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0013.flac", "answer": "WE MODERNS HOWEVER SEE THE ABSURDITY OF IT", "subset": "test_clean", "task_type": "understanding", "prediction": "we moderns however see the absurdity of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0043.flac", "answer": "TWO BITES ARE MADE AND THE BREAD IS CRUMBLED WITH AN AIR OF GREAT EAGERNESS INDEED ONE FEELS THAT IN REAL LIFE THE GUEST WOULD CLUTCH HOLD OF THE FOOTMAN AND SAY HALF A MO OLD CHAP I HAVEN'T NEARLY FINISHED BUT THE ACTOR IS BETTER SCHOOLED THAN THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "two bites are made and the bread is crumbled with an air of great eagerness indeed one feels that in real life the guest would clutch hold of the footman and say half a mould chap i haven nearly finished but the actor is better schooled than this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0017.flac", "answer": "IN THE OLD BADLY MADE PLAY IT WAS FREQUENTLY NECESSARY FOR ONE OF THE CHARACTERS TO TAKE THE AUDIENCE INTO HIS CONFIDENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "in the old badly made play it was frequently necessary for one of the characters to take the audience into his confidence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0035.flac", "answer": "THEN LORD TUPPENY WELL WHAT ABOUT AUCTION", "subset": "test_clean", "task_type": "understanding", "prediction": "then lord tuppenny well what about auction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0021.flac", "answer": "I SAY I'VE BEEN WONDERING ABOUT THIS BUSINESS", "subset": "test_clean", "task_type": "understanding", "prediction": "i say i have been wondering about this business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0025.flac", "answer": "IT IS TO LET HAMLET IF THAT HAPPEN TO BE THE NAME OF YOUR CHARACTER ENTER WITH A SMALL DOG PET FALCON MONGOOSE TAME BEAR OR WHATEVER ANIMAL IS MOST IN KEEPING WITH THE PART AND CONFIDE IN THIS ANIMAL SUCH SORROWS HOPES OR SECRET HISTORY AS THE AUDIENCE HAS GOT TO KNOW", "subset": "test_clean", "task_type": "understanding", "prediction": "it is to let hamlet if that happen to be the name of your character enter with a small dog pet falcon mongoose tame bear or whatever animal is most in keeping with the part and confide in this animal such sorrows hopes or secret history as the audience has got to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0022.flac", "answer": "TO BE OR NOT TO BE THAT IS THE QUESTION WHETHER TIS NOBLER IN THE MIND TO SUFFER THE SLINGS AND ARROWS WHAT NO HAMLET SPEAKING", "subset": "test_clean", "task_type": "understanding", "prediction": "to be or not to be that is the question whether tis nobler in the mind to suffer the slings and arrows what no hamlet speaking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0002.flac", "answer": "BUT EVEN THE UNSUCCESSFUL DRAMATIST HAS HIS MOMENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "but even the unsuccessful dramatist has his moments", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0038.flac", "answer": "A STAGE MEAL IS POPULAR BECAUSE IT PROVES TO THE AUDIENCE THAT THE ACTORS EVEN WHEN CALLED CHARLES HAWTREY OR OWEN NARES ARE REAL PEOPLE JUST LIKE YOU AND ME", "subset": "test_clean", "task_type": "understanding", "prediction": "a stage meal is popular because it proves to the audience that the actors even one called charles holtree or owen nares are real people just like you and me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0006.flac", "answer": "I'VE GOT A LITTLE IDEA FOR A PLAY ABOUT A MAN AND A WOMAN AND ANOTHER WOMAN AND BUT PERHAPS I'D BETTER KEEP THE PLOT A SECRET FOR THE MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "i have got a little idea for a play about a man and a woman and another woman and but perhaps i better keep the plot a secret for the moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0034.flac", "answer": "THE DUCHESS OF SOUTHBRIDGE TO LORD REGGIE OH REGGIE WHAT DID YOU SAY", "subset": "test_clean", "task_type": "understanding", "prediction": "the duchess of southbridge to lord reggie oh reggie what did you say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0045.flac", "answer": "LORD JOHN TAKING OUT GOLD CIGARETTE CASE FROM HIS LEFT HAND UPPER WAISTCOAT POCKET", "subset": "test_clean", "task_type": "understanding", "prediction": "lord john taking out gold cigarette case from his left hand upper waistcoat pocket", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0042.flac", "answer": "IN NOVELS THE HERO HAS OFTEN PUSHED HIS MEALS AWAY UNTASTED BUT NO STAGE HERO WOULD DO ANYTHING SO UNNATURAL AS THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "in novels the hero has often pushed his meals away untasted but no steed hero would do anything so unnatural as this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0012.flac", "answer": "INDEED IRRESOLUTION BEING THE KEYNOTE OF HAMLET'S SOLILOQUY A CLEVER PLAYER COULD TO SOME EXTENT INDICATE THE WHOLE THIRTY LINES BY A SILENT WORKING OF THE JAW BUT AT THE SAME TIME IT WOULD BE IDLE TO DENY THAT HE WOULD MISS THE FINER SHADES OF THE DRAMATIST'S MEANING", "subset": "test_clean", "task_type": "understanding", "prediction": "indeed irresolution being the keynote of hamlet s soliloquy a clever player could to some extent indicate the whole thirty lines by a silent working of the jaw but at the same time it would be idle to deny that he would miss the finer shades of the dramatist s meaning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0015.flac", "answer": "AND SO ON TILL YOU GET TO THE END WHEN OPHELIA MIGHT SAY AH YES OR SOMETHING NON COMMITTAL OF THAT SORT", "subset": "test_clean", "task_type": "understanding", "prediction": "and so on till you get to the end when ophelia might say ah yes or something noncommittal of that sort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0039.flac", "answer": "TEA PLEASE MATTHEWS BUTLER IMPASSIVELY", "subset": "test_clean", "task_type": "understanding", "prediction": "tea please matthews butler impassively", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0020.flac", "answer": "DOUBLE NINE TWO THREE ELSINORE DOUBLE NINE YES HALLO IS THAT YOU HORATIO HAMLET SPEAKING", "subset": "test_clean", "task_type": "understanding", "prediction": "double nine two three elsinore double knot yes hello is that you horatio hamlet speaking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0004.flac", "answer": "FRANKLY I CANNOT ALWAYS SAY", "subset": "test_clean", "task_type": "understanding", "prediction": "frankly i cannot always say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0027.flac", "answer": "LADY LARKSPUR STARTS SUDDENLY AND TURNS TOWARDS HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "lady larkspur started suddenly and turned toward him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0000.flac", "answer": "HE IS A WELCOME FIGURE AT THE GARDEN PARTIES OF THE ELECT WHO ARE ALWAYS READY TO ENCOURAGE HIM BY ACCEPTING FREE SEATS FOR HIS PLAY ACTOR MANAGERS NOD TO HIM EDITORS ALLOW HIM TO CONTRIBUTE WITHOUT CHARGE TO A SYMPOSIUM ON THE PRICE OF GOLF BALLS", "subset": "test_clean", "task_type": "understanding", "prediction": "he is a welcome figure at the garden parties of the elect who are always ready to encourage him by accepting free seats for his play actor managers nod to him editors allow him to contribute without charge to a symposium on the price of golf balls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0016.flac", "answer": "THIS WOULD BE AN EASY WAY OF DOING IT BUT IT WOULD NOT BE THE BEST WAY FOR THE REASON THAT IT IS TOO EASY TO CALL ATTENTION TO ITSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "this would be an easy way of doing it but it would not be the best way for the reason that it is too easy to call attention to itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0007.flac", "answer": "ANYHOW IT'S JOLLY EXCITING AND I CAN DO THE DIALOGUE ALL RIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "anyhow it is jolly exciting and i can do the dialogue all right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0031.flac", "answer": "AND THERE YOU ARE YOU WILL OF COURSE APPRECIATE THAT THE UNFINISHED SENTENCES NOT ONLY SAVE TIME BUT ALSO MAKE THE MANOEUVRING VERY MUCH MORE NATURAL", "subset": "test_clean", "task_type": "understanding", "prediction": "and there you are you will of course appreciate that the unfinished sentences not only save time but also make the manoeuvring very much more natural", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0037.flac", "answer": "THEN IS THE TIME TO INTRODUCE A MEAL ON THE STAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "then is the time to introduce a meal on the stage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0009.flac", "answer": "AND I SHOULD BEGIN WITH A SHORT HOMILY ON SOLILOQUY", "subset": "test_clean", "task_type": "understanding", "prediction": "and i should begin with a short homily on soliloquy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0040.flac", "answer": "HOSTESS REPLACES LUMP AND INCLINES EMPTY TEAPOT OVER TRAY FOR A MOMENT THEN HANDS HIM A CUP PAINTED BROWN INSIDE THUS DECEIVING THE GENTLEMAN WITH THE TELESCOPE IN THE UPPER CIRCLE", "subset": "test_clean", "task_type": "understanding", "prediction": "hostess replaces lamp and inclines empty teapot over tray for a moment then hands him a cup painted brown inside thus deceiving the gentleman with the telescope in the upper circle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0041.flac", "answer": "RE ENTER BUTLER AND THREE FOOTMEN WHO REMOVE THE TEA THINGS HOSTESS TO GUEST", "subset": "test_clean", "task_type": "understanding", "prediction": "reenter butler and three footmen who remove the tea things hostess to guest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0029.flac", "answer": "I WANT TO GET AWAY FROM IT ALL SWOONS", "subset": "test_clean", "task_type": "understanding", "prediction": "i want to get away from it all swoon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0030.flac", "answer": "ENTER LORD ARTHUR FLUFFINOSE", "subset": "test_clean", "task_type": "understanding", "prediction": "enter lord arthur fluffinose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/7176/92135/7176-92135-0011.flac", "answer": "NOW THE OBJECT OF THIS SOLILOQUY IS PLAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "now the object of this soliloquy is plain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0014.flac", "answer": "FORTUNATELY SAID MISTER VANDERPOOL NORTHERNERS AND SOUTHERNERS ARE ARRIVING AT A BETTER MUTUAL UNDERSTANDING ON MOST OF THESE MATTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "fortunately said mr vanderpool northerners and southerners are arriving at a better mutual understanding on most of these matters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0004.flac", "answer": "AS SHE AWAITED HER GUESTS SHE SURVEYED THE TABLE WITH BOTH SATISFACTION AND DISQUIETUDE FOR HER SOCIAL FUNCTIONS WERE FEW TONIGHT THERE WERE SHE CHECKED THEM OFF ON HER FINGERS SIR JAMES CREIGHTON THE RICH ENGLISH MANUFACTURER AND LADY CREIGHTON MISTER AND MISSUS VANDERPOOL MISTER HARRY CRESSWELL AND HIS SISTER JOHN TAYLOR AND HIS SISTER AND MISTER CHARLES SMITH WHOM THE EVENING PAPERS MENTIONED AS LIKELY TO BE UNITED STATES SENATOR FROM NEW JERSEY A SELECTION OF GUESTS THAT HAD BEEN DETERMINED UNKNOWN TO THE HOSTESS BY THE MEETING OF COTTON INTERESTS EARLIER IN THE DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "as she awaited her guests she surveyed the table with both satisfaction and disquietude for her social functions were few to night there were she checked them off on her fingers sir james crichton the rich english manufacturer and lady crichton mr and mrs vanderpool mr harry cresswell and his sister john taylor and his sister and mr charles smith whom the evening papers mentioned as likely to be united states senator from new jersey a selection of guests that had been determined unknown to the hostess by the meeting of cotton interests earlier in the day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0010.flac", "answer": "THE VANDERPOOLS WERE SURE OF THIS AND THE ENGLISHMAN INSTANCING INDIA BECAME QUITE ELOQUENT MISSUS GREY WAS MYSTIFIED BUT HARDLY DARED ADMIT IT THE GENERAL TREND OF THE CONVERSATION SEEMED TO BE THAT MOST INDIVIDUALS NEEDED TO BE SUBMITTED TO THE SHARPEST SCRUTINY BEFORE BEING ALLOWED MUCH EDUCATION AND AS FOR THE LOWER RACES IT WAS SIMPLY CRIMINAL TO OPEN SUCH USELESS OPPORTUNITIES TO THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "the vanderpools were sure of this and the englishman instancing india became quite eloquent mrs grey was mystified but hardly dared admit it the general trend of the conversation seemed to be that most individuals needed to be submitted to the sharpest scrutiny before being allowed much education and as for the lower races it was simply criminal to open such useless opportunities to them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0002.flac", "answer": "WHY SHOULD HE NOT BE AS OTHER MEN", "subset": "test_clean", "task_type": "understanding", "prediction": "why should he not be as other men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0009.flac", "answer": "BUT CRESSWELL ADDED SIGNIFICANTLY CAPACITY DIFFERS ENORMOUSLY BETWEEN RACES", "subset": "test_clean", "task_type": "understanding", "prediction": "but cresswell added significantly capacity differs enormously between races", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0011.flac", "answer": "POSITIVELY HEROIC ADDED CRESSWELL AVOIDING HIS SISTER'S EYES", "subset": "test_clean", "task_type": "understanding", "prediction": "positively heroic added cresswell avoiding his sister s eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0007.flac", "answer": "BUT YOU BELIEVE IN SOME EDUCATION ASKED MARY TAYLOR", "subset": "test_clean", "task_type": "understanding", "prediction": "do you believe in some education asked mary taylor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0008.flac", "answer": "I BELIEVE IN THE TRAINING OF PEOPLE TO THEIR HIGHEST CAPACITY THE ENGLISHMAN HERE HEARTILY SECONDED HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "i believe in the training of people to their highest capacity the englishman here heartily seconded him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0001.flac", "answer": "AT LAST THE COTTON COMBINE WAS TO ALL APPEARANCES AN ASSURED FACT AND HE WAS SLATED FOR THE SENATE", "subset": "test_clean", "task_type": "understanding", "prediction": "at last the cotton combine was to all appearances an assured fact and he was slated for the senate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0012.flac", "answer": "BUT WE'RE NOT ER EXACTLY WELCOMED", "subset": "test_clean", "task_type": "understanding", "prediction": "but we are not uh exactly welcome", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0003.flac", "answer": "SHE WAS NOT HERSELF A NOTABLY INTELLIGENT WOMAN SHE GREATLY ADMIRED INTELLIGENCE OR WHATEVER LOOKED TO HER LIKE INTELLIGENCE IN OTHERS", "subset": "test_clean", "task_type": "understanding", "prediction": "she was not herself a notably intelligent woman she greatly admired intelligence or whatever looked to her like intelligence in others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0013.flac", "answer": "MARY TAYLOR HOWEVER RELATED THE TALE OF ZORA TO MISSUS GREY'S PRIVATE EAR LATER", "subset": "test_clean", "task_type": "understanding", "prediction": "mary taylor however related the tale of zora to mrs gray s private ear later", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0006.flac", "answer": "SHE WAS THEREFORE MOST AGREEABLY SURPRISED TO HEAR MISTER CRESSWELL EXPRESS HIMSELF SO CORDIALLY AS APPROVING OF NEGRO EDUCATION", "subset": "test_clean", "task_type": "understanding", "prediction": "she was therefore most agreeably surprised to hear mr cresswell express himself so cordially as approving of negro education", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0000.flac", "answer": "THE HON CHARLES SMITH MISS SARAH'S BROTHER WAS WALKING SWIFTLY UPTOWN FROM MISTER EASTERLY'S WALL STREET OFFICE AND HIS FACE WAS PALE", "subset": "test_clean", "task_type": "understanding", "prediction": "the hon charles smith miss sarahs brother was walking swiftly uptown from mr easterlys wall street office and his face was pale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1836/1995-1836-0005.flac", "answer": "MISSUS GREY HAD MET SOUTHERNERS BEFORE BUT NOT INTIMATELY AND SHE ALWAYS HAD IN MIND VIVIDLY THEIR CRUELTY TO POOR NEGROES A SUBJECT SHE MADE A POINT OF INTRODUCING FORTHWITH", "subset": "test_clean", "task_type": "understanding", "prediction": "missus gray had met southerners before but not intimately and she always had in mind vividly their cruelty to poor negroes a subject she made a point of introducing forthwith", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0007.flac", "answer": "FIND SOME CRESSWELLS THERE BIG PLANTATIONS RATED AT TWO HUNDRED AND FIFTY THOUSAND DOLLARS", "subset": "test_clean", "task_type": "understanding", "prediction": "find some cresswells there big plantations rated at two hundred and fifty thousand dollars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0001.flac", "answer": "THE SOUTH SHE HAD NOT THOUGHT OF SERIOUSLY AND YET KNOWING OF ITS DELIGHTFUL HOSPITALITY AND MILD CLIMATE SHE WAS NOT AVERSE TO CHARLESTON OR NEW ORLEANS", "subset": "test_clean", "task_type": "understanding", "prediction": "the south she had not thought of seriously and yet knowing of its delightful hospitality and mild climate she was not averse to charleston or new orleans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0005.flac", "answer": "BUT JOHN THERE'S NO SOCIETY JUST ELEMENTARY WORK", "subset": "test_clean", "task_type": "understanding", "prediction": "but john there is no society just elementary work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0021.flac", "answer": "DON'T KNOW WELL OF ALL THINGS INWARDLY COMMENTED MISS TAYLOR LITERALLY BORN IN COTTON AND OH WELL AS MUCH AS TO ASK WHAT'S THE USE SHE TURNED AGAIN TO GO", "subset": "test_clean", "task_type": "understanding", "prediction": "dont know well of all things inwardly commented miss taylor literally born in cotton and oh well as much as to ask what is the use she turned again to go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0026.flac", "answer": "NOW FOR ONE LITTLE HALF HOUR SHE HAD BEEN A WOMAN TALKING TO A BOY NO NOT EVEN THAT SHE HAD BEEN TALKING JUST TALKING THERE WERE NO PERSONS IN THE CONVERSATION JUST THINGS ONE THING COTTON", "subset": "test_clean", "task_type": "understanding", "prediction": "now for one little half hour she had been a woman talking to a boy no not even that she had been talking just talking there were no persons in the conversation just things one thing cotton", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0004.flac", "answer": "MIGHT LEARN SOMETHING USEFUL DOWN THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "might learn something useful down there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0018.flac", "answer": "HER REGARD SHIFTED TO THE GREEN STALKS AND LEAVES AGAIN AND SHE STARTED TO MOVE AWAY", "subset": "test_clean", "task_type": "understanding", "prediction": "her regard shifted to the green stalks and leaves again and she started to move away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0019.flac", "answer": "COTTON IS A WONDERFUL THING IS IT NOT BOYS SHE SAID RATHER PRIMLY", "subset": "test_clean", "task_type": "understanding", "prediction": "cotton is a wonderful thing is it not boys she said rather primly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0023.flac", "answer": "GOOBERS DON'T GROW ON THE TOPS OF VINES BUT UNDERGROUND ON THE ROOTS LIKE YAMS IS THAT SO", "subset": "test_clean", "task_type": "understanding", "prediction": "gubbers dont grow on de tops of vines but on de ground on de roots like yams is that so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0014.flac", "answer": "COTTON SHE PAUSED", "subset": "test_clean", "task_type": "understanding", "prediction": "cotton she paused", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0010.flac", "answer": "AT ANY RATE I SAY GO", "subset": "test_clean", "task_type": "understanding", "prediction": "at any rate i say go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0008.flac", "answer": "SOME OTHERS TOO BIG COTTON COUNTY", "subset": "test_clean", "task_type": "understanding", "prediction": "some others too big cotton county", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0022.flac", "answer": "I SUPPOSE THOUGH IT'S TOO EARLY FOR THEM THEN CAME THE EXPLOSION", "subset": "test_clean", "task_type": "understanding", "prediction": "i suppose though it is too early for them then came the explosion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0003.flac", "answer": "BETTER GO HE HAD COUNSELLED SENTENTIOUSLY", "subset": "test_clean", "task_type": "understanding", "prediction": "better go he had counseled sententiously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0002.flac", "answer": "JOHN TAYLOR WHO HAD SUPPORTED HER THROUGH COLLEGE WAS INTERESTED IN COTTON", "subset": "test_clean", "task_type": "understanding", "prediction": "john taylor who had supported her through college was interested in cotton", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0024.flac", "answer": "THE GOLDEN FLEECE IT'S THE SILVER FLEECE HE HARKENED", "subset": "test_clean", "task_type": "understanding", "prediction": "the golden fleece it is the silver fleece he hearkened", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0020.flac", "answer": "MISS TAYLOR DID NOT KNOW MUCH ABOUT COTTON BUT AT LEAST ONE MORE REMARK SEEMED CALLED FOR", "subset": "test_clean", "task_type": "understanding", "prediction": "miss taylor did not know much about cotton but at least one more remark seemed called for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0016.flac", "answer": "THE GLIMMERING SEA OF DELICATE LEAVES WHISPERED AND MURMURED BEFORE HER STRETCHING AWAY TO THE NORTHWARD", "subset": "test_clean", "task_type": "understanding", "prediction": "the glimmering sea of delicate leaves whispered and murmured before her stretching away to the northward", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0009.flac", "answer": "YOU OUGHT TO KNOW JOHN IF I TEACH NEGROES I'LL SCARCELY SEE MUCH OF PEOPLE IN MY OWN CLASS", "subset": "test_clean", "task_type": "understanding", "prediction": "you ought to know john if i teach negroes i will scarcely see much of people in my own class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0000.flac", "answer": "IN THE DEBATE BETWEEN THE SENIOR SOCIETIES HER DEFENCE OF THE FIFTEENTH AMENDMENT HAD BEEN NOT ONLY A NOTABLE BIT OF REASONING BUT DELIVERED WITH REAL ENTHUSIASM", "subset": "test_clean", "task_type": "understanding", "prediction": "in the debate between the senior societies her defense of the fifteenth amendment had been not only a notable bit of reasoning but delivered with real enthusiasm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0011.flac", "answer": "HERE SHE WAS TEACHING DIRTY CHILDREN AND THE SMELL OF CONFUSED ODORS AND BODILY PERSPIRATION WAS TO HER AT TIMES UNBEARABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "here she was teaching dirty children and the smell of confused odors and bodily perspiration was to her at times unbearable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0017.flac", "answer": "THERE MIGHT BE A BIT OF POETRY HERE AND THERE BUT MOST OF THIS PLACE WAS SUCH DESPERATE PROSE", "subset": "test_clean", "task_type": "understanding", "prediction": "there might be a bit of poetry here and there but most of this place was such desperate prose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0025.flac", "answer": "SOME TIME YOU'LL TELL ME PLEASE WON'T YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "sometime you tell me please won t you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0006.flac", "answer": "BEEN LOOKING UP TOOMS COUNTY", "subset": "test_clean", "task_type": "understanding", "prediction": "been looking up tombs county", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0013.flac", "answer": "SO FOR THE HUNDREDTH TIME SHE WAS THINKING TODAY AS SHE WALKED ALONE UP THE LANE BACK OF THE BARN AND THEN SLOWLY DOWN THROUGH THE BOTTOMS", "subset": "test_clean", "task_type": "understanding", "prediction": "so for the hundredth time she was thinking to day as she walked alone up the lane back of the barn and then slowly down through the bottoms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0012.flac", "answer": "SHE WANTED A GLANCE OF THE NEW BOOKS AND PERIODICALS AND TALK OF GREAT PHILANTHROPIES AND REFORMS", "subset": "test_clean", "task_type": "understanding", "prediction": "she wanted a glance of the new books and periodicals and talk of great philanthropies and reforms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1826/1995-1826-0015.flac", "answer": "SHE HAD ALMOST FORGOTTEN THAT IT WAS HERE WITHIN TOUCH AND SIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "she had almost forgotten that it was here within touch and sight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0017.flac", "answer": "HE GAZED ABOUT PERPLEXED ASTONISHED", "subset": "test_clean", "task_type": "understanding", "prediction": "he gazed about perplexed astonished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0000.flac", "answer": "HE KNEW THE SILVER FLEECE HIS AND ZORA'S MUST BE RUINED", "subset": "test_clean", "task_type": "understanding", "prediction": "he knew the silver fleece his and zoraas must be ruined", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0010.flac", "answer": "PERHAPS SHE TOO MIGHT BE THERE WAITING WEEPING", "subset": "test_clean", "task_type": "understanding", "prediction": "perhaps she too might be there waiting weeping", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0006.flac", "answer": "THE WORLD WAS WATER VEILED IN MISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "the world was water veiled in mists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0009.flac", "answer": "THE LAGOON HAD BEEN LEVEL WITH THE DYKES A WEEK AGO AND NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "the lagoon had been level with the dikes a week ago and now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0028.flac", "answer": "THE CHAIR WAS EMPTY BUT HE KNEW", "subset": "test_clean", "task_type": "understanding", "prediction": "the chair was empty but he knew", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0007.flac", "answer": "THEN OF A SUDDEN AT MIDDAY THE SUN SHOT OUT HOT AND STILL NO BREATH OF AIR STIRRED THE SKY WAS LIKE BLUE STEEL THE EARTH STEAMED", "subset": "test_clean", "task_type": "understanding", "prediction": "then of a sudden at midday the sun shot out hot and still no breath of air stirred the sky was like blue steel the earth steamed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0024.flac", "answer": "FOR A WHILE SHE LAY IN HER CHAIR IN HAPPY DREAMY PLEASURE AT SUN AND BIRD AND TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "for a while she lay in her chair in happy dreamy pleasure at sun and bird and tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0020.flac", "answer": "THE YEARS OF THE DAYS OF HER DYING WERE TEN", "subset": "test_clean", "task_type": "understanding", "prediction": "the years of the days of her dying were ten", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0002.flac", "answer": "AH THE SWAMP THE CRUEL SWAMP", "subset": "test_clean", "task_type": "understanding", "prediction": "the swamp the cruel swamp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0027.flac", "answer": "ON SHE HURRIED UNTIL SWEEPING DOWN TO THE LAGOON AND THE ISLAND LO THE COTTON LAY BEFORE HER", "subset": "test_clean", "task_type": "understanding", "prediction": "on she hurried until sweeping down to the lagoon and the island lo the cotton lay before her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0021.flac", "answer": "THE HOPE AND DREAM OF HARVEST WAS UPON THE LAND", "subset": "test_clean", "task_type": "understanding", "prediction": "the hope and dream of harvest was upon the land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0001.flac", "answer": "IT WAS THE FIRST GREAT SORROW OF HIS LIFE IT WAS NOT SO MUCH THE LOSS OF THE COTTON ITSELF BUT THE FANTASY THE HOPES THE DREAMS BUILT AROUND IT", "subset": "test_clean", "task_type": "understanding", "prediction": "it was the first great sorrow of his life it was not so much the loss of the cotton itself but the fantasy the hopes the dreams built around it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0023.flac", "answer": "THE NET AND WEB OF ENDLESS THINGS HAD BEEN CRAWLING AND CREEPING AROUND HER SHE HAD STRUGGLED IN DUMB SPEECHLESS TERROR AGAINST SOME MIGHTY GRASPING THAT STROVE FOR HER LIFE WITH GNARLED AND CREEPING FINGERS BUT NOW AT LAST WEAKLY SHE OPENED HER EYES AND QUESTIONED", "subset": "test_clean", "task_type": "understanding", "prediction": "the net and web of endless things had been crawling and creeping around her she had struggled in dumb speechless terror against some mighty grasping that strove for her life with gnarled and creeping fingers but now at last weakly she opened her eyes and questioned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0011.flac", "answer": "HE STARTED AT THE THOUGHT HE HURRIED FORTH SADLY", "subset": "test_clean", "task_type": "understanding", "prediction": "he started at the thought he hurried forth sadly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0019.flac", "answer": "HE SAT DOWN WEAK BEWILDERED AND ONE THOUGHT WAS UPPERMOST ZORA", "subset": "test_clean", "task_type": "understanding", "prediction": "he sat down weak bewildered and one thought was uppermost sora", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0013.flac", "answer": "THEN HE LOOKED DOWN THE LAGOON WAS DRY", "subset": "test_clean", "task_type": "understanding", "prediction": "then he looked down the lagoon was dry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0026.flac", "answer": "SHE HAD BEEN BORN WITHIN ITS BORDERS WITHIN ITS BORDERS SHE HAD LIVED AND GROWN AND WITHIN ITS BORDERS SHE HAD MET HER LOVE", "subset": "test_clean", "task_type": "understanding", "prediction": "she had been born within its borders within its borders she had lived and grown and within its borders she had met her love", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0016.flac", "answer": "FOR ONE LONG MOMENT HE PAUSED STUPID AGAPE WITH UTTER AMAZEMENT THEN LEANED DIZZILY AGAINST A TREE", "subset": "test_clean", "task_type": "understanding", "prediction": "for one long moment he paused stupid agape with utter amazement then leaned dizzily against the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0018.flac", "answer": "HERE LAY THE READING OF THE RIDDLE WITH INFINITE WORK AND PAIN SOME ONE HAD DUG A CANAL FROM THE LAGOON TO THE CREEK INTO WHICH THE FORMER HAD DRAINED BY A LONG AND CROOKED WAY THUS ALLOWING IT TO EMPTY DIRECTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "here lay the reading of the riddle with infinite work and pains some one had dug a canal from the lagoon to the creek into which the former had drained by a long and crooked way thus allowing it to empty directly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0005.flac", "answer": "SHE WAS SO STRANGE AND HUMAN A CREATURE", "subset": "test_clean", "task_type": "understanding", "prediction": "she was so strange and human a creature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0012.flac", "answer": "HE SPLASHED AND STAMPED ALONG FARTHER AND FARTHER ONWARD UNTIL HE NEARED THE RAMPART OF THE CLEARING AND PUT FOOT UPON THE TREE BRIDGE", "subset": "test_clean", "task_type": "understanding", "prediction": "he splashed and stamped along farther and farther onward until he neared the rampart of the clearing and put foot upon the tree bridge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0004.flac", "answer": "HE PANTED TO KNOW IF SHE TOO KNEW OR KNEW AND CARED NOT OR CARED AND KNEW NOT", "subset": "test_clean", "task_type": "understanding", "prediction": "he panted to know if she too knew or knew and cared not or cared and knew not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0015.flac", "answer": "THE SQUARES OF COTTON SHARP EDGED HEAVY WERE JUST ABOUT TO BURST TO BOLLS", "subset": "test_clean", "task_type": "understanding", "prediction": "the squares of cotton sharp edged heavy were just about to burst to balls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0025.flac", "answer": "SHE ROSE WITH A FLEETING GLANCE GATHERED THE SHAWL ROUND HER THEN GLIDING FORWARD WAVERING TREMULOUS SLIPPED ACROSS THE ROAD AND INTO THE SWAMP", "subset": "test_clean", "task_type": "understanding", "prediction": "she rose with a fleeting glance gathered the shawl around her then gliding forward wavering tremulous slipped across the road and into the swamp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0008.flac", "answer": "WHERE WAS THE USE OF IMAGINING", "subset": "test_clean", "task_type": "understanding", "prediction": "where was the use of imagining", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0014.flac", "answer": "HE STOOD A MOMENT BEWILDERED THEN TURNED AND RUSHED UPON THE ISLAND A GREAT SHEET OF DAZZLING SUNLIGHT SWEPT THE PLACE AND BENEATH LAY A MIGHTY MASS OF OLIVE GREEN THICK TALL WET AND WILLOWY", "subset": "test_clean", "task_type": "understanding", "prediction": "he stood a moment bewildered then turned and rushed upon the island a great sheet of dazzling sunlight swept the place and beneath lay a mighty mass of olive green thick tall wet and willowy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0029.flac", "answer": "HE DARTED THROUGH THE TREES AND PAUSED A TALL MAN STRONGLY BUT SLIMLY MADE", "subset": "test_clean", "task_type": "understanding", "prediction": "he darted through the trees and paused a tall man strongly but slimly made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0003.flac", "answer": "THE REVELATION OF HIS LOVE LIGHTED AND BRIGHTENED SLOWLY TILL IT FLAMED LIKE A SUNRISE OVER HIM AND LEFT HIM IN BURNING WONDER", "subset": "test_clean", "task_type": "understanding", "prediction": "the revelation of his love lighted and brightened slowly till it flamed like a sunrise over him and left him in burning wonder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1995/1837/1995-1837-0022.flac", "answer": "UP IN THE SICK ROOM ZORA LAY ON THE LITTLE WHITE BED", "subset": "test_clean", "task_type": "understanding", "prediction": "up in the sick room zora lay on the little wide bed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0011.flac", "answer": "THE LORD WHO HAS GIVEN US POWER TO TEACH AND TO HEAR LET HIM ALSO GIVE US THE POWER TO SERVE AND TO DO LUKE TWO", "subset": "test_clean", "task_type": "understanding", "prediction": "the lord who has given us power to teach and to hear let him also give us the power to serve and to do luke two", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0008.flac", "answer": "IN OTHER WORDS THESE THREE MEN TOOK DOWN THE LECTURES WHICH LUTHER ADDRESSED TO HIS STUDENTS IN THE COURSE OF GALATIANS AND ROERER PREPARED THE MANUSCRIPT FOR THE PRINTER", "subset": "test_clean", "task_type": "understanding", "prediction": "in other words these three men took down the lectures which luther addressed to his students in the course of galatians and rorer prepared the manuscript for the printer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0009.flac", "answer": "IT PRESENTS LIKE NO OTHER OF LUTHER'S WRITINGS THE CENTRAL THOUGHT OF CHRISTIANITY THE JUSTIFICATION OF THE SINNER FOR THE SAKE OF CHRIST'S MERITS ALONE", "subset": "test_clean", "task_type": "understanding", "prediction": "it presents like no other of luther s writings the central thought of christianity the justification of the sinner for the sake of christ s merits alone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0007.flac", "answer": "MUCH LATER WHEN A FRIEND OF HIS WAS PREPARING AN EDITION OF ALL HIS LATIN WORKS HE REMARKED TO HIS HOME CIRCLE IF I HAD MY WAY ABOUT IT THEY WOULD REPUBLISH ONLY THOSE OF MY BOOKS WHICH HAVE DOCTRINE MY GALATIANS FOR INSTANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "much later when a friend of his was preparing an edition of all his latin works he remarked to his home circle if i had my way about it they would republish only those of my books which have doctrine my galatians for instance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0010.flac", "answer": "BUT THE ESSENCE OF LUTHER'S LECTURES IS THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "but the essence of luther s lectures is there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0006.flac", "answer": "A WORD SHOULD NOW BE SAID ABOUT THE ORIGIN OF LUTHER'S COMMENTARY ON GALATIANS", "subset": "test_clean", "task_type": "understanding", "prediction": "a word should now be said about the origin of luther s commentary on galatians", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0003.flac", "answer": "THE UNDERTAKING WHICH SEEMED SO ATTRACTIVE WHEN VIEWED AS A LITERARY TASK PROVED A MOST DIFFICULT ONE AND AT TIMES BECAME OPPRESSIVE", "subset": "test_clean", "task_type": "understanding", "prediction": "the undertaking which seemed so attractive when viewed as a literary task proved a most difficult one and at times became oppressive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0001.flac", "answer": "THE CONDITION IS THAT I WILL BE PERMITTED TO MAKE LUTHER TALK AMERICAN STREAMLINE HIM SO TO SPEAK BECAUSE YOU WILL NEVER GET PEOPLE WHETHER IN OR OUTSIDE THE LUTHERAN CHURCH ACTUALLY TO READ LUTHER UNLESS WE MAKE HIM TALK AS HE WOULD TALK TODAY TO AMERICANS", "subset": "test_clean", "task_type": "understanding", "prediction": "the condition is that i will be permitted to make luther talk american streamline him so to speak because you will never get people whether in or outside the lutheran church actually to read luther unless we make him talk as he would talk today to americans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0012.flac", "answer": "THE WORD OF OUR GOD SHALL STAND FOREVER", "subset": "test_clean", "task_type": "understanding", "prediction": "the word of our god shall stand forever", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0004.flac", "answer": "IT WAS WRITTEN IN LATIN", "subset": "test_clean", "task_type": "understanding", "prediction": "it was written in latin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0000.flac", "answer": "WE WANT YOU TO HELP US PUBLISH SOME LEADING WORK OF LUTHER'S FOR THE GENERAL AMERICAN MARKET WILL YOU DO IT", "subset": "test_clean", "task_type": "understanding", "prediction": "we want you to help us publish some leading work of luther s for the general american market will you do it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0005.flac", "answer": "THE WORK HAD TO BE CONDENSED", "subset": "test_clean", "task_type": "understanding", "prediction": "the work had to be condensed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3979/2830-3979-0002.flac", "answer": "LET US BEGIN WITH THAT HIS COMMENTARY ON GALATIANS", "subset": "test_clean", "task_type": "understanding", "prediction": "let us begin with that his commentary on galatians", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0046.flac", "answer": "WAS IT NOT ENOUGH TO SAY FROM GOD THE FATHER", "subset": "test_clean", "task_type": "understanding", "prediction": "was it not enough to say from god the father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0008.flac", "answer": "PAUL TAKES PRIDE IN HIS MINISTRY NOT TO HIS OWN PRAISE BUT TO THE PRAISE OF GOD", "subset": "test_clean", "task_type": "understanding", "prediction": "paul takes pride in his ministry not to his own praise but to the praise of god", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0036.flac", "answer": "WHEREVER THE MEANS OF GRACE ARE FOUND THERE IS THE HOLY CHURCH EVEN THOUGH ANTICHRIST REIGNS THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "wherever the means of grace are found there is the holy church even though antichrist reigns there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0038.flac", "answer": "GRACE BE TO YOU AND PEACE FROM GOD THE FATHER AND FROM OUR LORD JESUS CHRIST", "subset": "test_clean", "task_type": "understanding", "prediction": "grace be to you and peace from god the father and from our lord jesus christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0022.flac", "answer": "THE CLAUSE SEEMS SUPERFLUOUS ON FIRST SIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "the clause seems superfluous on first sight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0075.flac", "answer": "BUT THE REAL SIGNIFICANCE AND COMFORT OF THE WORDS FOR OUR SINS IS LOST UPON THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "but the real significance and comfort of the words for our sins is lost upon them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0005.flac", "answer": "DO YOU SUPPOSE THAT GOD FOR THE SAKE OF A FEW LUTHERAN HERETICS WOULD DISOWN HIS ENTIRE CHURCH", "subset": "test_clean", "task_type": "understanding", "prediction": "do you suppose that god for the sake of a few lutheran heretics would disown his entire church", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0018.flac", "answer": "I DID NOT THEN REALIZE THE IMPORTANCE OF THE MINISTRY", "subset": "test_clean", "task_type": "understanding", "prediction": "i did not then realize the importance of the ministry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0030.flac", "answer": "THEY DO NOT GO WHERE THE ENEMIES OF THE GOSPEL PREDOMINATE THEY GO WHERE THE CHRISTIANS ARE", "subset": "test_clean", "task_type": "understanding", "prediction": "they do not go where the enemies of the gospel predominate they go where the christians are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0052.flac", "answer": "WE ARE TO HEAR CHRIST WHO HAS BEEN APPOINTED BY THE FATHER AS OUR DIVINE TEACHER", "subset": "test_clean", "task_type": "understanding", "prediction": "we are to hear christ who has been appointed by the father as our divine teacher", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0015.flac", "answer": "FOR A PERSON TO POSSESS KNOWLEDGE IS NOT ENOUGH", "subset": "test_clean", "task_type": "understanding", "prediction": "for a person to possess knowledge is not enough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0065.flac", "answer": "PAUL ANSWERS THE MAN WHO IS NAMED JESUS CHRIST AND THE SON OF GOD GAVE HIMSELF FOR OUR SINS", "subset": "test_clean", "task_type": "understanding", "prediction": "paul answers the man who is named jesus christ and the son of god gave himself for our sins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0010.flac", "answer": "EITHER HE CALLS MINISTERS THROUGH THE AGENCY OF MEN OR HE CALLS THEM DIRECTLY AS HE CALLED THE PROPHETS AND APOSTLES", "subset": "test_clean", "task_type": "understanding", "prediction": "either he calls ministers through the agency of men or he calls them directly as he called the prophets and apostles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0073.flac", "answer": "THIS ATTITUDE SPRINGS FROM A FALSE CONCEPTION OF SIN THE CONCEPTION THAT SIN IS A SMALL MATTER EASILY TAKEN CARE OF BY GOOD WORKS THAT WE MUST PRESENT OURSELVES UNTO GOD WITH A GOOD CONSCIENCE THAT WE MUST FEEL NO SIN BEFORE WE MAY FEEL THAT CHRIST WAS GIVEN FOR OUR SINS", "subset": "test_clean", "task_type": "understanding", "prediction": "this attitude springs from a false conception of sin the conception that sin is a small matter easily taken care of by good works that we must present ourselves unto god with a good conscience that we must feel no sin before we may feel that christ was given for our sins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0011.flac", "answer": "PAUL DECLARES THAT THE FALSE APOSTLES WERE CALLED OR SENT NEITHER BY MEN NOR BY MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "paul declares that the false apostles were called or sent neither by men nor by man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0039.flac", "answer": "THE TERMS OF GRACE AND PEACE ARE COMMON TERMS WITH PAUL AND ARE NOW PRETTY WELL UNDERSTOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "the terms of grace and peace are common terms with paul and are now pretty well understood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0031.flac", "answer": "WHY DO THEY NOT INVADE THE CATHOLIC PROVINCES AND PREACH THEIR DOCTRINE TO GODLESS PRINCES BISHOPS AND DOCTORS AS WE HAVE DONE BY THE HELP OF GOD", "subset": "test_clean", "task_type": "understanding", "prediction": "why do they not invade the catholic provinces and preach their doctrine to godless princes bishops and doctors as we have done by the help of god", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0003.flac", "answer": "PAUL CAME LATER AND IS BENEATH US", "subset": "test_clean", "task_type": "understanding", "prediction": "paul came later and is beneath us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0072.flac", "answer": "THIS PASSAGE THEN BEARS OUT THE FACT THAT ALL MEN ARE SOLD UNDER SIN", "subset": "test_clean", "task_type": "understanding", "prediction": "this passage then bears out the fact that all men are sold under sin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0013.flac", "answer": "HE MENTIONS THE APOSTLES FIRST BECAUSE THEY WERE APPOINTED DIRECTLY BY GOD", "subset": "test_clean", "task_type": "understanding", "prediction": "he mentions the apostles first because they were appointed directly by god", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0032.flac", "answer": "WE LOOK FOR THAT REWARD WHICH EYE HATH NOT SEEN NOR EAR HEARD NEITHER HATH ENTERED INTO THE HEART OF MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "we look for that reward which eye hath not seen nor ear heard neither hath entered into the heart of man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0019.flac", "answer": "I KNEW NOTHING OF THE DOCTRINE OF FAITH BECAUSE WE WERE TAUGHT SOPHISTRY INSTEAD OF CERTAINTY AND NOBODY UNDERSTOOD SPIRITUAL BOASTING", "subset": "test_clean", "task_type": "understanding", "prediction": "i knew nothing of the doctrine of faith because we were taught sophistry instead of certainty and nobody understood spiritual boasting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0034.flac", "answer": "THESE MEANS CANNOT BE CONTAMINATED", "subset": "test_clean", "task_type": "understanding", "prediction": "these means cannot be contaminated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0053.flac", "answer": "AT THE SAME TIME PAUL CONFIRMS OUR CREED THAT CHRIST IS VERY GOD", "subset": "test_clean", "task_type": "understanding", "prediction": "at the same time paul confirms our creed that christ is very god", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0035.flac", "answer": "THEY REMAIN DIVINE REGARDLESS OF MEN'S OPINION", "subset": "test_clean", "task_type": "understanding", "prediction": "they remain divine regardless of men s opinion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0023.flac", "answer": "THESE PERVERTERS OF THE RIGHTEOUSNESS OF CHRIST RESIST THE FATHER AND THE SON AND THE WORKS OF THEM BOTH", "subset": "test_clean", "task_type": "understanding", "prediction": "these perverters of the righteousness of christ resist the father and the son and the works of them both", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0002.flac", "answer": "HE WAS THE LAST TO TURN TO CHRIST", "subset": "test_clean", "task_type": "understanding", "prediction": "he was the last to turn to christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0066.flac", "answer": "SINCE CHRIST WAS GIVEN FOR OUR SINS IT STANDS TO REASON THAT THEY CANNOT BE PUT AWAY BY OUR OWN EFFORTS", "subset": "test_clean", "task_type": "understanding", "prediction": "since christ was given for our sins it stands to reason that they cannot be put away by our own efforts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0012.flac", "answer": "THE MOST THEY COULD CLAIM IS THAT THEY WERE SENT BY OTHERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the most they could claim is that they were sent by others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0004.flac", "answer": "INDEED HE PERSECUTED THE CHURCH OF CHRIST FOR A LONG TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "indeed he persecuted the church of christ for a long time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0033.flac", "answer": "NOT ALL THE GALATIANS HAD BECOME PERVERTED", "subset": "test_clean", "task_type": "understanding", "prediction": "not all the galatians had become perverted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0014.flac", "answer": "THE CALL IS NOT TO BE TAKEN LIGHTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "the call is not to be taken lightly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0047.flac", "answer": "TO DO SO IS TO LOSE GOD ALTOGETHER BECAUSE GOD BECOMES INTOLERABLE WHEN WE SEEK TO MEASURE AND TO COMPREHEND HIS INFINITE MAJESTY", "subset": "test_clean", "task_type": "understanding", "prediction": "to do so is to lose god altogether because god becomes intolerable when we seek to measure and to comprehend his infinite majesty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0055.flac", "answer": "TO BESTOW PEACE AND GRACE LIES IN THE PROVINCE OF GOD WHO ALONE CAN CREATE THESE BLESSINGS THE ANGELS CANNOT", "subset": "test_clean", "task_type": "understanding", "prediction": "to bestow peace and grace lies in the province of god who alone can create these blessings the angels cannot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0027.flac", "answer": "AND ALL THE BRETHREN WHICH ARE WITH ME", "subset": "test_clean", "task_type": "understanding", "prediction": "and all the brethren which are with me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0001.flac", "answer": "THEY SAID TO THE GALATIANS YOU HAVE NO RIGHT TO THINK HIGHLY OF PAUL", "subset": "test_clean", "task_type": "understanding", "prediction": "they said to the galatians you have no right to think highly of paul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0041.flac", "answer": "GRACE INVOLVES THE REMISSION OF SINS PEACE AND A HAPPY CONSCIENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "grace involves the remission of sins peace and a happy conscience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0000.flac", "answer": "IN EVERY WAY THEY SOUGHT TO UNDERMINE THE AUTHORITY OF SAINT PAUL", "subset": "test_clean", "task_type": "understanding", "prediction": "in every way they sought to undermine the authority of saint paul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0044.flac", "answer": "HOWEVER THE GRACE AND PEACE OF GOD WILL", "subset": "test_clean", "task_type": "understanding", "prediction": "however the grace and peace of god will", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0070.flac", "answer": "BUT WE ARE CARELESS WE MAKE LIGHT OF SIN", "subset": "test_clean", "task_type": "understanding", "prediction": "but we are careless we make light of sin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0049.flac", "answer": "EMBRACE HIM AND FORGET ABOUT THE NATURE OF GOD", "subset": "test_clean", "task_type": "understanding", "prediction": "embrace him and forget about the nature of god", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0009.flac", "answer": "PAUL AN APOSTLE NOT OF MEN ET CETERA", "subset": "test_clean", "task_type": "understanding", "prediction": "paul an apostle not of men etc", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0056.flac", "answer": "OTHERWISE PAUL SHOULD HAVE WRITTEN GRACE FROM GOD THE FATHER AND PEACE FROM OUR LORD JESUS CHRIST", "subset": "test_clean", "task_type": "understanding", "prediction": "otherwise paul should have written grace from god the father and peace from our lord jesus christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0064.flac", "answer": "HOW MAY WE OBTAIN REMISSION OF OUR SINS", "subset": "test_clean", "task_type": "understanding", "prediction": "how may we obtain remission of our sins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0021.flac", "answer": "AND GOD THE FATHER WHO RAISED HIM FROM THE DEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "and god the father who raised him from the dead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0025.flac", "answer": "BY HIS RESURRECTION CHRIST WON THE VICTORY OVER LAW SIN FLESH WORLD DEVIL DEATH HELL AND EVERY EVIL", "subset": "test_clean", "task_type": "understanding", "prediction": "by his resurrection christ won the victory over law sin flesh world devil death hell and every evil", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0060.flac", "answer": "HE NEVER LOSES SIGHT OF THE PURPOSE OF HIS EPISTLE", "subset": "test_clean", "task_type": "understanding", "prediction": "he never loses sight of the purpose of his epistle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0043.flac", "answer": "EXPERIENCE PROVES THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "experience proves this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0040.flac", "answer": "THE GREETING OF THE APOSTLE IS REFRESHING", "subset": "test_clean", "task_type": "understanding", "prediction": "the greeting of the apostle is refreshing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0017.flac", "answer": "WHEN I WAS A YOUNG MAN I THOUGHT PAUL WAS MAKING TOO MUCH OF HIS CALL", "subset": "test_clean", "task_type": "understanding", "prediction": "when i was a young man i thought paul was making too much of his call", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0028.flac", "answer": "THIS SHOULD GO FAR IN SHUTTING THE MOUTHS OF THE FALSE APOSTLES", "subset": "test_clean", "task_type": "understanding", "prediction": "this should go far in shutting the mouths of the false apostles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0042.flac", "answer": "THE WORLD BRANDS THIS A PERNICIOUS DOCTRINE", "subset": "test_clean", "task_type": "understanding", "prediction": "the world brands this a pernicious doctrine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0057.flac", "answer": "THE ARIANS TOOK CHRIST FOR A NOBLE AND PERFECT CREATURE SUPERIOR EVEN TO THE ANGELS BECAUSE BY HIM GOD CREATED HEAVEN AND EARTH", "subset": "test_clean", "task_type": "understanding", "prediction": "the arians took christ for a noble and perfect creature superior even to the angels because by him god created heaven and earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0061.flac", "answer": "NOT GOLD OR SILVER OR PASCHAL LAMBS OR AN ANGEL BUT HIMSELF WHAT FOR", "subset": "test_clean", "task_type": "understanding", "prediction": "not gold or silver or paschal lambs or an angel but himself what for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0069.flac", "answer": "THE VICIOUS CHARACTER OF SIN IS BROUGHT OUT BY THE WORDS WHO GAVE HIMSELF FOR OUR SINS", "subset": "test_clean", "task_type": "understanding", "prediction": "the vicious character of sin is brought out by the words who gave himself for our sins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0006.flac", "answer": "AGAINST THESE BOASTING FALSE APOSTLES PAUL BOLDLY DEFENDS HIS APOSTOLIC AUTHORITY AND MINISTRY", "subset": "test_clean", "task_type": "understanding", "prediction": "against these boasting false apostles paul boldly defends his apostolic authority and ministry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0045.flac", "answer": "MEN SHOULD NOT SPECULATE ABOUT THE NATURE OF GOD", "subset": "test_clean", "task_type": "understanding", "prediction": "men should not speculate about the nature of god", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0074.flac", "answer": "THIS ATTITUDE IS UNIVERSAL AND PARTICULARLY DEVELOPED IN THOSE WHO CONSIDER THEMSELVES BETTER THAN OTHERS", "subset": "test_clean", "task_type": "understanding", "prediction": "this attitude is universal and particularly developed in those who consider themselves better than others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0076.flac", "answer": "ON THE OTHER HAND WE ARE NOT TO REGARD THEM AS SO TERRIBLE THAT WE MUST DESPAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "on the other hand we are not to regard them as so terrible that we must despair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0016.flac", "answer": "IT SPOILS ONE'S BEST WORK", "subset": "test_clean", "task_type": "understanding", "prediction": "it spoils ones best work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0058.flac", "answer": "MOHAMMED ALSO SPEAKS HIGHLY OF CHRIST", "subset": "test_clean", "task_type": "understanding", "prediction": "mahomet also speaks highly of christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0059.flac", "answer": "PAUL STICKS TO HIS THEME", "subset": "test_clean", "task_type": "understanding", "prediction": "paul sticks to his theme", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0063.flac", "answer": "UNDERSCORE THESE WORDS FOR THEY ARE FULL OF COMFORT FOR SORE CONSCIENCES", "subset": "test_clean", "task_type": "understanding", "prediction": "underscore these words for they are full of comfort for sore consciences", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0054.flac", "answer": "THAT CHRIST IS VERY GOD IS APPARENT IN THAT PAUL ASCRIBES TO HIM DIVINE POWERS EQUALLY WITH THE FATHER AS FOR INSTANCE THE POWER TO DISPENSE GRACE AND PEACE", "subset": "test_clean", "task_type": "understanding", "prediction": "that christ is very god is apparent in that paul ascribes to him divine powers equally with the father as for instance the power to dispense grace and peace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0024.flac", "answer": "IN THIS WHOLE EPISTLE PAUL TREATS OF THE RESURRECTION OF CHRIST", "subset": "test_clean", "task_type": "understanding", "prediction": "in this whole epistle paul treats of the resurrection of christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0029.flac", "answer": "ALTHOUGH THE BRETHREN WITH ME ARE NOT APOSTLES LIKE MYSELF YET THEY ARE ALL OF ONE MIND WITH ME THINK WRITE AND TEACH AS I DO", "subset": "test_clean", "task_type": "understanding", "prediction": "although the brethren with me are not apostles like myself yet they are all of one mind with me think write and teach as i do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0051.flac", "answer": "WHEN YOU ARGUE ABOUT THE NATURE OF GOD APART FROM THE QUESTION OF JUSTIFICATION YOU MAY BE AS PROFOUND AS YOU LIKE", "subset": "test_clean", "task_type": "understanding", "prediction": "when you argue about the nature of god apart from the question of justification you may be as profound as you like", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0048.flac", "answer": "HE CAME DOWN TO EARTH LIVED AMONG MEN SUFFERED WAS CRUCIFIED AND THEN HE DIED STANDING CLEARLY BEFORE US SO THAT OUR HEARTS AND EYES MAY FASTEN UPON HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "he came down to earth lived among men suffered was crucified and then he died standing clearly before us so that our hearts and eyes may fasten upon him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0062.flac", "answer": "NOT FOR A CROWN OR A KINGDOM OR OUR GOODNESS BUT FOR OUR SINS", "subset": "test_clean", "task_type": "understanding", "prediction": "not for a crown or a kingdom or our goodness but for our sins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1840, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0026.flac", "answer": "VERSE TWO", "subset": "test_clean", "task_type": "understanding", "prediction": "verse two", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1841, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0068.flac", "answer": "THE GREATNESS OF THE RANSOM CHRIST THE SON OF GOD INDICATES THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "the greatness of the ransom christ the son of god indicates this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1842, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0020.flac", "answer": "THIS IS NO SINFUL PRIDE IT IS HOLY PRIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "this is no sinful pride it is holy pride", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1843, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0071.flac", "answer": "WE THINK THAT BY SOME LITTLE WORK OR MERIT WE CAN DISMISS SIN", "subset": "test_clean", "task_type": "understanding", "prediction": "we think that by some little work or merit we can dismiss sin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1844, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0067.flac", "answer": "THIS SENTENCE ALSO DEFINES OUR SINS AS GREAT SO GREAT IN FACT THAT THE WHOLE WORLD COULD NOT MAKE AMENDS FOR A SINGLE SIN", "subset": "test_clean", "task_type": "understanding", "prediction": "this sentence also defines our sins as great so great in fact that the whole world could not make amends for a single sin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1845, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0007.flac", "answer": "AS THE AMBASSADOR OF A GOVERNMENT IS HONORED FOR HIS OFFICE AND NOT FOR HIS PRIVATE PERSON SO THE MINISTER OF CHRIST SHOULD EXALT HIS OFFICE IN ORDER TO GAIN AUTHORITY AMONG MEN", "subset": "test_clean", "task_type": "understanding", "prediction": "as the ambassador of a government is honored for his office and not for his private person so the minister of christ should exalt his office in order to gain authority among men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1846, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0050.flac", "answer": "DID NOT CHRIST HIMSELF SAY I AM THE WAY AND THE TRUTH AND THE LIFE NO MAN COMETH UNTO THE FATHER BUT BY ME", "subset": "test_clean", "task_type": "understanding", "prediction": "did not christ himself say i am the way and the truth and the life no man cometh unto the father but by me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1847, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/2830/3980/2830-3980-0037.flac", "answer": "SO MUCH FOR THE TITLE OF THE EPISTLE NOW FOLLOWS THE GREETING OF THE APOSTLE VERSE THREE", "subset": "test_clean", "task_type": "understanding", "prediction": "so much for the title of the epistle now follows the greeting of the apostle verse three", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1848, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0020.flac", "answer": "AS A SAMPLE OF THE PRESS COMMENTS AGAINST THE BRUTALITY OF THE MISSOURIANS I QUOTE A PARAGRAPH FROM THE QUINCY ARGUS MARCH SIXTEENTH EIGHTEEN THIRTY NINE", "subset": "test_clean", "task_type": "understanding", "prediction": "as a sample of the press comments against the brutality of the missourians i quote a paragraph from the quincy argus march sixteenth eighteen thirty nine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1849, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0011.flac", "answer": "SOON THOUSANDS OF CONVERTS HAD RENTED OR PURCHASED HOMES IN MISSOURI INDEPENDENCE JACKSON COUNTY BEING THEIR CENTER BUT FROM THE FIRST THEY WERE UNPOPULAR AMONG THE MISSOURIANS", "subset": "test_clean", "task_type": "understanding", "prediction": "soon thousands of converts had rented or purchased homes in missouri independence jackson county being their center but from the first they were unpopular among the missourians", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1850, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0016.flac", "answer": "BE IT SAID TO THE HONOR OF SOME OF THE OFFICERS ENTRUSTED WITH THE TERRIBLE COMMISSION THAT WHEN THEY LEARNED ITS TRUE SIGNIFICANCE THEY RESIGNED THEIR AUTHORITY RATHER THAN HAVE ANYTHING TO DO WITH WHAT THEY DESIGNATED A COLD BLOODED BUTCHERY", "subset": "test_clean", "task_type": "understanding", "prediction": "be it said to the honor of some of the officers intrusted with the terrible commission that when they learned its true significance they resigned their authority rather than have anything to do with what they designated a cold blooded butchery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1851, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0008.flac", "answer": "IT IS NOTABLE THAT THE INDIAN TRIBES HAVE GENERALLY REGARDED THE RELIGION OF THE LATTER DAY SAINTS WITH FAVOR SEEING IN THE BOOK OF MORMON STRIKING AGREEMENT WITH THEIR OWN TRADITIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "it is notable that the indian tribes have generally regarded the religion of the latter day saints with favor seeing in the book of mormon striking agreement with their own traditions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1852, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0021.flac", "answer": "IT WILL BE OBSERVED THAT AN ORGANIZED MOB AIDED BY MANY OF THE CIVIL AND MILITARY OFFICERS OF MISSOURI WITH GOVERNOR BOGGS AT THEIR HEAD HAVE BEEN THE PROMINENT ACTORS IN THIS BUSINESS INCITED TOO IT APPEARS AGAINST THE MORMONS BY POLITICAL HATRED AND BY THE ADDITIONAL MOTIVES OF PLUNDER AND REVENGE", "subset": "test_clean", "task_type": "understanding", "prediction": "it will be observed that an organized mob aided by many of the civil and military officers of missouri with governor boggs at their head have been the prominent actors in this business incited too it appears against the mormons by political hatred and by the additional motives of plunder and revenge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1853, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0018.flac", "answer": "AMERICAN SCHOOL BOYS READ WITH EMOTIONS OF HORROR OF THE ALBIGENSES DRIVEN BEATEN AND KILLED WITH A PAPAL LEGATE DIRECTING THE BUTCHERY AND OF THE VAUDOIS HUNTED AND HOUNDED LIKE BEASTS AS THE EFFECT OF A ROYAL DECREE AND THEY YET SHALL READ IN THE HISTORY OF THEIR OWN COUNTRY OF SCENES AS TERRIBLE AS THESE IN THE EXHIBITION OF INJUSTICE AND INHUMAN HATE", "subset": "test_clean", "task_type": "understanding", "prediction": "american schoolboys read with emotions of horror of the albigenses driven beaten and killed with a papal legate directing the butchery and of the vaudois hunted and hounded like beasts as the effect of a royal decree and they yet shall read in the history of their own country of scenes as terrible as these in the exhibition of injustice and inhuman hate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1854, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0014.flac", "answer": "MAKING THEIR WAY ACROSS THE RIVER MOST OF THE REFUGEES FOUND SHELTER AMONG THE MORE HOSPITABLE PEOPLE OF CLAY COUNTY AND AFTERWARD ESTABLISHED THEMSELVES IN CALDWELL COUNTY THEREIN FOUNDING THE CITY OF FAR WEST", "subset": "test_clean", "task_type": "understanding", "prediction": "making their way across the river most of the refugees found shelter among the more hospitable people of clay county and afterward established themselves in caldwell county therein founding the city of far west", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1855, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0002.flac", "answer": "INSTEAD OF BUT SIX REGULARLY AFFILIATED MEMBERS AND AT MOST TWO SCORE OF ADHERENTS THE ORGANIZATION NUMBERS TODAY MANY HUNDRED THOUSAND SOULS", "subset": "test_clean", "task_type": "understanding", "prediction": "instead of but six regularly affiliated members and at most two score of adherents the organization numbers today many hundred thousand souls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1856, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0006.flac", "answer": "THEIR EYES WERE FROM THE FIRST TURNED IN ANTICIPATION TOWARD THE EVENING SUN NOT MERELY THAT THE WORK OF PROSELYTING SHOULD BE CARRIED ON IN THE WEST BUT THAT THE HEADQUARTERS OF THE CHURCH SHOULD BE THERE ESTABLISHED", "subset": "test_clean", "task_type": "understanding", "prediction": "their eyes were from the first turned in anticipation toward the evening sun not merely that the work of proselyting should be carried on in the west but that the headquarters of the church should be there established", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1857, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0004.flac", "answer": "THE PRACTISE OF GATHERING ITS PROSELYTES INTO ONE PLACE PREVENTS THE BUILDING UP AND STRENGTHENING OF FOREIGN BRANCHES AND INASMUCH AS EXTENSIVE AND STRONG ORGANIZATIONS ARE SELDOM MET WITH ABROAD VERY ERRONEOUS IDEAS EXIST CONCERNING THE STRENGTH OF THE CHURCH", "subset": "test_clean", "task_type": "understanding", "prediction": "the practice of gathering its proselytes into one place prevents the building up and strengthening of foreign branches and inasmuch as extensive and strong organizations are seldom met with abroad very erroneous ideas exist concerning the strength of the church", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1858, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0010.flac", "answer": "TO THE FERVENT LATTER DAY SAINT A TEMPLE IS NOT SIMPLY A CHURCH BUILDING A HOUSE FOR RELIGIOUS ASSEMBLY", "subset": "test_clean", "task_type": "understanding", "prediction": "to the fervent latter day saint a temple is not simply a church building a house for religious assembly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1859, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0019.flac", "answer": "WHO BEGAN THE QUARREL WAS IT THE MORMONS", "subset": "test_clean", "task_type": "understanding", "prediction": "who began the quarrel was it the mormons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1860, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0001.flac", "answer": "ITS ORIGIN WAS SMALL A GERM AN INSIGNIFICANT SEED HARDLY TO BE THOUGHT OF AS LIKELY TO AROUSE OPPOSITION", "subset": "test_clean", "task_type": "understanding", "prediction": "its origin was small a germ an insignificant seed hardly to be thought of as likely to arouse opposition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1861, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0003.flac", "answer": "IN PLACE OF A SINGLE HAMLET IN THE SMALLEST CORNER OF WHICH THE MEMBERS COULD HAVE CONGREGATED THERE NOW ARE ABOUT SEVENTY STAKES OF ZION AND ABOUT SEVEN HUNDRED ORGANIZED WARDS EACH WARD AND STAKE WITH ITS FULL COMPLEMENT OF OFFICERS AND PRIESTHOOD ORGANIZATIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "in place of a single hamlet in the smallest corner of which the members could have congregated there now are about seventy stakes of zion and about seven hundred organized wards each ward and stake with its full complement of officers and priesthood organizations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1862, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0009.flac", "answer": "THE FIRST WELL ESTABLISHED SEAT OF THE CHURCH WAS IN THE PRETTY LITTLE TOWN OF KIRTLAND OHIO ALMOST WITHIN SIGHT OF LAKE ERIE AND HERE SOON ROSE THE FIRST TEMPLE OF MODERN TIMES", "subset": "test_clean", "task_type": "understanding", "prediction": "the first well established seat of the church was in the pretty little town of kirtland ohio almost within sight of lake erie and here soon rose the first temple of modern times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1863, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0013.flac", "answer": "THEIR SUFFERINGS HAVE NEVER YET BEEN FITLY CHRONICLED BY HUMAN SCRIBE", "subset": "test_clean", "task_type": "understanding", "prediction": "their sufferings have never yet been fitly chronicled by human scribe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1864, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0000.flac", "answer": "ON THE SIXTH OF APRIL EIGHTEEN THIRTY THE CHURCH OF JESUS CHRIST OF LATTER DAY SAINTS WAS FORMALLY ORGANIZED AND THUS TOOK ON A LEGAL EXISTENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "on the sixth of april eighteen thirty the church of jesus christ of latter day saints was formally organized and thus took on a legal existence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1865, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0012.flac", "answer": "THE LIEUTENANT GOVERNOR LILBURN W BOGGS AFTERWARD GOVERNOR WAS A PRONOUNCED MORMON HATER AND THROUGHOUT THE PERIOD OF THE TROUBLES HE MANIFESTED SYMPATHY WITH THE PERSECUTORS", "subset": "test_clean", "task_type": "understanding", "prediction": "the lieutenant governor lilburn w boggs afterward governor was a pronounced mormon hater and throughout the period of the troubles he manifested his sympathy with the persecutors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1866, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0005.flac", "answer": "NEVERTHELESS THE MUSTARD SEED AMONG THE SMALLEST OF ALL SEEDS HAS ATTAINED THE PROPORTIONS OF A TREE AND THE BIRDS OF THE AIR ARE NESTING IN ITS BRANCHES THE ACORN IS NOW AN OAK OFFERING PROTECTION AND THE SWEETS OF SATISFACTION TO EVERY EARNEST PILGRIM JOURNEYING ITS WAY FOR TRUTH", "subset": "test_clean", "task_type": "understanding", "prediction": "nevertheless the mustard seed among the smallest of all seeds has attained the proportions of a tree and the birds of the air are nesting in its branches the acorn is now an oak offering protection and the sweets of satisfaction to every earnest pilgrim journeying its way for truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1867, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0015.flac", "answer": "A SMALL SETTLEMENT HAD BEEN FOUNDED BY MORMON FAMILIES ON SHOAL CREEK AND HERE ON THE THIRTIETH OF OCTOBER EIGHTEEN THIRTY EIGHT A COMPANY OF TWO HUNDRED AND FORTY FELL UPON THE HAPLESS SETTLERS AND BUTCHERED A SCORE", "subset": "test_clean", "task_type": "understanding", "prediction": "a small settlement had been founded by mormon families on shoal creek and here on the thirtieth of october eighteen thirty eight a company of two hundred and forty fell upon the hapless settlers and butchered a score", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1868, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0007.flac", "answer": "THE BOOK OF MORMON HAD TAUGHT THE PEOPLE THE TRUE ORIGIN AND DESTINY OF THE AMERICAN INDIANS AND TOWARD THIS DARK SKINNED REMNANT OF A ONCE MIGHTY PEOPLE THE MISSIONARIES OF MORMONISM EARLY TURNED THEIR EYES AND WITH THEIR EYES WENT THEIR HEARTS AND THEIR HOPES", "subset": "test_clean", "task_type": "understanding", "prediction": "the book of mormon had taught the people the true origin and destiny of the american indians and toward this dark skinned remnant of a once mighty people the missionaries of mormonism early turned their eyes and with their eyes went their hearts and their hopes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1869, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13751/4077-13751-0017.flac", "answer": "OH WHAT A RECORD TO READ WHAT A PICTURE TO GAZE UPON HOW AWFUL THE FACT", "subset": "test_clean", "task_type": "understanding", "prediction": "oh what a record to read what a picture to gaze upon how awful the fact", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1870, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0003.flac", "answer": "MOREOVER HAD THE PEOPLE BEEN INCLINED TO REBELLION WHAT GREATER OPPORTUNITY COULD THEY HAVE WISHED", "subset": "test_clean", "task_type": "understanding", "prediction": "moreover had the people been inclined to rebellion what greater opportunity could they have wished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1871, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0010.flac", "answer": "IN EIGHTEEN SIXTY TWO A LAW WAS ENACTED WITH THE PURPOSE OF SUPPRESSING PLURAL MARRIAGE AND AS HAD BEEN PREDICTED IN THE NATIONAL SENATE PRIOR TO ITS PASSAGE IT LAY FOR MANY YEARS A DEAD LETTER", "subset": "test_clean", "task_type": "understanding", "prediction": "in eighteen sixty two a law was enacted with the purpose of suppressing plural marriage and as had been predicted in the national senate prior to its passage it lay for many years a dead letter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1872, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0004.flac", "answer": "ALREADY A NORTH AND A SOUTH WERE TALKED OF WHY NOT SET UP ALSO A WEST", "subset": "test_clean", "task_type": "understanding", "prediction": "already a north and a south were talked of why not set up also a west", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1873, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0006.flac", "answer": "WHAT THE LATTER DAY SAINTS CALL CELESTIAL MARRIAGE IS CHARACTERISTIC OF THE CHURCH AND IS IN VERY GENERAL PRACTISE BUT OF CELESTIAL MARRIAGE PLURALITY OF WIVES WAS AN INCIDENT NEVER AN ESSENTIAL", "subset": "test_clean", "task_type": "understanding", "prediction": "what the latter day saints call celestial marriage is characteristic of the church and is in very general practice but of celestial marriage plurality of wives was an incident never an essential", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1874, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0007.flac", "answer": "WE BELIEVE IN A LITERAL RESURRECTION AND AN ACTUAL HEREAFTER IN WHICH FUTURE STATE SHALL BE RECOGNIZED EVERY SANCTIFIED AND AUTHORIZED RELATIONSHIP EXISTING HERE ON EARTH OF PARENT AND CHILD BROTHER AND SISTER HUSBAND AND WIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "we believe in a literal resurrection and an actual hereafter in which future states shall be recognized every sanctified and authorized relationship existing here on earth of parent and child brother and sister husband and wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1875, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0001.flac", "answer": "BUT A WORD FURTHER CONCERNING THE EXPEDITION IN GENERAL", "subset": "test_clean", "task_type": "understanding", "prediction": "but a word further concerning the expedition in general", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1876, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0002.flac", "answer": "IT WAS THROUGH FLOYD'S ADVICE THAT BUCHANAN ORDERED THE MILITARY EXPEDITION TO UTAH OSTENSIBLY TO INSTALL CERTAIN FEDERAL OFFICIALS AND TO REPRESS AN ALLEGED INFANTILE REBELLION WHICH IN FACT HAD NEVER COME INTO EXISTENCE BUT IN REALITY TO FURTHER THE INTERESTS OF THE SECESSIONISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "it was through floyd s advice that buchanan ordered the military expedition to utah ostensibly to install certain federal officials and to repress an alleged infantile rebellion which in fact had never come into existence but in reality to further the interests of the secessionists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1877, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0013.flac", "answer": "BEFORE THIS TRAVESTY ON THE ADMINISTRATION OF LAW COULD BE BROUGHT BEFORE THE COURT OF LAST RESORT AND THERE MEET WITH THE REVERSAL AND REBUKE IT DESERVED MEN WERE IMPRISONED UNDER SENTENCES OF MANY YEARS DURATION", "subset": "test_clean", "task_type": "understanding", "prediction": "before this travesty on the administration of law could be brought before the court of last resort and there met with the reversal and rebuke it deserved men were imprisoned under sentence of many years duration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1878, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0000.flac", "answer": "THE ARMY FOUND THE PEOPLE IN POVERTY AND LEFT THEM IN COMPARATIVE WEALTH", "subset": "test_clean", "task_type": "understanding", "prediction": "the army found the people in poverty and left them in comparative wealth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1879, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0008.flac", "answer": "IT HAS BEEN MY PRIVILEGE TO TREAD THE SOIL OF MANY LANDS TO OBSERVE THE CUSTOMS AND STUDY THE HABITS OF MORE NATIONS THAN ONE AND I HAVE YET TO FIND THE PLACE AND MEET THE PEOPLE WHERE AND WITH WHOM THE PURITY OF MAN AND WOMAN IS HELD MORE PRECIOUS THAN AMONG THE MALIGNED MORMONS IN THE MOUNTAIN VALLEYS OF THE WEST", "subset": "test_clean", "task_type": "understanding", "prediction": "it has been my privilege to tread the soil of many lands to observe the customs and study the habits of more nations than one and i have yet to find the place and meet the people where and with whom the purity of man and woman is held more precious than among the maligned mormons in the mountain valleys of the west", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1880, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0005.flac", "answer": "THEY KNEW NO NORTH NO SOUTH NO EAST NO WEST THEY STOOD POSITIVELY BY THE CONSTITUTION AND WOULD HAVE NOTHING TO DO IN THE BLOODY STRIFE BETWEEN BROTHERS UNLESS INDEED THEY WERE SUMMONED BY THE AUTHORITY TO WHICH THEY HAD ALREADY ONCE LOYALLY RESPONDED TO FURNISH MEN AND ARMS FOR THEIR COUNTRY'S NEED", "subset": "test_clean", "task_type": "understanding", "prediction": "they knew no north no south no east no west they stood positively by the constitution and would have nothing to do in the bloody strife between brothers unless indeed they were summoned by the authority to which they had already once loyally responded to furnish men and arms for the country s need", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1881, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0014.flac", "answer": "THE PEOPLE CONTESTED THESE MEASURES ONE BY ONE IN THE COURTS PRESENTING IN CASE AFTER CASE THE DIFFERENT PHASES OF THE SUBJECT AND URGING THE UNCONSTITUTIONALITY OF THE MEASURE", "subset": "test_clean", "task_type": "understanding", "prediction": "the people contested these measures one by one in the courts presenting in case after case the different phases of the subject and urging the unconstitutionality of the measure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1882, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0009.flac", "answer": "AT THE INCEPTION OF PLURAL MARRIAGE AMONG THE LATTER DAY SAINTS THERE WAS NO LAW NATIONAL OR STATE AGAINST ITS PRACTISE", "subset": "test_clean", "task_type": "understanding", "prediction": "at the inception of plural marriage among the latter day saints there was no law national or state against its practice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1883, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0015.flac", "answer": "THEN THE CHURCH WAS DISINCORPORATED AND ITS PROPERTY BOTH REAL AND PERSONAL CONFISCATED AND ESCHEATED TO THE GOVERNMENT OF THE UNITED STATES AND ALTHOUGH THE PERSONAL PROPERTY WAS SOON RESTORED REAL ESTATE OF GREAT VALUE LONG LAY IN THE HANDS OF THE COURT'S RECEIVER AND THE MORMON CHURCH HAD TO PAY THE NATIONAL GOVERNMENT HIGH RENTAL ON ITS OWN PROPERTY", "subset": "test_clean", "task_type": "understanding", "prediction": "then the church was disincorporated and its property both real and personal confiscated and escheated to the government of the united states and although the personal property was soon restored real estate of great value long lay in the hands of the court receiver and the mormon church had to pay the national government high rental on its own property", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1884, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0011.flac", "answer": "FEDERAL JUDGES AND UNITED STATES ATTORNEYS IN UTAH WHO WERE NOT MORMONS NOR LOVERS OF MORMONISM REFUSED TO ENTERTAIN COMPLAINTS OR PROSECUTE CASES UNDER THE LAW BECAUSE OF ITS MANIFEST INJUSTICE AND INADEQUACY", "subset": "test_clean", "task_type": "understanding", "prediction": "federal judges and united states attorneys in utah who were not mormons nor lovers of mormonism refused to entertain complaints or prosecute cases under the law because of its manifest injustice and inadequacy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1885, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0012.flac", "answer": "THIS MEANT THAT FOR AN ALLEGED MISDEMEANOR FOR WHICH CONGRESS PRESCRIBED A MAXIMUM PENALTY OF SIX MONTHS IMPRISONMENT AND A FINE OF THREE HUNDRED DOLLARS A MAN MIGHT BE IMPRISONED FOR LIFE AYE FOR MANY TERMS OF A MAN'S NATURAL LIFE DID THE COURT'S POWER TO ENFORCE ITS SENTENCES EXTEND SO FAR AND MIGHT BE FINED MILLIONS OF DOLLARS", "subset": "test_clean", "task_type": "understanding", "prediction": "this meant that for an alleged misdemeanor for which congress prescribed a maximum penalty of six months imprisonment and a fine of three hundred dollars a man might be imprisoned for life ay for many terms of a man s natural life did the court s power to enforce its sentences extend so far and might be fined millions of dollars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1886, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4077/13754/4077-13754-0016.flac", "answer": "AND SO THE STORY OF MORMONISM RUNS ON ITS FINALE HAS NOT YET BEEN WRITTEN THE CURRENT PRESS PRESENTS CONTINUOUSLY NEW STAGES OF ITS PROGRESS NEW DEVELOPMENTS OF ITS PLAN", "subset": "test_clean", "task_type": "understanding", "prediction": "and so the story of mormonism runs on its finale has not yet been written the current press presents continuously new stages of its progress new developments of its plan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1887, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0011.flac", "answer": "THE ENGLISH IT IS EVIDENT HAD THEY NOT BEEN PREVIOUSLY ASSURED OF RECEIVING THE KING WOULD NEVER HAVE PARTED WITH SO CONSIDERABLE A SUM AND WHILE THEY WEAKENED THEMSELVES BY THE SAME MEASURE HAVE STRENGTHENED A PEOPLE WITH WHOM THEY MUST AFTERWARDS HAVE SO MATERIAL AN INTEREST TO DISCUSS", "subset": "test_clean", "task_type": "understanding", "prediction": "the english it is evident had they not been previously assured of receiving the king would never have parted with so considerable a sum and while they weaken themselves by the same measure have strengthened a people with whom they must afterwards have so material an interest to discuss", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1888, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0000.flac", "answer": "HE PASSED THROUGH HENLEY SAINT ALBANS AND CAME SO NEAR TO LONDON AS HARROW ON THE HILL", "subset": "test_clean", "task_type": "understanding", "prediction": "he passed through henley st albans and came so near to london as harrow on the hill", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1889, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0008.flac", "answer": "THE GOOD NATURED AUDIENCE IN PITY TO FALLEN MAJESTY SHOWED FOR ONCE GREATER DEFERENCE TO THE KING THAN TO THE MINISTER AND SUNG THE PSALM WHICH THE FORMER HAD CALLED FOR", "subset": "test_clean", "task_type": "understanding", "prediction": "the good natured audience in pity to fallen majesty showed for once greater deference to the king than to the minister and sung the psalm which the former had called for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1890, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0001.flac", "answer": "THE SCOTTISH GENERALS AND COMMISSIONERS AFFECTED GREAT SURPRISE ON THE APPEARANCE OF THE KING AND THOUGH THEY PAID HIM ALL THE EXTERIOR RESPECT DUE TO HIS DIGNITY THEY INSTANTLY SET A GUARD UPON HIM UNDER COLOR OF PROTECTION AND MADE HIM IN REALITY A PRISONER", "subset": "test_clean", "task_type": "understanding", "prediction": "the scottish generals and commissioners affected great surprise on the appearance of the king and though they paid him all the exterior respect due to his dignity they instantly set a guard upon him under color of protection and made him in reality a prisoner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1891, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0004.flac", "answer": "AND THE MEN OF ISRAEL ANSWERED THE MEN OF JUDAH AND SAID WE HAVE TEN PARTS IN THE KING AND WE HAVE ALSO MORE RIGHT IN DAVID THAN YE WHY THEN DID YE DESPISE US THAT OUR ADVICE SHOULD NOT BE FIRST HAD IN BRINGING BACK OUR KING", "subset": "test_clean", "task_type": "understanding", "prediction": "and the men of israel answered the men of judah and said we have ten parts in the king and we have also more right in david than ye why then did ye despise us that our advice should not be first had in bringing back our king", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1892, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0013.flac", "answer": "HIS DEATH IN THIS CONJUNCTURE WAS A PUBLIC MISFORTUNE", "subset": "test_clean", "task_type": "understanding", "prediction": "his death in this conjuncture was a public misfortune", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1893, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0012.flac", "answer": "IF ANY STILL RETAINED RANCOR AGAINST HIM IN HIS PRESENT CONDITION THEY PASSED IN SILENCE WHILE HIS WELL WISHERS MORE GENEROUS THAN PRUDENT ACCOMPANIED HIS MARCH WITH TEARS WITH ACCLAMATIONS AND WITH PRAYERS FOR HIS SAFETY", "subset": "test_clean", "task_type": "understanding", "prediction": "if any still retained rancour against him in his present condition they passed in silence while his well wishers more generous than prudent accompanied his march with tears with acclamations and with prayers for his safety", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1894, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0005.flac", "answer": "ANOTHER PREACHER AFTER REPROACHING HIM TO HIS FACE WITH HIS MISGOVERNMENT ORDERED THIS PSALM TO BE SUNG", "subset": "test_clean", "task_type": "understanding", "prediction": "another preacher after reproaching him to his face with his misgovernment ordered this psalm to be sung", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1895, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0003.flac", "answer": "OR HATH HE GIVEN US ANY GIFT", "subset": "test_clean", "task_type": "understanding", "prediction": "or hath he given us any gift", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1896, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0007.flac", "answer": "HAVE MERCY LORD ON ME I PRAY FOR MEN WOULD ME DEVOUR", "subset": "test_clean", "task_type": "understanding", "prediction": "have mercy lord on me i pray for men would me devour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1897, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0006.flac", "answer": "THE KING STOOD UP AND CALLED FOR THAT PSALM WHICH BEGINS WITH THESE WORDS", "subset": "test_clean", "task_type": "understanding", "prediction": "the king stood up and called for that psalm which begins with these words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1898, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0009.flac", "answer": "THE PARLIAMENT AND THE SCOTS LAID THEIR PROPOSALS BEFORE THE KING", "subset": "test_clean", "task_type": "understanding", "prediction": "the parliament and the scots laid their proposals before the king", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1899, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0010.flac", "answer": "BEFORE THE SETTLEMENT OF TERMS THE ADMINISTRATION MUST BE POSSESSED ENTIRELY BY THE PARLIAMENTS OF BOTH KINGDOMS AND HOW INCOMPATIBLE THAT SCHEME WITH THE LIBERTY OF THE KING IS EASILY IMAGINED", "subset": "test_clean", "task_type": "understanding", "prediction": "before the settlement of terms the administration must be possessed entirely by the parliaments of both kingdoms and how incompatible that scheme with the liberty of the king is easily imagined", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1900, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274384/8224-274384-0002.flac", "answer": "THEY INFORMED THE ENGLISH PARLIAMENT OF THIS UNEXPECTED INCIDENT AND ASSURED THEM THAT THEY HAD ENTERED INTO NO PRIVATE TREATY WITH THE KING", "subset": "test_clean", "task_type": "understanding", "prediction": "they informed the english parliament of this unexpected incident and assured them that they had entered into no private treaty with the king", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1901, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0008.flac", "answer": "WITH THESE AND SOME REENFORCEMENTS OF THE ATHOLEMEN AND MACDONALDS WHOM HE HAD RECALLED MONTROSE FELL SUDDENLY UPON ARGYLE'S COUNTRY AND LET LOOSE UPON IT ALL THE RAGE OF WAR CARRYING OFF THE CATTLE BURNING THE HOUSES AND PUTTING THE INHABITANTS TO THE SWORD", "subset": "test_clean", "task_type": "understanding", "prediction": "with these and some reinforcements of the athole men and macdonalds whom he had recalled montrose fell suddenly upon argylls country and let loose upon it all the rage of war carrying off the cattle burning the houses and putting the inhabitants to the sword", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1902, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0011.flac", "answer": "HIS CONDUCT AND PRESENCE OF MIND IN THIS EMERGENCE APPEARED CONSPICUOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "his conduct and presence of mind in this emergence appeared conspicuous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1903, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0004.flac", "answer": "FIVE HUNDRED MEN MORE WHO HAD BEEN LEVIED BY THE COVENANTERS WERE PERSUADED TO EMBRACE THE ROYAL CAUSE AND WITH THIS COMBINED FORCE HE HASTENED TO ATTACK LORD ELCHO WHO LAY AT PERTH WITH AN ARMY OF SIX THOUSAND MEN ASSEMBLED UPON THE FIRST NEWS OF THE IRISH INVASION", "subset": "test_clean", "task_type": "understanding", "prediction": "five hundred men more who had been levied by the covenanters were persuaded to embrace the royal cause and with this combined force he hastened to attack lord elcho who lay at perth with an army of six thousand men assembled upon the first news of the irish invasion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1904, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0003.flac", "answer": "THE KING'S EARS WERE NOW OPEN TO MONTROSE'S COUNSELS WHO PROPOSED NONE BUT THE BOLDEST AND MOST DARING AGREEABLY TO THE DESPERATE STATE OF THE ROYAL CAUSE IN SCOTLAND", "subset": "test_clean", "task_type": "understanding", "prediction": "the king s ears were now open to montrose s counsels who proposed none but the boldest and most daring agreeably to the desperate state of the royal cause in scotland", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1905, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0005.flac", "answer": "DREADING THE SUPERIOR POWER OF ARGYLE WHO HAVING JOINED HIS VASSALS TO A FORCE LEVIED BY THE PUBLIC WAS APPROACHING WITH A CONSIDERABLE ARMY MONTROSE HASTENED NORTHWARDS IN ORDER TO ROUSE AGAIN THE MARQUIS OF HUNTLEY AND THE GORDONS WHO HAVING BEFORE HASTILY TAKEN ARMS HAD BEEN INSTANTLY SUPPRESSED BY THE COVENANTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "dreading the superior power of argyle who having joined his vassals to a force levied by the public was approaching with a considerable army montrose hastened northward in order to rouse again the marquis of huntly and the gordons who having before hastily taken arms had been instantly suppressed by the covenanters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1906, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0010.flac", "answer": "BY A QUICK AND UNEXPECTED MARCH MONTROSE HASTENED TO INNERLOCHY AND PRESENTED HIMSELF IN ORDER OF BATTLE BEFORE THE SURPRISED BUT NOT AFFRIGHTENED COVENANTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "by a quick and unexpected march montrose hastened to innerlochy and presented himself in order of battle before the surprised but not affrighted covenanters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1907, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0015.flac", "answer": "THOUGH THE DISCIPLINE OF THE FORMER PARLIAMENTARY ARMY WAS NOT CONTEMPTIBLE A MORE EXACT PLAN WAS INTRODUCED AND RIGOROUSLY EXECUTED BY THESE NEW COMMANDERS", "subset": "test_clean", "task_type": "understanding", "prediction": "though the discipline of the former parliamentary army was not contemptible a more exact plan was introduced and rigorously executed by these new commanders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1908, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0002.flac", "answer": "WHILE THE FORMER FORETOLD THAT THE SCOTTISH COVENANTERS WERE SECRETLY FORMING A UNION WITH THE ENGLISH PARLIAMENT AND INCULCATED THE NECESSITY OF PREVENTING THEM BY SOME VIGOROUS UNDERTAKING THE LATTER STILL INSISTED THAT EVERY SUCH ATTEMPT WOULD PRECIPITATE THEM INTO MEASURES TO WHICH OTHERWISE THEY WERE NOT PERHAPS INCLINED", "subset": "test_clean", "task_type": "understanding", "prediction": "while the former foretold that the scottish covenanters were secretly forming a union with the english parliament and inculcated the necessity of preventing them by some vigorous undertaking the latter still insisted that every such attempt would precipitate them into measures to which otherwise they were not perhaps inclined", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1909, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0012.flac", "answer": "MONTROSE WEAK IN CAVALRY HERE LINED HIS TROOPS OF HORSE WITH INFANTRY AND AFTER PUTTING THE ENEMY'S HORSE TO ROUT FELL WITH UNITED FORCE UPON THEIR FOOT WHO WERE ENTIRELY CUT IN PIECES THOUGH WITH THE LOSS OF THE GALLANT LORD GORDON ON THE PART OF THE ROYALISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "montrose weak in cavalry here lined his troops of horse with infantry and after putting the enemy s horse to rout fell with united force upon their foot who were entirely cut in pieces though with the loss of the gallant lord gordon on the part of the royalists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1910, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0001.flac", "answer": "AMONG OTHER PERSONS OF DISTINCTION WHO UNITED THEMSELVES TO HIM WAS LORD NAPIER OF MERCHISTON SON OF THE FAMOUS INVENTOR OF THE LOGARITHMS THE PERSON TO WHOM THE TITLE OF A GREAT MAN IS MORE JUSTLY DUE THAN TO ANY OTHER WHOM HIS COUNTRY EVER PRODUCED", "subset": "test_clean", "task_type": "understanding", "prediction": "among other persons of distinction who united themselves to him was lord napier of murchiston son of the famous inventor of the logarithms the person to whom the title of a great man is more justly due than to any other whom his country ever produced", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1911, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0016.flac", "answer": "VALOR INDEED WAS VERY GENERALLY DIFFUSED OVER THE ONE PARTY AS WELL AS THE OTHER DURING THIS PERIOD DISCIPLINE ALSO WAS ATTAINED BY THE FORCES OF THE PARLIAMENT BUT THE PERFECTION OF THE MILITARY ART IN CONCERTING THE GENERAL PLANS OF ACTION AND THE OPERATIONS OF THE FIELD SEEMS STILL ON BOTH SIDES TO HAVE BEEN IN A GREAT MEASURE WANTING", "subset": "test_clean", "task_type": "understanding", "prediction": "valor indeed was very generally diffused over the one party as well as the other during this period discipline also was attained by the forces of the parliament but the perfection of the military art in concerting the general plans of action and the operations of the field seems still on both sides to have been in a great measure wanting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1912, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0006.flac", "answer": "THIS NOBLEMAN'S CHARACTER THOUGH CELEBRATED FOR POLITICAL COURAGE AND CONDUCT WAS VERY LOW FOR MILITARY PROWESS AND AFTER SOME SKIRMISHES IN WHICH HE WAS WORSTED HE HERE ALLOWED MONTROSE TO ESCAPE HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "this nobleman s character though celebrated for political courage and conduct was very low for military prowess and after some skirmishes in which he was worsted he here allowed montrose to escape him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1913, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0013.flac", "answer": "FROM THE SAME MEN NEW REGIMENTS AND NEW COMPANIES WERE FORMED DIFFERENT OFFICERS APPOINTED AND THE WHOLE MILITARY FORCE PUT INTO SUCH HANDS AS THE INDEPENDENTS COULD RELY ON", "subset": "test_clean", "task_type": "understanding", "prediction": "from the same men new regiments and new companies were formed different officers appointed and the whole military force put into such hands as the independents could rely on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1914, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0009.flac", "answer": "THIS SEVERITY BY WHICH MONTROSE SULLIED HIS VICTORIES WAS THE RESULT OF PRIVATE ANIMOSITY AGAINST THE CHIEFTAIN AS MUCH AS OF ZEAL FOR THE PUBLIC CAUSE ARGYLE COLLECTING THREE THOUSAND MEN MARCHED IN QUEST OF THE ENEMY WHO HAD RETIRED WITH THEIR PLUNDER AND HE LAY AT INNERLOCHY SUPPOSING HIMSELF STILL AT A CONSIDERABLE DISTANCE FROM THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "this severity by which montrose sullied his victories was the result of private animosity against the chieftain as much as of zeal for the public cause argyle collecting three thousand men marched in quest of the enemy who had retired with their plunder and he lay at innerlochy supposing himself still at a considerable distance from them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1915, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0000.flac", "answer": "THOUGH THROWN INTO PRISON FOR THIS ENTERPRISE AND DETAINED SOME TIME HE WAS NOT DISCOURAGED BUT STILL CONTINUED BY HIS COUNTENANCE AND PROTECTION TO INFUSE SPIRIT INTO THE DISTRESSED ROYALISTS", "subset": "test_clean", "task_type": "understanding", "prediction": "though thrown into prison for this enterprise and detained some time he was not discouraged but still continued by his countenance and protection to infuse spirit into the distressed royalists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1916, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0007.flac", "answer": "BY QUICK MARCHES THROUGH THESE INACCESSIBLE MOUNTAINS THAT GENERAL FREED HIMSELF FROM THE SUPERIOR FORCES OF THE COVENANTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "by quick marches through these inaccessible mountains that general freed himself from the superior forces of the covenanters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1917, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0014.flac", "answer": "BESIDES MEMBERS OF PARLIAMENT WHO WERE EXCLUDED MANY OFFICERS UNWILLING TO SERVE UNDER THE NEW GENERALS THREW UP THEIR COMMISSIONS AND UNWARILY FACILITATED THE PROJECT OF PUTTING THE ARMY ENTIRELY INTO THE HANDS OF THAT FACTION", "subset": "test_clean", "task_type": "understanding", "prediction": "besides members of parliament who were excluded many officers unwilling to serve under the new generals threw up their commissions and unwarily facilitated the project of putting the army entirely into the hands of that faction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1918, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8224/274381/8224-274381-0017.flac", "answer": "HISTORIANS AT LEAST PERHAPS FROM THEIR OWN IGNORANCE AND INEXPERIENCE HAVE NOT REMARKED ANY THING BUT A HEADLONG IMPETUOUS CONDUCT EACH PARTY HURRYING TO A BATTLE WHERE VALOR AND FORTUNE CHIEFLY DETERMINED THE SUCCESS", "subset": "test_clean", "task_type": "understanding", "prediction": "historians at least perhaps from their own ignorance and inexperience have not remarked any thing but a headlong impetuous conduct each party hurrying to a battle where valor and fortune chiefly determine the success", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1919, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0025.flac", "answer": "TO MEET THE NEEDS OF THIS CONFLICT WRETCHEDNESS HAS INVENTED A LANGUAGE OF COMBAT WHICH IS SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "to meet the needs of this conflict wretchedness has invented a language of combat which is slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1920, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0052.flac", "answer": "THE REAL HUMAN DIVISION IS THIS THE LUMINOUS AND THE SHADY", "subset": "test_clean", "task_type": "understanding", "prediction": "the real human division is this the luminous and the shady", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1921, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0026.flac", "answer": "TO KEEP AFLOAT AND TO RESCUE FROM OBLIVION TO HOLD ABOVE THE GULF WERE IT BUT A FRAGMENT OF SOME LANGUAGE WHICH MAN HAS SPOKEN AND WHICH WOULD OTHERWISE BE LOST THAT IS TO SAY ONE OF THE ELEMENTS GOOD OR BAD OF WHICH CIVILIZATION IS COMPOSED OR BY WHICH IT IS COMPLICATED TO EXTEND THE RECORDS OF SOCIAL OBSERVATION IS TO SERVE CIVILIZATION ITSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "to keep afloat and to rescue from oblivion to hold above the gulf were it but a fragment of some language which man has spoken and which would otherwise be lost that is to say one of the elements good or bad of which civilization is composed or by which it is complicated to extend the records of social observation is to serve civilization itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1922, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0041.flac", "answer": "IT IS UNINTELLIGIBLE IN THE DARK", "subset": "test_clean", "task_type": "understanding", "prediction": "it is unintelligible in the dark", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1923, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0037.flac", "answer": "THERE IT CLOTHES ITSELF IN WORD MASKS IN METAPHOR RAGS", "subset": "test_clean", "task_type": "understanding", "prediction": "there it clothes itself in word masks in metaphor rags", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1924, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0022.flac", "answer": "THERE IS THE SLANG OF THE AFFECTED LADY AS WELL AS OF THE PRECIEUSES", "subset": "test_clean", "task_type": "understanding", "prediction": "there is the slang of the affected lady as well as of the pressuses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1925, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0055.flac", "answer": "TO TEACH READING MEANS TO LIGHT THE FIRE EVERY SYLLABLE SPELLED OUT SPARKLES", "subset": "test_clean", "task_type": "understanding", "prediction": "to teach reading means to light the fire every syllable spelled out sparkles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1926, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0021.flac", "answer": "THE PAINTER WHO SAYS MY GRINDER THE NOTARY WHO SAYS MY SKIP THE GUTTER THE HAIRDRESSER WHO SAYS MY MEALYBACK THE COBBLER WHO SAYS MY CUB TALKS SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "the painter who says my grinder the notary who says my skip the gutter the hairdresser who says my mealy back the cobbler who says my cub talks slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1927, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0057.flac", "answer": "PEOPLE SUFFER IN THE LIGHT EXCESS BURNS", "subset": "test_clean", "task_type": "understanding", "prediction": "people suffer in the light excess burns", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1928, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0030.flac", "answer": "ASSUREDLY IF THE TONGUE WHICH A NATION OR A PROVINCE HAS SPOKEN IS WORTHY OF INTEREST THE LANGUAGE WHICH HAS BEEN SPOKEN BY A MISERY IS STILL MORE WORTHY OF ATTENTION AND STUDY", "subset": "test_clean", "task_type": "understanding", "prediction": "assuredly if the tongue which a nation or a province has spoken is worthy of interest the language which has been spoken by a misery is still more worthy of attention and study", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1929, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0011.flac", "answer": "WHY SHOULD ONE NOT EXPLORE EVERYTHING AND STUDY EVERYTHING", "subset": "test_clean", "task_type": "understanding", "prediction": "why should one not explore everything and study everything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1930, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0054.flac", "answer": "THAT IS WHY WE CRY EDUCATION SCIENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "that is why we cry education science", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1931, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0003.flac", "answer": "SHE HAS A SON THEFT AND A DAUGHTER HUNGER", "subset": "test_clean", "task_type": "understanding", "prediction": "she has a son theft and a daughter hunger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1932, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0009.flac", "answer": "WHEN IT IS A QUESTION OF PROBING A WOUND A GULF A SOCIETY SINCE WHEN HAS IT BEEN CONSIDERED WRONG TO GO TOO FAR TO GO TO THE BOTTOM", "subset": "test_clean", "task_type": "understanding", "prediction": "when it is a question of probing a wound a gulf a society since when has it been considered wrong to go too far to go to the bottom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1933, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0015.flac", "answer": "SINCE WHEN HAS MALADY BANISHED MEDICINE", "subset": "test_clean", "task_type": "understanding", "prediction": "since when has malady banished medicine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1934, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0043.flac", "answer": "THE EARTH IS NOT DEVOID OF RESEMBLANCE TO A JAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "the earth is not devoid of resemblance to a jail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1935, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0020.flac", "answer": "WE MAY BE STOPPED THE FACT MAY BE PUT TO US IN GENERAL TERMS WHICH IS ONE WAY OF ATTENUATING IT WE MAY BE TOLD THAT ALL TRADES PROFESSIONS IT MAY BE ADDED ALL THE ACCIDENTS OF THE SOCIAL HIERARCHY AND ALL FORMS OF INTELLIGENCE HAVE THEIR OWN SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "we may be stopped the fact may be put to us in general terms which is one way of attenuating it we may be told that all trades professions it may be added all the accidents of the social hierarchy and all forms of intelligence have their own slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1936, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0019.flac", "answer": "IT IS THE LANGUAGE OF WRETCHEDNESS", "subset": "test_clean", "task_type": "understanding", "prediction": "it is the language of wretchedness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1937, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0038.flac", "answer": "IN THIS GUISE IT BECOMES HORRIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "in this guise it becomes horrible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1938, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0008.flac", "answer": "WHO DENIES THAT OF COURSE IT DOES", "subset": "test_clean", "task_type": "understanding", "prediction": "who denies that of course it does", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1939, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0053.flac", "answer": "TO DIMINISH THE NUMBER OF THE SHADY TO AUGMENT THE NUMBER OF THE LUMINOUS THAT IS THE OBJECT", "subset": "test_clean", "task_type": "understanding", "prediction": "to diminish the number of the shady to augment the number of the luminous that is the object", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1940, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0046.flac", "answer": "EACH DAY HAS ITS OWN GREAT GRIEF OR ITS LITTLE CARE", "subset": "test_clean", "task_type": "understanding", "prediction": "each day has its own great grief or its little care", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1941, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0050.flac", "answer": "AND YOU BELONG TO THAT SMALL CLASS WHO ARE HAPPY", "subset": "test_clean", "task_type": "understanding", "prediction": "and you belong to that small class who are happy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1942, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0017.flac", "answer": "HE WOULD BE LIKE A PHILOLOGIST REFUSING TO EXAMINE A FACT IN LANGUAGE A PHILOSOPHER HESITATING TO SCRUTINIZE A FACT IN HUMANITY", "subset": "test_clean", "task_type": "understanding", "prediction": "he would be like a philologist refusing to examine a fact in language a philosopher hesitating to scrutinize a fact in humanity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1943, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0039.flac", "answer": "ONE PERCEIVES WITHOUT UNDERSTANDING IT A HIDEOUS MURMUR SOUNDING ALMOST LIKE HUMAN ACCENTS BUT MORE NEARLY RESEMBLING A HOWL THAN AN ARTICULATE WORD", "subset": "test_clean", "task_type": "understanding", "prediction": "one perceives without understanding it a hideous murmur sounding almost like human accents but more nearly resembling a howl than an articulate word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1944, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0028.flac", "answer": "EVEN DIALECT LET THAT PASS", "subset": "test_clean", "task_type": "understanding", "prediction": "even dialect let that pass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1945, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0018.flac", "answer": "WHAT IS SLANG PROPERLY SPEAKING", "subset": "test_clean", "task_type": "understanding", "prediction": "what is slang properly speaking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1946, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0051.flac", "answer": "IN THIS WORLD EVIDENTLY THE VESTIBULE OF ANOTHER THERE ARE NO FORTUNATE", "subset": "test_clean", "task_type": "understanding", "prediction": "in this world evidently the vestibule of another there are no fortunate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1947, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0044.flac", "answer": "LOOK CLOSELY AT LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "look closely at life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1948, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0036.flac", "answer": "FACTS FORM ONE OF THESE AND IDEAS THE OTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "facts form one of these and ideas the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1949, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0040.flac", "answer": "ONE THINKS ONE HEARS HYDRAS TALKING", "subset": "test_clean", "task_type": "understanding", "prediction": "one thinks one hears hydras talking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1950, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0014.flac", "answer": "NOW WHEN HAS HORROR EVER EXCLUDED STUDY", "subset": "test_clean", "task_type": "understanding", "prediction": "now when has horror ever excluded study", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1951, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0047.flac", "answer": "YESTERDAY YOU WERE TREMBLING FOR A HEALTH THAT IS DEAR TO YOU TO DAY YOU FEAR FOR YOUR OWN TO MORROW IT WILL BE ANXIETY ABOUT MONEY THE DAY AFTER TO MORROW THE DIATRIBE OF A SLANDERER THE DAY AFTER THAT THE MISFORTUNE OF SOME FRIEND THEN THE PREVAILING WEATHER THEN SOMETHING THAT HAS BEEN BROKEN OR LOST THEN A PLEASURE WITH WHICH YOUR CONSCIENCE AND YOUR VERTEBRAL COLUMN REPROACH YOU AGAIN THE COURSE OF PUBLIC AFFAIRS", "subset": "test_clean", "task_type": "understanding", "prediction": "yesterday you were trembling for a health that is dear to you to day you fear for your own to morrow it will be anxiety about money the day after to morrow the diatribe of a slanderer the day after that the misfortune of some friend then the prevailing weather then something that has been broken or lost then a pleasure with which your conscience and your vertebral column reproach you again the course of public affairs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1952, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0045.flac", "answer": "IT IS SO MADE THAT EVERYWHERE WE FEEL THE SENSE OF PUNISHMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "it is so made that everywhere we feel the sense of punishment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1953, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0010.flac", "answer": "WE HAVE ALWAYS THOUGHT THAT IT WAS SOMETIMES A COURAGEOUS ACT AND AT LEAST A SIMPLE AND USEFUL DEED WORTHY OF THE SYMPATHETIC ATTENTION WHICH DUTY ACCEPTED AND FULFILLED MERITS", "subset": "test_clean", "task_type": "understanding", "prediction": "we have always thought that it was sometimes a courageous act and at least a simple and useful deed worthy of the sympathetic attention which duty accepted and fulfilled merits", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1954, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0002.flac", "answer": "THUS IDLENESS IS THE MOTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "thus idleness is the mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1955, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0042.flac", "answer": "IT IS BLACK IN MISFORTUNE IT IS BLACKER STILL IN CRIME THESE TWO BLACKNESSES AMALGAMATED COMPOSE SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "it is black in misfortune it is blacker still in crime these two blacknesses amalgamated compose slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1956, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0000.flac", "answer": "CHAPTER ONE ORIGIN", "subset": "test_clean", "task_type": "understanding", "prediction": "chapter one origin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1957, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0012.flac", "answer": "WHY SHOULD ONE HALT ON THE WAY", "subset": "test_clean", "task_type": "understanding", "prediction": "why should one halt on the way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1958, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0029.flac", "answer": "TO THIS WE REPLY IN ONE WORD ONLY", "subset": "test_clean", "task_type": "understanding", "prediction": "to this we reply in one word only", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1959, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0016.flac", "answer": "CAN ONE IMAGINE A NATURALIST REFUSING TO STUDY THE VIPER THE BAT THE SCORPION THE CENTIPEDE THE TARANTULA AND ONE WHO WOULD CAST THEM BACK INTO THEIR DARKNESS SAYING OH HOW UGLY THAT IS", "subset": "test_clean", "task_type": "understanding", "prediction": "can one imagine a naturalist refusing to study the viper the bat the scorpion the centipede the tarantula and one who would cast them back into their darkness saying oh how ugly that is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1960, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0058.flac", "answer": "THE FLAME IS THE ENEMY OF THE WING", "subset": "test_clean", "task_type": "understanding", "prediction": "the flame is the enemy of the wing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1961, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0032.flac", "answer": "HE MUST DESCEND WITH HIS HEART FULL OF CHARITY AND SEVERITY AT THE SAME TIME AS A BROTHER AND AS A JUDGE TO THOSE IMPENETRABLE CASEMATES WHERE CRAWL PELL MELL THOSE WHO BLEED AND THOSE WHO DEAL THE BLOW THOSE WHO WEEP AND THOSE WHO CURSE THOSE WHO FAST AND THOSE WHO DEVOUR THOSE WHO ENDURE EVIL AND THOSE WHO INFLICT IT", "subset": "test_clean", "task_type": "understanding", "prediction": "he must descend with his heart full of charity and severity at the same time as a brother and as a judge to those impenetrable casemates where crawl pell mell those who bleed and those who deal the blow those who weep and those who curse those who fast and those who devour those who endure evil and those who inflict it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1962, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0048.flac", "answer": "THIS WITHOUT RECKONING IN THE PAINS OF THE HEART AND SO IT GOES ON", "subset": "test_clean", "task_type": "understanding", "prediction": "this without reckoning in the pains of the heart and so it goes on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1963, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0035.flac", "answer": "TRUE HISTORY BEING A MIXTURE OF ALL THINGS THE TRUE HISTORIAN MINGLES IN EVERYTHING", "subset": "test_clean", "task_type": "understanding", "prediction": "true history being a mixture of all things the true historian mingles in everything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1964, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0059.flac", "answer": "TO BURN WITHOUT CEASING TO FLY THEREIN LIES THE MARVEL OF GENIUS", "subset": "test_clean", "task_type": "understanding", "prediction": "to burn without ceasing to fly therein lies the marvel of genius", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1965, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0001.flac", "answer": "IT ENGENDERS A WHOLE WORLD LA PEGRE FOR WHICH READ THEFT AND A HELL LA PEGRENNE FOR WHICH READ HUNGER", "subset": "test_clean", "task_type": "understanding", "prediction": "it engenders a whole world la pgre for which red theft and a hell la pgreine for which red hunger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1966, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0027.flac", "answer": "PHOENICIAN VERY GOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "phoenician very good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1967, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0024.flac", "answer": "ALGEBRA MEDICINE BOTANY HAVE EACH THEIR SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "algebra medicine botany have ye ch there slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1968, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0033.flac", "answer": "DO WE REALLY KNOW THE MOUNTAIN WELL WHEN WE ARE NOT ACQUAINTED WITH THE CAVERN", "subset": "test_clean", "task_type": "understanding", "prediction": "do we really know the mountain well when we are not acquainted with the cavern", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1969, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0007.flac", "answer": "SLANG MAKES ONE SHUDDER", "subset": "test_clean", "task_type": "understanding", "prediction": "slang makes one shudder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1970, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0006.flac", "answer": "SLANG IS ODIOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "slang is odious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1971, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0034.flac", "answer": "THEY CONSTITUTE TWO DIFFERENT ORDERS OF FACTS WHICH CORRESPOND TO EACH OTHER WHICH ARE ALWAYS INTERLACED AND WHICH OFTEN BRING FORTH RESULTS", "subset": "test_clean", "task_type": "understanding", "prediction": "they constitute two different orders of facts which correspond to each other which are always interlaced and which often bring forth results", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1972, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0013.flac", "answer": "NOTHING IS MORE LUGUBRIOUS THAN THE CONTEMPLATION THUS IN ITS NUDITY IN THE BROAD LIGHT OF THOUGHT OF THE HORRIBLE SWARMING OF SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "nothing is more lugubrious than the contemplation thus in its nudity in the broad light of thought of the horrible swarming of slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1973, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0056.flac", "answer": "HOWEVER HE WHO SAYS LIGHT DOES NOT NECESSARILY SAY JOY", "subset": "test_clean", "task_type": "understanding", "prediction": "however he who says light does not necessarily say joy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1974, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0004.flac", "answer": "WHAT IS SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "what is slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1975, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0049.flac", "answer": "THERE IS HARDLY ONE DAY OUT OF A HUNDRED WHICH IS WHOLLY JOYOUS AND SUNNY", "subset": "test_clean", "task_type": "understanding", "prediction": "there is hardly one day out of a hundred which is wholly joyous and sunny", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1976, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0031.flac", "answer": "AND THEN WE INSIST UPON IT THE STUDY OF SOCIAL DEFORMITIES AND INFIRMITIES AND THE TASK OF POINTING THEM OUT WITH A VIEW TO REMEDY IS NOT A BUSINESS IN WHICH CHOICE IS PERMITTED", "subset": "test_clean", "task_type": "understanding", "prediction": "and then we insist upon it the study of social deformities and infirmities and the task of pointing them out with a view to remedy is not a business in which choice is permitted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1977, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0005.flac", "answer": "WE HAVE NEVER UNDERSTOOD THIS SORT OF OBJECTIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "we have never understood this sort of objections", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1978, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/4507/16021/4507-16021-0023.flac", "answer": "THE SUGAR MANUFACTURER WHO SAYS LOAF CLARIFIED LUMPS BASTARD COMMON BURNT THIS HONEST MANUFACTURER TALKS SLANG", "subset": "test_clean", "task_type": "understanding", "prediction": "the sugar manufacturer who says loaf clarified lumps bastard common burnt this honest manufacturer talks slang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1979, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0008.flac", "answer": "THE EARTH HAS UNDOUBTEDLY ENTERED UPON A NEW ORBIT BUT SHE IS NOT INCURRING ANY PROBABLE RISK OF BEING PRECIPITATED ONTO THE SUN", "subset": "test_clean", "task_type": "understanding", "prediction": "the earth has undoubtedly entered upon a new orbit but she is not incurring any probable risk of being precipitated on to the sun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1980, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0015.flac", "answer": "TO THE SURPRISE OF ALL AND ESPECIALLY OF LIEUTENANT PROCOPE THE LINE INDICATED A BOTTOM AT A NEARLY UNIFORM DEPTH OF FROM FOUR TO FIVE FATHOMS AND ALTHOUGH THE SOUNDING WAS PERSEVERED WITH CONTINUOUSLY FOR MORE THAN TWO HOURS OVER A CONSIDERABLE AREA THE DIFFERENCES OF LEVEL WERE INSIGNIFICANT NOT CORRESPONDING IN ANY DEGREE TO WHAT WOULD BE EXPECTED OVER THE SITE OF A CITY THAT HAD BEEN TERRACED LIKE THE SEATS OF AN AMPHITHEATER", "subset": "test_clean", "task_type": "understanding", "prediction": "to the surprise of all and especially of lieutenant procope the line indicated a bottom at a nearly uniform depth of from four to five fathoms and although the sounding was persevered with continuously for more than two hours over a considerable area the differences of level were insignificant not corresponding in any degree to what would be expected over the site of a city that had been terraced like the seats of an amphitheatre", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1981, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0006.flac", "answer": "THE LOG AND THE COMPASS THEREFORE WERE ABLE TO BE CALLED UPON TO DO THE WORK OF THE SEXTANT WHICH HAD BECOME UTTERLY USELESS", "subset": "test_clean", "task_type": "understanding", "prediction": "the log and the compass therefore were able to be called upon to do the work of the sextant which had become utterly useless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1982, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0016.flac", "answer": "YOU MUST SEE LIEUTENANT I SHOULD THINK THAT WE ARE NOT SO NEAR THE COAST OF ALGERIA AS YOU IMAGINED", "subset": "test_clean", "task_type": "understanding", "prediction": "you must see lieutenant i should think that we are not so near the coast of algeria as you imagined", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1983, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0003.flac", "answer": "STEAM UP AND CANVAS SPREAD THE SCHOONER STARTED EASTWARDS", "subset": "test_clean", "task_type": "understanding", "prediction": "steam up and canvas spread the schooner started eastwards", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1984, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0005.flac", "answer": "FOR A FEW MILES SHE FOLLOWED THE LINE HITHERTO PRESUMABLY OCCUPIED BY THE COAST OF ALGERIA BUT NO LAND APPEARED TO THE SOUTH", "subset": "test_clean", "task_type": "understanding", "prediction": "for a few miles she followed the line hitherto presumably occupied by the coast of algeria but no land appeared to the south", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1985, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0017.flac", "answer": "AFTER PONDERING AWHILE HE SAID IF WE WERE FARTHER AWAY I SHOULD EXPECT TO FIND A DEPTH OF TWO OR THREE HUNDRED FATHOMS INSTEAD OF FIVE FATHOMS FIVE FATHOMS", "subset": "test_clean", "task_type": "understanding", "prediction": "after pondering a while he said if we were farther away i should expect to find a depth of two or three hundred fathoms instead of five fathoms five fathoms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1986, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0019.flac", "answer": "NOTHING WAS TO BE DONE BUT TO PUT ABOUT AND RETURN IN DISAPPOINTMENT TOWARDS THE NORTH", "subset": "test_clean", "task_type": "understanding", "prediction": "nothing was to be done but to put about and return in disappointment toward the north", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1987, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0010.flac", "answer": "OCEAN REIGNED SUPREME", "subset": "test_clean", "task_type": "understanding", "prediction": "ocean reigned supreme", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1988, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0007.flac", "answer": "THERE IS NO FEAR OF THAT SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "there is no fear of that sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1989, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0001.flac", "answer": "AFTER AN APPRENTICESHIP ON A MERCHANT SHIP HE HAD ENTERED THE IMPERIAL NAVY AND HAD ALREADY REACHED THE RANK OF LIEUTENANT WHEN THE COUNT APPOINTED HIM TO THE CHARGE OF HIS OWN PRIVATE YACHT IN WHICH HE WAS ACCUSTOMED TO SPEND BY FAR THE GREATER PART OF HIS TIME THROUGHOUT THE WINTER GENERALLY CRUISING IN THE MEDITERRANEAN WHILST IN THE SUMMER HE VISITED MORE NORTHERN WATERS", "subset": "test_clean", "task_type": "understanding", "prediction": "after an apprenticeship on a merchant ship he had entered the imperial navy and had already reached the rank of lieutenant when the count appointed him to the charge of his own private yacht in which he was accustomed to spend by far the greater part of his time throughout the winter generally cruising in the mediterranean whilst in the summer he visited more northern waters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1990, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0012.flac", "answer": "IS IT NOT IMPOSSIBLE HE MURMURED ALOUD THAT ANY CITY SHOULD DISAPPEAR SO COMPLETELY", "subset": "test_clean", "task_type": "understanding", "prediction": "is it not impossible he murmured aloud that any city should disappear so completely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1991, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0002.flac", "answer": "THE LATE ASTOUNDING EVENTS HOWEVER HAD RENDERED PROCOPE MANIFESTLY UNEASY AND NOT THE LESS SO FROM HIS CONSCIOUSNESS THAT THE COUNT SECRETLY PARTOOK OF HIS OWN ANXIETY", "subset": "test_clean", "task_type": "understanding", "prediction": "the late astounding events however had rendered procope manifestly uneasy and not the less so from his consciousness that the count secretly partook of his own anxiety", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1992, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0000.flac", "answer": "HER SEA GOING QUALITIES WERE EXCELLENT AND WOULD HAVE AMPLY SUFFICED FOR A CIRCUMNAVIGATION OF THE GLOBE", "subset": "test_clean", "task_type": "understanding", "prediction": "her sea going qualities were excellent and would have amply sufficed for a circumnavigation of the globe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1993, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0009.flac", "answer": "AND WHAT DEMONSTRATION DO YOU OFFER ASKED SERVADAC EAGERLY THAT IT WILL NOT HAPPEN", "subset": "test_clean", "task_type": "understanding", "prediction": "and what demonstration do you offer asked servadac eagerly that it will not happen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1994, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0013.flac", "answer": "WOULD NOT THE LOFTIEST EMINENCES OF THE CITY AT LEAST BE VISIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "would not the loftiest eminences of the city at least be visible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1995, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0014.flac", "answer": "ANOTHER CIRCUMSTANCE WAS MOST REMARKABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "another circumstance was most remarkable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1996, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0018.flac", "answer": "ITS DEPTH REMAINED INVARIABLE STILL FOUR OR AT MOST FIVE FATHOMS AND ALTHOUGH ITS BOTTOM WAS ASSIDUOUSLY DREDGED IT WAS ONLY TO PROVE IT BARREN OF MARINE PRODUCTION OF ANY TYPE", "subset": "test_clean", "task_type": "understanding", "prediction": "its depth remained invariable still four or at most five fathoms and although its bottom was assiduously dredged it was only to prove it barren of marine production of any type", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1997, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0004.flac", "answer": "ALTHOUGH ONLY A MODERATE BREEZE WAS BLOWING THE SEA WAS ROUGH A CIRCUMSTANCE TO BE ACCOUNTED FOR ONLY BY THE DIMINUTION IN THE FORCE OF THE EARTH'S ATTRACTION RENDERING THE LIQUID PARTICLES SO BUOYANT THAT BY THE MERE EFFECT OF OSCILLATION THEY WERE CARRIED TO A HEIGHT THAT WAS QUITE UNPRECEDENTED", "subset": "test_clean", "task_type": "understanding", "prediction": "although only a moderate breeze was blowing the sea was rough a circumstance to be accounted for only by the diminution in the force of the earths attraction rendering the liquid particles so buoyant that by the mere effect of oscillation they were carried to a height that was quite unprecedented", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1998, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28241/5105-28241-0011.flac", "answer": "ALL THE IMAGES OF HIS PAST LIFE FLOATED UPON HIS MEMORY HIS THOUGHTS SPED AWAY TO HIS NATIVE FRANCE ONLY TO RETURN AGAIN TO WONDER WHETHER THE DEPTHS OF OCEAN WOULD REVEAL ANY TRACES OF THE ALGERIAN METROPOLIS", "subset": "test_clean", "task_type": "understanding", "prediction": "all the images of his past life floated upon his memory his thoughts sped away to his native france only to return again to wonder whether the depths of ocean would reveal any traces of the algerian metropolis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1999, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0005.flac", "answer": "SOMETIMES HE WOULD WANDER ON FOOT UPON THE SANDY SHORE AND SOMETIMES HE WOULD ENJOY A RIDE ALONG THE SUMMIT OF THE CLIFF ALTOGETHER BEING IN NO HURRY AT ALL TO BRING HIS TASK TO AN END", "subset": "test_clean", "task_type": "understanding", "prediction": "sometimes he would wander on foot upon the sandy shore and sometimes he would enjoy a ride along the summit of the cliff altogether being in no hurry at all to bring his task to an end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2000, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0002.flac", "answer": "IT MUST BE OWNED AND NO ONE WAS MORE READY TO CONFESS IT THAN HIMSELF THAT HIS LITERARY ATTAINMENTS WERE BY NO MEANS OF A HIGH ORDER", "subset": "test_clean", "task_type": "understanding", "prediction": "it must be owned and no one was more ready to confess it than himself that his literary attainments were by no means of a high order", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2001, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0004.flac", "answer": "ONCE IN ACTION HE WAS LEADING A DETACHMENT OF INFANTRY THROUGH AN INTRENCHMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "once in action he was leading a detachment of infantry through an entrenchment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2002, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0009.flac", "answer": "THE BOND OF UNION THUS EFFECTED COULD NEVER BE SEVERED AND ALTHOUGH BEN ZOOF'S ACHIEVEMENTS HAD FAIRLY EARNED HIM THE RIGHT OF RETIREMENT HE FIRMLY DECLINED ALL HONORS OR ANY PENSION THAT MIGHT PART HIM FROM HIS SUPERIOR OFFICER", "subset": "test_clean", "task_type": "understanding", "prediction": "the bond of union thus effected could never be severed and although ben zoof s achievements had fairly earned him the right of retirement he firmly declined all honours or any pension that might part him from his superior officer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2003, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0001.flac", "answer": "HE SEEMED BORN TO PLEASE WITHOUT BEING CONSCIOUS OF THE POWER HE POSSESSED", "subset": "test_clean", "task_type": "understanding", "prediction": "he seemed born to please without being conscious of the power he possessed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2004, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0006.flac", "answer": "NO CATHEDRAL NOT EVEN BURGOS ITSELF COULD VIE WITH THE CHURCH AT MONTMARTRE", "subset": "test_clean", "task_type": "understanding", "prediction": "no cathedral not even burgos itself could vie with the church at montmartre", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2005, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0008.flac", "answer": "WHEN A PRIVATE IN THE EIGHTH CAVALRY HE HAD BEEN ON THE POINT OF QUITTING THE ARMY AT TWENTY EIGHT YEARS OF AGE BUT UNEXPECTEDLY HE HAD BEEN APPOINTED ORDERLY TO CAPTAIN SERVADAC", "subset": "test_clean", "task_type": "understanding", "prediction": "when a private in the eighth cavalry he had been on the point of quitting the army at twenty eight years of age but unexpectedly he had been appointed orderly to captain servadac", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2006, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0010.flac", "answer": "UNLIKE HIS MASTER HE MADE NO PRETENSION TO ANY GIFT OF POETIC POWER BUT HIS INEXHAUSTIBLE MEMORY MADE HIM A LIVING ENCYCLOPAEDIA AND FOR HIS STOCK OF ANECDOTES AND TROOPER'S TALES HE WAS MATCHLESS", "subset": "test_clean", "task_type": "understanding", "prediction": "on micahs master he made no pretension to any gift of poetic power but his inexhaustible memory made him a living encyclopaedia and for his stock of anecdotes and troopers tales he was matchless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2007, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0003.flac", "answer": "WE DON'T SPIN TOPS IS A FAVORITE SAYING AMONGST ARTILLERY OFFICERS INDICATING THAT THEY DO NOT SHIRK THEIR DUTY BY FRIVOLOUS PURSUITS BUT IT MUST BE CONFESSED THAT SERVADAC BEING NATURALLY IDLE WAS VERY MUCH GIVEN TO SPINNING TOPS", "subset": "test_clean", "task_type": "understanding", "prediction": "we dont spin tops is a favourite saying amongst artillery officers indicating that they do not shirk their duty by frivolous pursuits but it must be confessed that servadac being naturally idle was very much given to spinning tops", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2008, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0007.flac", "answer": "BEN ZOOF'S MOST AMBITIOUS DESIRE WAS TO INDUCE THE CAPTAIN TO GO WITH HIM AND END HIS DAYS IN HIS MUCH LOVED HOME AND SO INCESSANTLY WERE SERVADAC'S EARS BESIEGED WITH DESCRIPTIONS OF THE UNPARALLELED BEAUTIES AND ADVANTAGES OF THIS EIGHTEENTH ARRONDISSEMENT OF PARIS THAT HE COULD SCARCELY HEAR THE NAME OF MONTMARTRE WITHOUT A CONSCIOUS THRILL OF AVERSION", "subset": "test_clean", "task_type": "understanding", "prediction": "ben zoof s most ambitious desire was to induce the captain to go with him and end his days in his much loved home and so incessantly were servadac s ears besieged with descriptions of the unparalleled beauties and advantages of this eighteenth arrondissement of paris that he could scarcely hear the name of montmartre without a conscious thrill of aversion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2009, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28233/5105-28233-0000.flac", "answer": "LENGTH OF SERVICE FOURTEEN YEARS THREE MONTHS AND FIVE DAYS", "subset": "test_clean", "task_type": "understanding", "prediction": "length of service fourteen years three months and five days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2010, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0016.flac", "answer": "TO ALL THESE INQUIRIES THE COUNT RESPONDED IN THE AFFIRMATIVE", "subset": "test_clean", "task_type": "understanding", "prediction": "to all these inquiries the count responded in the affirmative", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2011, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0007.flac", "answer": "SERVADAC TOOK IT FOR GRANTED THAT THE DOBRYNA WAS ENDEAVORING TO PUT IN", "subset": "test_clean", "task_type": "understanding", "prediction": "servadac took it for granted that the dobrina was endeavoring to put in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2012, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0019.flac", "answer": "MY YACHT IS AT YOUR SERVICE SIR EVEN SHOULD YOU REQUIRE TO MAKE A TOUR ROUND THE WORLD", "subset": "test_clean", "task_type": "understanding", "prediction": "my yacht is at your service sir even should you require to make a tour around the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2013, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0013.flac", "answer": "NOTHING MORE THAN YOU KNOW YOURSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "nothing more than you know yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2014, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0008.flac", "answer": "A NARROW CHANNEL FORMED A PASSAGE THROUGH THE RIDGE OF ROCKS THAT PROTECTED IT FROM THE OPEN SEA AND WHICH EVEN IN THE ROUGHEST WEATHER WOULD ENSURE THE CALMNESS OF ITS WATERS", "subset": "test_clean", "task_type": "understanding", "prediction": "a narrow channel formed a passage through the ridge of rocks that protected it from the open sea and which even in the roughest weather would ensure the calmness of its waters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2015, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0015.flac", "answer": "FOR SOME MOMENTS HE SEEMED PERFECTLY STUPEFIED THEN RECOVERING HIMSELF HE BEGAN TO OVERWHELM THE COUNT WITH A TORRENT OF QUESTIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "for some moments he seemed perfectly stupefied and then recovering himself he began to overwhelm the count with a torrent of questions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2016, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0024.flac", "answer": "DOUBTS NOW AROSE AND SOME DISCUSSION FOLLOWED WHETHER OR NOT IT WAS DESIRABLE FOR BEN ZOOF TO ACCOMPANY HIS MASTER", "subset": "test_clean", "task_type": "understanding", "prediction": "doubts now arose and some discussion followed whether or not it was desirable for ben zoof to accompany his master", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2017, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0023.flac", "answer": "A SLIGHT DIMINUTION IN THE EXCESSIVELY HIGH TEMPERATURE WHICH HAD PREVAILED FOR THE LAST FEW WEEKS WAS THE ONLY APPARENT CHANGE IN THE GENERAL ORDER OF THINGS BUT WHETHER THIS WAS TO BE ATTRIBUTED TO ANY ALTERATION IN THE EARTH'S ORBIT WAS A QUESTION WHICH WOULD STILL REQUIRE SEVERAL DAYS TO DECIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "a slight diminution in the excessively high temperature which had prevailed for the last few weeks was the only apparent change in the general order of things but whether this was to be attributed to any alteration in the earths orbit was a question which would still require several days to decide", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2018, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0002.flac", "answer": "EXCLAIMED SERVADAC KEEPING HIS EYE UNMOVED AT HIS TELESCOPE", "subset": "test_clean", "task_type": "understanding", "prediction": "exclaimed servadac keeping his eye unmoved at his telescope", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2019, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0000.flac", "answer": "FAST AS HIS LEGS COULD CARRY HIM SERVADAC HAD MADE HIS WAY TO THE TOP OF THE CLIFF", "subset": "test_clean", "task_type": "understanding", "prediction": "fast as his legs could carry him servadac had made his way to the top of the cliff", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2020, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0009.flac", "answer": "SLIGHTLY CHANGING HER COURSE SHE FIRST STRUCK HER MAINSAIL AND IN ORDER TO FACILITATE THE MOVEMENTS OF HER HELMSMAN SOON CARRIED NOTHING BUT HER TWO TOPSAILS BRIGANTINE AND JIB", "subset": "test_clean", "task_type": "understanding", "prediction": "slightly changing her course she first struck her mainsail and in order to facilitate the movements of her helmsman soon carried nothing but her two top sails brigantine and jib", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2021, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0003.flac", "answer": "SHE IS UNDER SAIL BUT SHE IS COUNT TIMASCHEFF'S YACHT HE WAS RIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "she is under sail but she is count timasheffs yacht he was right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2022, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0001.flac", "answer": "IT WAS QUITE TRUE THAT A VESSEL WAS IN SIGHT HARDLY MORE THAN SIX MILES FROM THE SHORE BUT OWING TO THE INCREASE IN THE EARTH'S CONVEXITY AND THE CONSEQUENT LIMITATION OF THE RANGE OF VISION THE RIGGING OF THE TOPMASTS ALONE WAS VISIBLE ABOVE THE WATER", "subset": "test_clean", "task_type": "understanding", "prediction": "it was quite true that a vessel was in sight hardly more than six miles from the shore but owing to the increase in the earths convexity and the consequent limitation of the range of vision the rigging of the topmasts alone was visible above the water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2023, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0005.flac", "answer": "HE RECKONED THEREFORE NOT ONLY UPON ASCERTAINING THE EXTENT OF THE LATE CATASTROPHE BUT UPON LEARNING ITS CAUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "he reckoned therefore not only upon ascertaining the extent of the late catastrophe but upon learning its cause", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2024, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0021.flac", "answer": "BEFORE STARTING IT WAS INDISPENSABLE THAT THE ENGINE OF THE DOBRYNA SHOULD BE REPAIRED TO SAIL UNDER CANVAS ONLY WOULD IN CONTRARY WINDS AND ROUGH SEAS BE BOTH TEDIOUS AND DIFFICULT", "subset": "test_clean", "task_type": "understanding", "prediction": "before starting it was indispensable that the engine of the dobrina should be repaired to sail under canvas only would in contrary winds and rough seas be both tedious and difficult", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2025, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0022.flac", "answer": "IT WAS ON THE LAST DAY OF JANUARY THAT THE REPAIRS OF THE SCHOONER WERE COMPLETED", "subset": "test_clean", "task_type": "understanding", "prediction": "it was on the last day of january that the repairs of the schooner were completed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2026, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0012.flac", "answer": "NEVER MIND NOW INTERPOSED THE CAPTAIN WE WILL TALK OF THAT BY AND BY", "subset": "test_clean", "task_type": "understanding", "prediction": "never mind now interposed the captain we will talk of that by and by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2027, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0020.flac", "answer": "THE COUNT SHOOK HIS HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "the count shook his head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2028, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0018.flac", "answer": "YOU WILL TAKE ME ON BOARD COUNT WILL YOU NOT", "subset": "test_clean", "task_type": "understanding", "prediction": "you will take me on board count will you not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2029, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0017.flac", "answer": "SOME MYSTERIOUS FORCE SEEMED TO HAVE BROUGHT ABOUT A CONVULSION OF THE ELEMENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "some mysterious force seemed to have brought about a convulsion of the elements", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2030, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0006.flac", "answer": "THE WIND BEING ADVERSE THE DOBRYNA DID NOT MAKE VERY RAPID PROGRESS BUT AS THE WEATHER IN SPITE OF A FEW CLOUDS REMAINED CALM AND THE SEA WAS QUITE SMOOTH SHE WAS ENABLED TO HOLD A STEADY COURSE", "subset": "test_clean", "task_type": "understanding", "prediction": "the wind being adverse the dobryna did not make very rapid progress but as the weather in spite of a few clouds remained calm and the sea was quite smooth she was enabled to hold a steady course", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2031, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0010.flac", "answer": "CAPTAIN SERVADAC HASTENED TOWARDS HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "captain servadac hastened toward him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2032, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0011.flac", "answer": "I LEFT YOU ON A CONTINENT AND HERE I HAVE THE HONOR OF FINDING YOU ON AN ISLAND", "subset": "test_clean", "task_type": "understanding", "prediction": "i left you on a continent and here i have the honor of finding you on an island", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2033, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0014.flac", "answer": "ARE YOU CERTAIN THAT THIS IS THE MEDITERRANEAN", "subset": "test_clean", "task_type": "understanding", "prediction": "are you certain that this is the mediterranean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2034, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/5105/28240/5105-28240-0004.flac", "answer": "IF THE COUNT WERE ON BOARD A STRANGE FATALITY WAS BRINGING HIM TO THE PRESENCE OF HIS RIVAL", "subset": "test_clean", "task_type": "understanding", "prediction": "if the count were on board a strange fatality was bringing him to the presence of his rival", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2035, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0002.flac", "answer": "IN ORDER TO PLEASE HER I SPOKE TO HER OF THE ABBE CONTI AND I HAD OCCASION TO QUOTE TWO LINES OF THAT PROFOUND WRITER", "subset": "test_clean", "task_type": "understanding", "prediction": "in order to please her i spoke to her of the abbe conti and i had occasion to quote two lines of that profound writer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2036, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0037.flac", "answer": "SHE INTRODUCED ME TO ALL HER GUESTS AND GAVE ME SOME PARTICULARS RESPECTING EVERY ONE OF THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "she introduced me to all her guests and gave me some particulars respecting every one of them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2037, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0028.flac", "answer": "ALL THESE HONEST PERSONS ARE WAITING THEIR TURN TO GET THEIR SNUFF BOXES FILLED", "subset": "test_clean", "task_type": "understanding", "prediction": "all these honest persons are waiting their turn to get their snuff boxes filled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2038, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0016.flac", "answer": "MADAME QUINSON BESIDES CAN ANSWER YOUR ENQUIRIES", "subset": "test_clean", "task_type": "understanding", "prediction": "madame coensson besides can answer your inquiries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2039, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0005.flac", "answer": "SILVIA WAS THE ADORATION OF FRANCE AND HER TALENT WAS THE REAL SUPPORT OF ALL THE COMEDIES WHICH THE GREATEST AUTHORS WROTE FOR HER ESPECIALLY OF THE PLAYS OF MARIVAUX FOR WITHOUT HER HIS COMEDIES WOULD NEVER HAVE GONE TO POSTERITY", "subset": "test_clean", "task_type": "understanding", "prediction": "sylvia was the adoration of france and her talent was the real support of all the comedies which the greatest authors wrote for her especially of the plays of marivaux for without her his comedies would never have gone to posterity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2040, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0045.flac", "answer": "HE HAD A GOOD APPETITE COULD TELL A GOOD STORY WITHOUT LAUGHING WAS CELEBRATED FOR HIS WITTY REPARTEES AND HIS SOCIABLE MANNERS BUT HE SPENT HIS LIFE AT HOME SELDOM GOING OUT AND SEEING HARDLY ANYONE BECAUSE HE ALWAYS HAD A PIPE IN HIS MOUTH AND WAS SURROUNDED BY AT LEAST TWENTY CATS WITH WHICH HE WOULD AMUSE HIMSELF ALL DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "he had a good appetite could tell a good story without laughing was celebrated for his witty repartees and his sociable manners but he spent his life at home seldom going out and seeing hardly any one because he always had a pipe in his mouth and was surrounded by at least twenty cats with which he would amuse himself all day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2041, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0035.flac", "answer": "IT SEEMS TO ME I REPLIED THAT SUCH APPROVAL SUCH RATIFICATION OF THE OPINION EXPRESSED BY THE KING THE PRINCES OF THE BLOOD ET CETERA IS RATHER A PROOF OF THE AFFECTION FELT FOR THEM BY THE NATION FOR THE FRENCH CARRY THAT AFFECTION TO SUCH AN EXTENT THAT THEY BELIEVE THEM INFALLIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "it seems to me i replied that such approval such ratification of the opinion expressed by the king the princes of the blood etc is rather a proof of the affection felt for them by the nation for the french carry that affection to such an extent that they believe them infallible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2042, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0040.flac", "answer": "FOR THE FIRST DAY SIR I THINK THAT WHAT YOU HAVE DONE GIVES GREAT HOPES OF YOU AND WITHOUT ANY DOUBT YOU WILL MAKE RAPID PROGRESS", "subset": "test_clean", "task_type": "understanding", "prediction": "for the first day sir i think that what you have done gives great hopes of you and without any doubt you will make rapid progress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2043, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0008.flac", "answer": "SHE WAS HONOURABLY BURIED IN THE CHURCH OF SAINT SAUVEUR WITHOUT THE SLIGHTEST OPPOSITION FROM THE VENERABLE PRIEST WHO FAR FROM SHARING THE ANTI CHRISTAIN INTOLERANCY OF THE CLERGY IN GENERAL SAID THAT HER PROFESSION AS AN ACTRESS HAD NOT HINDERED HER FROM BEING A GOOD CHRISTIAN AND THAT THE EARTH WAS THE COMMON MOTHER OF ALL HUMAN BEINGS AS JESUS CHRIST HAD BEEN THE SAVIOUR OF ALL MANKIND", "subset": "test_clean", "task_type": "understanding", "prediction": "she was honorably buried in the church of saint sever without the slightest opposition from the venerable priest who far from sharing the anti christian intolerancy of the clergy in general said that her profession as an actress had not hindered her from being a good christian and that the earth was a common mother of all human beings as jesus christ had been the saviour of all mankind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2044, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0019.flac", "answer": "I TELL HIM TO GIVE ME SOME COFFEE IF IT IS GOOD", "subset": "test_clean", "task_type": "understanding", "prediction": "i tell him to give me some coffee if it is good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2045, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0041.flac", "answer": "I BELIEVE IT SIR AND THAT IS WHAT I FEAR THEREFORE THE PRINCIPAL OBJECT OF MY VISIT HERE IS TO DEVOTE MYSELF ENTIRELY TO THE STUDY OF THE FRENCH LANGUAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "i believe it sir and that is what i fear therefore the principal object of my visit here is to devote myself entirely to the study of the french language", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2046, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0018.flac", "answer": "I SIT DOWN AT A SMALL TABLE A WAITER COMES IMMEDIATELY TO ENQUIRE MY WISHES", "subset": "test_clean", "task_type": "understanding", "prediction": "i sit down at a small table a waiter comes immediately to inquire my wishes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2047, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0003.flac", "answer": "MADAM CORRECTED ME WITH A PATRONIZING AIR FOR MY PRONUNCIATION OF THE WORD SCEVRA WHICH MEANS DIVIDED SAYING THAT IT OUGHT TO BE PRONOUNCED SCEURA AND SHE ADDED THAT I OUGHT TO BE VERY GLAD TO HAVE LEARNED SO MUCH ON THE FIRST DAY OF MY ARRIVAL IN PARIS TELLING ME THAT IT WOULD BE AN IMPORTANT DAY IN MY LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "madame corrected me with a patronizing air for my pronunciation of the word scavra which means divided saying that it ought to be pronounced sciura and she added that i ought to be very glad to have learned so much on the first day of my arrival in paris telling me that it would be an important day in my life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2048, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0039.flac", "answer": "HE HIMSELF RECITED THE SAME PASSAGE IN FRENCH AND POLITELY POINTED OUT THE PARTS IN WHICH HE THOUGHT THAT I HAD IMPROVED ON THE ORIGINAL", "subset": "test_clean", "task_type": "understanding", "prediction": "he himself recited the same passage in french and politely pointed out the parts in which he thought that i had improved on the original", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2049, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0024.flac", "answer": "I SEE A CROWD IN ONE CORNER OF THE GARDEN EVERYBODY STANDING STILL AND LOOKING UP", "subset": "test_clean", "task_type": "understanding", "prediction": "i see a crowd in one corner of the garden everybody standing still and looking up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2050, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0022.flac", "answer": "I ADDRESS HIM IN ITALIAN AND HE ANSWERS VERY WITTILY BUT HIS WAY OF SPEAKING MAKES ME SMILE AND I TELL HIM WHY", "subset": "test_clean", "task_type": "understanding", "prediction": "i address him in italian and he answers very wittily but his way of speaking makes me smile and i tell him why", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2051, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0017.flac", "answer": "I SEE A QUANTITY OF CHAIRS FOR HIRE AT THE RATE OF ONE SOU MEN READING THE NEWSPAPER UNDER THE SHADE OF THE TREES GIRLS AND MEN BREAKFASTING EITHER ALONE OR IN COMPANY WAITERS WHO WERE RAPIDLY GOING UP AND DOWN A NARROW STAIRCASE HIDDEN UNDER THE FOLIAGE", "subset": "test_clean", "task_type": "understanding", "prediction": "i see a quantity of chairs for hire at the rate of one sou men reading the newspaper under the shade of the trees girls and men breakfasting either alone or in company waiters who were rapidly going up and down a narrow staircase hidden under the foliage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2052, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0038.flac", "answer": "WHAT SIR I SAID TO HIM AM I FORTUNATE ENOUGH TO SEE YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "what sir i said to him am i fortunate enough to see you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2053, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0023.flac", "answer": "MY REMARK PLEASES HIM BUT I SOON PROVE TO HIM THAT IT IS NOT THE RIGHT WAY TO SPEAK HOWEVER PERFECT MAY HAVE BEEN THE LANGUAGE OF THAT ANCIENT WRITER", "subset": "test_clean", "task_type": "understanding", "prediction": "my remark pleases him but i soon prove to him that it is not the right way to speak however perfect may have been the language of that ancient writer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2054, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0043.flac", "answer": "I RESIDE IN THE MARAIS RUE DE DOUZE PORTES", "subset": "test_clean", "task_type": "understanding", "prediction": "i reside in the marais rue de deux ports", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2055, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0009.flac", "answer": "YOU WILL FORGIVE ME DEAR READER IF I HAVE MADE YOU ATTEND THE FUNERAL OF SILVIA TEN YEARS BEFORE HER DEATH BELIEVE ME I HAVE NO INTENTION OF PERFORMING A MIRACLE YOU MAY CONSOLE YOURSELF WITH THE IDEA THAT I SHALL SPARE YOU THAT UNPLEASANT TASK WHEN POOR SILVIA DIES", "subset": "test_clean", "task_type": "understanding", "prediction": "you will forgive me dear reader if i have made you attend the funeral of sylvia ten years before her death believe me i have no intention of performing a miracle you may console yourself with the idea that i shall spare you that unpleasant task when poor sylvia dies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2056, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0006.flac", "answer": "SILVIA DID NOT THINK THAT HER GOOD CONDUCT WAS A MERIT FOR SHE KNEW THAT SHE WAS VIRTUOUS ONLY BECAUSE HER SELF LOVE COMPELLED HER TO BE SO AND SHE NEVER EXHIBITED ANY PRIDE OR ASSUMED ANY SUPERIORITY TOWARDS HER THEATRICAL SISTERS ALTHOUGH SATISFIED TO SHINE BY THEIR TALENT OR THEIR BEAUTY THEY CARED LITTLE ABOUT RENDERING THEMSELVES CONSPICUOUS BY THEIR VIRTUE", "subset": "test_clean", "task_type": "understanding", "prediction": "sylvia did not think that her good conduct was a merit for she knew that she was virtuous only because her self love compelled her to be so and she never exhibited any pride or assumed any superiority towards her theatrical sisters although satisfied to shine by their talent or their beauty they cared little about rendering themselves conspicuous by their virtue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2057, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0029.flac", "answer": "IT IS SOLD EVERYWHERE BUT FOR THE LAST THREE WEEKS NOBODY WILL USE ANY SNUFF BUT THAT SOLD AT THE CIVET CAT", "subset": "test_clean", "task_type": "understanding", "prediction": "it is sold everywhere but for the last three weeks nobody will use any snuff but that sold at the savette cat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2058, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0025.flac", "answer": "IS THERE NOT A MERIDIAN EVERYWHERE", "subset": "test_clean", "task_type": "understanding", "prediction": "is there not a meridian everywhere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2059, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0036.flac", "answer": "WHEN THE KING COMES TO PARIS EVERYBODY CALLS OUT VIVE LE ROI", "subset": "test_clean", "task_type": "understanding", "prediction": "when the king comes to paris everybody calls out vive le roi", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2060, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0027.flac", "answer": "THAT IS TRUE BADAUDERIE", "subset": "test_clean", "task_type": "understanding", "prediction": "that is true bad dog gray", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2061, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0010.flac", "answer": "I NEVER HAD ANY FAMILY", "subset": "test_clean", "task_type": "understanding", "prediction": "i never had any family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2062, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0021.flac", "answer": "I THANK HIM AND TAKE MY LEAVE", "subset": "test_clean", "task_type": "understanding", "prediction": "i thank him and take my leave", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2063, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0034.flac", "answer": "LET A MAN RUN AND EVERYBODY WILL RUN AFTER HIM THE CROWD WILL NOT STOP UNLESS THE MAN IS PROVED TO BE MAD BUT TO PROVE IT IS INDEED A DIFFICULT TASK BECAUSE WE HAVE A CROWD OF MEN WHO MAD FROM THEIR BIRTH ARE STILL CONSIDERED WISE", "subset": "test_clean", "task_type": "understanding", "prediction": "let a man run and everybody will run after him the crowd will not stop unless the man is proved to be mad but to prove it is indeed a difficult task because we have a crowd of men who mad from their birth are still considered wise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2064, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0013.flac", "answer": "YOU DO ME A GREAT HONOUR", "subset": "test_clean", "task_type": "understanding", "prediction": "you do me a great honor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2065, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0000.flac", "answer": "TO CELEBRATE THE ARRIVAL OF HER SON SILVIA GAVE A SPLENDID SUPPER TO WHICH SHE HAD INVITED ALL HER RELATIVES AND IT WAS A GOOD OPPORTUNITY FOR ME TO MAKE THEIR ACQUAINTANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "to celebrate the arrival of her son sylvia gave a splendid supper to which she had invited all her relatives and it was a good opportunity for me to make their acquaintance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2066, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0046.flac", "answer": "HIS HOUSEKEEPER HAD THE MANAGEMENT OF EVERYTHING SHE NEVER ALLOWED HIM TO BE IN NEED OF ANYTHING AND SHE GAVE NO ACCOUNT OF HIS MONEY WHICH SHE KEPT ALTOGETHER BECAUSE HE NEVER ASKED HER TO RENDER ANY ACCOUNTS", "subset": "test_clean", "task_type": "understanding", "prediction": "his housekeeper had the management of everything she never allowed him to be in need of anything and she gave no account of his money which she kept altogether because he never asked her to render any accounts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2067, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0004.flac", "answer": "HER FACE WAS AN ENIGMA FOR IT INSPIRED EVERYONE WITH THE WARMEST SYMPATHY AND YET IF YOU EXAMINED IT ATTENTIVELY THERE WAS NOT ONE BEAUTIFUL FEATURE SHE COULD NOT BE CALLED HANDSOME BUT NO ONE COULD HAVE THOUGHT HER UGLY", "subset": "test_clean", "task_type": "understanding", "prediction": "her face was an enigma for it inspired every one with the warmest sympathy and yet if you examined it attentively there was not one beautiful feature she could not be called handsome but no one could have thought her ugly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2068, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0032.flac", "answer": "SIMPLY BY STOPPING HER CARRIAGE TWO OR THREE TIMES BEFORE THE SHOP TO HAVE HER SNUFF BOX FILLED AND BY SAYING ALOUD TO THE YOUNG GIRL WHO HANDED BACK THE BOX THAT HER SNUFF WAS THE VERY BEST IN PARIS", "subset": "test_clean", "task_type": "understanding", "prediction": "simply by stopping her carriage two or three times before the shop to have her snuff box filled and by saying aloud to the young girl who handed back the box that her snuff was the very best in paris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2069, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0044.flac", "answer": "I WILL MAKE YOU TRANSLATE THEM INTO FRENCH AND YOU NEED NOT BE AFRAID OF MY FINDING YOU INSATIABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "i will make you translate them into french and you need not be afraid of my finding you insatiable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2070, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0026.flac", "answer": "YES BUT THE MERIDIAN OF THE PALAIS ROYAL IS THE MOST EXACT", "subset": "test_clean", "task_type": "understanding", "prediction": "yes but the meridian of the palais royal is the most exact", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2071, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0031.flac", "answer": "BUT HOW DID SHE MANAGE TO RENDER IT SO FASHIONABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "but how did she manage to render it so fashionable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2072, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0030.flac", "answer": "IS IT BETTER THAN ANYWHERE ELSE", "subset": "test_clean", "task_type": "understanding", "prediction": "is it better than anywhere else", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2073, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0007.flac", "answer": "TWO YEARS BEFORE HER DEATH I SAW HER PERFORM THE CHARACTER OF MARIANNE IN THE COMEDY OF MARIVAUX AND IN SPITE OF HER AGE AND DECLINING HEALTH THE ILLUSION WAS COMPLETE", "subset": "test_clean", "task_type": "understanding", "prediction": "two years before her death i saw her perform the character of marianne in the comedy of marivaux and in spite of her age and declining health the illusion was complete", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2074, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0033.flac", "answer": "YOU ARE NOW IN THE ONLY COUNTRY IN THE WORLD WHERE WIT CAN MAKE A FORTUNE BY SELLING EITHER A GENUINE OR A FALSE ARTICLE IN THE FIRST CASE IT RECEIVES THE WELCOME OF INTELLIGENT AND TALENTED PEOPLE AND IN THE SECOND FOOLS ARE ALWAYS READY TO REWARD IT FOR SILLINESS IS TRULY A CHARACTERISTIC OF THE PEOPLE HERE AND HOWEVER WONDERFUL IT MAY APPEAR SILLINESS IS THE DAUGHTER OF WIT", "subset": "test_clean", "task_type": "understanding", "prediction": "you are now in the only country in the world where wit can make a fortune by selling either a genuine or a false article in the first case it receives the welcome of intelligent and talented people and in the second fools are always ready to reward it for silliness is truly a characteristic of the people here and however wonderful it may appear silliness is the daughter of wit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2075, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0011.flac", "answer": "I HAD A NAME I BELIEVE IN MY YOUNG DAYS BUT I HAVE FORGOTTEN IT SINCE I HAVE BEEN IN SERVICE", "subset": "test_clean", "task_type": "understanding", "prediction": "i had a name i believe in my young days but i have forgotten it since i have been in service", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2076, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0012.flac", "answer": "I SHALL CALL YOU ESPRIT", "subset": "test_clean", "task_type": "understanding", "prediction": "i shall call you a spree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2077, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0020.flac", "answer": "THEN TURNING TOWARDS ME HE SAYS THAT I LOOK LIKE A FOREIGNER AND WHEN I SAY THAT I AM AN ITALIAN HE BEGINS TO SPEAK TO ME OF THE COURT OF THE CITY OF THE THEATRES AND AT LAST HE OFFERS TO ACCOMPANY ME EVERYWHERE", "subset": "test_clean", "task_type": "understanding", "prediction": "then turning towards me he says that i look like a foreigner and when i say that i am an italian he begins to speak to me of the court the city of the theatres and at last he offers to accompany me everywhere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2078, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0042.flac", "answer": "I AM A VERY UNPLEASANT PUPIL ALWAYS ASKING QUESTIONS CURIOUS TROUBLESOME INSATIABLE AND EVEN SUPPOSING THAT I COULD MEET WITH THE TEACHER I REQUIRE I AM AFRAID I AM NOT RICH ENOUGH TO PAY HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "i am a very unpleasant pupil always asking questions curious troublesome insatiable and even supposing that i could meet with the teacher i require i am afraid i am not rich enough to pay him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2079, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0015.flac", "answer": "AT YOUR SERVICE SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "at your service sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2080, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0001.flac", "answer": "WITHOUT SAYING IT POSITIVELY SHE MADE ME UNDERSTAND THAT BEING HERSELF AN ILLUSTRIOUS MEMBER OF THE REPUBLIC OF LETTERS SHE WAS WELL AWARE THAT SHE WAS SPEAKING TO AN INSECT", "subset": "test_clean", "task_type": "understanding", "prediction": "without saying it positively she made me understand that being herself an illustrious member of the republic of letters she was well aware that she was speaking to an insect", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2081, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3729/6852/3729-6852-0014.flac", "answer": "HERE GO AND GET ME CHANGE FOR A LOUIS I HAVE IT SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "here go and get me change for a louis i have it sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2082, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0016.flac", "answer": "THEY WERE VOYAGING ACROSS THE DESERTS OF THE SKY A HOST OF NOMADS ON THE MARCH VOYAGING HIGH OVER IRELAND WESTWARD BOUND", "subset": "test_clean", "task_type": "understanding", "prediction": "they were voyaging across the deserts of the sky a host of nomads on the march voyaging high over ireland westward bound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2083, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0000.flac", "answer": "HE COULD WAIT NO LONGER", "subset": "test_clean", "task_type": "understanding", "prediction": "he could wait no longer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2084, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0025.flac", "answer": "A MOMENT BEFORE THE GHOST OF THE ANCIENT KINGDOM OF THE DANES HAD LOOKED FORTH THROUGH THE VESTURE OF THE HAZEWRAPPED CITY", "subset": "test_clean", "task_type": "understanding", "prediction": "a moment before the ghost of the ancient kingdom of the danes had looked forth through the vesture of the haze wrapt city", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2085, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0021.flac", "answer": "THEIR DIVING STONE POISED ON ITS RUDE SUPPORTS AND ROCKING UNDER THEIR PLUNGES AND THE ROUGH HEWN STONES OF THE SLOPING BREAKWATER OVER WHICH THEY SCRAMBLED IN THEIR HORSEPLAY GLEAMED WITH COLD WET LUSTRE", "subset": "test_clean", "task_type": "understanding", "prediction": "their diving stone poised on its rude supports and rocking under their plunges and the rough hewn stones of the sloping breakwater over which they scrambled in their horseplay gleamed with cold wet lustre", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2086, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0022.flac", "answer": "HE STOOD STILL IN DEFERENCE TO THEIR CALLS AND PARRIED THEIR BANTER WITH EASY WORDS", "subset": "test_clean", "task_type": "understanding", "prediction": "he stood still in deference to their calls and parried their banter with easy words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2087, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0012.flac", "answer": "IT WAS IDLE FOR HIM TO MOVE HIMSELF TO BE GENEROUS TOWARDS THEM TO TELL HIMSELF THAT IF HE EVER CAME TO THEIR GATES STRIPPED OF HIS PRIDE BEATEN AND IN BEGGAR'S WEEDS THAT THEY WOULD BE GENEROUS TOWARDS HIM LOVING HIM AS THEMSELVES", "subset": "test_clean", "task_type": "understanding", "prediction": "it was idle for him to move himself to be generous towards them to tell himself that if he ever came to their gates stripped of his pride beaten and in beggars weeds that they would be generous towards him loving him as themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2088, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0001.flac", "answer": "FOR A FULL HOUR HE HAD PACED UP AND DOWN WAITING BUT HE COULD WAIT NO LONGER", "subset": "test_clean", "task_type": "understanding", "prediction": "for a full hour he had paced up and down waiting but he could wait no longer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2089, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0005.flac", "answer": "WHOSE FEET ARE AS THE FEET OF HARTS AND UNDERNEATH THE EVERLASTING ARMS", "subset": "test_clean", "task_type": "understanding", "prediction": "whose feet are as the feet of harts and underneath the everlasting arms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2090, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0009.flac", "answer": "ANGRY WITH HIMSELF HE TRIED TO HIDE HIS FACE FROM THEIR EYES BY GAZING DOWN SIDEWAYS INTO THE SHALLOW SWIRLING WATER UNDER THE BRIDGE BUT HE STILL SAW A REFLECTION THEREIN OF THEIR TOP HEAVY SILK HATS AND HUMBLE TAPE LIKE COLLARS AND LOOSELY HANGING CLERICAL CLOTHES BROTHER HICKEY", "subset": "test_clean", "task_type": "understanding", "prediction": "angry with himself he tried to hide his face from their eyes by gazing down sideways into the shallow swirling water under the bridge but he still saw a reflection therein of their top heavy silk hats and humble tape like collars and loosely hanging clerical clothes brother hickey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2091, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0002.flac", "answer": "HE SET OFF ABRUPTLY FOR THE BULL WALKING RAPIDLY LEST HIS FATHER'S SHRILL WHISTLE MIGHT CALL HIM BACK AND IN A FEW MOMENTS HE HAD ROUNDED THE CURVE AT THE POLICE BARRACK AND WAS SAFE", "subset": "test_clean", "task_type": "understanding", "prediction": "he set off abruptly for the bull walking rapidly lest his father s shrill whistle might call him back and in a few moments he had rounded the curve at the police barrack and was safe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2092, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0024.flac", "answer": "STEPHANOS DEDALOS", "subset": "test_clean", "task_type": "understanding", "prediction": "stephanos dellos", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2093, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0007.flac", "answer": "SOON THE WHOLE BRIDGE WAS TREMBLING AND RESOUNDING", "subset": "test_clean", "task_type": "understanding", "prediction": "soon the whole bridge was trembling and resounding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2094, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0017.flac", "answer": "THE EUROPE THEY HAD COME FROM LAY OUT THERE BEYOND THE IRISH SEA EUROPE OF STRANGE TONGUES AND VALLEYED AND WOODBEGIRT AND CITADELLED AND OF ENTRENCHED AND MARSHALLED RACES", "subset": "test_clean", "task_type": "understanding", "prediction": "the europe they had come from lay out there beyond the irish sea europe of strange tongues and valleyed and wood begirt and citadelled and of entrenched and marshalled races", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2095, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0003.flac", "answer": "THE UNIVERSITY", "subset": "test_clean", "task_type": "understanding", "prediction": "the university", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2096, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0011.flac", "answer": "THEIR PIETY WOULD BE LIKE THEIR NAMES LIKE THEIR FACES LIKE THEIR CLOTHES AND IT WAS IDLE FOR HIM TO TELL HIMSELF THAT THEIR HUMBLE AND CONTRITE HEARTS IT MIGHT BE PAID A FAR RICHER TRIBUTE OF DEVOTION THAN HIS HAD EVER BEEN A GIFT TENFOLD MORE ACCEPTABLE THAN HIS ELABORATE ADORATION", "subset": "test_clean", "task_type": "understanding", "prediction": "their piety would be like their names like their faces like their clothes and it was idle for him to tell himself that their humble and contrite hearts it might be paid a far richer tribute of devotion than his had ever been a gift tenfold more acceptable than his elaborate adoration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2097, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0008.flac", "answer": "THE UNCOUTH FACES PASSED HIM TWO BY TWO STAINED YELLOW OR RED OR LIVID BY THE SEA AND AS HE STROVE TO LOOK AT THEM WITH EASE AND INDIFFERENCE A FAINT STAIN OF PERSONAL SHAME AND COMMISERATION ROSE TO HIS OWN FACE", "subset": "test_clean", "task_type": "understanding", "prediction": "the uncouth faces passed him two by two stained yellow or red or livid by the sea and as he strove to look at them with ease and indifference a faint stain of personal shame and commiseration rose to his own face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2098, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0014.flac", "answer": "THE PHRASE AND THE DAY AND THE SCENE HARMONIZED IN A CHORD", "subset": "test_clean", "task_type": "understanding", "prediction": "the phrase and the day and the scene harmonized in accord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2099, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0023.flac", "answer": "IT WAS A PAIN TO SEE THEM AND A SWORD LIKE PAIN TO SEE THE SIGNS OF ADOLESCENCE THAT MADE REPELLENT THEIR PITIABLE NAKEDNESS", "subset": "test_clean", "task_type": "understanding", "prediction": "it was a pain to see them and a sword like pain to see the signs of adolescence that made repellent their pitiable nakedness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0015.flac", "answer": "WORDS WAS IT THEIR COLOURS", "subset": "test_clean", "task_type": "understanding", "prediction": "words was it their colors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0018.flac", "answer": "AGAIN AGAIN", "subset": "test_clean", "task_type": "understanding", "prediction": "again again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0020.flac", "answer": "HELLO STEPHANOS HERE COMES THE DEDALUS", "subset": "test_clean", "task_type": "understanding", "prediction": "hello stephanos here comes the daedalus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0006.flac", "answer": "THE PRIDE OF THAT DIM IMAGE BROUGHT BACK TO HIS MIND THE DIGNITY OF THE OFFICE HE HAD REFUSED", "subset": "test_clean", "task_type": "understanding", "prediction": "the pride of that dim image brought back to his mind the dignity of the office he had refused", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0019.flac", "answer": "A VOICE FROM BEYOND THE WORLD WAS CALLING", "subset": "test_clean", "task_type": "understanding", "prediction": "a voice from beyond the world was calling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0013.flac", "answer": "IDLE AND EMBITTERING FINALLY TO ARGUE AGAINST HIS OWN DISPASSIONATE CERTITUDE THAT THE COMMANDMENT OF LOVE BADE US NOT TO LOVE OUR NEIGHBOUR AS OURSELVES WITH THE SAME AMOUNT AND INTENSITY OF LOVE BUT TO LOVE HIM AS OURSELVES WITH THE SAME KIND OF LOVE", "subset": "test_clean", "task_type": "understanding", "prediction": "idle and embittering finally to argue against his own dispassionate certitude that the commandment of love bade us not to love our neighbour as ourselves with the same amount and intensity of love but to love him as ourselves with the same kind of love", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0010.flac", "answer": "BROTHER MAC ARDLE BROTHER KEOGH", "subset": "test_clean", "task_type": "understanding", "prediction": "brother mccardle brother key off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134691/1089-134691-0004.flac", "answer": "PRIDE AFTER SATISFACTION UPLIFTED HIM LIKE LONG SLOW WAVES", "subset": "test_clean", "task_type": "understanding", "prediction": "pride after satisfaction uplifted him like long slow waves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0030.flac", "answer": "BEWARE OF MAKING THAT MISTAKE", "subset": "test_clean", "task_type": "understanding", "prediction": "beware of making that mistake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0023.flac", "answer": "WHY WAS THE SACRAMENT OF THE EUCHARIST INSTITUTED UNDER THE TWO SPECIES OF BREAD AND WINE IF JESUS CHRIST BE PRESENT BODY AND BLOOD SOUL AND DIVINITY IN THE BREAD ALONE AND IN THE WINE ALONE", "subset": "test_clean", "task_type": "understanding", "prediction": "why was the sacrament of the eucharist instituted under the two species of bread and wine if jesus christ be present body and blood soul and divinity in the bread alone and in the wine alone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0008.flac", "answer": "THE CHAOS IN WHICH HIS ARDOUR EXTINGUISHED ITSELF WAS A COLD INDIFFERENT KNOWLEDGE OF HIMSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "the chaos in which his ardour extinguished itself was a cold indifferent knowledge of himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0037.flac", "answer": "IN THE SILENCE THEIR DARK FIRE KINDLED THE DUSK INTO A TAWNY GLOW", "subset": "test_clean", "task_type": "understanding", "prediction": "in the silence their dark fire kindled the dusk into a tawny glow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0010.flac", "answer": "WELL NOW ENNIS I DECLARE YOU HAVE A HEAD AND SO HAS MY STICK", "subset": "test_clean", "task_type": "understanding", "prediction": "well now ennis i declare you have a head and so has my stick", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0002.flac", "answer": "AFTER EARLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROTHELS", "subset": "test_clean", "task_type": "understanding", "prediction": "after early nightfall the yellow lamps would light up here and there the squalid quarter of the brothels", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0004.flac", "answer": "NUMBER TEN FRESH NELLY IS WAITING ON YOU GOOD NIGHT HUSBAND", "subset": "test_clean", "task_type": "understanding", "prediction": "number ten fresh nellie is waiting on you good night husband", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0013.flac", "answer": "IF EVER HE WAS IMPELLED TO CAST SIN FROM HIM AND TO REPENT THE IMPULSE THAT MOVED HIM WAS THE WISH TO BE HER KNIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "if ever he was impelled to cast sin from him and to repent the impulse that moved him was the wish to be her knight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0016.flac", "answer": "THEN YOU CAN ASK HIM QUESTIONS ON THE CATECHISM DEDALUS", "subset": "test_clean", "task_type": "understanding", "prediction": "then you can ask him questions on the catechism dedalus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0026.flac", "answer": "THE RECTOR DID NOT ASK FOR A CATECHISM TO HEAR THE LESSON FROM", "subset": "test_clean", "task_type": "understanding", "prediction": "the rector did not ask for a catechism to hear the lesson from", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0015.flac", "answer": "BUT THE DUSK DEEPENING IN THE SCHOOLROOM COVERED OVER HIS THOUGHTS THE BELL RANG", "subset": "test_clean", "task_type": "understanding", "prediction": "but the dusk deepening in the schoolroom covered over his thoughts the bell rang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0019.flac", "answer": "THE SENTENCE OF SAINT JAMES WHICH SAYS THAT HE WHO OFFENDS AGAINST ONE COMMANDMENT BECOMES GUILTY OF ALL HAD SEEMED TO HIM FIRST A SWOLLEN PHRASE UNTIL HE HAD BEGUN TO GROPE IN THE DARKNESS OF HIS OWN STATE", "subset": "test_clean", "task_type": "understanding", "prediction": "the sentence of st james which says that he who offends against one commandment becomes guilty of all had seemed to him first a swollen phrase until he had begun to grope in the darkness of his own state", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0017.flac", "answer": "STEPHEN LEANING BACK AND DRAWING IDLY ON HIS SCRIBBLER LISTENED TO THE TALK ABOUT HIM WHICH HERON CHECKED FROM TIME TO TIME BY SAYING", "subset": "test_clean", "task_type": "understanding", "prediction": "stephen leaning back and drawing idly on his scribbler listened to the talk about him which heron checked from time to time by saying", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0033.flac", "answer": "A GREAT SAINT SAINT FRANCIS XAVIER", "subset": "test_clean", "task_type": "understanding", "prediction": "a great saint saint francis xavier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0014.flac", "answer": "HE TRIED TO THINK HOW IT COULD BE", "subset": "test_clean", "task_type": "understanding", "prediction": "he tried to think how it could be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0009.flac", "answer": "AT MOST BY AN ALMS GIVEN TO A BEGGAR WHOSE BLESSING HE FLED FROM HE MIGHT HOPE WEARILY TO WIN FOR HIMSELF SOME MEASURE OF ACTUAL GRACE", "subset": "test_clean", "task_type": "understanding", "prediction": "at most by an alms given to a beggar whose blessing he fled from he might hope wearily to win for himself some measure of actual grace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0022.flac", "answer": "HOW COMES IT THAT WHILE THE FIRST BEATITUDE PROMISES THE KINGDOM OF HEAVEN TO THE POOR OF HEART THE SECOND BEATITUDE PROMISES ALSO TO THE MEEK THAT THEY SHALL POSSESS THE LAND", "subset": "test_clean", "task_type": "understanding", "prediction": "how comes it that while the first beatitude promises the kingdom of heaven to the poor of heart the second beatitude promises also to the meek that they shall possess the land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0028.flac", "answer": "THE RETREAT WILL BEGIN ON WEDNESDAY AFTERNOON IN HONOUR OF SAINT FRANCIS XAVIER WHOSE FEAST DAY IS SATURDAY", "subset": "test_clean", "task_type": "understanding", "prediction": "the retreat will begin on wednesday afternoon in honor of st francis xavier whose feast day is saturday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0005.flac", "answer": "THE MUSIC CAME NEARER AND HE RECALLED THE WORDS THE WORDS OF SHELLEY'S FRAGMENT UPON THE MOON WANDERING COMPANIONLESS PALE FOR WEARINESS", "subset": "test_clean", "task_type": "understanding", "prediction": "the music came nearer and he recalled the words the words of shelley s fragment upon the moon wandering companionless pale for weariness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0029.flac", "answer": "ON FRIDAY CONFESSION WILL BE HEARD ALL THE AFTERNOON AFTER BEADS", "subset": "test_clean", "task_type": "understanding", "prediction": "on friday confession will be heard all the afternoon after beads", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0032.flac", "answer": "HE IS CALLED AS YOU KNOW THE APOSTLE OF THE INDIES", "subset": "test_clean", "task_type": "understanding", "prediction": "he is called as you know the apostle of the indies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0031.flac", "answer": "STEPHEN'S HEART BEGAN SLOWLY TO FOLD AND FADE WITH FEAR LIKE A WITHERING FLOWER", "subset": "test_clean", "task_type": "understanding", "prediction": "stephen s heart began slowly to fold and fade with fear like a withering flower", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0003.flac", "answer": "HELLO BERTIE ANY GOOD IN YOUR MIND", "subset": "test_clean", "task_type": "understanding", "prediction": "hello bertie any good in your mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0012.flac", "answer": "HER EYES SEEMED TO REGARD HIM WITH MILD PITY HER HOLINESS A STRANGE LIGHT GLOWING FAINTLY UPON HER FRAIL FLESH DID NOT HUMILIATE THE SINNER WHO APPROACHED HER", "subset": "test_clean", "task_type": "understanding", "prediction": "her eyes seemed to regard him with mild pity her holiness a strange light glowing faintly upon her frail flesh did not humiliate the sinner who approached her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0036.flac", "answer": "A GREAT SAINT SAINT FRANCIS XAVIER", "subset": "test_clean", "task_type": "understanding", "prediction": "a great saint saint francis xavier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0027.flac", "answer": "HE CLASPED HIS HANDS ON THE DESK AND SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "he clasped his hands on the desk and said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0011.flac", "answer": "ON SATURDAY MORNINGS WHEN THE SODALITY MET IN THE CHAPEL TO RECITE THE LITTLE OFFICE HIS PLACE WAS A CUSHIONED KNEELING DESK AT THE RIGHT OF THE ALTAR FROM WHICH HE LED HIS WING OF BOYS THROUGH THE RESPONSES", "subset": "test_clean", "task_type": "understanding", "prediction": "on saturday mornings when the sodality met in the chapel to recite the little office his place was a cushioned kneeling desk at the right of the altar from which he led his wing of boys through the responses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0001.flac", "answer": "STUFF IT INTO YOU HIS BELLY COUNSELLED HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "stuff it into you his belly counselled him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0024.flac", "answer": "IF THE WINE CHANGE INTO VINEGAR AND THE HOST CRUMBLE INTO CORRUPTION AFTER THEY HAVE BEEN CONSECRATED IS JESUS CHRIST STILL PRESENT UNDER THEIR SPECIES AS GOD AND AS MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "if the wine change into vinegar and the host crumble into corruption after they have been consecrated is jesus christ still present under their species as god and as man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0020.flac", "answer": "IF A MAN HAD STOLEN A POUND IN HIS YOUTH AND HAD USED THAT POUND TO AMASS A HUGE FORTUNE HOW MUCH WAS HE OBLIGED TO GIVE BACK THE POUND HE HAD STOLEN ONLY OR THE POUND TOGETHER WITH THE COMPOUND INTEREST ACCRUING UPON IT OR ALL HIS HUGE FORTUNE", "subset": "test_clean", "task_type": "understanding", "prediction": "if a man had stolen a pound in his youth and had used that pound to amass a huge fortune how much was he obliged to give back the pound he had stolen only or the pound together with the compound interest accruing upon it or all his huge fortune", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0007.flac", "answer": "A COLD LUCID INDIFFERENCE REIGNED IN HIS SOUL", "subset": "test_clean", "task_type": "understanding", "prediction": "a cold lucid indifference reigned in his soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0025.flac", "answer": "A GENTLE KICK FROM THE TALL BOY IN THE BENCH BEHIND URGED STEPHEN TO ASK A DIFFICULT QUESTION", "subset": "test_clean", "task_type": "understanding", "prediction": "a gentle kick from the tall boy in the bench behind urged stephen to ask a difficult question", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0035.flac", "answer": "HE HAD THE FAITH IN HIM THAT MOVES MOUNTAINS", "subset": "test_clean", "task_type": "understanding", "prediction": "he had the faith in him that moves mountains", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0021.flac", "answer": "IF A LAYMAN IN GIVING BAPTISM POUR THE WATER BEFORE SAYING THE WORDS IS THE CHILD BAPTIZED", "subset": "test_clean", "task_type": "understanding", "prediction": "if a layman in giving baptism pour the water before saying the words is the child baptized", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0018.flac", "answer": "IT WAS STRANGE TOO THAT HE FOUND AN ARID PLEASURE IN FOLLOWING UP TO THE END THE RIGID LINES OF THE DOCTRINES OF THE CHURCH AND PENETRATING INTO OBSCURE SILENCES ONLY TO HEAR AND FEEL THE MORE DEEPLY HIS OWN CONDEMNATION", "subset": "test_clean", "task_type": "understanding", "prediction": "it was strange too that he found an arid pleasure in following up to the end the rigid lines of the doctrines of the church and penetrating into obscure silences only to hear and feel the more deeply his own condemnation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0034.flac", "answer": "THE RECTOR PAUSED AND THEN SHAKING HIS CLASPED HANDS BEFORE HIM WENT ON", "subset": "test_clean", "task_type": "understanding", "prediction": "the rector paused and then shaking his clasped hands before him went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0000.flac", "answer": "HE HOPED THERE WOULD BE STEW FOR DINNER TURNIPS AND CARROTS AND BRUISED POTATOES AND FAT MUTTON PIECES TO BE LADLED OUT IN THICK PEPPERED FLOUR FATTENED SAUCE", "subset": "test_clean", "task_type": "understanding", "prediction": "he hoped there would be stew for dinner turnips and carrots and bruised potatoes and fat mutton pieces to be ladled out in thick peppered flour fattened sauce", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1089/134686/1089-134686-0006.flac", "answer": "THE DULL LIGHT FELL MORE FAINTLY UPON THE PAGE WHEREON ANOTHER EQUATION BEGAN TO UNFOLD ITSELF SLOWLY AND TO SPREAD ABROAD ITS WIDENING TAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "the dull light fell more faintly upon the page whereon another equation began to unfold itself slowly and to spread abroad its widening tail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0034.flac", "answer": "I'M GOING TO SEE MISTER MARSHALL SAID KENNETH AND DISCOVER WHAT I CAN DO TO ASSIST YOU THANK YOU SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "i am going to see mr marshall said kenneth and discover what i can do to assist you thank you sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0040.flac", "answer": "SOME GIRL HAS BEEN HERE TWICE TO INTERVIEW MY MEN AND I HAVE REFUSED TO ADMIT HER", "subset": "test_clean", "task_type": "understanding", "prediction": "some girl has been in here twice to interview my men and i have refused to admit her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0026.flac", "answer": "HE SPOKE SIMPLY BUT PACED UP AND DOWN THE NARROW CELL IN FRONT OF THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "he spoke simply but paced up and down the narrow cell in front of them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0051.flac", "answer": "THERE WAS A GRIM SMILE OF AMUSEMENT ON HIS SHREWD FACE", "subset": "test_clean", "task_type": "understanding", "prediction": "there was a grim smile of amusement on his shrewd face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0025.flac", "answer": "THEN ROGERS WOULDN'T DO ANYTHING BUT LEAD HER AROUND AND WAIT UPON HER AND THE PLACE WENT TO RACK AND RUIN", "subset": "test_clean", "task_type": "understanding", "prediction": "then rogers wouldnt do anything but lead her around and wait upon her and the place went to wrack and ruin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0027.flac", "answer": "WHOSE NAME DID YOU SIGN TO THE CHECK ASKED KENNETH", "subset": "test_clean", "task_type": "understanding", "prediction": "whose name did you sign to the check asked kenneth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0049.flac", "answer": "HE DETESTED THE GRASPING DISPOSITION THAT WOULD ENDEAVOR TO TAKE ADVANTAGE OF HIS EVIDENT DESIRE TO HELP YOUNG GATES", "subset": "test_clean", "task_type": "understanding", "prediction": "he detested the grasping disposition that would endeavor to take advantage of his evident desire to help young gates", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0014.flac", "answer": "THEY FOLLOWED THE JAILER ALONG A SUCCESSION OF PASSAGES", "subset": "test_clean", "task_type": "understanding", "prediction": "they followed the jailer along a succession of passages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0006.flac", "answer": "IF THE PROSECUTION WERE WITHDRAWN AND THE CASE SETTLED WITH THE VICTIM OF THE FORGED CHECK THEN THE YOUNG MAN WOULD BE ALLOWED HIS FREEDOM", "subset": "test_clean", "task_type": "understanding", "prediction": "if the prosecution were withdrawn and the case settled with the victim of the forged check then the young man would be allowed his freedom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0021.flac", "answer": "A FRESH WHOLESOME LOOKING BOY WAS TOM GATES WITH STEADY GRAY EYES AN INTELLIGENT FOREHEAD BUT A SENSITIVE RATHER WEAK MOUTH", "subset": "test_clean", "task_type": "understanding", "prediction": "a fresh wholesome looking boy was tom gates with steady grey eyes an intelligent forehead but a sensitive rather weak mouth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0010.flac", "answer": "WE WISH TO TALK WITH HIM ANSWERED KENNETH TALK", "subset": "test_clean", "task_type": "understanding", "prediction": "we wish to talk with him answered kenneth talk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0048.flac", "answer": "GIVE ME A CHECK FOR A HUNDRED AND FIFTY AND I'LL TURN OVER TO YOU THE FORGED CHECK AND QUASH FURTHER PROCEEDINGS", "subset": "test_clean", "task_type": "understanding", "prediction": "give me a check for a hundred and fifty and i will turn over to you the forged check and quash further proceedings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0043.flac", "answer": "AND HE DESERVES A TERM IN STATE'S PRISON", "subset": "test_clean", "task_type": "understanding", "prediction": "and he deserves a term in states prison", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0050.flac", "answer": "BETH UNEASY AT HIS SILENCE NUDGED HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "beth uneasy at his silence nudged him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0041.flac", "answer": "I'M NOT ELECTIONEERING JUST NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "i am not electioneering just now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0011.flac", "answer": "I'M RUNNING FOR REPRESENTATIVE ON THE REPUBLICAN TICKET SAID KENNETH QUIETLY", "subset": "test_clean", "task_type": "understanding", "prediction": "i am running for representative on the republican ticket said kenneth quietly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0030.flac", "answer": "I WAS BOOKKEEPER SO IT WAS EASY TO GET A BLANK CHECK AND FORGE THE SIGNATURE", "subset": "test_clean", "task_type": "understanding", "prediction": "i was bit keeper so it was easy to get a blank check and forge the signature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0004.flac", "answer": "BUT THEY COULD NOT HAVE PROVEN A CASE AGAINST LUCY IF SHE WAS INNOCENT AND ALL THEIR THREATS OF ARRESTING HER WERE PROBABLY MERE BLUFF", "subset": "test_clean", "task_type": "understanding", "prediction": "but they could not have proven a case against lucy if she was innocent and all their threats of arresting her were probably a mere bluff", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0031.flac", "answer": "AS REGARDS MY ROBBING THE COMPANY I'LL SAY THAT I SAVED THEM A HEAVY LOSS ONE DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "as regards my robbing the company i ll say that i saved him a heavy loss one day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0053.flac", "answer": "AND TO THINK WE CAN SAVE ALL THAT MISERY AND DESPAIR BY THE PAYMENT OF A HUNDRED AND FIFTY DOLLARS", "subset": "test_clean", "task_type": "understanding", "prediction": "and to think we can save all that misery and despair by the payment of a hundred and fifty dollars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0045.flac", "answer": "I'LL PAY ALL THE COSTS BESIDES", "subset": "test_clean", "task_type": "understanding", "prediction": "ill pay all the costs besides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0003.flac", "answer": "IT WAS A DELIBERATE THEFT FROM HIS EMPLOYERS TO PROTECT A GIRL HE LOVED", "subset": "test_clean", "task_type": "understanding", "prediction": "it was a deliberate theft from his employers to protect a girl he loved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0046.flac", "answer": "YOU'RE FOOLISH WHY SHOULD YOU DO ALL THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "you are foolish why should you do all this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0047.flac", "answer": "I HAVE MY OWN REASONS MISTER MARSHALL", "subset": "test_clean", "task_type": "understanding", "prediction": "i have my own reasons mr marshall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0008.flac", "answer": "FAIRVIEW WAS TWELVE MILES AWAY BUT BY TEN O'CLOCK THEY DREW UP AT THE COUNTY JAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "fairview was twelve miles away but by ten o clock they drew up at the county jail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0023.flac", "answer": "I DIDN'T STOP TO THINK WHETHER IT WAS FOOLISH OR NOT I DID IT AND I'M GLAD I DID", "subset": "test_clean", "task_type": "understanding", "prediction": "i did n t stop to think whether it was foolish or not i did it and i m glad i did it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0017.flac", "answer": "WORSE TOM WORSE N EVER REPLIED THE JAILER GLOOMILY", "subset": "test_clean", "task_type": "understanding", "prediction": "worse tom worse than ever replied the jailer gloomily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0052.flac", "answer": "HE MIGHT HAVE HAD THAT FORGED CHECK FOR THE FACE OF IT IF HE'D BEEN SHARP", "subset": "test_clean", "task_type": "understanding", "prediction": "he might have had that forged check for the face of it if he had been sharp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0035.flac", "answer": "IT WON'T BE MUCH BUT I'M GRATEFUL TO FIND A FRIEND", "subset": "test_clean", "task_type": "understanding", "prediction": "it won t be much but i m grateful to find a friend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0001.flac", "answer": "IT WAS A SERIOUS CRIME INDEED MISTER WATSON TOLD THEM AND TOM GATES BADE FAIR TO SERVE A LENGTHY TERM IN STATE'S PRISON AS A CONSEQUENCE OF HIS RASH ACT", "subset": "test_clean", "task_type": "understanding", "prediction": "it was a serious crime indeed mr watson told them and tom gates bade fair to serve a lengthy term in the state prison as a consequence of his rash act", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0024.flac", "answer": "OLD WILL IS A FINE FELLOW BUT POOR AND HELPLESS SINCE MISSUS ROGERS HAD HER ACCIDENT", "subset": "test_clean", "task_type": "understanding", "prediction": "old will is a fine fellow but poor and helpless since mrs rogers had her accident", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0016.flac", "answer": "HE UNLOCKED THE DOOR AND CALLED HERE'S VISITORS TOM", "subset": "test_clean", "task_type": "understanding", "prediction": "he unlocked the door and called here is visitors tom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0019.flac", "answer": "SORRY WE HAVEN'T ANY RECEPTION ROOM IN THE JAIL", "subset": "test_clean", "task_type": "understanding", "prediction": "sorry we haven t any reception room in the jail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0007.flac", "answer": "BUT UNDER THE CIRCUMSTANCES I DOUBT IF SUCH AN ARRANGEMENT COULD BE MADE", "subset": "test_clean", "task_type": "understanding", "prediction": "but under the circumstances i doubt if such an arrangement could be made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0037.flac", "answer": "I'VE SEEN LOTS OF THAT KIND IN MY DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "i have seen lots of that kind in my day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0013.flac", "answer": "MAY WE SEE GATES AT ONCE ASKED KENNETH", "subset": "test_clean", "task_type": "understanding", "prediction": "may we see gates at once asked kenneth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0032.flac", "answer": "I DISCOVERED AND PUT OUT A FIRE THAT WOULD HAVE DESTROYED THE WHOLE PLANT BUT MARSHALL NEVER EVEN THANKED ME", "subset": "test_clean", "task_type": "understanding", "prediction": "i discovered and put out a fire that would have destroyed the whole plant but marshall never even thanked me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0029.flac", "answer": "IT'S A STOCK COMPANY AND RICH", "subset": "test_clean", "task_type": "understanding", "prediction": "its a stock company in rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0033.flac", "answer": "IT WAS BETTER FOR HIM TO THINK THE GIRL UNFEELING THAN TO KNOW THE TRUTH", "subset": "test_clean", "task_type": "understanding", "prediction": "it was better for him to think the girl unfailing than to know the truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0036.flac", "answer": "THEY LEFT HIM THEN FOR THE JAILER ARRIVED TO UNLOCK THE DOOR AND ESCORT THEM TO THE OFFICE", "subset": "test_clean", "task_type": "understanding", "prediction": "they left him then for the jailer arrived to unlock the door and escort them to the office", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0028.flac", "answer": "HE IS SUPPOSED TO SIGN ALL THE CHECKS OF THE CONCERN", "subset": "test_clean", "task_type": "understanding", "prediction": "he is supposed to sign all the checks of the concern", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0002.flac", "answer": "I CAN'T SEE IT IN THAT LIGHT SAID THE OLD LAWYER", "subset": "test_clean", "task_type": "understanding", "prediction": "i can see it in that light said the old lawyer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0009.flac", "answer": "THEY WERE RECEIVED IN THE LITTLE OFFICE BY A MAN NAMED MARKHAM WHO WAS THE JAILER", "subset": "test_clean", "task_type": "understanding", "prediction": "they were received in the little office by a man named markham who was the jailer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0038.flac", "answer": "AND IT RUINS A MAN'S DISPOSITION", "subset": "test_clean", "task_type": "understanding", "prediction": "and it ruins a man s disposition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0018.flac", "answer": "MISS DE GRAF SAID KENNETH NOTICING THE BOY'S FACE CRITICALLY AS HE STOOD WHERE THE LIGHT FROM THE PASSAGE FELL UPON IT", "subset": "test_clean", "task_type": "understanding", "prediction": "mr graff said kenneth noticing the boy s face critically as he stood where the light from the passage fell upon it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0005.flac", "answer": "HE WAS SOFT HEARTED AND IMPETUOUS SAID BETH AND BEING IN LOVE HE DIDN'T STOP TO COUNT THE COST", "subset": "test_clean", "task_type": "understanding", "prediction": "he was soft hearted and impetuous said beth and being in love he did n't stop to count the cost", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0020.flac", "answer": "SIT DOWN PLEASE SAID GATES IN A CHEERFUL AND PLEASANT VOICE THERE'S A BENCH HERE", "subset": "test_clean", "task_type": "understanding", "prediction": "sit down please said gates in a cheerful and pleasant voice there is a bench here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0012.flac", "answer": "OH SAY THAT'S DIFFERENT OBSERVED MARKHAM ALTERING HIS DEMEANOR", "subset": "test_clean", "task_type": "understanding", "prediction": "oh say that is different observed markham altering his demeanor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0044.flac", "answer": "IT HAS COST ME TWICE SIXTY DOLLARS IN ANNOYANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "it has cost me twice sixty dollars in annoyance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0000.flac", "answer": "KENNETH AND BETH REFRAINED FROM TELLING THE OTHER GIRLS OR UNCLE JOHN OF OLD WILL ROGERS'S VISIT BUT THEY GOT MISTER WATSON IN THE LIBRARY AND QUESTIONED HIM CLOSELY ABOUT THE PENALTY FOR FORGING A CHECK", "subset": "test_clean", "task_type": "understanding", "prediction": "gareth and beth refrained from telling the other girls or uncle john of old will rogers visit but they got mr watson in the library and questioned him closely about the penalty for forging a check", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0042.flac", "answer": "OH WELL SIR WHAT ABOUT HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "oh well sir what about em", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0022.flac", "answer": "WE HAVE HEARD SOMETHING OF YOUR STORY SAID KENNETH AND ARE INTERESTED IN IT", "subset": "test_clean", "task_type": "understanding", "prediction": "we have heard something of your story said kenneth and are interested in it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0015.flac", "answer": "SOMETIMES I'M THAT YEARNING FOR A SMOKE I'M NEARLY CRAZY AN I DUNNO WHICH IS WORST DYIN ONE WAY OR ANOTHER", "subset": "test_clean", "task_type": "understanding", "prediction": "sometimes i m that yearnin for a smoke i m nearly crazy and i dunno which is worse dyin one way or the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68769/6829-68769-0039.flac", "answer": "HE LOOKED UP RATHER UNGRACIOUSLY BUT MOTIONED THEM TO BE SEATED", "subset": "test_clean", "task_type": "understanding", "prediction": "he looked up rather ungraciously but motioned them to be seated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0035.flac", "answer": "WILL YOU LEAVE ME ALONE IN MY OWN ROOM OR MUST I GO AWAY TO ESCAPE YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "will you leave me alone in my own room or must i go away to escape you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0024.flac", "answer": "FOR THE FIRST TIME THE MAID SEEMED A LITTLE CONFUSED AND HER GAZE WANDERED FROM THE FACE OF HER VISITOR", "subset": "test_clean", "task_type": "understanding", "prediction": "for the first time the maid seemed a little confused and her gaze wandered from the face of her visitor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0010.flac", "answer": "THE FAIRVIEW BAND WAS ENGAGED TO DISCOURSE AS MUCH HARMONY AS IT COULD PRODUCE AND THE RESOURCES OF THE GREAT HOUSE WERE TAXED TO ENTERTAIN THE GUESTS", "subset": "test_clean", "task_type": "understanding", "prediction": "the fairview band was engaged to discourse as much harmony as it could produce and the resources of the great house were taxed to entertain the guests", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0036.flac", "answer": "ELIZA CLOSED THE DOOR BEHIND HER WITH A DECIDED SLAM AND A KEY CLICKED IN THE LOCK", "subset": "test_clean", "task_type": "understanding", "prediction": "eliza closed the door behind her with a decided slam and a key clicked in the lock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0013.flac", "answer": "THE ATTENDANCE WAS UNEXPECTEDLY LARGE AND THE GIRLS WERE DELIGHTED FORESEEING GREAT SUCCESS FOR THEIR FETE", "subset": "test_clean", "task_type": "understanding", "prediction": "the attendance was unexpectedly large and the girls were delighted foreseeing great success for their fight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0022.flac", "answer": "I ATTEND TO THE HOUSEHOLD MENDING YOU KNOW AND CARE FOR THE LINEN", "subset": "test_clean", "task_type": "understanding", "prediction": "i attend to the household mending you know and care for the linen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0032.flac", "answer": "HOWEVER HER FEATURES AND FORM MIGHT REPRESS ANY EVIDENCE OF NERVOUSNESS THESE HANDS TOLD A DIFFERENT STORY", "subset": "test_clean", "task_type": "understanding", "prediction": "however her features and form might repress any evidence of nervousness these hands told a different story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0016.flac", "answer": "SHE WAS VERY FOND OF THE YOUNG LADIES WHOM SHE HAD KNOWN WHEN AUNT JANE WAS THE MISTRESS HERE AND BETH WAS HER ESPECIAL FAVORITE", "subset": "test_clean", "task_type": "understanding", "prediction": "she was very fond of the young ladies whom she had known when aunt jane was their mistress here and beth was her especial favorite", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0003.flac", "answer": "THE DEMOCRATIC COMMITTEE FIGURED OUT A WAY TO DO THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "the democratic committee figured out a way to do this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0000.flac", "answer": "SO TO THE SURPRISE OF THE DEMOCRATIC COMMITTEE AND ALL HIS FRIENDS MISTER HOPKINS ANNOUNCED THAT HE WOULD OPPOSE FORBES'S AGGRESSIVE CAMPAIGN WITH AN EQUAL AGGRESSIVENESS AND SPEND AS MANY DOLLARS IN DOING SO AS MIGHT BE NECESSARY", "subset": "test_clean", "task_type": "understanding", "prediction": "so to the surprise of the democratic committee and all his friends mr hopkins announced that he would oppose forbes aggressive campaign with an equal aggressiveness and spend as many dollars in doing so as might be necessary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0009.flac", "answer": "LOUISE HOPED FOR EXCELLENT RESULTS FROM THIS ORGANIZATION AND WISHED THE ENTERTAINMENT TO BE SO EFFECTIVE IN WINNING THEIR GOOD WILL THAT THEY WOULD WORK EARNESTLY FOR THE CAUSE IN WHICH THEY WERE ENLISTED", "subset": "test_clean", "task_type": "understanding", "prediction": "louise hoped for excellent results from this organization and wished the entertainment to be so effective in winning their good will that they would work earnestly for the cause in which they were enlisted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0031.flac", "answer": "HER EYES WANDERED TO THE MAID'S HANDS", "subset": "test_clean", "task_type": "understanding", "prediction": "her eyes wandered to the maid s hands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0002.flac", "answer": "THE WEAK KNEED CONTINGENCY MUST BE STRENGTHENED AND FORTIFIED AND A COUPLE OF HUNDRED VOTES IN ONE WAY OR ANOTHER SECURED FROM THE OPPOSITION", "subset": "test_clean", "task_type": "understanding", "prediction": "the weak kneed contingency must be strengthened and fortified and a couple of hundred votes in one way or the other secured from the opposition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0017.flac", "answer": "THE HOUSEKEEPER LED THE WAY AND BETH FOLLOWED", "subset": "test_clean", "task_type": "understanding", "prediction": "the housekeeper led the way and beth followed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0027.flac", "answer": "THEY THEY EXCITE ME IN SOME WAY AND I I CAN'T BEAR THEM YOU MUST EXCUSE ME", "subset": "test_clean", "task_type": "understanding", "prediction": "they they excite me in some way and i i cant bear them you must excuse me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0025.flac", "answer": "SHE SAT DOWN IN A ROCKING CHAIR AND CLASPING HER HANDS IN HER LAP ROCKED SLOWLY BACK AND FORTH I'M SORRY SAID BETH", "subset": "test_clean", "task_type": "understanding", "prediction": "she sat down in a rocking chair and clasping her hands in her lap rocked slowly back and forth i am sorry said beth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0012.flac", "answer": "THIS WAS THE FIRST OCCASION WITHIN A GENERATION WHEN SUCH AN ENTERTAINMENT HAD BEEN GIVEN AT ELMHURST AND THE ONLY ONE WITHIN THE MEMORY OF MAN WHERE THE NEIGHBORS AND COUNTRY PEOPLE HAD BEEN INVITED GUESTS", "subset": "test_clean", "task_type": "understanding", "prediction": "this was the first occasion within a generation when such an entertainment had been given at elmhurst and the only one within the memory of man where the neighbors and country people had been the invited guests", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0004.flac", "answer": "UNDER ORDINARY CONDITIONS REYNOLDS WAS SURE TO BE ELECTED BUT THE COMMITTEE PROPOSED TO SACRIFICE HIM IN ORDER TO ELECT HOPKINS", "subset": "test_clean", "task_type": "understanding", "prediction": "under ordinary conditions reynolds was sure to be elected but the committee proposed to sacrifice him in order to elect hopkins", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0001.flac", "answer": "ONE OF MISTER HOPKINS'S FIRST TASKS AFTER CALLING HIS FAITHFUL HENCHMEN AROUND HIM WAS TO MAKE A CAREFUL CANVASS OF THE VOTERS OF HIS DISTRICT TO SEE WHAT WAS STILL TO BE ACCOMPLISHED", "subset": "test_clean", "task_type": "understanding", "prediction": "one of mr hopkins first tasks after calling his faithful henchmen around him was to make a careful canvass of the voters of his district to see what was still to be accomplished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0026.flac", "answer": "ELIZA PARSONS SHOOK HER HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "eliza parsons shook her head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0028.flac", "answer": "SHE EVEN SEEMED MILDLY AMUSED AT THE ATTENTION SHE ATTRACTED", "subset": "test_clean", "task_type": "understanding", "prediction": "she even seemed mildly amused at the attention she attracted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0023.flac", "answer": "YOU SPEAK LIKE AN EDUCATED PERSON SAID BETH WONDERINGLY WHERE IS YOUR HOME", "subset": "test_clean", "task_type": "understanding", "prediction": "you speak like an educated person said beth wonderingly where is your home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0033.flac", "answer": "SHE ROSE QUICKLY TO HER FEET WITH AN IMPETUOUS GESTURE THAT MADE HER VISITOR CATCH HER BREATH", "subset": "test_clean", "task_type": "understanding", "prediction": "she rose quickly to her feet with an impetuous gesture that made her visitor catch her breath", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0006.flac", "answer": "AND THIS WAS WHY KENNETH AND BETH DISCOVERED HIM CONVERSING WITH THE YOUNG WOMAN IN THE BUGGY", "subset": "test_clean", "task_type": "understanding", "prediction": "and this was why kenneth and beth discovered him conversing with the young woman in the buggy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0019.flac", "answer": "SHE WAS DRESSED IN THE REGULATION COSTUME OF THE MAIDS AT ELMHURST A PLAIN BLACK GOWN WITH WHITE APRON AND CAP", "subset": "test_clean", "task_type": "understanding", "prediction": "she was dressed in the regulation costume of the maids at elmhurst a plain black gown with a white apron and cap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0021.flac", "answer": "BUT IT CAN'T BE PROTESTED THE GIRL", "subset": "test_clean", "task_type": "understanding", "prediction": "but it can t be protested the girl", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0011.flac", "answer": "TABLES WERE SPREAD ON THE LAWN AND A DAINTY BUT SUBSTANTIAL REPAST WAS TO BE SERVED", "subset": "test_clean", "task_type": "understanding", "prediction": "tables were spread on the lawn and a dainty but substantial repast was to be served", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0015.flac", "answer": "WON'T YOU RUN INTO THE HOUSE AND SEE IF MARTHA CAN'T SPARE ONE OR TWO MORE MAIDS", "subset": "test_clean", "task_type": "understanding", "prediction": "wont you run into the house and see if martha cant spare one or two more maids", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0014.flac", "answer": "WE OUGHT TO HAVE MORE ATTENDANTS BETH SAID LOUISE APPROACHING HER COUSIN", "subset": "test_clean", "task_type": "understanding", "prediction": "we ought to have more attendance beth said louise approaching her cousin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0029.flac", "answer": "BETH WAS A BEAUTIFUL GIRL THE HANDSOMEST OF THE THREE COUSINS BY FAR YET ELIZA SURPASSED HER IN NATURAL CHARM AND SEEMED WELL AWARE OF THE FACT", "subset": "test_clean", "task_type": "understanding", "prediction": "beth was a beautiful girl the handsomest of the three cousins by far yet eliza surpassed her in natural charm and seemed well aware of the fact", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0008.flac", "answer": "THESE WOMEN WERE FLATTERED BY THE ATTENTION OF THE YOUNG LADY AND HAD PROMISED TO ASSIST IN ELECTING MISTER FORBES", "subset": "test_clean", "task_type": "understanding", "prediction": "these women were flattered by the attention of the young lady and had promised to assist in electing mr forbes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0030.flac", "answer": "HER MANNER WAS NEITHER INDEPENDENT NOR ASSERTIVE BUT RATHER ONE OF WELL BRED COMPOSURE AND CALM RELIANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "her manner was neither independent nor assertive but rather one of well bred composure and calm reliance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0005.flac", "answer": "THE ONLY THING NECESSARY WAS TO FIX SETH REYNOLDS AND THIS HOPKINS ARRANGED PERSONALLY", "subset": "test_clean", "task_type": "understanding", "prediction": "the only thing necessary was to fix seth reynolds and this hopkins arranged personally", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0007.flac", "answer": "THE DESCRIPTION SHE GAVE OF THE COMING RECEPTION TO THE WOMAN'S POLITICAL LEAGUE WAS SO HUMOROUS AND DIVERTING THAT THEY WERE BOTH LAUGHING HEARTILY OVER THE THING WHEN THE YOUNG PEOPLE PASSED THEM AND THUS MISTER HOPKINS FAILED TO NOTICE WHO THE OCCUPANTS OF THE OTHER VEHICLE WERE", "subset": "test_clean", "task_type": "understanding", "prediction": "the description she gave of the coming reception to the women s political league was so humorous and diverting that they were both laughing heartily over the thing when the young people passed them and thus mr hopkins failed to notice who the occupants of the other vehicle were", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0018.flac", "answer": "FOR A MOMENT BETH STOOD STARING WHILE THE NEW MAID REGARDED HER WITH COMPOSURE AND A SLIGHT SMILE UPON HER BEAUTIFUL FACE", "subset": "test_clean", "task_type": "understanding", "prediction": "for a moment beth stood staring while the new maid regarded her with composure and a slight smile upon her beautiful face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0020.flac", "answer": "THEN SHE GAVE A LITTLE LAUGH AND REPLIED NO MISS BETH I'M ELIZABETH PARSONS", "subset": "test_clean", "task_type": "understanding", "prediction": "then she gave a little laugh and replied no miss beth i am elizabeth parsons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/6829/68771/6829-68771-0034.flac", "answer": "I WISH I KNEW MYSELF SHE CRIED FIERCELY", "subset": "test_clean", "task_type": "understanding", "prediction": "i wish i knew myself she cried fiercely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0047.flac", "answer": "DID YOU LOOK AT THESE PAPERS ON THE TABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "did you look at these papers on the table", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0010.flac", "answer": "I GAVE HIM A LITTLE BRANDY AND LEFT HIM COLLAPSED IN A CHAIR WHILE I MADE A MOST CAREFUL EXAMINATION OF THE ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "i gave him a little brandy and left him collapsed in a chair while i made a most careful examination of the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0016.flac", "answer": "I WAS IN SUCH A HURRY TO COME TO YOU YOU LEFT YOUR DOOR OPEN", "subset": "test_clean", "task_type": "understanding", "prediction": "i was in such a hurry to come to you you left your door open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0020.flac", "answer": "THEN HE APPROACHED IT AND STANDING ON TIPTOE WITH HIS NECK CRANED HE LOOKED INTO THE ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "then he approached it and standing on tiptoe with his neck craned he looked into the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0003.flac", "answer": "WITHOUT HIS SCRAPBOOKS HIS CHEMICALS AND HIS HOMELY UNTIDINESS HE WAS AN UNCOMFORTABLE MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "without his scrapbooks his chemicals and his homely untidiness he was an uncomfortable man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0023.flac", "answer": "ONE COULD HARDLY HOPE FOR ANY UPON SO DRY A DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "one could hardly hope for any upon so dry a day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0015.flac", "answer": "DID ANYONE KNOW THAT THESE PROOFS WOULD BE THERE NO ONE SAVE THE PRINTER", "subset": "test_clean", "task_type": "understanding", "prediction": "did any one know that these proofs would be there no one save the printer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0043.flac", "answer": "THE TOP FLOOR BELONGS TO MILES MC LAREN", "subset": "test_clean", "task_type": "understanding", "prediction": "the top floor belongs to miles mclaren", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0002.flac", "answer": "MY FRIEND'S TEMPER HAD NOT IMPROVED SINCE HE HAD BEEN DEPRIVED OF THE CONGENIAL SURROUNDINGS OF BAKER STREET", "subset": "test_clean", "task_type": "understanding", "prediction": "my friend s temper had not improved since he had been deprived of the congenial surroundings of baker street", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0024.flac", "answer": "YOU LEFT HIM IN A CHAIR YOU SAY WHICH CHAIR BY THE WINDOW THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "you left him in a chair you say which chair by the window there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0035.flac", "answer": "HOLMES TURNED AWAY AND STOOPED SUDDENLY TO THE FLOOR HALLOA WHAT'S THIS", "subset": "test_clean", "task_type": "understanding", "prediction": "holmes turned away and stooped suddenly to the floor hallo what is this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0011.flac", "answer": "A BROKEN TIP OF LEAD WAS LYING THERE ALSO", "subset": "test_clean", "task_type": "understanding", "prediction": "a broken tip of lead was lying there also", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0039.flac", "answer": "AND THEY ARE ALL IN FOR THIS EXAMINATION YES", "subset": "test_clean", "task_type": "understanding", "prediction": "and they are all in for this examination yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0040.flac", "answer": "ONE HARDLY LIKES TO THROW SUSPICION WHERE THERE ARE NO PROOFS", "subset": "test_clean", "task_type": "understanding", "prediction": "one hardly likes to throw suspicion where there are no proofs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0045.flac", "answer": "HE WAS STILL SUFFERING FROM THIS SUDDEN DISTURBANCE OF THE QUIET ROUTINE OF HIS LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "he was still suffering from the sudden disturbance of the quiet routine of his life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0013.flac", "answer": "ABOVE ALL THINGS I DESIRE TO SETTLE THE MATTER QUIETLY AND DISCREETLY", "subset": "test_clean", "task_type": "understanding", "prediction": "above all things i desire to settle the matter quietly and discreetly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0022.flac", "answer": "I AM AFRAID THERE ARE NO SIGNS HERE SAID HE", "subset": "test_clean", "task_type": "understanding", "prediction": "i am afraid there are no signs here said he", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0029.flac", "answer": "HE WAS IN THE MIDST OF THAT WHEN YOUR RETURN CAUSED HIM TO MAKE A VERY HURRIED RETREAT VERY HURRIED SINCE HE HAD NOT TIME TO REPLACE THE PAPERS WHICH WOULD TELL YOU THAT HE HAD BEEN THERE", "subset": "test_clean", "task_type": "understanding", "prediction": "he was in the midst of that when your return caused him to make a very hurried retreat very hurried since he had not time to replace the papers which would tell you that he had been there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0027.flac", "answer": "HOW LONG WOULD IT TAKE HIM TO DO THAT USING EVERY POSSIBLE CONTRACTION A QUARTER OF AN HOUR NOT LESS", "subset": "test_clean", "task_type": "understanding", "prediction": "how long would it take him to do that using every possible contraction a quarter of an hour not less", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0017.flac", "answer": "SO IT SEEMS TO ME", "subset": "test_clean", "task_type": "understanding", "prediction": "so it seems to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0053.flac", "answer": "YOU HAVEN'T SEEN ANY OF THEM NO SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "you have n t seen any of them no sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0041.flac", "answer": "LET US HEAR THE SUSPICIONS I WILL LOOK AFTER THE PROOFS", "subset": "test_clean", "task_type": "understanding", "prediction": "let us hear the suspicions i will look after the proofs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0021.flac", "answer": "THERE IS NO OPENING EXCEPT THE ONE PANE SAID OUR LEARNED GUIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "there is no opening except the one pane said our learned guide", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0038.flac", "answer": "I UNDERSTAND YOU TO SAY THAT THERE ARE THREE STUDENTS WHO USE THIS STAIR AND ARE IN THE HABIT OF PASSING YOUR DOOR YES THERE ARE", "subset": "test_clean", "task_type": "understanding", "prediction": "i understand you to say that there are three students who use this stair and are in the habit of passing your door yes there are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0014.flac", "answer": "TO THE BEST OF MY BELIEF THEY WERE ROLLED UP", "subset": "test_clean", "task_type": "understanding", "prediction": "to the best of my belief they were rolled up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0028.flac", "answer": "THEN HE TOSSED IT DOWN AND SEIZED THE NEXT", "subset": "test_clean", "task_type": "understanding", "prediction": "then he tossed it down and seized the next", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0025.flac", "answer": "THE MAN ENTERED AND TOOK THE PAPERS SHEET BY SHEET FROM THE CENTRAL TABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "the men entered and took the papers sheet by sheet from the central table", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0042.flac", "answer": "MY SCHOLAR HAS BEEN LEFT VERY POOR BUT HE IS HARD WORKING AND INDUSTRIOUS HE WILL DO WELL", "subset": "test_clean", "task_type": "understanding", "prediction": "my scholar has been left very poor but he is hard working and industrious he will do well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0004.flac", "answer": "I HAD TO READ IT OVER CAREFULLY AS THE TEXT MUST BE ABSOLUTELY CORRECT", "subset": "test_clean", "task_type": "understanding", "prediction": "i had to read it over carefully as the text must be absolutely correct", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0001.flac", "answer": "I HAD ALWAYS KNOWN HIM TO BE RESTLESS IN HIS MANNER BUT ON THIS PARTICULAR OCCASION HE WAS IN SUCH A STATE OF UNCONTROLLABLE AGITATION THAT IT WAS CLEAR SOMETHING VERY UNUSUAL HAD OCCURRED", "subset": "test_clean", "task_type": "understanding", "prediction": "i had always known him to be restless in his manner but on this particular occasion he was in such a state of uncontrollable agitation that it was clear something very unusual had occurred", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0037.flac", "answer": "WHAT COULD HE DO HE CAUGHT UP EVERYTHING WHICH WOULD BETRAY HIM AND HE RUSHED INTO YOUR BEDROOM TO CONCEAL HIMSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "what could he do he caught up everything which would betray him and he rushed into your bedroom to conceal himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0030.flac", "answer": "MISTER SOAMES WAS SOMEWHAT OVERWHELMED BY THIS FLOOD OF INFORMATION", "subset": "test_clean", "task_type": "understanding", "prediction": "mr solmes was somewhat overwhelmed by this flood of information", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0008.flac", "answer": "THE PROOF WAS IN THREE LONG SLIPS I HAD LEFT THEM ALL TOGETHER", "subset": "test_clean", "task_type": "understanding", "prediction": "the proof was in three long slips i had left them all together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0018.flac", "answer": "NOW MISTER SOAMES AT YOUR DISPOSAL", "subset": "test_clean", "task_type": "understanding", "prediction": "now mr solmes at your disposal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0050.flac", "answer": "I REALLY DON'T THINK HE KNEW MUCH ABOUT IT MISTER HOLMES", "subset": "test_clean", "task_type": "understanding", "prediction": "i really don't think he knew much about it mr holmes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0007.flac", "answer": "THE MOMENT I LOOKED AT MY TABLE I WAS AWARE THAT SOMEONE HAD RUMMAGED AMONG MY PAPERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the moment i looked at my table i was aware that some one had rummaged among my papers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0044.flac", "answer": "I DARE NOT GO SO FAR AS THAT BUT OF THE THREE HE IS PERHAPS THE LEAST UNLIKELY", "subset": "test_clean", "task_type": "understanding", "prediction": "i dare not go so far as that but of the three he is perhaps the least unlikely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0019.flac", "answer": "ABOVE WERE THREE STUDENTS ONE ON EACH STORY", "subset": "test_clean", "task_type": "understanding", "prediction": "above were three students one on each story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0032.flac", "answer": "WATSON I HAVE ALWAYS DONE YOU AN INJUSTICE THERE ARE OTHERS", "subset": "test_clean", "task_type": "understanding", "prediction": "watson i have always done you an injustice there are others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0036.flac", "answer": "HOLMES HELD IT OUT ON HIS OPEN PALM IN THE GLARE OF THE ELECTRIC LIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "holmes held it out on his open palm in the glare of the electric light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0005.flac", "answer": "I WAS ABSENT RATHER MORE THAN AN HOUR", "subset": "test_clean", "task_type": "understanding", "prediction": "i was absent rather more than an hour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0048.flac", "answer": "HOW CAME YOU TO LEAVE THE KEY IN THE DOOR", "subset": "test_clean", "task_type": "understanding", "prediction": "how came you to leave the key in the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0026.flac", "answer": "AS A MATTER OF FACT HE COULD NOT SAID SOAMES FOR I ENTERED BY THE SIDE DOOR", "subset": "test_clean", "task_type": "understanding", "prediction": "as a matter of fact he could not said solmes for i entered by the side door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0051.flac", "answer": "ONLY FOR A MINUTE OR SO", "subset": "test_clean", "task_type": "understanding", "prediction": "only for a minute or so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0006.flac", "answer": "THE ONLY DUPLICATE WHICH EXISTED SO FAR AS I KNEW WAS THAT WHICH BELONGED TO MY SERVANT BANNISTER A MAN WHO HAS LOOKED AFTER MY ROOM FOR TEN YEARS AND WHOSE HONESTY IS ABSOLUTELY ABOVE SUSPICION", "subset": "test_clean", "task_type": "understanding", "prediction": "the only duplicate which existed so far as i knew was that which belonged to my servant bannister a man who has looked after my room for ten years and whose honesty is absolutely above suspicion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0009.flac", "answer": "THE ALTERNATIVE WAS THAT SOMEONE PASSING HAD OBSERVED THE KEY IN THE DOOR HAD KNOWN THAT I WAS OUT AND HAD ENTERED TO LOOK AT THE PAPERS", "subset": "test_clean", "task_type": "understanding", "prediction": "the alternative was that some one passing had observed the key in the door had known that i was out and had entered to look at the papers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0012.flac", "answer": "NOT ONLY THIS BUT ON THE TABLE I FOUND A SMALL BALL OF BLACK DOUGH OR CLAY WITH SPECKS OF SOMETHING WHICH LOOKS LIKE SAWDUST IN IT", "subset": "test_clean", "task_type": "understanding", "prediction": "not only this but on the table i found a small ball of black dough or clay with specks of something which looks like sawdust in it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0031.flac", "answer": "HOLMES HELD OUT A SMALL CHIP WITH THE LETTERS N N AND A SPACE OF CLEAR WOOD AFTER THEM YOU SEE", "subset": "test_clean", "task_type": "understanding", "prediction": "holmes held out a small chip with the letters n n and a space of clear wood after them you see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0052.flac", "answer": "OH I WOULD NOT VENTURE TO SAY SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "oh i would not venture to say sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0049.flac", "answer": "ANYONE IN THE ROOM COULD GET OUT YES SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "any one in the room could get out yes sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0046.flac", "answer": "BUT I HAVE OCCASIONALLY DONE THE SAME THING AT OTHER TIMES", "subset": "test_clean", "task_type": "understanding", "prediction": "but i have occasionally done the same thing at other times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0000.flac", "answer": "I WILL ENDEAVOUR IN MY STATEMENT TO AVOID SUCH TERMS AS WOULD SERVE TO LIMIT THE EVENTS TO ANY PARTICULAR PLACE OR GIVE A CLUE AS TO THE PEOPLE CONCERNED", "subset": "test_clean", "task_type": "understanding", "prediction": "i will endeavor in my statement to avoid such terms as would serve to limit the events to any particular place or give a clue as to the people concerned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0034.flac", "answer": "AS HOLMES DREW THE CURTAIN I WAS AWARE FROM SOME LITTLE RIGIDITY AND ALERTNESS OF HIS ATTITUDE THAT HE WAS PREPARED FOR AN EMERGENCY", "subset": "test_clean", "task_type": "understanding", "prediction": "as holmes drew the curtain i was aware from some little rigidity and an alertness of his attitude that he was prepared for an emergency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141083/1580-141083-0033.flac", "answer": "I WAS HOPING THAT IF THE PAPER ON WHICH HE WROTE WAS THIN SOME TRACE OF IT MIGHT COME THROUGH UPON THIS POLISHED SURFACE NO I SEE NOTHING", "subset": "test_clean", "task_type": "understanding", "prediction": "i was hoping that if the paper on which he wrote was thin some trace of it might come through upon this polished surface no i see nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0037.flac", "answer": "WHEN I APPROACHED YOUR ROOM I EXAMINED THE WINDOW", "subset": "test_clean", "task_type": "understanding", "prediction": "when i approached your room i examined the window", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0010.flac", "answer": "I WILL TAKE THE BLACK CLAY WITH ME ALSO THE PENCIL CUTTINGS GOOD BYE", "subset": "test_clean", "task_type": "understanding", "prediction": "i will take the black clay with me also the pencil cuttings good bye", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0003.flac", "answer": "NO NAMES PLEASE SAID HOLMES AS WE KNOCKED AT GILCHRIST'S DOOR", "subset": "test_clean", "task_type": "understanding", "prediction": "no names please said holmes as we knocked at gilchrist s door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0014.flac", "answer": "WHY BANNISTER THE SERVANT WHAT'S HIS GAME IN THE MATTER", "subset": "test_clean", "task_type": "understanding", "prediction": "why bannister the servant what is his game in the matter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0027.flac", "answer": "NO SIR CERTAINLY NOT", "subset": "test_clean", "task_type": "understanding", "prediction": "no sir certainly not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0001.flac", "answer": "HE WAS PACING SWIFTLY UP AND DOWN HIS ROOM", "subset": "test_clean", "task_type": "understanding", "prediction": "he was pacing swiftly up and down his room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0022.flac", "answer": "AND ONE MORE THIS MORNING", "subset": "test_clean", "task_type": "understanding", "prediction": "and one more this morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0033.flac", "answer": "COME COME SAID HOLMES KINDLY IT IS HUMAN TO ERR AND AT LEAST NO ONE CAN ACCUSE YOU OF BEING A CALLOUS CRIMINAL", "subset": "test_clean", "task_type": "understanding", "prediction": "come come said holmes kindly it is human to err and at least no one can accuse you of being a callous criminal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0007.flac", "answer": "TO MORROW IS THE EXAMINATION", "subset": "test_clean", "task_type": "understanding", "prediction": "tomorrow is the examination", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0032.flac", "answer": "FOR A MOMENT GILCHRIST WITH UPRAISED HAND TRIED TO CONTROL HIS WRITHING FEATURES", "subset": "test_clean", "task_type": "understanding", "prediction": "for a moment gilchrist with upraised hand tried to control his writhing features", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0041.flac", "answer": "NO HARM WOULD HAVE BEEN DONE HAD IT NOT BEEN THAT AS HE PASSED YOUR DOOR HE PERCEIVED THE KEY WHICH HAD BEEN LEFT BY THE CARELESSNESS OF YOUR SERVANT", "subset": "test_clean", "task_type": "understanding", "prediction": "no harm would have been done had it not been that as he passed your door he perceived the key which had been left by the carelessness of your servant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0002.flac", "answer": "THIS SET OF ROOMS IS QUITE THE OLDEST IN THE COLLEGE AND IT IS NOT UNUSUAL FOR VISITORS TO GO OVER THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "this set of rooms is quite the oldest in the college and it is not unusual for visitors to go over them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0024.flac", "answer": "HE COULD HARDLY STAND STILL SO GREAT WAS HIS MENTAL AGITATION AND HE RAN TOWARDS HOLMES WITH TWO EAGER HANDS OUTSTRETCHED THANK HEAVEN THAT YOU HAVE COME", "subset": "test_clean", "task_type": "understanding", "prediction": "he could hardly stand still so great was his mental agitation and he ran towards holmes with two eager hands outstretched thank heaven that you have come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0023.flac", "answer": "IN A FEW HOURS THE EXAMINATION WOULD COMMENCE AND HE WAS STILL IN THE DILEMMA BETWEEN MAKING THE FACTS PUBLIC AND ALLOWING THE CULPRIT TO COMPETE FOR THE VALUABLE SCHOLARSHIP", "subset": "test_clean", "task_type": "understanding", "prediction": "in a few hours the examination would commence and he was still in the dilemma between making the facts public and allowing the culprit to compete for the valuable scholarship", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0016.flac", "answer": "MY FRIEND DID NOT APPEAR TO BE DEPRESSED BY HIS FAILURE BUT SHRUGGED HIS SHOULDERS IN HALF HUMOROUS RESIGNATION", "subset": "test_clean", "task_type": "understanding", "prediction": "my friend did not appear to be depressed by his failure but shrugged his shoulders in half humorous resignation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0042.flac", "answer": "A SUDDEN IMPULSE CAME OVER HIM TO ENTER AND SEE IF THEY WERE INDEED THE PROOFS", "subset": "test_clean", "task_type": "understanding", "prediction": "a sudden impulse came over him to enter and see if they were indeed the proofs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0044.flac", "answer": "GLOVES SAID THE YOUNG MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "gloves said the young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0030.flac", "answer": "JUST CLOSE THE DOOR SAID HOLMES", "subset": "test_clean", "task_type": "understanding", "prediction": "just close the door said holmes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0006.flac", "answer": "YOU DON'T SEEM TO REALIZE THE POSITION", "subset": "test_clean", "task_type": "understanding", "prediction": "you dont seem to realize the position", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0000.flac", "answer": "IT WAS THE INDIAN WHOSE DARK SILHOUETTE APPEARED SUDDENLY UPON HIS BLIND", "subset": "test_clean", "task_type": "understanding", "prediction": "it was the indian whose dark silhouette appeared suddenly upon his blind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0028.flac", "answer": "THERE WAS NO MAN SIR", "subset": "test_clean", "task_type": "understanding", "prediction": "there was no man sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0012.flac", "answer": "THE FOUL MOUTHED FELLOW AT THE TOP", "subset": "test_clean", "task_type": "understanding", "prediction": "the foul mouthed fellow at the top", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0009.flac", "answer": "IT IS POSSIBLE THAT I MAY BE IN A POSITION THEN TO INDICATE SOME COURSE OF ACTION", "subset": "test_clean", "task_type": "understanding", "prediction": "it is possible that i may be in a position then to indicate some course of action", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0048.flac", "answer": "IT WILL BE CLEAR TO YOU FROM WHAT I HAVE SAID THAT ONLY YOU COULD HAVE LET THIS YOUNG MAN OUT SINCE YOU WERE LEFT IN THE ROOM AND MUST HAVE LOCKED THE DOOR WHEN YOU WENT OUT", "subset": "test_clean", "task_type": "understanding", "prediction": "it would be clear to you from what i have said that only you could have let this young man out since you were left in the room and must have locked the door when you went out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0031.flac", "answer": "WE WANT TO KNOW MISTER GILCHRIST HOW YOU AN HONOURABLE MAN EVER CAME TO COMMIT SUCH AN ACTION AS THAT OF YESTERDAY", "subset": "test_clean", "task_type": "understanding", "prediction": "we want to know mr gilchrist how you an honorable man ever came to commit such an action as that of yesterday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0046.flac", "answer": "HAVE I TOLD THE TRUTH MISTER GILCHRIST", "subset": "test_clean", "task_type": "understanding", "prediction": "have i told the truth mr gilchrist", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0029.flac", "answer": "HIS TROUBLED BLUE EYES GLANCED AT EACH OF US AND FINALLY RESTED WITH AN EXPRESSION OF BLANK DISMAY UPON BANNISTER IN THE FARTHER CORNER", "subset": "test_clean", "task_type": "understanding", "prediction": "his troubled blue eyes glanced at each of us and finally rested with an expression of blank dismay upon bannister in the farther corner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0008.flac", "answer": "I CANNOT ALLOW THE EXAMINATION TO BE HELD IF ONE OF THE PAPERS HAS BEEN TAMPERED WITH THE SITUATION MUST BE FACED", "subset": "test_clean", "task_type": "understanding", "prediction": "i cannot allow the examination to be held if one of the papers has been tampered with the situation must be faced", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0045.flac", "answer": "SUDDENLY HE HEARD HIM AT THE VERY DOOR THERE WAS NO POSSIBLE ESCAPE", "subset": "test_clean", "task_type": "understanding", "prediction": "suddenly he heard him at the very door there was no possible escape", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0040.flac", "answer": "HE RETURNED CARRYING HIS JUMPING SHOES WHICH ARE PROVIDED AS YOU ARE AWARE WITH SEVERAL SHARP SPIKES", "subset": "test_clean", "task_type": "understanding", "prediction": "he returned carrying his jumping shoes which are provided as you are aware with several sharp spikes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0050.flac", "answer": "IF MISTER SOAMES SAW THEM THE GAME WAS UP", "subset": "test_clean", "task_type": "understanding", "prediction": "if mr solmes saw them the game was up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0021.flac", "answer": "ON THE PALM WERE THREE LITTLE PYRAMIDS OF BLACK DOUGHY CLAY", "subset": "test_clean", "task_type": "understanding", "prediction": "on the palm were three little pyramids of black doughy clay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0017.flac", "answer": "NO GOOD MY DEAR WATSON", "subset": "test_clean", "task_type": "understanding", "prediction": "no good my dear watson", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0019.flac", "answer": "YES MY DEAR WATSON I HAVE SOLVED THE MYSTERY", "subset": "test_clean", "task_type": "understanding", "prediction": "yes my dear watson i have solved the mystery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0020.flac", "answer": "LOOK AT THAT HE HELD OUT HIS HAND", "subset": "test_clean", "task_type": "understanding", "prediction": "look at that he held out his hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0026.flac", "answer": "IF THIS MATTER IS NOT TO BECOME PUBLIC WE MUST GIVE OURSELVES CERTAIN POWERS AND RESOLVE OURSELVES INTO A SMALL PRIVATE COURT MARTIAL", "subset": "test_clean", "task_type": "understanding", "prediction": "if this matter is not to become public we must give ourselves certain powers and resolve ourselves into a small private court martial", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0013.flac", "answer": "HE IS THE ONE WITH THE WORST RECORD", "subset": "test_clean", "task_type": "understanding", "prediction": "he is the one with the worst record", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0038.flac", "answer": "NO ONE LESS THAN THAT WOULD HAVE A CHANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "no one less than that would have a chance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0043.flac", "answer": "HE PUT HIS SHOES ON THE TABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "he put his shoes on the table", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0018.flac", "answer": "I THINK SO YOU HAVE FORMED A CONCLUSION", "subset": "test_clean", "task_type": "understanding", "prediction": "i think so you have formed a conclusion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0047.flac", "answer": "I HAVE A LETTER HERE MISTER SOAMES WHICH I WROTE TO YOU EARLY THIS MORNING IN THE MIDDLE OF A RESTLESS NIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "i have a letter here mr solmes which i wrote to you early this morning in the middle of a restless night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0049.flac", "answer": "IT WAS SIMPLE ENOUGH SIR IF YOU ONLY HAD KNOWN BUT WITH ALL YOUR CLEVERNESS IT WAS IMPOSSIBLE THAT YOU COULD KNOW", "subset": "test_clean", "task_type": "understanding", "prediction": "it was simple enough sir if you only had known but with all your cleverness it was impossible that you could know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0011.flac", "answer": "WHEN WE WERE OUT IN THE DARKNESS OF THE QUADRANGLE WE AGAIN LOOKED UP AT THE WINDOWS", "subset": "test_clean", "task_type": "understanding", "prediction": "when we were out in the darkness of the quadrangle we again looked up at the windows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0025.flac", "answer": "YOU KNOW HIM I THINK SO", "subset": "test_clean", "task_type": "understanding", "prediction": "you know him i think so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0015.flac", "answer": "HE IMPRESSED ME AS BEING A PERFECTLY HONEST MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "he impressed me as being a perfectly honest man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0036.flac", "answer": "THE INDIAN I ALSO THOUGHT NOTHING OF", "subset": "test_clean", "task_type": "understanding", "prediction": "the indian i also thought nothing of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0035.flac", "answer": "HE COULD EXAMINE THE PAPERS IN HIS OWN OFFICE", "subset": "test_clean", "task_type": "understanding", "prediction": "he could examine the papers in his own office", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0039.flac", "answer": "I ENTERED AND I TOOK YOU INTO MY CONFIDENCE AS TO THE SUGGESTIONS OF THE SIDE TABLE", "subset": "test_clean", "task_type": "understanding", "prediction": "i entered and i took you into my confidence as to the suggestions of the side table", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0034.flac", "answer": "WELL WELL DON'T TROUBLE TO ANSWER LISTEN AND SEE THAT I DO YOU NO INJUSTICE", "subset": "test_clean", "task_type": "understanding", "prediction": "well well dont trouble to answer listen and see that i do you no injustice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0005.flac", "answer": "THAT IS VERY IMPORTANT SAID HOLMES", "subset": "test_clean", "task_type": "understanding", "prediction": "that is very important said holmes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1580/141084/1580-141084-0004.flac", "answer": "OF COURSE HE DID NOT REALIZE THAT IT WAS I WHO WAS KNOCKING BUT NONE THE LESS HIS CONDUCT WAS VERY UNCOURTEOUS AND INDEED UNDER THE CIRCUMSTANCES RATHER SUSPICIOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "of course he did not realize that it was i who was knocking but none the less his conduct was very uncourteous and indeed under the circumstances rather suspicious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0036.flac", "answer": "GEORGE MONTFICHET WILL NEVER FORGET THIS DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "george montfichet will never forget this day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0047.flac", "answer": "MASTER MONCEUX THE SHERIFF OF NOTTINGHAM WAS MIGHTILY PUT ABOUT WHEN TOLD OF THE RIOTING", "subset": "test_clean", "task_type": "understanding", "prediction": "master monceux the sheriff of nottingham was mightily put about when told of the rioting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0058.flac", "answer": "WILL YOU FORGIVE ME NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "will you forgive me now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0007.flac", "answer": "SISTER NELL DO YOU HEAR THESE MARVELS", "subset": "test_clean", "task_type": "understanding", "prediction": "sister nell do you hear these marvels", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0032.flac", "answer": "HE FELT FOR AND FOUND THE WIZARD'S BLACK CLOTH THE SQUIRE WAS QUITE OUT OF BREATH", "subset": "test_clean", "task_type": "understanding", "prediction": "he felt for and found the wizard s black cloth the squire was quite out of breath", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0062.flac", "answer": "AY AND SHOW YOU SOME PRETTY TRICKS", "subset": "test_clean", "task_type": "understanding", "prediction": "ay and show you some pretty tricks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0008.flac", "answer": "TAKE YOUR PLACE AND LET US SEE WHAT THE CRYSTAL CAN SHOW TO YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "take your place and let us see what the crystal can show to you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0025.flac", "answer": "COME TO ME MEN HERE HERE HE RAISED HIS VOICE STILL LOUDER", "subset": "test_clean", "task_type": "understanding", "prediction": "come to me men here here he raised his voice still louder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0022.flac", "answer": "TIS FINE FOR YOU TO TALK OLD MAN ANSWERED THE LEAN SULLEN APPRENTICE", "subset": "test_clean", "task_type": "understanding", "prediction": "tis fine for you to talk old man answered the lean sullen apprentice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0010.flac", "answer": "FORTHWITH ALL RAN TO THE OPENING OF THE TENT TO SEE WHAT MIGHT BE AMISS BUT MASTER WILL WHO PEEPED OUT FIRST NEEDED NO MORE THAN ONE GLANCE", "subset": "test_clean", "task_type": "understanding", "prediction": "forthwith all ran to the opening of the tent to see what might be amiss but master will who peeped out first needed no more than one glance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0051.flac", "answer": "BEG ME A ROOM OF THE SHERIFF CHILD QUICKLY", "subset": "test_clean", "task_type": "understanding", "prediction": "beg me a room of the sheriff child quickly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0016.flac", "answer": "AND THEN THEY BECAME VEXED AND WOULD HAVE SNATCHED YOUR PURSE FROM US", "subset": "test_clean", "task_type": "understanding", "prediction": "and then they became vexed and would have snatched your purse from us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0044.flac", "answer": "IT WILL NOT BE SAFE FOR YOU TO STAY HERE NOW", "subset": "test_clean", "task_type": "understanding", "prediction": "it will not be safe for you to stay here now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0018.flac", "answer": "SO I DID PUSH THIS FELLOW", "subset": "test_clean", "task_type": "understanding", "prediction": "so i did push this fellow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0048.flac", "answer": "AND HENRY MIGHT RETURN TO ENGLAND AT ANY MOMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "and henry might return to england at any moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0005.flac", "answer": "THIS WAS SO SWEET A LADY SIR AND IN SOME MANNER I DO THINK SHE DIED", "subset": "test_clean", "task_type": "understanding", "prediction": "this was so sweet a lady sir and in some manner i do think she died", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0053.flac", "answer": "HE IS MY ESQUIRE EXCELLENCY RETURNED ROBIN WITH DIGNITY", "subset": "test_clean", "task_type": "understanding", "prediction": "he is my esquire excellency returned robin with dignity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0050.flac", "answer": "HE MADE AN EFFORT TO HIDE HIS CONDITION FROM THEM ALL AND ROBIN FELT HIS FINGERS TIGHTEN UPON HIS ARM", "subset": "test_clean", "task_type": "understanding", "prediction": "he made an effort to hide his condition from them all and robin felt his fingers tighten upon his arm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0033.flac", "answer": "THRUSTING OPEN THE PROPER ENTRANCE OF THE TENT ROBIN SUDDENLY RUSHED FORTH WITH HIS BURDEN WITH A GREAT SHOUT", "subset": "test_clean", "task_type": "understanding", "prediction": "thrusting open the proper entrance of the tent robin suddenly rushed forth with his burden with a great shout", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0039.flac", "answer": "AND MINE IS WILL STUTELEY SHALL WE BE COMRADES", "subset": "test_clean", "task_type": "understanding", "prediction": "and mine is will stuteley shall we be comrades", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0023.flac", "answer": "BUT I WRESTLED WITH THIS FELLOW AND DO KNOW THAT HE PLAYED UNFAIRLY IN THE SECOND BOUT", "subset": "test_clean", "task_type": "understanding", "prediction": "but i wrestled with this fellow and do know that he played unfairly in the second bout", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0013.flac", "answer": "BEFORE THEM FLED THE STROLLER AND HIS THREE SONS CAPLESS AND TERRIFIED", "subset": "test_clean", "task_type": "understanding", "prediction": "before them fled the stroller and his three sons capless and terrified", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0056.flac", "answer": "THE WINE DID CERTAINLY BRING BACK THE COLOR TO THE SQUIRE'S CHEEKS", "subset": "test_clean", "task_type": "understanding", "prediction": "the wine did certainly bring back the colour to the squire s cheeks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0061.flac", "answer": "YOU ARE A WORTHY LEECH WILL PRESENTLY WHISPERED ROBIN THE WINE HAS WORKED A MARVEL", "subset": "test_clean", "task_type": "understanding", "prediction": "you are a worthy leech will presently whispered robin the wine has worked a marvel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0040.flac", "answer": "RIGHT WILLINGLY FOR BETWEEN US WE HAVE WON THE BATTLE ANSWERED ROBIN", "subset": "test_clean", "task_type": "understanding", "prediction": "right willingly for between us we have won the battle answered robin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0031.flac", "answer": "SILENCE YOU KNAVE CRIED MONTFICHET", "subset": "test_clean", "task_type": "understanding", "prediction": "silence you knave cried montfichet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0020.flac", "answer": "SHAME ON YOU CITIZENS CRIED HE I BLUSH FOR MY FELLOWS OF NOTTINGHAM", "subset": "test_clean", "task_type": "understanding", "prediction": "shame on you citizens cried he i blush for my fellows of nottingham", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0059.flac", "answer": "IT WILL BE NO DISAPPOINTMENT TO ME", "subset": "test_clean", "task_type": "understanding", "prediction": "it will be no disappointment to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0017.flac", "answer": "I COULD NOT SEE MY BOY INJURED EXCELLENCE FOR BUT DOING HIS DUTY AS ONE OF CUMBERLAND'S SONS", "subset": "test_clean", "task_type": "understanding", "prediction": "i could not see my boy injured excellence for but doing his duty as one of cumberland sons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0055.flac", "answer": "ROBIN WAS GLAD WHEN AT LENGTH THEY WERE LEFT TO THEIR OWN DEVICES", "subset": "test_clean", "task_type": "understanding", "prediction": "robin was glad when at length they were left to their own devices", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0054.flac", "answer": "MISTRESS FITZOOTH HAD BEEN CARRIED OFF BY THE SHERIFF'S DAUGHTER AND HER MAIDS AS SOON AS THEY HAD ENTERED THE HOUSE SO THAT ROBIN ALONE HAD THE CARE OF MONTFICHET", "subset": "test_clean", "task_type": "understanding", "prediction": "mistress fitzooth had been carried off by the sheriff s daughter and her maids as soon as they had entered the house so that robin alone had the care of mountfitchet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0052.flac", "answer": "BUT WHO IS THIS FELLOW PLUCKING AT YOUR SLEEVE", "subset": "test_clean", "task_type": "understanding", "prediction": "but who is this fellow plucking at your sleeve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0003.flac", "answer": "HE WAS LIKE UNTO MY FATHER IN A WAY AND YET WAS NOT MY FATHER", "subset": "test_clean", "task_type": "understanding", "prediction": "he was like unto my father in a way and yet was not my father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0057.flac", "answer": "THESE ESCAPADES ARE NOT FOR OLD GAMEWELL LAD HIS DAY HAS COME TO TWILIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "these escapades are not for old game well lad his day has come to twilight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0045.flac", "answer": "PRAY FOLLOW US WITH MINE AND MY LORD SHERIFF'S MEN", "subset": "test_clean", "task_type": "understanding", "prediction": "pray follow us with mine and my lord sheriffs men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0030.flac", "answer": "NOW BE SILENT ON YOUR LIVES HE BEGAN BUT THE CAPTURED APPRENTICE SET UP AN INSTANT SHOUT", "subset": "test_clean", "task_type": "understanding", "prediction": "now be silent on your lives he began but the captured apprentice set up an instant shout", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0035.flac", "answer": "TAKING ADVANTAGE OF THIS THE SQUIRE'S FEW MEN REDOUBLED THEIR EFFORTS AND ENCOURAGED BY ROBIN'S AND THE LITTLE STROLLER'S CRIES FOUGHT THEIR WAY TO HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "taking advantage of this the squire s few men redoubled their efforts and encouraged by robin s and the little stroller s cries fought their way to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0004.flac", "answer": "ALSO THERE WAS A STRIPLING PAGE WHO TURNED INTO A MAID", "subset": "test_clean", "task_type": "understanding", "prediction": "also there was a stripling page who turned into a maid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0011.flac", "answer": "HE GAVE WAY TO THE OTHERS VERY READILY AND RETREATED UNPERCEIVED BY THE SQUIRE AND MISTRESS FITZOOTH TO THE REAR OF THE TENT", "subset": "test_clean", "task_type": "understanding", "prediction": "he gave way to the others very readily and retreated unperceived by the squire and mistress fitzooth to the rear of the tent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0049.flac", "answer": "HAVE YOUR WILL CHILD IF THE BOY ALSO WILLS IT MONTFICHET ANSWERED FEELING TOO ILL TO OPPOSE ANYTHING VERY STRONGLY JUST THEN", "subset": "test_clean", "task_type": "understanding", "prediction": "have your will child if the boy also wills it montfichet answered feeling too ill to oppose anything very strongly just then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0037.flac", "answer": "WHAT IS YOUR NAME LORDING ASKED THE LITTLE STROLLER PRESENTLY", "subset": "test_clean", "task_type": "understanding", "prediction": "what is your name lording asked the little stroller presently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0002.flac", "answer": "A GOLDEN FORTUNE AND A HAPPY LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "a golden fortune and a happy life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0027.flac", "answer": "ROBIN AND THE LITTLE TUMBLER BETWEEN THEM TRIED TO FORCE THE SQUIRE TO STAND BACK AND VERY VALIANTLY DID THESE TWO COMPORT THEMSELVES", "subset": "test_clean", "task_type": "understanding", "prediction": "robin and the little tumbler between them tried to force the squire to stand back and very valiantly did these two comport themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0043.flac", "answer": "FRIENDS SAID MONTFICHET FAINTLY TO THE WRESTLERS BEAR US ESCORT SO FAR AS THE SHERIFF'S HOUSE", "subset": "test_clean", "task_type": "understanding", "prediction": "friends said montfichet faintly to the wrestlers bear us escort so far as the sheriff s house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0014.flac", "answer": "WHAT IS THE TUMULT AND RIOTING CRIED OUT THE SQUIRE AUTHORITATIVELY AND HE BLEW TWICE ON A SILVER WHISTLE WHICH HUNG AT HIS BELT", "subset": "test_clean", "task_type": "understanding", "prediction": "what is that tumult and rioting cried out the squire authoritatively and he blew twice on the silver whistle which hung at his belt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0021.flac", "answer": "SURELY WE CAN SUBMIT WITH GOOD GRACE", "subset": "test_clean", "task_type": "understanding", "prediction": "surely we can submit with good grace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0034.flac", "answer": "A MONTFICHET A MONTFICHET GAMEWELL TO THE RESCUE", "subset": "test_clean", "task_type": "understanding", "prediction": "a montfichet a montfichet game well to the rescue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0028.flac", "answer": "THE HEAD AND CHIEF OF THE RIOT THE NOTTINGHAM APPRENTICE WITH CLENCHED FISTS THREATENED MONTFICHET", "subset": "test_clean", "task_type": "understanding", "prediction": "the head and chief of the riot the nottingham apprentice with clenched fists threatened montfichet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0029.flac", "answer": "THE SQUIRE HELPED TO THRUST THEM ALL IN AND ENTERED SWIFTLY HIMSELF", "subset": "test_clean", "task_type": "understanding", "prediction": "the squire helped to thrust them all in and entered swiftly himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0026.flac", "answer": "THE STROLLERS TOOK THEIR PART IN IT WITH HEARTY ZEST NOW THAT THEY HAD SOME CHANCE OF BEATING OFF THEIR FOES", "subset": "test_clean", "task_type": "understanding", "prediction": "the strollers took their part in it with hearty zest now that they had some chance of beating off their foes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0006.flac", "answer": "BUT THEN THE PICTURE WAS GONE AS QUICKLY AS IT CAME", "subset": "test_clean", "task_type": "understanding", "prediction": "but then the picture was gone as quickly as it came", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0001.flac", "answer": "GIVE NOT SO EARNEST A MIND TO THESE MUMMERIES CHILD", "subset": "test_clean", "task_type": "understanding", "prediction": "give not so earnest a mind to these mummeries child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0019.flac", "answer": "IT IS ENOUGH SAID GEORGE GAMEWELL SHARPLY AND HE TURNED UPON THE CROWD", "subset": "test_clean", "task_type": "understanding", "prediction": "it is enough said george gamewell sharply as he turned upon the crowd", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0000.flac", "answer": "HE BEGAN A CONFUSED COMPLAINT AGAINST THE WIZARD WHO HAD VANISHED BEHIND THE CURTAIN ON THE LEFT", "subset": "test_clean", "task_type": "understanding", "prediction": "he began a confused complaint against the wizard who had vanished behind the curtain on the left", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0046.flac", "answer": "NOTTINGHAM CASTLE WAS REACHED AND ADMITTANCE WAS DEMANDED", "subset": "test_clean", "task_type": "understanding", "prediction": "nottingham castle was reached and admittance was demanded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0015.flac", "answer": "NAY WE REFUSED THEIR REQUEST MOST POLITELY MOST NOBLE SAID THE LITTLE STROLLER", "subset": "test_clean", "task_type": "understanding", "prediction": "nay we refused their request most politely most noble said the little stroller", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0012.flac", "answer": "CRIES OF A NOTTINGHAM A NOTTINGHAM", "subset": "test_clean", "task_type": "understanding", "prediction": "cries of a nottingham a nottingham", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0060.flac", "answer": "NO THANKS I AM GLAD TO GIVE YOU SUCH EASY HAPPINESS", "subset": "test_clean", "task_type": "understanding", "prediction": "no thanks i am glad to give you such easy happiness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0009.flac", "answer": "LIKE AS NOT YOUNG MASTER THOUGH I AM AN OLD MAN", "subset": "test_clean", "task_type": "understanding", "prediction": "like as not young master though i am an old man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0041.flac", "answer": "I LIKE YOU WILL YOU ARE THE SECOND WILL THAT I HAVE MET AND LIKED WITHIN TWO DAYS IS THERE A SIGN IN THAT", "subset": "test_clean", "task_type": "understanding", "prediction": "i like you will you are the second will that i have met and liked within two days is there a sign in that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0042.flac", "answer": "MONTFICHET CALLED OUT FOR ROBIN TO GIVE HIM AN ARM", "subset": "test_clean", "task_type": "understanding", "prediction": "montfichet called out for robin to give him an arm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0024.flac", "answer": "SPOKE THE SQUIRE LOSING ALL PATIENCE AND IT WAS TO YOU THAT I GAVE ANOTHER PURSE IN CONSOLATION", "subset": "test_clean", "task_type": "understanding", "prediction": "spoke the squire losing all patience and it was to you that i gave another person consolation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70968/61-70968-0038.flac", "answer": "ROBIN FITZOOTH", "subset": "test_clean", "task_type": "understanding", "prediction": "robin fitzooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0013.flac", "answer": "THERE WAS NO CHANCE TO ALTER HIS SLEEPING ROOM TO ONE NEARER TO GAMEWELL'S CHAMBER", "subset": "test_clean", "task_type": "understanding", "prediction": "there was no chance to alter his sleeping room to one nearer to gamewell s chamber", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0025.flac", "answer": "THEY WERE UPON THE VERGE OF AN OPEN TRAP IN THE FAR CORNER OF THE HUT AND STUTELEY HAD TRIPPED OVER THE EDGE OF THE REVERSED FLAP MOUTH OF THIS PIT", "subset": "test_clean", "task_type": "understanding", "prediction": "they were upon the verge of an open trap in the far corner of the hut and studley had tripped over the edge of the reversed flap mouth of this pit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0001.flac", "answer": "THERE BEFELL AN ANXIOUS INTERVIEW MISTRESS FITZOOTH ARGUING FOR AND AGAINST THE SQUIRE'S PROJECT IN A BREATH", "subset": "test_clean", "task_type": "understanding", "prediction": "there befell an anxious interview mistress fitzooth arguing for and against the squire s project in a breath", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0009.flac", "answer": "TIS LATE AND I GO MYSELF WITHIN A SHORT SPACE", "subset": "test_clean", "task_type": "understanding", "prediction": "tis late and i go myself within a short space", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0021.flac", "answer": "THEY THEN RENEWED THEIR JOURNEY AND UNDER THE BETTER LIGHT MADE A SAFE CROSSING OF THE STABLE ROOFS", "subset": "test_clean", "task_type": "understanding", "prediction": "they then renewed their journey and under the better light made a safe crossing of the stable roofs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0015.flac", "answer": "WILL CRIED HE SOFTLY AND STUTELEY WHO HAD CHOSEN HIS COUCH ACROSS THE DOOR OF HIS YOUNG MASTER'S CHAMBER SPRANG UP AT ONCE IN ANSWER", "subset": "test_clean", "task_type": "understanding", "prediction": "will cried he softly and studleigh who had chosen his couch across the door of his young master s chamber sprang up at once in answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0026.flac", "answer": "FITZOOTH'S HAND RESTED AT LAST UPON THE TOP RUNG OF A LADDER AND SLOWLY THE TRUTH CAME TO HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "fitzooths hand rested at last upon the top rung of a ladder and slowly the truth came to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0006.flac", "answer": "NEVER THAT SIR HE HAD SAID", "subset": "test_clean", "task_type": "understanding", "prediction": "never that sir he had said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0005.flac", "answer": "THE LAD HAD CHECKED HIM THEN", "subset": "test_clean", "task_type": "understanding", "prediction": "the lad had checked him then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0002.flac", "answer": "MOST OF ALL ROBIN THOUGHT OF HIS FATHER WHAT WOULD HE COUNSEL", "subset": "test_clean", "task_type": "understanding", "prediction": "most of all robin thought of his father what would he counsel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0040.flac", "answer": "THEY REGAINED THEIR APARTMENT APPARENTLY WITHOUT DISTURBING THE HOUSEHOLD OF GAMEWELL", "subset": "test_clean", "task_type": "understanding", "prediction": "they regained their apartment apparently without disturbing the household of gainewell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0022.flac", "answer": "ROBIN ENTERED THE HUT DRAGGING THE UNWILLING ESQUIRE AFTER HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "robin entered the hut dragging the unwilling esquire after him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0003.flac", "answer": "IF FOR A WHIM YOU BEGGAR YOURSELF I CANNOT STAY YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "if for a whim you beggar yourself i cannot stay you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0000.flac", "answer": "YOUNG FITZOOTH HAD BEEN COMMANDED TO HIS MOTHER'S CHAMBER SO SOON AS HE HAD COME OUT FROM HIS CONVERSE WITH THE SQUIRE", "subset": "test_clean", "task_type": "understanding", "prediction": "young fitzooth had been commanded to his mother s chamber so soon as he had come out from his converse with the squire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0034.flac", "answer": "NAY NAY LORDING ANSWERED WARRENTON WITH A HALF LAUGH", "subset": "test_clean", "task_type": "understanding", "prediction": "nay nay lording answered warrenton with a half laugh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0017.flac", "answer": "REST AND BE STILL UNTIL I WARN YOU", "subset": "test_clean", "task_type": "understanding", "prediction": "rest and be still until i warn you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0011.flac", "answer": "AS ANY IN ENGLAND I WOULD SAY SAID GAMEWELL PROUDLY THAT IS IN HIS DAY", "subset": "test_clean", "task_type": "understanding", "prediction": "as any in england i would say said gamewell proudly that is in his day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0031.flac", "answer": "CRIED HE WAVING THE LANTHORN BEFORE HIM TO MAKE SURE THAT THESE WERE NO GHOSTS IN FRONT OF HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "cried he waving the lanthorn before him to make sure that these were no ghosts in front of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0028.flac", "answer": "STUTELEY WAS BY HIS SIDE IN A FLASH AND THEN THEY BOTH BEGAN FEELING ABOUT THEM TO ASCERTAIN THE SHAPE AND CHARACTER OF THIS VAULT", "subset": "test_clean", "task_type": "understanding", "prediction": "stuteley was by his side in a flash and then they both began feeling about them to ascertain the shape and character of this vault", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0012.flac", "answer": "YET HE WILL TEACH YOU A FEW TRICKS WHEN MORNING IS COME", "subset": "test_clean", "task_type": "understanding", "prediction": "yet he will teach you a few tricks when morning is come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0036.flac", "answer": "ROBIN FITZOOTH SAW THAT HIS DOUBTS OF WARRENTON HAD BEEN UNFAIR AND HE BECAME ASHAMED OF HIMSELF FOR HARBORING THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "robin fitzooth saw that his doubts of warrenton had been unfair and he became ashamed of himself for harboring them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0037.flac", "answer": "HIS TONES RANG PLEASANTLY ON WARRENTON'S EARS AND FORTHWITH A GOOD FELLOWSHIP WAS HERALDED BETWEEN THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "his tones rang pleasantly on warringtons ears and forthwith a good fellowship was heralded between them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0029.flac", "answer": "FROM THE BLACKNESS BEHIND THE LIGHT THEY HEARD A VOICE WARRENTON'S", "subset": "test_clean", "task_type": "understanding", "prediction": "from the blackness behind the light they heard a voice warrenton s", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0032.flac", "answer": "ENQUIRED ROBIN WITH HIS SUSPICIONS STILL UPON HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "inquired robin with his suspicion still upon him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0014.flac", "answer": "PRESENTLY HE CROSSED THE FLOOR OF HIS ROOM WITH DECIDED STEP", "subset": "test_clean", "task_type": "understanding", "prediction": "presently he crossed the floor of his room with decided step", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0019.flac", "answer": "AT LAST ALL WAS QUIET AND BLACK IN THE COURTYARD OF GAMEWELL", "subset": "test_clean", "task_type": "understanding", "prediction": "at last all was quiet and black in the courtyard of gamewell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0035.flac", "answer": "WARRENTON SPOKE THUS WITH SIGNIFICANCE TO SHOW ROBIN THAT HE WAS NOT TO THINK GEOFFREY'S CLAIMS TO THE ESTATE WOULD BE PASSED BY", "subset": "test_clean", "task_type": "understanding", "prediction": "warrington spoke thus with significance to show robin that he was not to think geoffrey s claims to the estate would be passed by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0033.flac", "answer": "TRULY SUCH A HORSE SHOULD BE WORTH MUCH IN NOTTINGHAM FAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "truly such a horse would be worth much in nodding him fair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0024.flac", "answer": "THEY MOVED THEREAFTER CAUTIOUSLY ABOUT THE HUT GROPING BEFORE AND ABOUT THEM TO FIND SOMETHING TO SHOW THAT WARRENTON HAD FULFILLED HIS MISSION", "subset": "test_clean", "task_type": "understanding", "prediction": "they moved thereafter cautiously about the hut groping before and about them to find something to show that the warrant in had fulfilled his mission", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0023.flac", "answer": "BE NOT SO FOOLISH FRIEND SAID FITZOOTH CROSSLY", "subset": "test_clean", "task_type": "understanding", "prediction": "be not so foolish friend said fitzooth crossly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0007.flac", "answer": "HE WAS IN DEEP CONVERSE WITH THE CLERK AND ENTERED THE HALL HOLDING HIM BY THE ARM", "subset": "test_clean", "task_type": "understanding", "prediction": "he was in deep converse with the clerk and entered the hall holding him by the arm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0018.flac", "answer": "THE HOURS PASSED WEARILY BY AND MOVEMENT COULD YET BE HEARD ABOUT THE HALL", "subset": "test_clean", "task_type": "understanding", "prediction": "the hours passed wearily by and movement could yet be heard about the hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0010.flac", "answer": "DISMISS YOUR SQUIRE ROBIN AND BID ME GOOD E E N", "subset": "test_clean", "task_type": "understanding", "prediction": "dismiss your squire robin and bid me good e'en", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0030.flac", "answer": "SAVE ME MASTERS BUT YOU STARTLED ME RARELY", "subset": "test_clean", "task_type": "understanding", "prediction": "save me masters but you startled me rarely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0008.flac", "answer": "NOW TO BED BOY", "subset": "test_clean", "task_type": "understanding", "prediction": "now to bed boy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0038.flac", "answer": "THE OLD SERVANT TOLD HIM QUIETLY AS THEY CREPT BACK TO GAMEWELL THAT THIS PASSAGE WAY LED FROM THE HUT IN THE PLEASANCE TO SHERWOOD AND THAT GEOFFREY FOR THE TIME WAS HIDING WITH THE OUTLAWS IN THE FOREST", "subset": "test_clean", "task_type": "understanding", "prediction": "the old servant told him quietly as they crept back to gamewell that this passageway led from the hut in the pleasance to sherwood and that geoffrey for the time was hiding with the outlaws in the forest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0020.flac", "answer": "WILL WHISPERED ROBIN OPENING HIS DOOR AS HE SPOKE ARE YOU READY", "subset": "test_clean", "task_type": "understanding", "prediction": "will whispered robin opening his door as he spoke are you ready", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0004.flac", "answer": "BUT TAKE IT WHILST I LIVE AND WEAR MONTFICHET'S SHIELD IN THE DAYS WHEN MY EYES CAN BE REJOICED BY SO BRAVE A SIGHT FOR YOU WILL NE'ER DISGRACE OUR SCUTCHEON I WARRANT ME", "subset": "test_clean", "task_type": "understanding", "prediction": "but take it whilst i live and wear montfichet s shield in the days when my eyes can be rejoiced by so brave a sight for you will ne'er disgrace our stuchan i warrant me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0039.flac", "answer": "HE IMPLORES US TO BE DISCREET AS THE GRAVE IN THIS MATTER FOR IN SOOTH HIS LIFE IS IN THE HOLLOW OF OUR HANDS", "subset": "test_clean", "task_type": "understanding", "prediction": "he implores us to be discreet as the grave in this matter for in sooth his life is in the hollow of our hands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0027.flac", "answer": "ROBIN CAREFULLY DESCENDED THE LADDER AND FOUND HIMSELF SOON UPON FIRM ROCKY GROUND", "subset": "test_clean", "task_type": "understanding", "prediction": "robin carefully descended the ladder and found himself soon upon firm rocky ground", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/61/70970/61-70970-0016.flac", "answer": "WE WILL GO OUT TOGETHER TO THE BOWER THERE IS A WAY DOWN TO THE COURT FROM MY WINDOW", "subset": "test_clean", "task_type": "understanding", "prediction": "we will go out together to the bower there is a way down to the court from my window", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0006.flac", "answer": "THE PLEASANT GRAVEYARD OF MY SOUL WITH SENTIMENTAL CYPRESS TREES AND FLOWERS IS FILLED THAT I MAY STROLL IN MEDITATION AT MY EASE", "subset": "test_clean", "task_type": "understanding", "prediction": "the pleasant graveyard of my soul with sentimental cypress trees and flowers is filled that i may stroll in meditation at my ease", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0002.flac", "answer": "VENICE", "subset": "test_clean", "task_type": "understanding", "prediction": "venice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0012.flac", "answer": "THROUGH THE BLACK NIGHT RAIN HE SANG TO HER WINDOW BARS", "subset": "test_clean", "task_type": "understanding", "prediction": "through the black night rain he sang to her window bars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0010.flac", "answer": "OLD DANCES ARE SIMPLIFIED OF THEIR YEARNING BLEACHED BY TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "old dances are simplified of their yearning bleached by time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0000.flac", "answer": "BRIGHTER THAN EARLY DAWN'S MOST BRILLIANT DYE ARE BLOWN CLEAR BANDS OF COLOR THROUGH THE SKY THAT SWIRL AND SWEEP AND MEET TO BREAK AND FOAM LIKE RAINBOW VEILS UPON A BUBBLE'S DOME", "subset": "test_clean", "task_type": "understanding", "prediction": "brighter than early dawn s most brilliant dye are blown clear bands of color through the sky that swirl and sweep and meet to break and foam like rainbow veils upon a bubble s dome", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0015.flac", "answer": "HE HAD BROKEN INTO HER COURTYARD", "subset": "test_clean", "task_type": "understanding", "prediction": "he had broken into her courtyard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0013.flac", "answer": "THAT WAS BUT RUSTLING OF DRIPPING PLANTS IN THE DARK", "subset": "test_clean", "task_type": "understanding", "prediction": "that was but rustling of dripping plants in the dark", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0011.flac", "answer": "HE HAD GOT INTO HER COURTYARD", "subset": "test_clean", "task_type": "understanding", "prediction": "he had got into her courtyard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0007.flac", "answer": "IT IS MY HEART HUNG IN THE SKY AND NO CLOUDS EVER FLOAT BETWEEN THE GRAVE FLOWERS AND MY HEART ON HIGH", "subset": "test_clean", "task_type": "understanding", "prediction": "it is my heart hung in the sky and no clouds ever float between the grave flowers and my heart on high", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0004.flac", "answer": "THE PITY THAT WE MUST COME AND GO", "subset": "test_clean", "task_type": "understanding", "prediction": "the pity that we must come and go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0014.flac", "answer": "SHE WAS ALONE THAT NIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "she was alone that night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0008.flac", "answer": "OVER THE TRACK LINED CITY STREET THE YOUNG MEN THE GRINNING MEN PASS", "subset": "test_clean", "task_type": "understanding", "prediction": "over the track lined city street the young man the grinning man pass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0009.flac", "answer": "HO YE SAILS THAT SEEM TO WANDER IN DREAM FILLED MEADOWS SAY IS THE SHORE WHERE I STAND THE ONLY FIELD OF STRUGGLE OR ARE YE HIT AND BATTERED OUT THERE BY WAVES AND WIND GUSTS AS YE TACK OVER A CLASHING SEA OF WATERY ECHOES", "subset": "test_clean", "task_type": "understanding", "prediction": "ho ye sails that seem to wander in dream filled meadows say is the shore where i stand the only field of struggle or are ye hit and battered out there by waves and wind gusts as ye tack over a clashing sea of watery echoes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0005.flac", "answer": "WHILE THE OLD GOLD AND THE MARBLE STAYS FOREVER GLEAMING ITS SOFT STRONG BLAZE CALM IN THE EARLY EVENING GLOW", "subset": "test_clean", "task_type": "understanding", "prediction": "while the old gold and the marble stays forever gleaming its soft strong blaze calm in the early evening glow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0003.flac", "answer": "IN A SUNSET GLOWING OF CRIMSON AND GOLD SHE LIES THE GLORY OF THE WORLD A BEACHED KING'S GALLEY WHOSE SAILS ARE FURLED WHO IS HUNG WITH TAPESTRIES RICH AND OLD", "subset": "test_clean", "task_type": "understanding", "prediction": "in a sunset glowing of crimson and gold she lies the glory of the world a beached kings galley whose sails are furled who is hung with tapestries rich and old", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/292519/8555-292519-0001.flac", "answer": "GUIDED BY YOU HOW WE MIGHT STROLL TOWARDS DEATH OUR ONLY MUSIC ONE ANOTHER'S BREATH THROUGH GARDENS INTIMATE WITH HOLLYHOCKS WHERE SILENT POPPIES BURN BETWEEN THE ROCKS BY POOLS WHERE BIRCHES BEND TO CONFIDANTS ABOVE GREEN WATERS SCUMMED WITH LILY PLANTS", "subset": "test_clean", "task_type": "understanding", "prediction": "guided by you how we might stroll towards death our only music one anothers breath through gardens intimate with hollyhocks where silent poppies burn between the rocks by pools where birches bend to confidants above green waters scummed with lily plants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0019.flac", "answer": "BEFORE ANY COULD STOP HIM HE BUTTED HIS MAJESTY SO FURIOUSLY THAT THE KING SOARED FAR INTO THE AIR AND TUMBLED IN A HEAP AMONG THE BENCHES WHERE HE LAY MOANING AND GROANING", "subset": "test_clean", "task_type": "understanding", "prediction": "before any could stop him he butted his majesty so furiously that the king soared far into the air and tumbled in a heap among the benches where he lay moaning and groaning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0016.flac", "answer": "FINE GLORIOUS", "subset": "test_clean", "task_type": "understanding", "prediction": "fine glorious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0008.flac", "answer": "RICH JEWELS OF BLUE STONES GLITTERED UPON THEIR PERSONS AND THE ROYAL LADIES WERE FULLY AS GORGEOUS AS THEY WERE HAUGHTY AND OVERBEARING", "subset": "test_clean", "task_type": "understanding", "prediction": "rich jewels of blue stones glittered upon their persons and the royal ladies were fully as gorgeous as they were haughty and overbearing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0005.flac", "answer": "THE ROOM OF THE GREAT KNIFE WAS HIGH AND BIG AND AROUND IT RAN ROWS OF BENCHES FOR THE SPECTATORS TO SIT UPON", "subset": "test_clean", "task_type": "understanding", "prediction": "the room of the great knife was high and big and around it ran rows of benches for the spectators to sit upon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0003.flac", "answer": "BUT CAP'N BILL MADE NO SUCH ATTEMPT KNOWING IT WOULD BE USELESS", "subset": "test_clean", "task_type": "understanding", "prediction": "but capn bill made no such attempt knowing it would be useless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0006.flac", "answer": "IN ONE PLACE AT THE HEAD OF THE ROOM WAS A RAISED PLATFORM FOR THE ROYAL FAMILY WITH ELEGANT THRONE CHAIRS FOR THE KING AND QUEEN AND SIX SMALLER BUT RICHLY UPHOLSTERED CHAIRS FOR THE SNUBNOSED PRINCESSES", "subset": "test_clean", "task_type": "understanding", "prediction": "in one place at the head of the room was a raised platform for the royal family with elegant throne chairs for the king and queen and six smaller but richly upholstered chairs for the snubnosed princesses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0018.flac", "answer": "AT ONCE THE GOAT GAVE A LEAP ESCAPED FROM THE SOLDIERS AND WITH BOWED HEAD RUSHED UPON THE BOOLOOROO", "subset": "test_clean", "task_type": "understanding", "prediction": "at once the goat gave a leap escaped from the soldiers and with bowed head rushed upon the boolooroo", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0014.flac", "answer": "THE IDEA OF PATCHING CAP'N BILL TO A GOAT WAS VASTLY AMUSING TO HIM AND THE MORE HE THOUGHT OF IT THE MORE HE ROARED WITH LAUGHTER", "subset": "test_clean", "task_type": "understanding", "prediction": "the idea of patching capn bill to a goat was vastly amusing to him and the more he thought of it the more he roared with laughter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0020.flac", "answer": "THE GOAT'S WARLIKE SPIRIT WAS ROUSED BY THIS SUCCESSFUL ATTACK", "subset": "test_clean", "task_type": "understanding", "prediction": "the goat s warlike spirit was aroused by this successful attack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0021.flac", "answer": "THEN THEY SPED IN GREAT HASTE FOR THE DOOR AND THE GOAT GAVE A FINAL BUTT THAT SENT THE ROW OF ROYAL LADIES ALL DIVING INTO THE CORRIDOR IN ANOTHER TANGLE WHEREUPON THEY SHRIEKED IN A MANNER THAT TERRIFIED EVERYONE WITHIN SOUND OF THEIR VOICES", "subset": "test_clean", "task_type": "understanding", "prediction": "then they sped in great haste for the door and the goat gave a final butt that sent the row of royal ladies all diving into the corridor in another tangle whereupon they shrieked in a manner that terrified every one within sound of their voices", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0009.flac", "answer": "MORNIN GIRLS HOPE YE FEEL AS WELL AS YE LOOK", "subset": "test_clean", "task_type": "understanding", "prediction": "morning girls hope ye feel as well as ye look", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0004.flac", "answer": "AS SOON AS THEY ENTERED THE ROOM OF THE GREAT KNIFE THE BOOLOOROO GAVE A YELL OF DISAPPOINTMENT", "subset": "test_clean", "task_type": "understanding", "prediction": "as soon as they entered the room of the great knife the boolooroo gave a yell of disappointment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0000.flac", "answer": "THEN HE RUSHED DOWN STAIRS INTO THE COURTYARD SHOUTING LOUDLY FOR HIS SOLDIERS AND THREATENING TO PATCH EVERYBODY IN HIS DOMINIONS IF THE SAILORMAN WAS NOT RECAPTURED", "subset": "test_clean", "task_type": "understanding", "prediction": "then he rushed downstairs into the courtyard shouting loudly for his soldiers and threatening to patch everybody in his dominions if the sailorman was not recaptured", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0007.flac", "answer": "THEREFORE HER MAJESTY PAID NO ATTENTION TO ANYONE AND NO ONE PAID ANY ATTENTION TO HER", "subset": "test_clean", "task_type": "understanding", "prediction": "therefore her majesty paid no attention to any one and no one paid any attention to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0011.flac", "answer": "SUPPOSE IT'S A FRIEND", "subset": "test_clean", "task_type": "understanding", "prediction": "suppose it is a friend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0010.flac", "answer": "CONTROL YOURSELVES MY DEARS REPLIED THE BOOLOOROO THE WORST PUNISHMENT I KNOW HOW TO INFLICT ON ANYONE THIS PRISONER IS ABOUT TO SUFFER YOU'LL SEE A VERY PRETTY PATCHING MY ROYAL DAUGHTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "control yourselves my dears replied the boolooroo the worst punishment i know how to inflict on anyone this prisoner is about to suffer you will see a very pretty patching my royal daughters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0023.flac", "answer": "I COULDN'T SHIVER MUCH BEIN BOUND SO TIGHT BUT WHEN I'M LOOSE I MEAN TO HAVE JUS ONE GOOD SHIVER TO RELIEVE MY FEELIN'S", "subset": "test_clean", "task_type": "understanding", "prediction": "i couldnt shiver much being bound so tight but when i am loose i mean to have just one good shiver to relieve my feelings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0012.flac", "answer": "THE CAPTAIN SHOOK HIS HEAD", "subset": "test_clean", "task_type": "understanding", "prediction": "the captain shook his head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0017.flac", "answer": "WHEN THIS HAD BEEN ACCOMPLISHED THE BOOLOOROO LEANED OVER TO TRY TO DISCOVER WHY THE FRAME ROLLED AWAY SEEMINGLY OF ITS OWN ACCORD AND HE WAS THE MORE PUZZLED BECAUSE IT HAD NEVER DONE SUCH A THING BEFORE", "subset": "test_clean", "task_type": "understanding", "prediction": "when this had been accomplished the boolooroo leaned over to try to discover why the frame rolled away seemingly of its own accord and he was the more puzzled because it had never done such a thing before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0013.flac", "answer": "WHY YOU SAID TO FETCH THE FIRST LIVING CREATURE WE MET AND THAT WAS THIS BILLYGOAT REPLIED THE CAPTAIN PANTING HARD AS HE HELD FAST TO ONE OF THE GOAT'S HORNS", "subset": "test_clean", "task_type": "understanding", "prediction": "why you said to fetch the first living critter we met and that was the spilligot replied the captain panting hard as he held fast to one of the goat s horns", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0015.flac", "answer": "THEY LOOK SOMETHING ALIKE YOU KNOW SUGGESTED THE CAPTAIN OF THE GUARDS LOOKING FROM ONE TO THE OTHER DOUBTFULLY AND THEY'RE NEARLY THE SAME SIZE IF YOU STAND THE GOAT ON HIS HIND LEGS THEY'VE BOTH GOT THE SAME STYLE OF WHISKERS AND THEY'RE BOTH OF EM OBSTINATE AND DANGEROUS SO THEY OUGHT TO MAKE A GOOD PATCH SPLENDID", "subset": "test_clean", "task_type": "understanding", "prediction": "they look something alike you know suggested the captain of the guards looking from one to the other doubtfully and they are nearly the same size if you stand the goat on his hind legs they have both got the same style of whiskers and they are both of them obstinate and dangerous so they ought to make a good match splendid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0024.flac", "answer": "COME AND GET THE BOOLOOROO SHE SAID GOING TOWARD THE BENCHES", "subset": "test_clean", "task_type": "understanding", "prediction": "come and get the boolooroo she said going toward the benches", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0002.flac", "answer": "I WOULDN'T MIND A CUP O COFFEE MYSELF SAID CAP'N BILL I'VE HAD CONSID'BLE EXERCISE THIS MORNIN AND I'M ALL READY FOR BREAKFAS", "subset": "test_clean", "task_type": "understanding", "prediction": "i wouldn mind a cup o coffee myself said capn bill i ve had considerable exercise this mornin an im all ready for breakfast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0001.flac", "answer": "HOLD HIM FAST MY MEN AND AS SOON AS I'VE HAD MY COFFEE AND OATMEAL I'LL TAKE HIM TO THE ROOM OF THE GREAT KNIFE AND PATCH HIM", "subset": "test_clean", "task_type": "understanding", "prediction": "hold him fast my men and as soon as i ve had my coffee and oatmeal i ll take him to the room of the great knife and patch him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284447/8555-284447-0022.flac", "answer": "I HAD A NOTION IT WAS YOU MATE AS SAVED ME FROM THE KNIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "i had a notion it was you mate as saved me from the knife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0004.flac", "answer": "SINCE LAST THURSDAY I GHIP GHISIZZLE HAVE BEEN THE LAWFUL BOOLOOROO OF THE BLUE COUNTRY BUT NOW THAT YOU ARE CONQUERED BY QUEEN TROT I SUPPOSE I AM CONQUERED TOO AND YOU HAVE NO BOOLOOROO AT ALL", "subset": "test_clean", "task_type": "understanding", "prediction": "since last thursday i ghip ghisizzle have been the lawful boolooroo of the blue country but now that you are conquered by queen trot i suppose i am conquered too and you have no boolooroo at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0012.flac", "answer": "I'LL GLADLY DO THAT PROMISED THE NEW BOOLOOROO AND I'LL FEED THE HONORABLE GOAT ALL THE SHAVINGS AND LEATHER AND TIN CANS HE CAN EAT BESIDES THE GRASS", "subset": "test_clean", "task_type": "understanding", "prediction": "i will gladly do that promised the new boolooroo and i will feed the honorable goat all the shavings and leather and tin cans he can eat besides the grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0003.flac", "answer": "WHEN THE BLUESKINS SAW GHIP GHISIZZLE THEY RAISED ANOTHER GREAT SHOUT FOR HE WAS THE FAVORITE OF THE SOLDIERS AND VERY POPULAR WITH ALL THE PEOPLE", "subset": "test_clean", "task_type": "understanding", "prediction": "when the blueskins saw gitka sizzle they raised another great shout for he was the favorite of the soldiers and very popular with all the people", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0000.flac", "answer": "SO THEY WERE QUITE WILLING TO OBEY THE ORDERS OF THEIR GIRL QUEEN AND IN A SHORT TIME THE BLASTS OF TRUMPETS AND ROLL OF DRUMS AND CLASHING OF CYMBALS TOLD TROT AND CAP'N BILL THAT THE BLUE BANDS HAD ASSEMBLED BEFORE THE PALACE", "subset": "test_clean", "task_type": "understanding", "prediction": "so they were quite willing to obey the orders of their girl queen and in a short time the blast of trumpets and roll of drums and clashing of cymbals told trot and capn bill that the blue bands had assembled before the palace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0014.flac", "answer": "THE FORMER BOOLOOROO GROANED", "subset": "test_clean", "task_type": "understanding", "prediction": "the former boolooroo groaned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0001.flac", "answer": "THEN THEY ALL MARCHED OUT A LITTLE WAY INTO THE FIELDS AND FOUND THAT THE ARMY OF PINKIES HAD ALREADY FORMED AND WAS ADVANCING STEADILY TOWARD THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "then they all marched out a little way into the fields and found that the army of pinkies had already formed and was advancing steadily toward them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0005.flac", "answer": "WHEN HE FINISHED SHE SAID CHEERFULLY", "subset": "test_clean", "task_type": "understanding", "prediction": "when he finished she said cheerfully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0002.flac", "answer": "AT THE HEAD OF THE PINKIES WERE GHIP GHISIZZLE AND BUTTON BRIGHT WHO HAD THE PARROT ON HIS SHOULDER AND THEY WERE SUPPORTED BY CAPTAIN CORALIE AND CAPTAIN TINTINT AND ROSALIE THE WITCH", "subset": "test_clean", "task_type": "understanding", "prediction": "at the head of the pinkies were ghip ghisizzle and button bright who had the parrot on his shoulder and they were supported by captain coralie and captain tintint and rosalie the witch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0013.flac", "answer": "SCUSE ME SAID TROT I NEGLECTED TO TELL YOU THAT YOU'RE NOT THE BOOLOOROO ANY MORE", "subset": "test_clean", "task_type": "understanding", "prediction": "excuse me said trot i neglected to tell you that you are not the boolooroo any more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0008.flac", "answer": "THEN SHE GAVE ROSALIE BACK HER MAGIC RING THANKING THE KIND WITCH FOR ALL SHE HAD DONE FOR THEM", "subset": "test_clean", "task_type": "understanding", "prediction": "then she gave rosalie back her magic ring thanking the kind witch for all she had done for them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0020.flac", "answer": "THE COMBINED BANDS OF BOTH THE COUNTRIES PLAYED THE MUSIC AND A FINE SUPPER WAS SERVED", "subset": "test_clean", "task_type": "understanding", "prediction": "the combined bands of both the countries played the music and a fine supper was served", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0015.flac", "answer": "I'LL NOT BE WICKED ANY MORE SIGHED THE OLD BOOLOOROO I'LL REFORM", "subset": "test_clean", "task_type": "understanding", "prediction": "i will not be wicked any more sighed the old boolooroo i will reform", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0017.flac", "answer": "WHEN FIRST THEY ENTERED THE THRONE ROOM THEY TRIED TO BE AS HAUGHTY AND SCORNFUL AS EVER BUT THE BLUES WHO WERE ASSEMBLED THERE ALL LAUGHED AT THEM AND JEERED THEM FOR THERE WAS NOT A SINGLE PERSON IN ALL THE BLUE COUNTRY WHO LOVED THE PRINCESSES THE LEAST LITTLE BIT", "subset": "test_clean", "task_type": "understanding", "prediction": "when first they entered the throne room they tried to be as haughty and scornful as ever but the blues who were assembled there all laughed at them and jeered them for there was not a single person in all the blue country who loved the princess the least little bit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0016.flac", "answer": "AS A PRIVATE CITIZEN I SHALL BE A MODEL OF DEPORTMENT BECAUSE IT WOULD BE DANGEROUS TO BE OTHERWISE", "subset": "test_clean", "task_type": "understanding", "prediction": "as a private citizen i shall be a model of deportment because it would be dangerous to be otherwise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0009.flac", "answer": "YOU ARE MATE REPLIED THE SAILOR", "subset": "test_clean", "task_type": "understanding", "prediction": "you are mate replied the sailor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0010.flac", "answer": "IT WILL BE SUCH A SATISFACTION", "subset": "test_clean", "task_type": "understanding", "prediction": "it will be such a satisfaction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0019.flac", "answer": "THAT EVENING TROT GAVE A GRAND BALL IN THE PALACE TO WHICH THE MOST IMPORTANT OF THE PINKIES AND THE BLUESKINS WERE INVITED", "subset": "test_clean", "task_type": "understanding", "prediction": "that evening trot gave a grand ball in the palace to which the most important of the pinkies and the blueskins were invited", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0006.flac", "answer": "DON'T WORRY SIZZLE DEAR IT'LL ALL COME RIGHT PRETTY SOON", "subset": "test_clean", "task_type": "understanding", "prediction": "dont worry sizzle dear it will all come right pretty soon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0007.flac", "answer": "NOW THEN LET'S ENTER THE CITY AN ENJOY THE GRAND FEAST THAT'S BEING COOKED I'M NEARLY STARVED MYSELF FOR THIS CONQUERIN KINGDOMS IS HARD WORK", "subset": "test_clean", "task_type": "understanding", "prediction": "now then let us enter the city and enjoy the great feast that is being cooked i am nearly starving myself for this conquering kingdoms is hard work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0018.flac", "answer": "SO GHIP GHISIZZLE ORDERED THE CAPTAIN TO TAKE A FILE OF SOLDIERS AND ESCORT THE RAVING BEAUTIES TO THEIR NEW HOME", "subset": "test_clean", "task_type": "understanding", "prediction": "so ghip ghisizzle ordered the captain to take a file of soldiers and escort the raving beauties to their new home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/8555/284449/8555-284449-0011.flac", "answer": "THE GUARDS HAD A TERRIBLE STRUGGLE WITH THE GOAT WHICH WAS LOOSE IN THE ROOM AND STILL WANTED TO FIGHT BUT FINALLY THEY SUBDUED THE ANIMAL AND THEN THEY TOOK THE BOOLOOROO OUT OF THE FRAME HE WAS TIED IN AND BROUGHT BOTH HIM AND THE GOAT BEFORE QUEEN TROT WHO AWAITED THEM IN THE THRONE ROOM OF THE PALACE", "subset": "test_clean", "task_type": "understanding", "prediction": "the guards had a terrible struggle with the goat which was loose in the room and still wanted to fight but finally they subdued the animal and then they took the boolooroo out of the frame he was tied in and brought both him and the goat before queen trot who awaited them in the throne room of the palace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0021.flac", "answer": "WHENEVER AS IN THESE CASES THE MENIAL SERVICE IN QUESTION HAS TO DO DIRECTLY WITH THE PRIMARY LEISURE EMPLOYMENTS OF FIGHTING AND HUNTING IT EASILY ACQUIRES A REFLECTED HONORIFIC CHARACTER", "subset": "test_clean", "task_type": "understanding", "prediction": "whenever as in these cases the menial service in question has to do directly with the primary leisure employments of fighting and hunting it easily acquires a reflected honorific character", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0010.flac", "answer": "THE OBJECTION OF COURSE PRESENTS ITSELF THAT EXPENDITURE ON WOMEN'S DRESS AND HOUSEHOLD PARAPHERNALIA IS AN OBVIOUS EXCEPTION TO THIS RULE BUT IT WILL APPEAR IN THE SEQUEL THAT THIS EXCEPTION IS MUCH MORE OBVIOUS THAN SUBSTANTIAL", "subset": "test_clean", "task_type": "understanding", "prediction": "the objection of course presents itself that expenditure on women s dress and household paraphernalia is an obvious exception to this rule but it will appear in the sequel that this exception is much more obvious than substantial", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0002.flac", "answer": "SUCH CONSUMPTION AS FALLS TO THE WOMEN IS MERELY INCIDENTAL TO THEIR WORK IT IS A MEANS TO THEIR CONTINUED LABOUR AND NOT A CONSUMPTION DIRECTED TO THEIR OWN COMFORT AND FULNESS OF LIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "such consumption as falls to the women is merely incidental to their work it is a means to their continued labor and not a consumption directed to their own comfort and fullness of life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0007.flac", "answer": "IT HAS EVEN HAPPENED THAT THE NAME FOR CERTAIN DISEASED CONDITIONS OF THE BODY ARISING FROM SUCH AN ORIGIN HAS PASSED INTO EVERYDAY SPEECH AS A SYNONYM FOR NOBLE OR GENTLE", "subset": "test_clean", "task_type": "understanding", "prediction": "it has even happened that the name for certain diseased conditions of the body arising from such an origin has passed into everyday speech as a synonym for noble or gentle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0003.flac", "answer": "WITH A FURTHER ADVANCE IN CULTURE THIS TABU MAY CHANGE INTO SIMPLE CUSTOM OF A MORE OR LESS RIGOROUS CHARACTER BUT WHATEVER BE THE THEORETICAL BASIS OF THE DISTINCTION WHICH IS MAINTAINED WHETHER IT BE A TABU OR A LARGER CONVENTIONALITY THE FEATURES OF THE CONVENTIONAL SCHEME OF CONSUMPTION DO NOT CHANGE EASILY", "subset": "test_clean", "task_type": "understanding", "prediction": "with a further advance in culture this taboo may change into simple custom of a more or less rigorous character but whatever be the theoretical basis of the distinction which is maintained whether it be a taboo or a larger conventionality the features of the conventional scheme of consumption do not change easily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0004.flac", "answer": "IN THE NATURE OF THINGS LUXURIES AND THE COMFORTS OF LIFE BELONG TO THE LEISURE CLASS", "subset": "test_clean", "task_type": "understanding", "prediction": "in the nature of things luxuries and the comforts of life belong to the leisure class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0009.flac", "answer": "WITH MANY QUALIFICATIONS WITH MORE QUALIFICATIONS AS THE PATRIARCHAL TRADITION HAS GRADUALLY WEAKENED THE GENERAL RULE IS FELT TO BE RIGHT AND BINDING THAT WOMEN SHOULD CONSUME ONLY FOR THE BENEFIT OF THEIR MASTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "with many qualifications with more qualifications as the patriarchal tradition has gradually weakened the general rule is felt to be right and binding that women should consume only for the benefit of their masters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0014.flac", "answer": "MANY OF THESE AFFILIATED GENTLEMEN OF LEISURE ARE AT THE SAME TIME LESSER MEN OF SUBSTANCE IN THEIR OWN RIGHT SO THAT SOME OF THEM ARE SCARCELY AT ALL OTHERS ONLY PARTIALLY TO BE RATED AS VICARIOUS CONSUMERS", "subset": "test_clean", "task_type": "understanding", "prediction": "many of these affiliated gentlemen of leisure are at the same time lesser men of substance in their own right so that some of them are scarcely at all others only partially to be rated as vicarious consumers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0011.flac", "answer": "THE CUSTOM OF FESTIVE GATHERINGS PROBABLY ORIGINATED IN MOTIVES OF CONVIVIALITY AND RELIGION THESE MOTIVES ARE ALSO PRESENT IN THE LATER DEVELOPMENT BUT THEY DO NOT CONTINUE TO BE THE SOLE MOTIVES", "subset": "test_clean", "task_type": "understanding", "prediction": "the custom of festive gatherings probably originated in motives of conviviality and religion these motives are also present in the later development but they do not continue to be the sole motives", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0015.flac", "answer": "SO MANY OF THEM HOWEVER AS MAKE UP THE RETAINER AND HANGERS ON OF THE PATRON MAY BE CLASSED AS VICARIOUS CONSUMER WITHOUT QUALIFICATION", "subset": "test_clean", "task_type": "understanding", "prediction": "so many of them however as make up the retainer and hangers on of the patron may be classed as vicarious consumer without qualification", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0022.flac", "answer": "THE LIVERY BECOMES OBNOXIOUS TO NEARLY ALL WHO ARE REQUIRED TO WEAR IT", "subset": "test_clean", "task_type": "understanding", "prediction": "the livery becomes obnoxious to nearly all who are required to wear it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0006.flac", "answer": "DRUNKENNESS AND THE OTHER PATHOLOGICAL CONSEQUENCES OF THE FREE USE OF STIMULANTS THEREFORE TEND IN THEIR TURN TO BECOME HONORIFIC AS BEING A MARK AT THE SECOND REMOVE OF THE SUPERIOR STATUS OF THOSE WHO ARE ABLE TO AFFORD THE INDULGENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "drunkenness and the other pathological consequences of the free use of stimulants therefore tend in their turn to become honorific as being a mark at the second remove of the superior status of those who are able to afford the indulgence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0008.flac", "answer": "THE CONSUMPTION OF LUXURIES IN THE TRUE SENSE IS A CONSUMPTION DIRECTED TO THE COMFORT OF THE CONSUMER HIMSELF AND IS THEREFORE A MARK OF THE MASTER", "subset": "test_clean", "task_type": "understanding", "prediction": "the consumption of luxuries in the true sense is a consumption directed to the comfort of the consumer himself and is therefore a mark of the master", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0017.flac", "answer": "THE WEARING OF UNIFORMS OR LIVERIES IMPLIES A CONSIDERABLE DEGREE OF DEPENDENCE AND MAY EVEN BE SAID TO BE A MARK OF SERVITUDE REAL OR OSTENSIBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "the wearing of uniforms or liveries implies a considerable degree of dependence and may even be said to be a mark of servitude real or ostensible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0001.flac", "answer": "THE UTILITY OF CONSUMPTION AS AN EVIDENCE OF WEALTH IS TO BE CLASSED AS A DERIVATIVE GROWTH", "subset": "test_clean", "task_type": "understanding", "prediction": "the utility of consumption as an evidence of wealth is to be classed as a derivative growth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0012.flac", "answer": "THERE IS A MORE OR LESS ELABORATE SYSTEM OF RANK AND GRADES", "subset": "test_clean", "task_type": "understanding", "prediction": "there is a more or less elaborate system of rank and grades", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0005.flac", "answer": "UNDER THE TABU CERTAIN VICTUALS AND MORE PARTICULARLY CERTAIN BEVERAGES ARE STRICTLY RESERVED FOR THE USE OF THE SUPERIOR CLASS", "subset": "test_clean", "task_type": "understanding", "prediction": "under the taboo certain victuals and more particularly certain beverages are strictly reserved for the use of the superior class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0013.flac", "answer": "THIS DIFFERENTIATION IS FURTHERED BY THE INHERITANCE OF WEALTH AND THE CONSEQUENT INHERITANCE OF GENTILITY", "subset": "test_clean", "task_type": "understanding", "prediction": "this differentiation is furthered by the inheritance of wealth and the consequent inheritance of gentility", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0016.flac", "answer": "MANY OF THESE AGAIN AND ALSO MANY OF THE OTHER ARISTOCRACY OF LESS DEGREE HAVE IN TURN ATTACHED TO THEIR PERSONS A MORE OR LESS COMPREHENSIVE GROUP OF VICARIOUS CONSUMER IN THE PERSONS OF THEIR WIVES AND CHILDREN THEIR SERVANTS RETAINERS ET CETERA", "subset": "test_clean", "task_type": "understanding", "prediction": "many of these again and also many of the other aristocracy of lesteegry have in turn attached to their persons a more or less comprehensive group of vicarious consumers in the persons of their wives and children their servants retainers etc", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0018.flac", "answer": "THE WEARERS OF UNIFORMS AND LIVERIES MAY BE ROUGHLY DIVIDED INTO TWO CLASSES THE FREE AND THE SERVILE OR THE NOBLE AND THE IGNOBLE", "subset": "test_clean", "task_type": "understanding", "prediction": "the wearers of uniforms and liveries may be roughly divided into two classes the free and the servile or the noble and the ignoble", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0019.flac", "answer": "BUT THE GENERAL DISTINCTION IS NOT ON THAT ACCOUNT TO BE OVERLOOKED", "subset": "test_clean", "task_type": "understanding", "prediction": "but the general distinction is not on that account to be overlooked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0020.flac", "answer": "SO THOSE OFFICES WHICH ARE BY RIGHT THE PROPER EMPLOYMENT OF THE LEISURE CLASS ARE NOBLE SUCH AS GOVERNMENT FIGHTING HUNTING THE CARE OF ARMS AND ACCOUTREMENTS AND THE LIKE IN SHORT THOSE WHICH MAY BE CLASSED AS OSTENSIBLY PREDATORY EMPLOYMENTS", "subset": "test_clean", "task_type": "understanding", "prediction": "so those offices which are by right the proper employment of the leisure class are noble such as government fighting hunting the care of arms and accoutrements and the like in short those which may be classed as ostensibly predatory employments", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5694/3570-5694-0000.flac", "answer": "BUT ALREADY AT A POINT IN ECONOMIC EVOLUTION FAR ANTEDATING THE EMERGENCE OF THE LADY SPECIALISED CONSUMPTION OF GOODS AS AN EVIDENCE OF PECUNIARY STRENGTH HAD BEGUN TO WORK OUT IN A MORE OR LESS ELABORATE SYSTEM", "subset": "test_clean", "task_type": "understanding", "prediction": "but already at a point in economic evolution far antedating the emergence of the lady specialized consumption of goods as an evidence of pecuniary strength had begun to work out in a more or less elaborate system", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0002.flac", "answer": "BUT AS WE DESCEND THE SOCIAL SCALE THE POINT IS PRESENTLY REACHED WHERE THE DUTIES OF VICARIOUS LEISURE AND CONSUMPTION DEVOLVE UPON THE WIFE ALONE", "subset": "test_clean", "task_type": "understanding", "prediction": "but as we descend the social scale the point is presently reached where the duties of vicarious leisure and consumption devolve upon the wife alone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0010.flac", "answer": "THE MODERN ORGANIZATION OF INDUSTRY WORKS IN THE SAME DIRECTION ALSO BY ANOTHER LINE", "subset": "test_clean", "task_type": "understanding", "prediction": "the modern organization of industry works in the same direction also by another line", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0004.flac", "answer": "IF BEAUTY OR COMFORT IS ACHIEVED AND IT IS A MORE OR LESS FORTUITOUS CIRCUMSTANCE IF THEY ARE THEY MUST BE ACHIEVED BY MEANS AND METHODS THAT COMMEND THEMSELVES TO THE GREAT ECONOMIC LAW OF WASTED EFFORT", "subset": "test_clean", "task_type": "understanding", "prediction": "if beauty or comfort is achieved and it is a more or less fortuitous circumstance if they are they must be achieved by means and methods that commend themselves through the great economic law of wasted effort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0008.flac", "answer": "THE QUESTION IS WHICH OF THE TWO METHODS WILL MOST EFFECTIVELY REACH THE PERSONS WHOSE CONVICTIONS IT IS DESIRED TO AFFECT", "subset": "test_clean", "task_type": "understanding", "prediction": "the question is which of the two methods will most effectively reach the persons whose convictions it is desired to effect", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0003.flac", "answer": "IN THE COMMUNITIES OF THE WESTERN CULTURE THIS POINT IS AT PRESENT FOUND AMONG THE LOWER MIDDLE CLASS", "subset": "test_clean", "task_type": "understanding", "prediction": "in the communities of the western culture this point is at present found among the lower middle class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0007.flac", "answer": "THERE IS NO CLASS AND NO COUNTRY THAT HAS YIELDED SO ABJECTLY BEFORE THE PRESSURE OF PHYSICAL WANT AS TO DENY THEMSELVES ALL GRATIFICATION OF THIS HIGHER OR SPIRITUAL NEED", "subset": "test_clean", "task_type": "understanding", "prediction": "there is no class and no country that has yielded so abjectly before the pressure of physical want as to deny themselves all gratification of this higher or spiritual need", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0015.flac", "answer": "THE RESULT IS A GREAT MOBILITY OF THE LABOR EMPLOYED IN PRINTING PERHAPS GREATER THAN IN ANY OTHER EQUALLY WELL DEFINED AND CONSIDERABLE BODY OF WORKMEN", "subset": "test_clean", "task_type": "understanding", "prediction": "the result is a great mobility of the labour employed in printing perhaps greater than in any other equally well defined and considerable body of workmen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0013.flac", "answer": "CONSUMPTION BECOMES A LARGER ELEMENT IN THE STANDARD OF LIVING IN THE CITY THAN IN THE COUNTRY", "subset": "test_clean", "task_type": "understanding", "prediction": "consumption becomes a larger element in the standard of living in the city than in the country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0009.flac", "answer": "EACH WILL THEREFORE SERVE ABOUT EQUALLY WELL DURING THE EARLIER STAGES OF SOCIAL GROWTH", "subset": "test_clean", "task_type": "understanding", "prediction": "each will therefore serve about equally well during the earlier stages of social growth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0000.flac", "answer": "IN A GENERAL WAY THOUGH NOT WHOLLY NOR CONSISTENTLY THESE TWO GROUPS COINCIDE", "subset": "test_clean", "task_type": "understanding", "prediction": "in a general way though not wholly nor consistently these two groups coincide", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0011.flac", "answer": "IT IS EVIDENT THEREFORE THAT THE PRESENT TREND OF THE DEVELOPMENT IS IN THE DIRECTION OF HEIGHTENING THE UTILITY OF CONSPICUOUS CONSUMPTION AS COMPARED WITH LEISURE", "subset": "test_clean", "task_type": "understanding", "prediction": "it is evident therefore that the present trend of the development is in the direction of heightening the utility of conspicuous consumption as compared with leisure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0001.flac", "answer": "THE DEPENDENT WHO WAS FIRST DELEGATED FOR THESE DUTIES WAS THE WIFE OR THE CHIEF WIFE AND AS WOULD BE EXPECTED IN THE LATER DEVELOPMENT OF THE INSTITUTION WHEN THE NUMBER OF PERSONS BY WHOM THESE DUTIES ARE CUSTOMARILY PERFORMED GRADUALLY NARROWS THE WIFE REMAINS THE LAST", "subset": "test_clean", "task_type": "understanding", "prediction": "the dependent who was first delegated for these duties was the wife or the chief wife and as would be expected in the later development of the institution when the number of persons by whom these duties are customarily performed gradually narrows the wife remains the last", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0014.flac", "answer": "AMONG THE COUNTRY POPULATION ITS PLACE IS TO SOME EXTENT TAKEN BY SAVINGS AND HOME COMFORTS KNOWN THROUGH THE MEDIUM OF NEIGHBORHOOD GOSSIP SUFFICIENTLY TO SERVE THE LIKE GENERAL PURPOSE OF PECUNIARY REPUTE", "subset": "test_clean", "task_type": "understanding", "prediction": "among the country population its place is to some extent taken by savings and home comforts known through the medium of neighbourhood gossip sufficiently to serve the like general purpose of pecuniary repute", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0006.flac", "answer": "VERY MUCH OF SQUALOR AND DISCOMFORT WILL BE ENDURED BEFORE THE LAST TRINKET OR THE LAST PRETENSE OF PECUNIARY DECENCY IS PUT AWAY", "subset": "test_clean", "task_type": "understanding", "prediction": "very much of squalor and discomfort will be endured before the last trinket or the last pretence of pecuniary decency is put away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0012.flac", "answer": "IT IS ALSO NOTICEABLE THAT THE SERVICEABILITY OF CONSUMPTION AS A MEANS OF REPUTE AS WELL AS THE INSISTENCE ON IT AS AN ELEMENT OF DECENCY IS AT ITS BEST IN THOSE PORTIONS OF THE COMMUNITY WHERE THE HUMAN CONTACT OF THE INDIVIDUAL IS WIDEST AND THE MOBILITY OF THE POPULATION IS GREATEST", "subset": "test_clean", "task_type": "understanding", "prediction": "it is also noticeable that the serviceability of consumption as a means of repute as well as the insistence on it as an element of decency is at its best in those portions of the community where the human contact of the individual is widest and the mobility of the population is greatest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5695/3570-5695-0005.flac", "answer": "THE MAN OF THE HOUSEHOLD ALSO CAN DO SOMETHING IN THIS DIRECTION AND INDEED HE COMMONLY DOES BUT WITH A STILL LOWER DESCENT INTO THE LEVELS OF INDIGENCE ALONG THE MARGIN OF THE SLUMS THE MAN AND PRESENTLY ALSO THE CHILDREN VIRTUALLY CEASE TO CONSUME VALUABLE GOODS FOR APPEARANCES AND THE WOMAN REMAINS VIRTUALLY THE SOLE EXPONENT OF THE HOUSEHOLD'S PECUNIARY DECENCY", "subset": "test_clean", "task_type": "understanding", "prediction": "the man of the household also can do something in this direction and indeed he commonly does but with a still lower descent into the levels of indigence along the margin of the slums the man and presently also the children virtually cease to consume valuable goods for appearances and the woman remains virtually the sole exponent of the household s pecuniary decency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0001.flac", "answer": "BUT THE ACTUAL COURSE OF DEVELOPMENT HAS BEEN SOMEWHAT DIFFERENT FROM THIS IDEAL SCHEME LEISURE HELD THE FIRST PLACE AT THE START AND CAME TO HOLD A RANK VERY MUCH ABOVE WASTEFUL CONSUMPTION OF GOODS BOTH AS A DIRECT EXPONENT OF WEALTH AND AS AN ELEMENT IN THE STANDARD OF DECENCY DURING THE QUASI PEACEABLE CULTURE", "subset": "test_clean", "task_type": "understanding", "prediction": "but the actual course of development has been somewhat different from this ideal scheme leisure held the first place at the start and came to hold a rank very much above wasteful consumption of goods both as a direct exponent of wealth and as an element in the standard of decency during the quasi peaceful culture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0010.flac", "answer": "AN ARTICLE MAY BE USEFUL AND WASTEFUL BOTH AND ITS UTILITY TO THE CONSUMER MAY BE MADE UP OF USE AND WASTE IN THE MOST VARYING PROPORTIONS", "subset": "test_clean", "task_type": "understanding", "prediction": "an article may be useful and wasteful both and its utility to the consumer may be made up of use and waste in the most varying proportions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0009.flac", "answer": "IN STRICT ACCURACY NOTHING SHOULD BE INCLUDED UNDER THE HEAD OF CONSPICUOUS WASTE BUT SUCH EXPENDITURE AS IS INCURRED ON THE GROUND OF AN INVIDIOUS PECUNIARY COMPARISON", "subset": "test_clean", "task_type": "understanding", "prediction": "in strict accuracy nothing should be included under the head of conspicuous waste but such expenditure as is incurred on the ground of an invidious pecuniary comparison", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0004.flac", "answer": "THE SALIENT FEATURES OF THIS DEVELOPMENT OF DOMESTIC SERVICE HAVE ALREADY BEEN INDICATED", "subset": "test_clean", "task_type": "understanding", "prediction": "the salient features of this development of domestic service have already been indicated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0007.flac", "answer": "THE USE OF THE WORD WASTE AS A TECHNICAL TERM THEREFORE IMPLIES NO DEPRECATION OF THE MOTIVES OR OF THE ENDS SOUGHT BY THE CONSUMER UNDER THIS CANON OF CONSPICUOUS WASTE", "subset": "test_clean", "task_type": "understanding", "prediction": "the use of the word waste as a technical term therefore implies no deprecation of the motives or of the ends sought by the consumer under this canon of conspicuous waste", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0006.flac", "answer": "AS USED IN THE SPEECH OF EVERYDAY LIFE THE WORD CARRIES AN UNDERTONE OF DEPRECATION", "subset": "test_clean", "task_type": "understanding", "prediction": "as used in the speech of everyday life the word carries an undertone of deprecation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0003.flac", "answer": "A RECONCILIATION BETWEEN THE TWO CONFLICTING REQUIREMENTS IS EFFECTED BY A RESORT TO MAKE BELIEVE MANY AND INTRICATE POLITE OBSERVANCES AND SOCIAL DUTIES OF A CEREMONIAL NATURE ARE DEVELOPED MANY ORGANIZATIONS ARE FOUNDED WITH SOME SPECIOUS OBJECT OF AMELIORATION EMBODIED IN THEIR OFFICIAL STYLE AND TITLE THERE IS MUCH COMING AND GOING AND A DEAL OF TALK TO THE END THAT THE TALKERS MAY NOT HAVE OCCASION TO REFLECT ON WHAT IS THE EFFECTUAL ECONOMIC VALUE OF THEIR TRAFFIC", "subset": "test_clean", "task_type": "understanding", "prediction": "a reconciliation between the two conflicting requirements is effected by resort to make believe many an intricate polite observances and social duties of a ceremonial nature are developed many organizations are founded with some specious object of amelioration embodied in their official style and title there is much coming and going and a deal of talk to the end that the talkers may not have occasion to reflect on what is the effectual economic value of their traffic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0000.flac", "answer": "UNDER THE SIMPLE TEST OF EFFECTIVENESS FOR ADVERTISING WE SHOULD EXPECT TO FIND LEISURE AND THE CONSPICUOUS CONSUMPTION OF GOODS DIVIDING THE FIELD OF PECUNIARY EMULATION PRETTY EVENLY BETWEEN THEM AT THE OUTSET", "subset": "test_clean", "task_type": "understanding", "prediction": "under the simple test of effectiveness for advertising we should expect to find leisure and the conspicuous consumption of goods dividing the field of pecuniary emulation pretty evenly between them at the outset", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0005.flac", "answer": "THROUGHOUT THE ENTIRE EVOLUTION OF CONSPICUOUS EXPENDITURE WHETHER OF GOODS OR OF SERVICES OR HUMAN LIFE RUNS THE OBVIOUS IMPLICATION THAT IN ORDER TO EFFECTUALLY MEND THE CONSUMER'S GOOD FAME IT MUST BE AN EXPENDITURE OF SUPERFLUITIES", "subset": "test_clean", "task_type": "understanding", "prediction": "throughout the entire evolution of conspicuous expenditure whether of goods or of services or human life runs the obvious implication that in order to effectually mend the consumers good fame it must be an expenditure of superfluities", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0002.flac", "answer": "OTHER CIRCUMSTANCES PERMITTING THAT INSTINCT DISPOSES MEN TO LOOK WITH FAVOR UPON PRODUCTIVE EFFICIENCY AND ON WHATEVER IS OF HUMAN USE", "subset": "test_clean", "task_type": "understanding", "prediction": "other circumstances permitting that instinct disposes men to look with favor upon productive efficiency and on whatever is of human use", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/3570/5696/3570-5696-0008.flac", "answer": "BUT IT IS ON OTHER GROUNDS WORTH NOTING THAT THE TERM WASTE IN THE LANGUAGE OF EVERYDAY LIFE IMPLIES DEPRECATION OF WHAT IS CHARACTERIZED AS WASTEFUL", "subset": "test_clean", "task_type": "understanding", "prediction": "but it is on other grounds worth noting that the term waste in the language of everyday life implies deprecation of what is characterized as wasteful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123859/121-123859-0000.flac", "answer": "YOU ARE MY ALL THE WORLD AND I MUST STRIVE TO KNOW MY SHAMES AND PRAISES FROM YOUR TONGUE NONE ELSE TO ME NOR I TO NONE ALIVE THAT MY STEEL'D SENSE OR CHANGES RIGHT OR WRONG", "subset": "test_clean", "task_type": "understanding", "prediction": "you are my all the world and i must strive to know my shames and praises from your tongue none else to me nor i to none alive that my steeld sense or changes right or wrong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123859/121-123859-0002.flac", "answer": "BUT RECKONING TIME WHOSE MILLION'D ACCIDENTS CREEP IN TWIXT VOWS AND CHANGE DECREES OF KINGS TAN SACRED BEAUTY BLUNT THE SHARP'ST INTENTS DIVERT STRONG MINDS TO THE COURSE OF ALTERING THINGS ALAS WHY FEARING OF TIME'S TYRANNY MIGHT I NOT THEN SAY NOW I LOVE YOU BEST WHEN I WAS CERTAIN O'ER INCERTAINTY CROWNING THE PRESENT DOUBTING OF THE REST", "subset": "test_clean", "task_type": "understanding", "prediction": "but reckoning time whose millioned accidents creep in twixt vows and change decrees of kings tans sacred beauty blunt the sharpest intents diverts strong minds to the course of altering things alas why fearing of times tyranny might i not then say now i love you best when i was certain or in certainty crowning the present doubting of the rest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123859/121-123859-0004.flac", "answer": "SO I RETURN REBUK'D TO MY CONTENT AND GAIN BY ILL THRICE MORE THAN I HAVE SPENT", "subset": "test_clean", "task_type": "understanding", "prediction": "so i return rebuked to my content and gain by ill thrice more than i have spent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123859/121-123859-0003.flac", "answer": "LOVE IS A BABE THEN MIGHT I NOT SAY SO TO GIVE FULL GROWTH TO THAT WHICH STILL DOTH GROW", "subset": "test_clean", "task_type": "understanding", "prediction": "love is a babe then might i not say so to give full growth to that which still doth grow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123859/121-123859-0001.flac", "answer": "O TIS THE FIRST TIS FLATTERY IN MY SEEING AND MY GREAT MIND MOST KINGLY DRINKS IT UP MINE EYE WELL KNOWS WHAT WITH HIS GUST IS GREEING AND TO HIS PALATE DOTH PREPARE THE CUP IF IT BE POISON'D TIS THE LESSER SIN THAT MINE EYE LOVES IT AND DOTH FIRST BEGIN", "subset": "test_clean", "task_type": "understanding", "prediction": "oh tis the first tis flattery in my seeing and my great mind most kingly drinks it up mine eye well knows what with his gust is greying and to his palate doth prepare the cup if it be poisoned tis the lesser sin that mine eye loves it and doth first begin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0020.flac", "answer": "WHO WAS IT SHE WAS IN LOVE WITH THE STORY WILL TELL I TOOK UPON MYSELF TO REPLY OH I CAN'T WAIT FOR THE STORY THE STORY WON'T TELL SAID DOUGLAS NOT IN ANY LITERAL VULGAR WAY MORE'S THE PITY THEN", "subset": "test_clean", "task_type": "understanding", "prediction": "who was it she was in love with the story will tell i took upon myself to reply oh i can not wait for the story the story won t tell said douglas not in any literal vulgar way more s the pity then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0018.flac", "answer": "CRIED THE LADIES WHOSE DEPARTURE HAD BEEN FIXED", "subset": "test_clean", "task_type": "understanding", "prediction": "cried the ladies whose departure had been fixed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0034.flac", "answer": "IT SOUNDED DULL IT SOUNDED STRANGE AND ALL THE MORE SO BECAUSE OF HIS MAIN CONDITION WHICH WAS", "subset": "test_clean", "task_type": "understanding", "prediction": "it sounded dull that sounded strange and all the more so because of his main condition which was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0033.flac", "answer": "IT WAS THE BEAUTY OF IT", "subset": "test_clean", "task_type": "understanding", "prediction": "it was the beauty of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0003.flac", "answer": "THERE WAS A UNANIMOUS GROAN AT THIS AND MUCH REPROACH AFTER WHICH IN HIS PREOCCUPIED WAY HE EXPLAINED", "subset": "test_clean", "task_type": "understanding", "prediction": "there was a unanimous groan at this and much reproach after which in his preoccupied way he explained", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0030.flac", "answer": "I DON'T ANTICIPATE", "subset": "test_clean", "task_type": "understanding", "prediction": "i dont anticipate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0024.flac", "answer": "POOR DOUGLAS BEFORE HIS DEATH WHEN IT WAS IN SIGHT COMMITTED TO ME THE MANUSCRIPT THAT REACHED HIM ON THE THIRD OF THESE DAYS AND THAT ON THE SAME SPOT WITH IMMENSE EFFECT HE BEGAN TO READ TO OUR HUSHED LITTLE CIRCLE ON THE NIGHT OF THE FOURTH", "subset": "test_clean", "task_type": "understanding", "prediction": "poor douglas before his death when it was in sight committed to me the manuscript that reached him on the third of these days and that on the same spot with immense effect he began to read to our hushed little circle on the night of the fourth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0026.flac", "answer": "THE FIRST OF THESE TOUCHES CONVEYED THAT THE WRITTEN STATEMENT TOOK UP THE TALE AT A POINT AFTER IT HAD IN A MANNER BEGUN", "subset": "test_clean", "task_type": "understanding", "prediction": "the first of these touches conveyed that the written statement took up the tale at a point after it had in a manner begun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0013.flac", "answer": "YOU'LL EASILY JUDGE WHY WHEN YOU HEAR BECAUSE THE THING HAD BEEN SUCH A SCARE HE CONTINUED TO FIX ME", "subset": "test_clean", "task_type": "understanding", "prediction": "you ll easily judge why when you hear because the thing had been such a scare he continued to fix me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0027.flac", "answer": "HE HAD FOR HIS OWN TOWN RESIDENCE A BIG HOUSE FILLED WITH THE SPOILS OF TRAVEL AND THE TROPHIES OF THE CHASE BUT IT WAS TO HIS COUNTRY HOME AN OLD FAMILY PLACE IN ESSEX THAT HE WISHED HER IMMEDIATELY TO PROCEED", "subset": "test_clean", "task_type": "understanding", "prediction": "he had for his own town residence a big house filled with the spoils of travel and the trophies of the chase but it was to his country home an old family place in essex that he wished her immediately to proceed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0036.flac", "answer": "BUT WAS THAT ALL HER REWARD ONE OF THE LADIES ASKED", "subset": "test_clean", "task_type": "understanding", "prediction": "but was that all her reward one of the ladies asked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0006.flac", "answer": "THE OTHERS RESENTED POSTPONEMENT BUT IT WAS JUST HIS SCRUPLES THAT CHARMED ME", "subset": "test_clean", "task_type": "understanding", "prediction": "the others resented postponement but it was just his scruples that charmed me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0010.flac", "answer": "SHE SENT ME THE PAGES IN QUESTION BEFORE SHE DIED", "subset": "test_clean", "task_type": "understanding", "prediction": "she sent me the pages in question before she died", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0000.flac", "answer": "IT WAS THIS OBSERVATION THAT DREW FROM DOUGLAS NOT IMMEDIATELY BUT LATER IN THE EVENING A REPLY THAT HAD THE INTERESTING CONSEQUENCE TO WHICH I CALL ATTENTION", "subset": "test_clean", "task_type": "understanding", "prediction": "it was this observation that drew from douglas not immediately but later in the evening a reply that had the interesting consequence to which i call attention", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0029.flac", "answer": "THERE WERE PLENTY OF PEOPLE TO HELP BUT OF COURSE THE YOUNG LADY WHO SHOULD GO DOWN AS GOVERNESS WOULD BE IN SUPREME AUTHORITY", "subset": "test_clean", "task_type": "understanding", "prediction": "there were plenty of people to help but of course the young lady who should go down as governess would be in supreme authority", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0025.flac", "answer": "THE DEPARTING LADIES WHO HAD SAID THEY WOULD STAY DIDN'T OF COURSE THANK HEAVEN STAY THEY DEPARTED IN CONSEQUENCE OF ARRANGEMENTS MADE IN A RAGE OF CURIOSITY AS THEY PROFESSED PRODUCED BY THE TOUCHES WITH WHICH HE HAD ALREADY WORKED US UP", "subset": "test_clean", "task_type": "understanding", "prediction": "the departing ladies who had said they would stay didnt of course thank heaven stay they departed in consequence of arrangements made in a rage of curiosity as they professed produced by the touches with which he had already worked us up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0022.flac", "answer": "WELL IF I DON'T KNOW WHO SHE WAS IN LOVE WITH I KNOW WHO HE WAS", "subset": "test_clean", "task_type": "understanding", "prediction": "well if i don t know who she was in love with i know who he was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0019.flac", "answer": "MISSUS GRIFFIN HOWEVER EXPRESSED THE NEED FOR A LITTLE MORE LIGHT", "subset": "test_clean", "task_type": "understanding", "prediction": "mrs griffin however expressed the need for a little more light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0001.flac", "answer": "SOMEONE ELSE TOLD A STORY NOT PARTICULARLY EFFECTIVE WHICH I SAW HE WAS NOT FOLLOWING", "subset": "test_clean", "task_type": "understanding", "prediction": "some one else told a story not particularly effective which i saw he was not following", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0014.flac", "answer": "YOU ARE ACUTE", "subset": "test_clean", "task_type": "understanding", "prediction": "you are acute", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0017.flac", "answer": "IT WAS ALMOST THE TONE OF HOPE EVERYBODY WILL STAY", "subset": "test_clean", "task_type": "understanding", "prediction": "it was almost the tone of hope everybody will stay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0005.flac", "answer": "I COULD WRITE TO MY MAN AND ENCLOSE THE KEY HE COULD SEND DOWN THE PACKET AS HE FINDS IT", "subset": "test_clean", "task_type": "understanding", "prediction": "i could write to my man and enclose the key he could send down the packet as he finds it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0023.flac", "answer": "LET ME SAY HERE DISTINCTLY TO HAVE DONE WITH IT THAT THIS NARRATIVE FROM AN EXACT TRANSCRIPT OF MY OWN MADE MUCH LATER IS WHAT I SHALL PRESENTLY GIVE", "subset": "test_clean", "task_type": "understanding", "prediction": "let me say here distinctly to have done with it that this narrative from an exact transcript of my own made much later is what i shall presently give", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0002.flac", "answer": "CRIED ONE OF THE WOMEN HE TOOK NO NOTICE OF HER HE LOOKED AT ME BUT AS IF INSTEAD OF ME HE SAW WHAT HE SPOKE OF", "subset": "test_clean", "task_type": "understanding", "prediction": "cried one of the women he took no notice of her he looked at me but as if instead of me he saw what he spoke of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0021.flac", "answer": "WON'T YOU TELL DOUGLAS", "subset": "test_clean", "task_type": "understanding", "prediction": "won t you tell douglas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0004.flac", "answer": "THE STORY'S WRITTEN", "subset": "test_clean", "task_type": "understanding", "prediction": "the story is written", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0028.flac", "answer": "THE AWKWARD THING WAS THAT THEY HAD PRACTICALLY NO OTHER RELATIONS AND THAT HIS OWN AFFAIRS TOOK UP ALL HIS TIME", "subset": "test_clean", "task_type": "understanding", "prediction": "the awkward thing was that they had practically no other relations and that his own affairs took up all his time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0008.flac", "answer": "HE HUNG FIRE AGAIN A WOMAN'S", "subset": "test_clean", "task_type": "understanding", "prediction": "he hung fire again a womans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0016.flac", "answer": "PROBABLY NOT TILL THE SECOND POST", "subset": "test_clean", "task_type": "understanding", "prediction": "probably not till the second post", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0009.flac", "answer": "SHE HAS BEEN DEAD THESE TWENTY YEARS", "subset": "test_clean", "task_type": "understanding", "prediction": "she has been dead these twenty years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0015.flac", "answer": "HE QUITTED THE FIRE AND DROPPED BACK INTO HIS CHAIR", "subset": "test_clean", "task_type": "understanding", "prediction": "he quitted the fire and dropped back into his chair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0031.flac", "answer": "SHE WAS YOUNG UNTRIED NERVOUS IT WAS A VISION OF SERIOUS DUTIES AND LITTLE COMPANY OF REALLY GREAT LONELINESS", "subset": "test_clean", "task_type": "understanding", "prediction": "she was young untried nervous it was a vision of serious duties and little company of really great loneliness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0011.flac", "answer": "SHE WAS THE MOST AGREEABLE WOMAN I'VE EVER KNOWN IN HER POSITION SHE WOULD HAVE BEEN WORTHY OF ANY WHATEVER", "subset": "test_clean", "task_type": "understanding", "prediction": "she was the most agreeable woman i have ever known in her position she would have been worthy of any whatever", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0035.flac", "answer": "SHE PROMISED TO DO THIS AND SHE MENTIONED TO ME THAT WHEN FOR A MOMENT DISBURDENED DELIGHTED HE HELD HER HAND THANKING HER FOR THE SACRIFICE SHE ALREADY FELT REWARDED", "subset": "test_clean", "task_type": "understanding", "prediction": "she promised to do this and she mentioned to me that when for a moment disburdened delighted he held her hand thanking her for the sacrifice she already felt rewarded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0032.flac", "answer": "YES BUT THAT'S JUST THE BEAUTY OF HER PASSION", "subset": "test_clean", "task_type": "understanding", "prediction": "yes but that is just the beauty of her passion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0012.flac", "answer": "IT WASN'T SIMPLY THAT SHE SAID SO BUT THAT I KNEW SHE HADN'T I WAS SURE I COULD SEE", "subset": "test_clean", "task_type": "understanding", "prediction": "it wasnt simply that she said so but that i knew she hadnt i was sure i could see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/127105/121-127105-0007.flac", "answer": "TO THIS HIS ANSWER WAS PROMPT OH THANK GOD NO AND IS THE RECORD YOURS", "subset": "test_clean", "task_type": "understanding", "prediction": "to this his answer was prompt oh thank god no and is the record yours", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123852/121-123852-0003.flac", "answer": "THOUGHT KILLS ME THAT I AM NOT THOUGHT TO LEAP LARGE LENGTHS OF MILES WHEN THOU ART GONE BUT THAT SO MUCH OF EARTH AND WATER WROUGHT I MUST ATTEND TIME'S LEISURE WITH MY MOAN RECEIVING NOUGHT BY ELEMENTS SO SLOW BUT HEAVY TEARS BADGES OF EITHER'S WOE", "subset": "test_clean", "task_type": "understanding", "prediction": "thought kills me that i am not thought to leap large lengths of miles when thou art gone but that so much of earth and water rot i must attend time s leisure with my moan receiving naught by elements so slow but heavy tears badges of either s woe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123852/121-123852-0000.flac", "answer": "THOSE PRETTY WRONGS THAT LIBERTY COMMITS WHEN I AM SOMETIME ABSENT FROM THY HEART THY BEAUTY AND THY YEARS FULL WELL BEFITS FOR STILL TEMPTATION FOLLOWS WHERE THOU ART", "subset": "test_clean", "task_type": "understanding", "prediction": "those pretty wrongs that liberty commits when i am some time absent from thy heart thy beauty and thy years full well befits for still temptation follows where thou art", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123852/121-123852-0004.flac", "answer": "MY HEART DOTH PLEAD THAT THOU IN HIM DOST LIE A CLOSET NEVER PIERC'D WITH CRYSTAL EYES BUT THE DEFENDANT DOTH THAT PLEA DENY AND SAYS IN HIM THY FAIR APPEARANCE LIES", "subset": "test_clean", "task_type": "understanding", "prediction": "my heart doth plead that thou in him dost lie a closet never pierced with crystal eyes but the defendant doth that plea deny and says in him thy fair appearance lies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123852/121-123852-0002.flac", "answer": "NO MATTER THEN ALTHOUGH MY FOOT DID STAND UPON THE FARTHEST EARTH REMOV'D FROM THEE FOR NIMBLE THOUGHT CAN JUMP BOTH SEA AND LAND AS SOON AS THINK THE PLACE WHERE HE WOULD BE BUT AH", "subset": "test_clean", "task_type": "understanding", "prediction": "no matter then although my foot did stand upon the farthest earth removed from thee for nimble thought can jump both sea and land as soon as think the place where he would be but ah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/123852/121-123852-0001.flac", "answer": "AY ME", "subset": "test_clean", "task_type": "understanding", "prediction": "aye me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0004.flac", "answer": "HEAVEN A GOOD PLACE TO BE RAISED TO", "subset": "test_clean", "task_type": "understanding", "prediction": "heaven a good place to be raised to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0000.flac", "answer": "ALSO A POPULAR CONTRIVANCE WHEREBY LOVE MAKING MAY BE SUSPENDED BUT NOT STOPPED DURING THE PICNIC SEASON", "subset": "test_clean", "task_type": "understanding", "prediction": "also a popular contrivance whereby love making may be suspended but not stopped during the picnic season", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0007.flac", "answer": "HORSE SENSE A DEGREE OF WISDOM THAT KEEPS ONE FROM BETTING ON THE RACES", "subset": "test_clean", "task_type": "understanding", "prediction": "horse sense a degree of wisdom that keeps one from betting on the races", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0010.flac", "answer": "HOUSECLEANING A DOMESTIC UPHEAVAL THAT MAKES IT EASY FOR THE GOVERNMENT TO ENLIST ALL THE SOLDIERS IT NEEDS", "subset": "test_clean", "task_type": "understanding", "prediction": "house cleaning a domestic upheaval that makes it easy for the government to enlist all the soldiers it needs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0008.flac", "answer": "HOSE MAN'S EXCUSE FOR WETTING THE WALK", "subset": "test_clean", "task_type": "understanding", "prediction": "hose mans excuse for wetting the walk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0005.flac", "answer": "HEDGE A FENCE", "subset": "test_clean", "task_type": "understanding", "prediction": "hedge a fence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0001.flac", "answer": "HARANGUE THE TIRESOME PRODUCT OF A TIRELESS TONGUE", "subset": "test_clean", "task_type": "understanding", "prediction": "harangue the tiresome product of a tireless tongue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0003.flac", "answer": "HAY FEVER A HEART TROUBLE CAUSED BY FALLING IN LOVE WITH A GRASS WIDOW", "subset": "test_clean", "task_type": "understanding", "prediction": "hay fever a heart trouble caused by falling in love with a grass widow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0006.flac", "answer": "HEREDITY THE CAUSE OF ALL OUR FAULTS", "subset": "test_clean", "task_type": "understanding", "prediction": "heredity the cause of all our faults", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0012.flac", "answer": "HUSSY WOMAN AND BOND TIE", "subset": "test_clean", "task_type": "understanding", "prediction": "hussy woman and bond tie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0013.flac", "answer": "TIED TO A WOMAN", "subset": "test_clean", "task_type": "understanding", "prediction": "tied to a woman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0011.flac", "answer": "HUSBAND THE NEXT THING TO A WIFE", "subset": "test_clean", "task_type": "understanding", "prediction": "husband the next thing to a wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0009.flac", "answer": "HOTEL A PLACE WHERE A GUEST OFTEN GIVES UP GOOD DOLLARS FOR POOR QUARTERS", "subset": "test_clean", "task_type": "understanding", "prediction": "hotel a place where a guest often gives up good dollars for poor quarters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0002.flac", "answer": "ANGOR PAIN PAINFUL TO HEAR", "subset": "test_clean", "task_type": "understanding", "prediction": "angor hain painful to hear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/121/121726/121-121726-0014.flac", "answer": "HYPOCRITE A HORSE DEALER", "subset": "test_clean", "task_type": "understanding", "prediction": "hypocrite a horse dealer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0035.flac", "answer": "I HAVE A REMEDY AGAINST THIRST QUITE CONTRARY TO THAT WHICH IS GOOD AGAINST THE BITING OF A MAD DOG", "subset": "test_other", "task_type": "understanding", "prediction": "i have a remedy against thirst quite contrary to that which is good against the biting of a mad dog", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0030.flac", "answer": "HO THIS WILL BANG IT SOUNDLY", "subset": "test_other", "task_type": "understanding", "prediction": "ho this was beng it soundly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0039.flac", "answer": "THERE IS NO ENCHANTMENT NOR CHARM THERE EVERY ONE OF YOU HATH SEEN IT", "subset": "test_other", "task_type": "understanding", "prediction": "there is no enchantment nor charm there every one of you hath seen it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0026.flac", "answer": "I WAS WONT HERETOFORE TO DRINK OUT ALL BUT NOW I LEAVE NOTHING", "subset": "test_other", "task_type": "understanding", "prediction": "i was wont heretofore to drink out all but now i leave nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0002.flac", "answer": "A CESSATION AND TRUCE WITH THIRST", "subset": "test_other", "task_type": "understanding", "prediction": "a cessation and truce with thirst", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0005.flac", "answer": "WHICH WAS FIRST THIRST OR DRINKING", "subset": "test_other", "task_type": "understanding", "prediction": "which was first thirst or drinking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0034.flac", "answer": "APPETITE COMES WITH EATING SAYS ANGESTON BUT THE THIRST GOES AWAY WITH DRINKING", "subset": "test_other", "task_type": "understanding", "prediction": "appetite comes with eating says anguston but the thirst goes away with drinking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0018.flac", "answer": "AND I TANQUAM SPONSUS", "subset": "test_other", "task_type": "understanding", "prediction": "and i tanquam sponsus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0008.flac", "answer": "IF I DRINK NOT I AM A GROUND DRY GRAVELLED AND SPENT I AM STARK DEAD WITHOUT DRINK AND MY SOUL READY TO FLY INTO SOME MARSH AMONGST FROGS THE SOUL NEVER DWELLS IN A DRY PLACE DROUTH KILLS IT", "subset": "test_other", "task_type": "understanding", "prediction": "if i drink not i am a ground dry gravelled and spent i am stark dead without drink and my soul ready to fly into some marsh amongst frogs the soul never dwells in a dry place drouth kill it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0024.flac", "answer": "HERE PAGE FILL", "subset": "test_other", "task_type": "understanding", "prediction": "here page phil", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0016.flac", "answer": "I DRINK NO MORE THAN A SPONGE", "subset": "test_other", "task_type": "understanding", "prediction": "i drink no more than a sponge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0019.flac", "answer": "AND I SICUT TERRA SINE AQUA", "subset": "test_other", "task_type": "understanding", "prediction": "and i sicca terras in aqua", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0001.flac", "answer": "SO MY FRIEND SO WHIP ME OFF THIS GLASS NEATLY BRING ME HITHER SOME CLARET A FULL WEEPING GLASS TILL IT RUN OVER", "subset": "test_other", "task_type": "understanding", "prediction": "so my friend so whip me off this glass neatly bring me hither some claret a full weeping glass till it run over", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0017.flac", "answer": "I DRINK LIKE A TEMPLAR KNIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "i drink like a templar knight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0033.flac", "answer": "THE GREAT GOD MADE THE PLANETS AND WE MAKE THE PLATTERS NEAT", "subset": "test_other", "task_type": "understanding", "prediction": "the great god made the planets and we make the platters neat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0021.flac", "answer": "IT IS THE COMPULSORY OF DRINKERS IT IS A PULLEY", "subset": "test_other", "task_type": "understanding", "prediction": "it is the compulsory of drinkers it is a pullie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0009.flac", "answer": "HE DRINKS IN VAIN THAT FEELS NOT THE PLEASURE OF IT", "subset": "test_other", "task_type": "understanding", "prediction": "he drinks in vain that feels not the pleasure of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0027.flac", "answer": "HEYDAY HERE ARE TRIPES FIT FOR OUR SPORT AND IN EARNEST EXCELLENT GODEBILLIOS OF THE DUN OX YOU KNOW WITH THE BLACK STREAK", "subset": "test_other", "task_type": "understanding", "prediction": "haidy here are types fit for our sport and in earnest excellent gored billets of the dun ox you know with the black streak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0014.flac", "answer": "WELL CACKED WELL SUNG", "subset": "test_other", "task_type": "understanding", "prediction": "well cagool well sung", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0000.flac", "answer": "DRAW REACH FILL MIX GIVE IT ME WITHOUT WATER", "subset": "test_other", "task_type": "understanding", "prediction": "draw reach fill mix give it me without water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0037.flac", "answer": "O LACHRYMA CHRISTI IT IS OF THE BEST GRAPE", "subset": "test_other", "task_type": "understanding", "prediction": "o lachryma christi it is of the best grape", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0004.flac", "answer": "BY THE BELLY OF SANCT BUFF LET US TALK OF OUR DRINK I NEVER DRINK BUT AT MY HOURS LIKE THE POPE'S MULE", "subset": "test_other", "task_type": "understanding", "prediction": "by the belly of st buff let us talk of our drink i never drink but at my hours like the pope s mule", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0031.flac", "answer": "BUT THIS SHALL BANISH IT UTTERLY", "subset": "test_other", "task_type": "understanding", "prediction": "but they shall vanish it utterly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0003.flac", "answer": "YOU HAVE CATCHED A COLD GAMMER YEA FORSOOTH SIR", "subset": "test_other", "task_type": "understanding", "prediction": "you have castig hold gammer yea forsooth sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0010.flac", "answer": "IT IS ENOUGH TO BREAK BOTH GIRDS AND PETREL", "subset": "test_other", "task_type": "understanding", "prediction": "it is enough to break both girds and petrel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0020.flac", "answer": "GIVE ME A SYNONYMON FOR A GAMMON OF BACON", "subset": "test_other", "task_type": "understanding", "prediction": "give me a synonym for a gammon of bacon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0006.flac", "answer": "WHAT IT SEEMS I DO NOT DRINK BUT BY AN ATTORNEY", "subset": "test_other", "task_type": "understanding", "prediction": "what it seems i do not drink but buy an attorney", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0015.flac", "answer": "COME LET US DRINK WILL YOU SEND NOTHING TO THE RIVER", "subset": "test_other", "task_type": "understanding", "prediction": "come let us drink will you send nothing to the river", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0022.flac", "answer": "A LITTLE RAIN ALLAYS A GREAT DEAL OF WIND LONG TIPPLING BREAKS THE THUNDER", "subset": "test_other", "task_type": "understanding", "prediction": "a little rain allays a great deal of wind long tippling breaks the thunder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0041.flac", "answer": "I SHOULD SAY MASTER PAST", "subset": "test_other", "task_type": "understanding", "prediction": "as they say master pears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0032.flac", "answer": "LET US WIND OUR HORNS BY THE SOUND OF FLAGONS AND BOTTLES AND CRY ALOUD THAT WHOEVER HATH LOST HIS THIRST COME NOT HITHER TO SEEK IT", "subset": "test_other", "task_type": "understanding", "prediction": "let us wind our horns by the sound of flagons and bottles and cry aloud that whoever hath lost his thirst come now hither to seek it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0042.flac", "answer": "O THE DRINKERS THOSE THAT ARE A DRY O POOR THIRSTY SOULS", "subset": "test_other", "task_type": "understanding", "prediction": "o the drinkers those that are adry o poor thirsty souls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0029.flac", "answer": "SPARROWS WILL NOT EAT UNLESS YOU BOB THEM ON THE TAIL NOR CAN I DRINK IF I BE NOT FAIRLY SPOKE TO", "subset": "test_other", "task_type": "understanding", "prediction": "sparrows will not eat unless you bob them on the tail nor can i drink if i be not fairly spoke to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0040.flac", "answer": "MY PRENTICESHIP IS OUT I AM A FREE MAN AT THIS TRADE", "subset": "test_other", "task_type": "understanding", "prediction": "my prenticeship is out i am a free man at this trade", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0043.flac", "answer": "CLEAR OFF NEAT SUPERNACULUM", "subset": "test_other", "task_type": "understanding", "prediction": "clear off neat super naculum", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0023.flac", "answer": "BUT IF THERE CAME SUCH LIQUOR FROM MY BALLOCK WOULD YOU NOT WILLINGLY THEREAFTER SUCK THE UDDER WHENCE IT ISSUED", "subset": "test_other", "task_type": "understanding", "prediction": "but if there came such liquor from my ballock will you not willingly thereafter suck the udder whence it issued", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0012.flac", "answer": "BRAVELY AND WELL PLAYED UPON THE WORDS", "subset": "test_other", "task_type": "understanding", "prediction": "bravely and well played upon the words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0013.flac", "answer": "OUR FATHERS DRANK LUSTILY AND EMPTIED THEIR CANS", "subset": "test_other", "task_type": "understanding", "prediction": "our fathers drank lustily and emptied their cans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0028.flac", "answer": "O FOR GOD'S SAKE LET US LASH THEM SOUNDLY YET THRIFTILY", "subset": "test_other", "task_type": "understanding", "prediction": "o for god sake let us last them soundly yet thriftily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0036.flac", "answer": "WHITE WINE HERE WINE BOYS", "subset": "test_other", "task_type": "understanding", "prediction": "white wine here wine boys", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0025.flac", "answer": "I APPEAL FROM THIRST AND DISCLAIM ITS JURISDICTION", "subset": "test_other", "task_type": "understanding", "prediction": "i appeal from thirst and disclaim its jurisdiction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0038.flac", "answer": "I'FAITH PURE GREEK GREEK O THE FINE WHITE WINE", "subset": "test_other", "task_type": "understanding", "prediction": "i faith pure greek greek o the fine white wine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0007.flac", "answer": "DRINK ALWAYS AND YOU SHALL NEVER DIE", "subset": "test_other", "task_type": "understanding", "prediction": "drink always and you shall never die", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12259/4198-12259-0011.flac", "answer": "WHAT DIFFERENCE IS THERE BETWEEN A BOTTLE AND A FLAGON", "subset": "test_other", "task_type": "understanding", "prediction": "what difference is there between a bottle and a flagon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0021.flac", "answer": "MENAHEM KING OF ISRAEL HAD DIED AND WAS SUCCEEDED BY HIS SON PEKAHIAH", "subset": "test_other", "task_type": "understanding", "prediction": "menahem king of israel had died and was succeeded by his son pekahiah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0023.flac", "answer": "HE CONDEMNED ISRAEL FOR ITS IDOLATRIES AND CRIED", "subset": "test_other", "task_type": "understanding", "prediction": "he condemned israel for its idolatries and cried", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0001.flac", "answer": "AT THE BEGINNING OF HIS REIGN THERE WAS MUCH SOCIAL DISCONTENT AND SUFFERING", "subset": "test_other", "task_type": "understanding", "prediction": "at the beginning of his reign there was much social discontent and suffering", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0005.flac", "answer": "AN ATTEMPT WAS MADE TO CAPTURE KING SHARDURIS WHO LEAPT FROM HIS CHARIOT AND MADE HASTY ESCAPE ON HORSEBACK HOTLY PURSUED IN THE GATHERING DARKNESS BY AN ASSYRIAN CONTINGENT OF CAVALRY", "subset": "test_other", "task_type": "understanding", "prediction": "an attempt was made to capture king shadurris who leapt from his chariot and made hasty escape on horseback hotly pursued in the gathering darkness by an assyrian contingent of cavalry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0010.flac", "answer": "ARPAD WAS CAPTURED AND MATI ILU DEPOSED AND PROBABLY PUT TO DEATH", "subset": "test_other", "task_type": "understanding", "prediction": "arpad was captured and manti ilu deposed and probably put to death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0020.flac", "answer": "IN THE FOLLOWING YEAR TIGLATH PILESER RETURNED TO SYRIA", "subset": "test_other", "task_type": "understanding", "prediction": "in the following year tiglath pileser returned to syria", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0011.flac", "answer": "ONCE AGAIN THE HEBREWS CAME INTO CONTACT WITH ASSYRIA", "subset": "test_other", "task_type": "understanding", "prediction": "once again the hebrews came into contact with this area", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0022.flac", "answer": "JUDAH HAD TAKEN ADVANTAGE OF THE DISTURBED CONDITIONS IN ISRAEL TO ASSERT ITS INDEPENDENCE", "subset": "test_other", "task_type": "understanding", "prediction": "judah had taken advantage of the disturbed conditions in israel to assert its independence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0000.flac", "answer": "IT IS SIGNIFICANT TO NOTE IN THIS CONNECTION THAT THE NEW KING WAS AN UNSWERVING ADHERENT OF THE CULT OF ASHUR BY THE ADHERENTS OF WHICH HE WAS PROBABLY STRONGLY SUPPORTED", "subset": "test_other", "task_type": "understanding", "prediction": "it is significant to note in this connection that the new king was an unswerving adherent of the cult of asher by the adherents of which he was probably strongly supported", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0030.flac", "answer": "UKINZER TOOK REFUGE IN HIS CAPITAL SHAPIA WHICH HELD OUT SUCCESSFULLY ALTHOUGH THE SURROUNDING COUNTRY WAS RAVAGED AND DESPOILED", "subset": "test_other", "task_type": "understanding", "prediction": "echnzer took refuge in his capital shabia which held out successfully although the surrounding country was ravaged and despoiled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0026.flac", "answer": "ISRAEL WAS ALSO DEALT WITH", "subset": "test_other", "task_type": "understanding", "prediction": "israel was also dealt with", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0015.flac", "answer": "THIS USURPER HELD SWAY AT SAMARIA FOR ONLY A MONTH", "subset": "test_other", "task_type": "understanding", "prediction": "this usurper held sway at samaria for only a month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0024.flac", "answer": "FOR THUS SAITH THE LORD UNTO THE HOUSE OF ISRAEL SEEK YE ME AND YE SHALL LIVE HAVE YE OFFERED UNTO ME SACRIFICES AND OFFERINGS IN THE WILDERNESS FORTY YEARS O HOUSE OF ISRAEL", "subset": "test_other", "task_type": "understanding", "prediction": "for thus saith the lord unto the house of israel seek ye me and ye shall live have ye offered unto me sacrifices and offerings in the wilderness forty years o house of israel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0004.flac", "answer": "A FIERCE BATTLE ENSUED AND ONE OF ITS DRAMATIC INCIDENTS WAS A SINGLE COMBAT BETWEEN THE RIVAL KINGS", "subset": "test_other", "task_type": "understanding", "prediction": "a fierce battle ensued and one of its dramatic incidents was a single combat between the rival kings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0028.flac", "answer": "THE PHILISTINES AND THE ARABIANS OF THE DESERT WERE ALSO SUBDUED", "subset": "test_other", "task_type": "understanding", "prediction": "the philistines and the arabians of the desert were also subdued", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0029.flac", "answer": "HE INVADED BABYLONIA", "subset": "test_other", "task_type": "understanding", "prediction": "he invaded babylonia", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0027.flac", "answer": "HE SWEPT THROUGH ISRAEL LIKE A HURRICANE", "subset": "test_other", "task_type": "understanding", "prediction": "he swept through israel like a hurricane", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0002.flac", "answer": "WELL MIGHT SHARDURIS EXCLAIM IN THE WORDS OF THE PROPHET WHERE IS THE KING OF ARPAD", "subset": "test_other", "task_type": "understanding", "prediction": "well might shohduras exclaim in the words of the prophet where is the king of arpad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0003.flac", "answer": "TIGLATH PILESER HOWEVER CROSSED THE EUPHRATES AND MOVING NORTHWARD DELIVERED AN UNEXPECTED ATTACK ON THE URARTIAN ARMY IN QUMMUKH", "subset": "test_other", "task_type": "understanding", "prediction": "tiglath pileser however crossing the euphrates and moving northward delivered an unexpected attack on the arachian army in kumuk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0018.flac", "answer": "HE OVERTHREW BUILDINGS DESTROYED ORCHARDS AND TRANSPORTED TO NINEVEH THOSE OF THE INHABITANTS HE HAD NOT PUT TO THE SWORD WITH ALL THE LIVE STOCK HE COULD LAY HANDS ON", "subset": "test_other", "task_type": "understanding", "prediction": "he overthrew buildings destroyed orchards and transported to nineveh those of the inhabitants he had not put to the sword with all the live stock he could lay hands on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0019.flac", "answer": "THUS WAS URARTU CRIPPLED AND HUMILIATED IT NEVER REGAINED ITS FORMER PRESTIGE AMONG THE NORTHERN STATES", "subset": "test_other", "task_type": "understanding", "prediction": "thus was uratu crippled and humiliated it never regained its former prestige among the northern states", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0013.flac", "answer": "JEHOASH THE GRANDSON OF JEHU HAD ACHIEVED SUCCESSES IN CONFLICT WITH DAMASCUS", "subset": "test_other", "task_type": "understanding", "prediction": "jehoash the grandson of jehu had achieved successes in conflict with damascus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0014.flac", "answer": "SIX MONTHS AFTERWARDS HE WAS ASSASSINATED BY SHALLUM", "subset": "test_other", "task_type": "understanding", "prediction": "six months afterward he was assassinated by schelim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0007.flac", "answer": "THE SHIFTY MATI ILU EITHER CHERISHED THE HOPE THAT SHARDURIS WOULD RECOVER STRENGTH AND AGAIN INVADE NORTH SYRIA OR THAT HE MIGHT HIMSELF ESTABLISH AN EMPIRE IN THAT REGION", "subset": "test_other", "task_type": "understanding", "prediction": "the shiftymetti illyu either cherished the hope that shahdurz would recover strength and again invade north syria or that he might himself establish an empire in that region", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0008.flac", "answer": "TIGLATH PILESER HAD THEREFORE TO MARCH WESTWARD AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "tiglath pileser had therefore to march westward again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0006.flac", "answer": "DESPITE THE BLOW DEALT AGAINST URARTU ASSYRIA DID NOT IMMEDIATELY REGAIN POSSESSION OF NORTH SYRIA", "subset": "test_other", "task_type": "understanding", "prediction": "despite the blow dealt against urartu assyria did not immediately regain possession of north syria", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0025.flac", "answer": "THE REMNANT OF THE PHILISTINES SHALL PERISH", "subset": "test_other", "task_type": "understanding", "prediction": "the remnant of the philistines shall perish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0016.flac", "answer": "NO RESISTANCE WAS POSSIBLE ON THE PART OF MENAHEM THE USURPER WHO WAS PROBABLY READY TO WELCOME THE ASSYRIAN CONQUEROR SO THAT BY ARRANGING AN ALLIANCE HE MIGHT SECURE HIS OWN POSITION", "subset": "test_other", "task_type": "understanding", "prediction": "no resistance was possible on the part of manehim the usurper who was probably ready to welcome the assyrian conqueror so that by arranging an alliance he might secure his own position", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0009.flac", "answer": "FOR THREE YEARS HE CONDUCTED VIGOROUS CAMPAIGNS IN THE WESTERN LAND WHERE HE MET WITH VIGOROUS RESISTANCE", "subset": "test_other", "task_type": "understanding", "prediction": "for three years he conducted vigorous campaigns in the western land where he met with vigorous resistance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0012.flac", "answer": "ITS FALL MAY NOT HAVE BEEN UNCONNECTED WITH THE TREND OF EVENTS IN ASSYRIA DURING THE CLOSING YEARS OF THE MIDDLE EMPIRE", "subset": "test_other", "task_type": "understanding", "prediction": "its fall may not have been unconnected with the trend of events in assyria during the closing years of the middle empire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/61336/4198-61336-0017.flac", "answer": "TIGLATH PILESER NEXT OPERATED AGAINST THE MEDIAN AND OTHER HILL TRIBES IN THE NORTH EAST", "subset": "test_other", "task_type": "understanding", "prediction": "teglath pileser next operated against the median and other hill tribes in the northeast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0003.flac", "answer": "BY THE VIRTUE OF GOD WHY DO NOT YOU SING PANNIERS FAREWELL VINTAGE IS DONE", "subset": "test_other", "task_type": "understanding", "prediction": "by the virtue of god why do not you sing panniers farewell vintage is done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0007.flac", "answer": "WHEREFORE IS IT THAT OUR DEVOTIONS WERE INSTITUTED TO BE SHORT IN THE TIME OF HARVEST AND VINTAGE AND LONG IN THE ADVENT AND ALL THE WINTER", "subset": "test_other", "task_type": "understanding", "prediction": "wherefore is it that our devotions were instituted to be short in the time of harvest and vintage and long in the advent and all the winter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0004.flac", "answer": "BY THE BELLY OF SANCT JAMES WHAT SHALL WE POOR DEVILS DRINK THE WHILE", "subset": "test_other", "task_type": "understanding", "prediction": "by the belly of saint james what shall we poor devils drink the while", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0010.flac", "answer": "TO SOME WITH A SMART SOUSE ON THE EPIGASTER HE WOULD MAKE THEIR MIDRIFF SWAG THEN REDOUBLING THE BLOW GAVE THEM SUCH A HOMEPUSH ON THE NAVEL THAT HE MADE THEIR PUDDINGS TO GUSH OUT", "subset": "test_other", "task_type": "understanding", "prediction": "to some would they smart soos on the epigaster he would make their midriff swag then redoubling the blow gave them such a home push on the navel that he made their puddings to gush out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0000.flac", "answer": "ALTHOUGH THE PLAGUE WAS THERE IN THE MOST PART OF ALL THE HOUSES THEY NEVERTHELESS ENTERED EVERYWHERE THEN PLUNDERED AND CARRIED AWAY ALL THAT WAS WITHIN AND YET FOR ALL THIS NOT ONE OF THEM TOOK ANY HURT WHICH IS A MOST WONDERFUL CASE", "subset": "test_other", "task_type": "understanding", "prediction": "although the plague was there in the most part of all the houses they nevertheless entered everywhere then plundered and carried away all that was within and yet for all this not one of them took any hurt which is a most wonderful case", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0013.flac", "answer": "SOME DIED WITHOUT SPEAKING OTHERS SPOKE WITHOUT DYING SOME DIED IN SPEAKING OTHERS SPOKE IN DYING", "subset": "test_other", "task_type": "understanding", "prediction": "some died without speaking others spoke without dying some died in speaking others spoke in dying", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0006.flac", "answer": "LET HIM BE CARRIED TO PRISON FOR TROUBLING THE DIVINE SERVICE", "subset": "test_other", "task_type": "understanding", "prediction": "let him be carried to prison for troubling the divine service", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0008.flac", "answer": "HARK YOU MY MASTERS YOU THAT LOVE THE WINE COP'S BODY FOLLOW ME FOR SANCT ANTHONY BURN ME AS FREELY AS A FAGGOT IF THEY GET LEAVE TO TASTE ONE DROP OF THE LIQUOR THAT WILL NOT NOW COME AND FIGHT FOR RELIEF OF THE VINE", "subset": "test_other", "task_type": "understanding", "prediction": "hark you my masters you that love the wine copps body follow me for st anthony burn me as freely as a faggot if they get leave to taste one drop of the liquor that would not now come and fight for relief of the vine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0002.flac", "answer": "NEVERTHELESS AT ALL ADVENTURES THEY RANG THE BELLS AD CAPITULUM CAPITULANTES", "subset": "test_other", "task_type": "understanding", "prediction": "nevertheless at all ventures they rang the bells ad capitulum capitulantes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0015.flac", "answer": "IN THE MEANTIME FRIAR JOHN WITH HIS FORMIDABLE BATON OF THE CROSS GOT TO THE BREACH WHICH THE ENEMIES HAD MADE AND THERE STOOD TO SNATCH UP THOSE THAT ENDEAVOURED TO ESCAPE", "subset": "test_other", "task_type": "understanding", "prediction": "in the mean time friar john with his formidable baton of the cross got to the breach which the enemies had made and there stood to snatch up those that endeavoured to escape", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0014.flac", "answer": "CAN YOU TELL WITH WHAT INSTRUMENTS THEY DID IT", "subset": "test_other", "task_type": "understanding", "prediction": "can you tell with what instruments they did it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0011.flac", "answer": "BELIEVE THAT IT WAS THE MOST HORRIBLE SPECTACLE THAT EVER ONE SAW", "subset": "test_other", "task_type": "understanding", "prediction": "believe that it was the most horrible spectacle that ever one saw", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0012.flac", "answer": "O THE HOLY LADY NYTOUCH SAID ONE THE GOOD SANCTESS O OUR LADY OF SUCCOURS SAID ANOTHER HELP HELP", "subset": "test_other", "task_type": "understanding", "prediction": "o the holy lady knights it said one the good sanctus o our lady of succours said another help help", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0009.flac", "answer": "TO OTHERS AGAIN HE UNJOINTED THE SPONDYLES OR KNUCKLES OF THE NECK DISFIGURED THEIR CHAPS GASHED THEIR FACES MADE THEIR CHEEKS HANG FLAPPING ON THEIR CHIN AND SO SWINGED AND BALAMMED THEM THAT THEY FELL DOWN BEFORE HIM LIKE HAY BEFORE A MOWER", "subset": "test_other", "task_type": "understanding", "prediction": "to others again he unjointed the spineyels or knuckles of the neck disfigured their chaps gashed their faces made their cheeks hang flapping on their chin and so swinged and belammed them that they fell down before him like hay before a mower", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0001.flac", "answer": "I BESEECH YOU THINK UPON IT", "subset": "test_other", "task_type": "understanding", "prediction": "i beseech you think upon it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4198/12281/4198-12281-0005.flac", "answer": "LORD GOD DA MIHI POTUM", "subset": "test_other", "task_type": "understanding", "prediction": "lord god domi potem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0024.flac", "answer": "FOR MY LIFE I CANNOT BEAT INTO THEIR HEADS A PASSION THAT MUST BE SUBJECT TO NO DECAY AN EVEN PERFECT KINDNESS THAT MUST LAST PERPETUALLY WITHOUT THE LEAST INTERMISSION", "subset": "test_other", "task_type": "understanding", "prediction": "for my life i cannot beat into their heads a passion that must be subject to no decay an even perfect kindness that must last perpetually without the least intermission", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0018.flac", "answer": "DIRECTED FOR YOUR MASTER", "subset": "test_other", "task_type": "understanding", "prediction": "directed for your master", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0002.flac", "answer": "SHE HAS TOLD NOW ALL THAT WAS TOLD HER BUT VOWS SHE WILL NEVER SAY FROM WHENCE SHE HAD IT WE SHALL SEE WHETHER HER RESOLUTIONS ARE AS UNALTERABLE AS THOSE OF MY LADY TALMASH", "subset": "test_other", "task_type": "understanding", "prediction": "she has told now all that was told her but vows she will never say from whence she had it we shall see whether her resolutions are as unalterable as those of my lady talmash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0017.flac", "answer": "BUT I AM CALLED UPON", "subset": "test_other", "task_type": "understanding", "prediction": "but i am called upon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0008.flac", "answer": "MY AUNT TOLD ME NO LONGER AGONE THAN YESTERDAY THAT I WAS THE MOST WILFUL WOMAN THAT EVER SHE KNEW AND HAD AN OBSTINACY OF SPIRIT NOTHING COULD OVERCOME TAKE HEED", "subset": "test_other", "task_type": "understanding", "prediction": "my aunt told me no longer gone than yesterday that i was the most wilful woman that ever she knew and had an obstinacy of spirit nothing could overcome take heed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0028.flac", "answer": "WILL YOU BE SO GOOD NATURED", "subset": "test_other", "task_type": "understanding", "prediction": "will you be so good natured", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0009.flac", "answer": "YOU SEE I GIVE YOU FAIR WARNING", "subset": "test_other", "task_type": "understanding", "prediction": "you see i give you fair warning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0016.flac", "answer": "I DO NOT FIND IT THOUGH I AM TOLD I WAS SO EXTREMELY WHEN I BELIEVED YOU LOVED ME", "subset": "test_other", "task_type": "understanding", "prediction": "i do not find it though i am told i was so extremely when i believed you loved me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0023.flac", "answer": "HOW WELCOME YOU WILL BE BUT ALAS", "subset": "test_other", "task_type": "understanding", "prediction": "how welcome you will be but alas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0006.flac", "answer": "DO NOT TAKE IT ILL FOR I WOULD ENDURE IT IF I COULD RATHER THAN FAIL BUT IN EARNEST I DO NOT THINK IT WERE POSSIBLE FOR ME", "subset": "test_other", "task_type": "understanding", "prediction": "do not take it ill for i would endure it if i could rather than fail but in earnest i do not think it were possible for me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0005.flac", "answer": "THE TRUTH IS I COULD NOT ENDURE TO BE MISSUS BRIDE IN A PUBLIC WEDDING TO BE MADE THE HAPPIEST PERSON ON EARTH", "subset": "test_other", "task_type": "understanding", "prediction": "the truth is i could not endure to be mrs bride in a public wedding to be made the happiest person on earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0022.flac", "answer": "BUT I AM TROUBLED MUCH YOU SHOULD MAKE SO ILL A JOURNEY TO SO LITTLE PURPOSE INDEED I WRIT BY THE FIRST POST AFTER MY ARRIVAL HERE AND CANNOT IMAGINE HOW YOU CAME TO MISS OF MY LETTERS", "subset": "test_other", "task_type": "understanding", "prediction": "but i am troubled much you should make so ill a journey to so little purpose indeed i writ by the first post after my arrival here and cannot imagine how you came to miss of my letters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0004.flac", "answer": "I NEVER SAW ANY ONE YET THAT DID NOT LOOK SIMPLY AND OUT OF COUNTENANCE NOR EVER KNEW A WEDDING WELL DESIGNED BUT ONE AND THAT WAS OF TWO PERSONS WHO HAD TIME ENOUGH I CONFESS TO CONTRIVE IT AND NOBODY TO PLEASE IN'T BUT THEMSELVES", "subset": "test_other", "task_type": "understanding", "prediction": "i never saw any one yet that did not look simply and out of countenance nor ever knew a wedding well designed but one and that was of two persons who had time enough i confess to contrive it and nobody to please in but themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0019.flac", "answer": "I SEE YOU CAN CHIDE WHEN YOU PLEASE AND WITH AUTHORITY BUT I DESERVE IT I CONFESS AND ALL I CAN SAY FOR MYSELF IS THAT MY FAULT PROCEEDED FROM A VERY GOOD PRINCIPLE IN ME", "subset": "test_other", "task_type": "understanding", "prediction": "i see you can chid when you please and with authority but i deserve it i confess and all i can say for myself is that my fault proceeded from a very good principle in me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0025.flac", "answer": "THEY LAUGH TO HEAR ME SAY THAT ONE UNKIND WORD WOULD DESTROY ALL THE SATISFACTION OF MY LIFE AND THAT I SHOULD EXPECT OUR KINDNESS SHOULD INCREASE EVERY DAY IF IT WERE POSSIBLE BUT NEVER LESSEN", "subset": "test_other", "task_type": "understanding", "prediction": "they laugh to hear me say that one unkind word would destroy all the satisfaction of my life and that i should expect our kindness should increase every day if it were possible but never lessen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0029.flac", "answer": "HE HAS ONE SON AND TIS THE FINEST BOY THAT E'ER YOU SAW AND HAS A NOBLE SPIRIT BUT YET STANDS IN THAT AWE OF HIS FATHER THAT ONE WORD FROM HIM IS AS MUCH AS TWENTY WHIPPINGS", "subset": "test_other", "task_type": "understanding", "prediction": "he has one son and tis the finest boy that e'er you saw and has a noble spirit but yet stands in that awe of his father that one word from him is as much as twenty whippings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0001.flac", "answer": "MY POOR LADY VAVASOUR IS CARRIED TO THE TOWER AND HER GREAT BELLY COULD NOT EXCUSE HER BECAUSE SHE WAS ACQUAINTED BY SOMEBODY THAT THERE WAS A PLOT AGAINST THE PROTECTOR AND DID NOT DISCOVER IT", "subset": "test_other", "task_type": "understanding", "prediction": "my poor lady vavasour is carried to the tower and her great belly could not excuse her because she was acquainted by somebody that there was a plot against the protector and did not discover it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0027.flac", "answer": "WELL IN SOBER EARNEST NOW I WOULD NOT LIVE THUS A TWELVEMONTH TO GAIN ALL THAT THE KING HAS LOST UNLESS IT WERE TO GIVE IT HIM AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "while in sober earnest now i would not live thus a twelvemonth to gain all that the king has lost unless it were to give it him again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0015.flac", "answer": "BECAUSE YOU FIND FAULT WITH MY OTHER LETTERS THIS IS LIKE TO BE SHORTER THAN THEY I DID NOT INTEND IT SO THOUGH I CAN ASSURE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "because you find fault with my other letters this is like to be shorter than they i did not intend it so though i can assure you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0011.flac", "answer": "HERE ARE SOME VERSES OF COWLEY'S TELL ME HOW YOU LIKE THEM", "subset": "test_other", "task_type": "understanding", "prediction": "here are some verses of kaulis tell me how you like them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0031.flac", "answer": "NOT TO KNOW WHEN YOU WOULD COME HOME I CAN ASSURE YOU NOR FOR ANY OTHER OCCASION OF MY OWN BUT WITH A COUSIN OF MINE THAT HAD LONG DESIGNED TO MAKE HERSELF SPORT WITH HIM AND DID NOT MISS OF HER AIM", "subset": "test_other", "task_type": "understanding", "prediction": "not to know when you would come home i can assure you not for any other occasion of my own but with a cousin of mine that had long designed to make herself sport with him and did not miss of her aim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0013.flac", "answer": "IF I DROWN BY THE WAY THIS WILL BE MY LAST LETTER AND LIKE A WILL I BEQUEATH ALL MY KINDNESS TO YOU IN IT WITH A CHARGE NEVER TO BESTOW IT ALL UPON ANOTHER MISTRESS LEST MY GHOST RISE AGAIN AND HAUNT YOU", "subset": "test_other", "task_type": "understanding", "prediction": "if i drown by the way this will be my last letter and like a will i bequeath all my kindness to you in it with a charge never to bestow it all upon another mistress lest my ghost rise again and haunt you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0012.flac", "answer": "I TOLD YOU IN MY LAST THAT MY SUFFOLK JOURNEY WAS LAID ASIDE AND THAT INTO KENT HASTENED", "subset": "test_other", "task_type": "understanding", "prediction": "i told you in my last that my suffolk journey was laid aside and that into kent i hastened", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0014.flac", "answer": "INDEED I LIKE HIM EXTREMELY AND HE IS COMMENDED TO ME BY PEOPLE THAT KNOW HIM VERY WELL AND ARE ABLE TO JUDGE FOR A MOST EXCELLENT SERVANT AND FAITHFUL AS POSSIBLE", "subset": "test_other", "task_type": "understanding", "prediction": "indeed i like him extremely and he is commended to me by people that know him very well and are able to judge for a most excellent servant and faithful as possible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0021.flac", "answer": "YOU ARE SATISFIED I HOPE ERE THIS THAT I SCAPED DROWNING", "subset": "test_other", "task_type": "understanding", "prediction": "you are satisfied i hope at this that i escaped drowning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0020.flac", "answer": "WE DARE NOT LET OUR TONGUES LIE MORE ON ONE SIDE OF OUR MOUTHS THAN T'OTHER FOR FEAR OF OVERTURNING IT", "subset": "test_other", "task_type": "understanding", "prediction": "we dare not let our tongues lie more on one side of our mouths than the other for fear of overturning it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0033.flac", "answer": "EVER SINCE THIS ADVENTURE I HAVE HAD SO GREAT A BELIEF IN ALL THINGS OF THIS NATURE THAT I COULD NOT FORBEAR LAYING A PEAS COD WITH NINE PEAS IN'T UNDER MY DOOR YESTERDAY AND WAS INFORMED BY IT THAT MY HUSBAND'S NAME SHOULD BE THOMAS HOW DO YOU LIKE THAT", "subset": "test_other", "task_type": "understanding", "prediction": "ever since this adventure i have had so great a belief in all things of this nature that i could not forbear laying a peascod with nine pease ants under my door yesterday and was informed by it that my husband s name should be thomas how do you like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0007.flac", "answer": "YET IN EARNEST YOUR FATHER WILL NOT FIND MY BROTHER PEYTON WANTING IN CIVILITY THOUGH HE IS NOT A MAN OF MUCH COMPLIMENT UNLESS IT BE IN HIS LETTERS TO ME NOR AN UNREASONABLE PERSON IN ANYTHING SO HE WILL ALLOW HIM OUT OF HIS KINDNESS TO HIS WIFE TO SET A HIGHER VALUE UPON HER SISTER THAN SHE DESERVES", "subset": "test_other", "task_type": "understanding", "prediction": "yet in earnest your father will not find my brother peyton wanting in civility though he is not a man of much compliment unless it be in his letters to me nor an unreasonable person in anything so he will allow him out of his kindness to his wife to set a higher value upon her sister than she deserves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0030.flac", "answer": "YOU MUST GIVE ME LEAVE TO ENTERTAIN YOU THUS WITH DISCOURSES OF THE FAMILY FOR I CAN TELL YOU NOTHING ELSE FROM HENCE", "subset": "test_other", "task_type": "understanding", "prediction": "you must give me leave to entertain you thus with discourses of the family for i can tell you nothing else from hence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0000.flac", "answer": "WOULD IT WOULD LEAVE ME AND THEN I COULD BELIEVE I SHALL NOT ALWAYS HAVE OCCASION FOR IT", "subset": "test_other", "task_type": "understanding", "prediction": "would it would leave me and then i could believe i shall not always have occasion for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0003.flac", "answer": "I WONDER HOW SHE BEHAVED HERSELF WHEN SHE WAS MARRIED", "subset": "test_other", "task_type": "understanding", "prediction": "i wonder how she behaved herself when she was married", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0026.flac", "answer": "WE GO ABROAD ALL DAY AND PLAY ALL NIGHT AND SAY OUR PRAYERS WHEN WE HAVE TIME", "subset": "test_other", "task_type": "understanding", "prediction": "we go abroad all day and play all night and say our prayers when we have time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0032.flac", "answer": "IN MY LIFE I NEVER HEARD SO RIDICULOUS A DISCOURSE AS HE MADE US AND NO OLD WOMAN WHO PASSES FOR A WITCH COULD HAVE BEEN MORE PUZZLED TO SEEK WHAT TO SAY TO REASONABLE PEOPLE THAN HE WAS", "subset": "test_other", "task_type": "understanding", "prediction": "in my life i never heard so ridiculous a discourse as he made us and no old woman who passes for a witch could have been more puzzled to seek what to say to reasonable people than he was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5040/3080-5040-0010.flac", "answer": "BY THE NEXT I SHALL BE GONE INTO KENT AND MY OTHER JOURNEY IS LAID ASIDE WHICH I AM NOT DISPLEASED AT BECAUSE IT WOULD HAVE BROKEN OUR INTERCOURSE VERY MUCH", "subset": "test_other", "task_type": "understanding", "prediction": "by the next i shall be gone into kent n my other journey is laid aside which i am not displeased at because it would have broken our intercourse very much", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0006.flac", "answer": "ALL THE PEOPLE THAT I HAD EVER IN MY LIFE REFUSED WERE BROUGHT AGAIN UPON THE STAGE LIKE RICHARD THE THREE S GHOSTS TO REPROACH ME WITHAL AND ALL THE KINDNESS HIS DISCOVERIES COULD MAKE I HAD FOR YOU WAS LAID TO MY CHARGE", "subset": "test_other", "task_type": "understanding", "prediction": "all the people that i had ever in my life refused were brought again upon the stage like richard the third s ghosts to reproach me withal and all the kindnesses discoveries could make i had for you was laid to my charge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0009.flac", "answer": "MISTER FISH IS THE SQUIRE OF DAMES AND HAS SO MANY MISTRESSES THAT ANYBODY MAY PRETEND A SHARE IN HIM AND BE BELIEVED BUT THOUGH I HAVE THE HONOUR TO BE HIS NEAR NEIGHBOUR TO SPEAK FREELY I CANNOT BRAG MUCH THAT HE MAKES ANY COURT TO ME AND I KNOW NO YOUNG WOMAN IN THE COUNTRY THAT HE DOES NOT VISIT OFTEN", "subset": "test_other", "task_type": "understanding", "prediction": "mr fish is a squire of dames and has so many mistresses that anybody may pretend a share in him and be believed but though i have the honour to be his near neighbour to speak freely i cannot brag much that he makes any court to me and i know no young woman in the country that he does not visit often", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0005.flac", "answer": "IN EARNEST WE HAVE HAD SUCH A SKIRMISH AND UPON SO FOOLISH AN OCCASION AS I CANNOT TELL WHICH IS STRANGEST", "subset": "test_other", "task_type": "understanding", "prediction": "in earnest we have had such a skirmish and upon so foolish an occasion as i cannot tell which is strangest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0001.flac", "answer": "I KNEW YOU COULD NOT CHOOSE BUT LIKE HER BUT YET LET ME TELL YOU YOU HAVE SEEN BUT THE WORST OF HER", "subset": "test_other", "task_type": "understanding", "prediction": "i knew you could not choose but like her but yet let me tell you you have seen but the worst of her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0010.flac", "answer": "I THINK MY YOUNGEST BROTHER COMES DOWN WITH HIM", "subset": "test_other", "task_type": "understanding", "prediction": "i think my youngest brother comes down with him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0022.flac", "answer": "I KNOW NOT HOW MY BROTHER COMES TO BE SO WELL INFORMED AS YOU SAY BUT I AM CERTAIN HE KNOWS THE UTMOST OF THE INJURIES YOU HAVE RECEIVED FROM HER", "subset": "test_other", "task_type": "understanding", "prediction": "i know not how my brother comes to be so well informed as you say but i am certain he knows the utmost of the injuries you have received from her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0018.flac", "answer": "WELL IN EARNEST IF I WERE A PRINCE THAT LADY SHOULD BE MY MISTRESS BUT I CAN GIVE NO RULE TO ANY ONE ELSE AND PERHAPS THOSE THAT ARE IN NO DANGER OF LOSING THEIR HEARTS TO HER MAY BE INFINITELY TAKEN WITH ONE I SHOULD NOT VALUE AT ALL FOR SO SAYS THE JUSTINIAN WISE PROVIDENCE HAS ORDAINED IT THAT BY THEIR DIFFERENT HUMOURS EVERYBODY MIGHT FIND SOMETHING TO PLEASE THEMSELVES WITHAL WITHOUT ENVYING THEIR NEIGHBOURS", "subset": "test_other", "task_type": "understanding", "prediction": "well in earnest if i were a prince that lady should be my mistress but i can give no rule to any one else and perhaps those that are in no danger of losing their hearts to her may be infinitely taken with one i should not value at all for saith the justinian wise providence has ordained it that by their different humours every body might find something to please themselves withal without envying their neighbours", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0008.flac", "answer": "TIS A STRANGE CHANGE AND I AM VERY SORRY FOR IT BUT I'LL SWEAR I KNOW NOT HOW TO HELP IT", "subset": "test_other", "task_type": "understanding", "prediction": "tis a strange change and i am very sorry for it but i will swear i know not how to help it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0002.flac", "answer": "HER CONVERSATION HAS MORE CHARMS THAN CAN BE IN MERE BEAUTY AND HER HUMOUR AND DISPOSITION WOULD MAKE A DEFORMED PERSON APPEAR LOVELY", "subset": "test_other", "task_type": "understanding", "prediction": "her conversation has more charms than can be in mere beauty and a humour and disposition would make a deformed person appear lovely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0011.flac", "answer": "I CAN NO SOONER GIVE YOU SOME LITTLE HINTS WHEREABOUTS THEY LIVE BUT YOU KNOW THEM PRESENTLY AND I MEANT YOU SHOULD BE BEHOLDING TO ME FOR YOUR ACQUAINTANCE", "subset": "test_other", "task_type": "understanding", "prediction": "i can no sooner give you some little hints whereabout they live but you know them presently and i meant you should be beholding to me for your acquaintance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0026.flac", "answer": "HOW KINDLY DO I TAKE THESE CIVILITIES OF YOUR FATHER'S IN EARNEST YOU CANNOT IMAGINE HOW HIS LETTER PLEASED ME", "subset": "test_other", "task_type": "understanding", "prediction": "how kindly do i take the civilities of your fathers in earnest you cannot imagine how his letter pleased me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0007.flac", "answer": "MY BEST QUALITIES IF I HAVE ANY THAT ARE GOOD SERVED BUT FOR AGGRAVATIONS OF MY FAULT AND I WAS ALLOWED TO HAVE WIT AND UNDERSTANDING AND DISCRETION IN OTHER THINGS THAT IT MIGHT APPEAR I HAD NONE IN THIS", "subset": "test_other", "task_type": "understanding", "prediction": "my best qualities if i have any that are good served but for aggravations of my fault and i was allowed to have wit and understanding and discretion in other things that it might appear i had none in this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0000.flac", "answer": "BUT I AM HUGELY PLEASED THAT YOU HAVE SEEN MY LADY", "subset": "test_other", "task_type": "understanding", "prediction": "but i am hugely pleased that you have seen my lady", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0003.flac", "answer": "WHY DID YOU NOT SEND ME THAT NEWS AND A GARLAND", "subset": "test_other", "task_type": "understanding", "prediction": "why did you not send me that news and a garland", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0015.flac", "answer": "I AM HERE MUCH MORE OUT OF PEOPLE'S WAY THAN IN TOWN WHERE MY AUNT AND SUCH AS PRETEND AN INTEREST IN ME AND A POWER OVER ME DO SO PERSECUTE ME WITH THEIR GOOD NATURE AND TAKE IT SO ILL THAT THEY ARE NOT ACCEPTED AS I WOULD LIVE IN A HOLLOW TREE TO AVOID THEM", "subset": "test_other", "task_type": "understanding", "prediction": "i am here much more out of people s way than in town where my aunts and such has pretended interest in me and a power over me do so persecute me with their good nature and take it so ill that they are not accepted as i would live in a hollow tree to avoid them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0004.flac", "answer": "WELL THE BEST ON'T IS I HAVE A SQUIRE NOW THAT IS AS GOOD AS A KNIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "well the best on it is that i have a squire now that is as good as a knight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0019.flac", "answer": "THE MATTER IS NOT GREAT FOR I CONFESS I DO NATURALLY HATE THE NOISE AND TALK OF THE WORLD AND SHOULD BE BEST PLEASED NEVER TO BE KNOWN IN'T UPON ANY OCCASION WHATSOEVER YET SINCE IT CAN NEVER BE WHOLLY AVOIDED ONE MUST SATISFY ONESELF BY DOING NOTHING THAT ONE NEED CARE WHO KNOWS", "subset": "test_other", "task_type": "understanding", "prediction": "the matter is not great for i confess i do naturally hate the noise and talk of the world and should be best pleased never to be known in it upon any occasion whatsoever yet since it can never be wholly avoided one must satisfy one self by doing nothing that one need care who knows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0020.flac", "answer": "IF I HAD A PICTURE THAT WERE FIT FOR YOU YOU SHOULD HAVE IT", "subset": "test_other", "task_type": "understanding", "prediction": "if i had a picture that were fit for you you should have it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0021.flac", "answer": "HOW CAN YOU TALK OF DEFYING FORTUNE NOBODY LIVES WITHOUT IT AND THEREFORE WHY SHOULD YOU IMAGINE YOU COULD", "subset": "test_other", "task_type": "understanding", "prediction": "how can you talk of defying fortune nobody lives without it and therefore why should you imagine you could", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0017.flac", "answer": "IF MARRIAGE AGREES NO BETTER WITH OTHER PEOPLE THAN IT DOES WITH HIM I SHALL PRAY THAT ALL MY FRIENDS MAY SCAPE IT", "subset": "test_other", "task_type": "understanding", "prediction": "if marriage agrees no better with other people than it does with him i shall pray that all my friends may scape it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0025.flac", "answer": "I HAVE BEEN STUDYING HOW TOM CHEEKE MIGHT COME BY HIS INTELLIGENCE AND I VERILY BELIEVE HE HAS IT FROM MY COUSIN PETERS", "subset": "test_other", "task_type": "understanding", "prediction": "i have been studying how tom cheek might come by his intelligence and i very believe he has it from my cousin peters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0023.flac", "answer": "WE HAVE HAD ANOTHER DEBATE BUT MUCH MORE CALMLY", "subset": "test_other", "task_type": "understanding", "prediction": "we have had another debate but much more calmly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0014.flac", "answer": "BUT BESIDES I CAN GIVE YOU OTHERS", "subset": "test_other", "task_type": "understanding", "prediction": "but besides i can give you others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0016.flac", "answer": "YOU WILL THINK HIM ALTERED AND IF IT BE POSSIBLE MORE MELANCHOLY THAN HE WAS", "subset": "test_other", "task_type": "understanding", "prediction": "you will think him altered and if it be possible more melancholy than he was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0024.flac", "answer": "AND BESIDES THERE WAS A TIME WHEN WE OURSELVES WERE INDIFFERENT TO ONE ANOTHER DID I DO SO THEN OR HAVE I LEARNED IT SINCE", "subset": "test_other", "task_type": "understanding", "prediction": "and besides there was a time when we ourselves were indifferent to one another did i do so then or have i learnt it since", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0012.flac", "answer": "BUT IT SEEMS THIS GENTLEMAN IS NOT SO EASY ACCESS BUT YOU MAY ACKNOWLEDGE SOMETHING DUE TO ME IF I INCLINE HIM TO LOOK GRACIOUSLY UPON YOU AND THEREFORE THERE IS NOT MUCH HARM DONE", "subset": "test_other", "task_type": "understanding", "prediction": "but it seems this gentleman is not so easy access but you may acknowledge something due to me if i incline him to look graciously upon you and therefore there is not much harm done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3080/5032/3080-5032-0013.flac", "answer": "I HAVE MISSED FOUR FITS AND HAD BUT FIVE AND HAVE RECOVERED SO MUCH STRENGTH AS MADE ME VENTURE TO MEET YOUR LETTER ON WEDNESDAY A MILE FROM HOME", "subset": "test_other", "task_type": "understanding", "prediction": "i have missed four fits and have had but five and have recovered so much strength as made me venture to meet your letter on wednesday a mile from home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0032.flac", "answer": "NO SIR HE IS NOT HERE", "subset": "test_other", "task_type": "understanding", "prediction": "no sir he is not here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0013.flac", "answer": "WITH ALL MY HEART IF YOU WILL STEP INTO THE GENTLEMEN'S CABIN WHERE THERE'S A LIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "with all my heart if you will step into the gentlemen s cabin where there is a light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0054.flac", "answer": "IT CAME FROM UNDER THE TABLE GASPED WARD LOOK WHAT'S THERE LOOK YOURSELF", "subset": "test_other", "task_type": "understanding", "prediction": "it came from under the table gasped toward look what is there look yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0020.flac", "answer": "IN A SMALL COUNTRY TOWN SEVEN OF THESE MYSTERIOUS PROVIDENCES OCCURRED WITHIN THE CIRCUIT OF A MILE ALL DIRECTLY TRACEABLE TO TOBACCO AND ANY PHYSICIAN ON A FEW MOMENTS REFLECTION CAN MATCH THIS FACT BY HIS OWN OBSERVATION", "subset": "test_other", "task_type": "understanding", "prediction": "in a small country town seven of these mysterious providences occurred within the circuit of a mile all directly traceable to tobacco and any physician on a few moments reflection can match this fact by his own observation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0048.flac", "answer": "THEY KEPT IT UP TILL AFTER MIDNIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "they kept it up till after midnight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0017.flac", "answer": "IS IT STRANGE THEN THAT SMOKERS AND CHEWERS HAVE A THOUSAND AILMENTS", "subset": "test_other", "task_type": "understanding", "prediction": "is it strange then that smokers and chewers have a thousand ailments", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0062.flac", "answer": "ELSIE ANSWERED PRESSING HER HAND AFFECTIONATELY ART WE NOT SISTERS IN CHRIST", "subset": "test_other", "task_type": "understanding", "prediction": "elsie answered pressing her hand affectionately are we not sisters in christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0000.flac", "answer": "OLD MISTER DINSMORE HAD ACCEPTED A PRESSING INVITATION FROM HIS GRANDDAUGHTER AND HER HUSBAND TO JOIN THE PARTY AND WITH THE ADDITION OF SERVANTS IT WAS A LARGE ONE", "subset": "test_other", "task_type": "understanding", "prediction": "old mr dinsmore had accepted a pressing invitation from his granddaughter and her husband to join the party and with the addition of servants it was a large one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0031.flac", "answer": "THE EYES OF THE WHOLE PARTY WERE AT ONCE TURNED IN THAT DIRECTION", "subset": "test_other", "task_type": "understanding", "prediction": "the eyes of the whole party were at once turned in that direction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0012.flac", "answer": "DOUBTLESS THAT IS THE CASE REMARKED MISTER DINSMORE", "subset": "test_other", "task_type": "understanding", "prediction": "doubtless that is the case remarked mr dinsmore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0044.flac", "answer": "I DINKS NO I DINKS I DEACH YOU VON LESSON RETURNED HIS CAPTOR NOT RELAXING HIS GRASP IN THE LEAST", "subset": "test_other", "task_type": "understanding", "prediction": "i dinks no i dinks i did you von messin returned his captor not relaxing his grasp in the least", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0014.flac", "answer": "HE LED THE WAY THE OTHERS ALL FOLLOWING AND TAKING OUT A SLIP OF PAPER READ FROM IT IN A DISTINCT TONE LOUD ENOUGH TO BE HEARD BY THOSE ABOUT HIM WITHOUT DISTURBING THE OTHER PASSENGERS", "subset": "test_other", "task_type": "understanding", "prediction": "he led the way the others all following and taking out a slip of paper read from it in a distinct tone loud enough to be heard by those all about him without disturbing the other passengers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0063.flac", "answer": "YE ARE ALL THE CHILDREN OF GOD BY FAITH IN CHRIST JESUS", "subset": "test_other", "task_type": "understanding", "prediction": "ye are all the children of god by faith in christ jesus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0050.flac", "answer": "AN INTENSE VOICELESS EXCITEMENT POSSESSED THE PLAYERS FOR THE GAME WAS A CLOSE ONE AND THE STAKES WERE VERY HEAVY", "subset": "test_other", "task_type": "understanding", "prediction": "an intense voiceless excitement possessed the players for the game was a close one and the stakes were very heavy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0019.flac", "answer": "NOTICE THE MULTITUDE OF SUDDEN DEATHS AND SEE HOW MANY ARE SMOKERS AND CHEWERS", "subset": "test_other", "task_type": "understanding", "prediction": "notice the multitude of sudden deaths and see how many are smokers and chewers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0065.flac", "answer": "WE FEEL MY HUSBAND AND I THAT WE ARE ONLY THE STEWARDS OF HIS BOUNTY AND THAT BECAUSE HE HAS SAID INASMUCH AS YE HAVE DONE IT UNTO ONE OF THE LEAST OF THESE MY BRETHREN YE HAVE DONE IT UNTO ME IT IS THE GREATEST PRIVILEGE AND DELIGHT TO DO ANYTHING FOR HIS PEOPLE", "subset": "test_other", "task_type": "understanding", "prediction": "we feel my husband and i that we are only the stewards of his bounty and because he has said inasmuch as ye have done it unto one of the least of these my brethren ye have done it unto me it is the greatest privilege and delight to do anything for his people", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0011.flac", "answer": "I DO INDEED THOUGH PROBABLY COMPARATIVELY FEW ARE AWARE THAT TOBACCO IS THE CAUSE OF THEIR AILMENTS", "subset": "test_other", "task_type": "understanding", "prediction": "i do indeed though probably comparatively few are aware that tobacco is the cause of their ailments", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0049.flac", "answer": "THEN MISTER LILBURN WAKING FROM HIS FIRST SLEEP IN A STATEROOM NEAR BY THOUGHT HE WOULD BREAK IT UP ONCE MORE", "subset": "test_other", "task_type": "understanding", "prediction": "then mr lilburn waking from his first sleep in a stateroom near by thought he would break it up once more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0021.flac", "answer": "AND THEN SUCH POWERFUL ACIDS PRODUCE INTENSE IRRITATION AND THIRST THIRST WHICH WATER DOES NOT QUENCH", "subset": "test_other", "task_type": "understanding", "prediction": "and then such powerful acids produce intense irritation and thirst thirst which water does not quench", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0010.flac", "answer": "SUPPOSE YOU AND HE SHAKE HANDS FRANK", "subset": "test_other", "task_type": "understanding", "prediction": "suppose you and he shake hands frank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0022.flac", "answer": "HENCE A RESORT TO CIDER AND BEER", "subset": "test_other", "task_type": "understanding", "prediction": "hence a resort to cider and beer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0036.flac", "answer": "WHAT DOES IT MEAN CRIED ONE", "subset": "test_other", "task_type": "understanding", "prediction": "what does it mean cried one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0064.flac", "answer": "YE ARE ALL ONE IN CHRIST JESUS", "subset": "test_other", "task_type": "understanding", "prediction": "ye are all one in christ jesus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0059.flac", "answer": "TO ELSIE'S OBSERVANT EYES IT PRESENTLY BECAME EVIDENT THAT THE DALYS WERE IN VERY STRAITENED CIRCUMSTANCES", "subset": "test_other", "task_type": "understanding", "prediction": "to elsie s observant eyes it presently became evident that the dailys were in very straitened circumstances", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0051.flac", "answer": "THEY BENT EAGERLY OVER THE BOARD EACH WATCHING WITH FEVERISH ANXIETY HIS COMPANION'S MOVEMENTS EACH CASTING NOW AND AGAIN A GLOATING EYE UPON THE HEAP OF GOLD AND GREENBACKS THAT LAY BETWEEN THEM AND AT TIMES HALF STRETCHING OUT HIS HAND TO CLUTCH IT", "subset": "test_other", "task_type": "understanding", "prediction": "they bent eagerly over the board each watching with feverish anxiety his companion's movements each casting now and again a gloating eye upon the heap of gold and greenbacks that lay between them and at times half stretching out his hand to clutch it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0024.flac", "answer": "FOR YE ARE BOUGHT WITH A PRICE THEREFORE GLORIFY GOD IN YOUR BODY AND IN YOUR SPIRIT WHICH ARE GOD'S", "subset": "test_other", "task_type": "understanding", "prediction": "for ye are bought with a price therefore glorify god in your body and in your spirit which are gods", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0016.flac", "answer": "THE HALF DOZEN CIGARS WHICH MOST SMOKERS USE A DAY CONTAIN SIX OR SEVEN GRAINS ENOUGH IF CONCENTRATED AND ABSORBED TO KILL THREE MEN AND A POUND OF TOBACCO ACCORDING TO ITS QUALITY CONTAINS FROM ONE QUARTER TO ONE AND A QUARTER OUNCES", "subset": "test_other", "task_type": "understanding", "prediction": "the half dozen cigars which most smokers use a day contain six or seven grains enough if concentrated and absorbed to kill three men and a pound of tobacco according to its quality contains from one quarter to one and a quarter ounces", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0037.flac", "answer": "A VENTRILOQUIST ABOARD OF COURSE RETURNED ANOTHER LET'S FOLLOW AND SEE THE FUN", "subset": "test_other", "task_type": "understanding", "prediction": "a ventriloquist aboard of course returned another let us follow and see the fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0030.flac", "answer": "THEY ARE GAMBLING YONDER AND I'M AFRAID THAT YOUNG FELLOW IS BEING BADLY FLEECED BY THAT MIDDLE AGED MAN OPPOSITE", "subset": "test_other", "task_type": "understanding", "prediction": "they are gambling yonder and i am afraid that young fellow is being badly fleeced by the middle aged man opposite", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0053.flac", "answer": "BUT ALL WAS SILENT AND AFTER A MOMENT OF ANXIOUS WAITING THEY SAT DOWN TO THEIR GAME AGAIN TRYING TO CONCEAL AND SHAKE OFF THEIR FEARS WITH A FORCED UNNATURAL LAUGH", "subset": "test_other", "task_type": "understanding", "prediction": "but all was silent and after a moment of anxious waiting they sat down to their game again trying to conceal and shake off their fears with a forced unnatural laugh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0001.flac", "answer": "AS THEY WERE IN NO HASTE AND THE CONFINEMENT OF A RAILROAD CAR WOULD BE VERY IRKSOME TO THE YOUNGER CHILDREN IT HAD BEEN DECIDED TO MAKE THE JOURNEY BY WATER", "subset": "test_other", "task_type": "understanding", "prediction": "as they were in no haste and the confinement of a railroad car would be very irksome to the younger children it had been decided to make the journey by water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0009.flac", "answer": "HE CERTAINLY LOOKS LIKE A VERY NICE LITTLE BOY", "subset": "test_other", "task_type": "understanding", "prediction": "he certainly looks like a very nice little boy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0029.flac", "answer": "THERE WAS A PAUSE BROKEN BY YOUNG HORACE WHO HAD BEEN WATCHING A GROUP OF MEN GATHERED ABOUT A TABLE AT THE FURTHER END OF THE ROOM", "subset": "test_other", "task_type": "understanding", "prediction": "there was a pause broken by young horace who had been watching a group of men gathered about a table at the further end of the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0027.flac", "answer": "IT MUST REQUIRE A GOOD DEAL OF RESOLUTION FOR ONE WHO HAS BECOME FOND OF THE INDULGENCE TO GIVE IT UP REMARKED MISTER DALY", "subset": "test_other", "task_type": "understanding", "prediction": "it must require a good deal of resolution for one who has become fond of the indulgence to give it up remarked mr daly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0005.flac", "answer": "BESIDE OURSELVES ADDED COUSIN RONALD LAUGHING", "subset": "test_other", "task_type": "understanding", "prediction": "besides ourselves added cousin ronald laughing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0034.flac", "answer": "NOW THE VOICE CAME FROM THE SKYLIGHT OVERHEAD APPARENTLY AND WITH A FIERCE IMPRECATION THE IRATE GAMESTER RUSHED UPON DECK AND RAN HITHER AND THITHER IN SEARCH OF HIS TORMENTOR", "subset": "test_other", "task_type": "understanding", "prediction": "now the voice came from the skylight overhead apparently and with a fierce imprecation the irate gamester rushed upon deck and ran hither and thither in search of his tormentor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0003.flac", "answer": "AT LENGTH THE LAND HAD QUITE DISAPPEARED NOTHING COULD BE SEEN BUT THE SKY OVERHEAD AND A VAST EXPANSE OF WATER ALL AROUND AND THE PASSENGERS FOUND LEISURE TO TURN THEIR ATTENTION UPON EACH OTHER", "subset": "test_other", "task_type": "understanding", "prediction": "at length the land had quite disappeared nothing could be seen but the sky overhead and a vast expanse of water all round and the passengers found leisure to turn their attention upon each other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0055.flac", "answer": "WHAT CAN IT HAVE BEEN THEY ASKED EACH OTHER", "subset": "test_other", "task_type": "understanding", "prediction": "what can it a been they asked each other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0002.flac", "answer": "THERE WERE NO SAD LEAVE TAKINGS TO MAR THEIR PLEASURE THE CHILDREN WERE IN WILD SPIRITS AND ALL SEEMED CHEERFUL AND HAPPY AS THEY SAT OR STOOD UPON THE DECK WATCHING THE RECEDING SHORE AS THE VESSEL STEAMED OUT OF THE HARBOR", "subset": "test_other", "task_type": "understanding", "prediction": "there were no sad leave takings to mar their pleasure the children were in wild spirits and all seemed cheerful and happy as they sat or stood upon the deck watching the receding shore as the vessel steamed out of the harbor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0035.flac", "answer": "HIS VICTIM WHO HAD BEEN LOOKING ON DURING THE LITTLE SCENE AND LISTENING TO THE MYSTERIOUS VOICE IN SILENT WIDE EYED WONDER AND FEAR NOW ROSE HASTILY HIS FACE DEATHLY PALE WITH TREMBLING HANDS GATHERED UP THE MONEY HE HAD STAKED AND HURRYING INTO HIS STATE ROOM LOCKED HIMSELF IN", "subset": "test_other", "task_type": "understanding", "prediction": "his victim who had been looking on during the little scene and listening to the mysterious voice in silent wide eyed wonder and fear now rose hastily his face deathly pale with trembling hands gathered up the money he had staked and hurrying to his stateroom locked himself in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0004.flac", "answer": "THERE ARE SOME NICE LOOKING PEOPLE ON BOARD REMARKED MISTER TRAVILLA IN AN UNDERTONE TO HIS WIFE", "subset": "test_other", "task_type": "understanding", "prediction": "there are some nice looking people on board remarked mr travilla in an undertone to his wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0007.flac", "answer": "AND WHAT A DEAR LITTLE FELLOW HE IS JUST ABOUT THE AGE OF OUR HAROLD I SHOULD JUDGE", "subset": "test_other", "task_type": "understanding", "prediction": "and what a dear little fellow he is just about the age of our harold i should judge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0026.flac", "answer": "AND AGAIN I BESEECH YOU THEREFORE BRETHREN BY THE MERCIES OF GOD THAT YE PRESENT YOUR BODIES A LIVING SACRIFICE HOLY ACCEPTABLE UNTO GOD WHICH IS YOUR REASONABLE SERVICE", "subset": "test_other", "task_type": "understanding", "prediction": "and again i beseech you therefore brethren by the mercies of god that ye present your bodies a living sacrifice holy acceptable unto god which is your reasonable service", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0008.flac", "answer": "DO YOU SON WAS THE SMILING REJOINDER", "subset": "test_other", "task_type": "understanding", "prediction": "do you son was the smiling rejoinder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0018.flac", "answer": "THAT THE FRENCH POLYTECHNIC INSTITUTE HAD TO PROHIBIT ITS USE ON ACCOUNT OF ITS EFFECTS ON THE MIND", "subset": "test_other", "task_type": "understanding", "prediction": "that the french polytechnic institute had to prohibit its use on account of its effects upon the mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0046.flac", "answer": "MISTER LILBURN AND MISTER DALY EACH AT A DIFFERENT TIME SOUGHT OUT THE YOUNG MAN WARD'S INTENDED VICTIM AND TRIED TO INFLUENCE HIM FOR GOOD", "subset": "test_other", "task_type": "understanding", "prediction": "mr lilburn and mr daly each at a different time sought out the young man words intended victim and tried to influence him for good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0058.flac", "answer": "THE CAPTAIN COMING IN SHORTLY AFTER THE SUDDEN FLIGHT OF THE GAMBLERS TOOK CHARGE OF THE MONEY AND THE NEXT DAY RESTORED IT TO THE OWNERS", "subset": "test_other", "task_type": "understanding", "prediction": "the captain coming in shortly after the sudden flight of the gamblers took charge of the money and the next day restored it to the owners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0056.flac", "answer": "OH NONSENSE WHAT FOOLS WE ARE", "subset": "test_other", "task_type": "understanding", "prediction": "oh nonsense what fools we are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0033.flac", "answer": "AND THE DOOR WAS SLAMMED VIOLENTLY TO", "subset": "test_other", "task_type": "understanding", "prediction": "and the door was slammed violently too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0060.flac", "answer": "OH HOW KIND HOW VERY KIND MISSUS DALY SAID WITH TEARS OF JOY AND GRATITUDE WE HAVE HARDLY KNOWN HOW WE SHOULD MEET THE MOST NECESSARY EXPENSES OF THIS TRIP BUT HAVE BEEN TRYING TO CAST OUR CARE UPON THE LORD ASKING HIM TO PROVIDE", "subset": "test_other", "task_type": "understanding", "prediction": "oh how kind how very kind mrs daly said with tears of joy and gratitude we have hardly known how we should meet the most necessary expenses of this trip but have been trying to cast our care upon the lord asking him to provide", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0052.flac", "answer": "A DEEP GROAN STARTLED THEM AND THEY SPRANG TO THEIR FEET PALE AND TREMBLING WITH SUDDEN TERROR EACH HOLDING HIS BREATH AND STRAINING HIS EAR TO CATCH A REPETITION OF THE DREAD SOUND", "subset": "test_other", "task_type": "understanding", "prediction": "a deep groan startled them and they sprang to their feet pale and trembling with sudden terror each holding his breath and straining his ear to catch a repetition of the dread sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0041.flac", "answer": "THEY HEARD HIM IN SILENCE WITH A COOL PHLEGMATIC INDIFFERENCE MOST EXASPERATING TO ONE IN HIS PRESENT MOOD", "subset": "test_other", "task_type": "understanding", "prediction": "they heard him in silence with a cool phlegmatic indifference most exasperating to one in his present mood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0039.flac", "answer": "THAT FELLOW NICK WARD IS A NOTED BLACKLEG AND RUFFIAN HAD HIS NOSE BROKEN IN A FIGHT AND IS SENSITIVE ON THE SUBJECT WAS CHEATING OF COURSE", "subset": "test_other", "task_type": "understanding", "prediction": "that fellow nick ward is a noted blackleg and ruffian had his nose broken in a fight and is sensitive on the subject was cheating of course", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0040.flac", "answer": "WHO ASKED THE MATE I'VE SEEN NONE UP HERE THOUGH THERE ARE SOME IN THE STEERAGE", "subset": "test_other", "task_type": "understanding", "prediction": "who asked the mate i have seen none up here though there are some in the steerage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0023.flac", "answer": "NO SIR WHAT KNOW YE NOT THAT YOUR BODY IS THE TEMPLE OF THE HOLY GHOST WHICH IS IN YOU WHICH YE HAVE OF GOD AND YE ARE NOT YOUR OWN", "subset": "test_other", "task_type": "understanding", "prediction": "no sir what know ye not that your body is the temple of the holy ghost which is in you which ye have of god and ye are not your own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0045.flac", "answer": "THE GERMAN RELEASED HIS PRISONER AND THE LATTER SLUNK AWAY WITH MUTTERED THREATS AND IMPRECATIONS UPON THE HEAD OF HIS TORMENTOR", "subset": "test_other", "task_type": "understanding", "prediction": "the german released his prisoner and the latter slunk away with muttered threats and imprecations upon the head of his tormentor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0038.flac", "answer": "I WONDER WHICH OF US IT IS REMARKED THE FIRST LOOKING HARD AT OUR PARTY I DON'T KNOW BUT COME ON", "subset": "test_other", "task_type": "understanding", "prediction": "i wonder which of us it is remarked the first looking hard at our party i don t know but come on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0025.flac", "answer": "WE CERTAINLY HAVE NO RIGHT TO INJURE OUR BODIES EITHER BY NEGLECT OR SELF INDULGENCE", "subset": "test_other", "task_type": "understanding", "prediction": "we certainly have no right to injure our bodies either by neglect or self indulgence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0028.flac", "answer": "NO DOUBT NO DOUBT RETURNED MISTER LILBURN BUT IF THY RIGHT EYE OFFEND THEE PLUCK IT OUT AND CAST IT FROM THEE FOR IT IS PROFITABLE FOR THEE THAT ONE OF THY MEMBERS SHOULD PERISH AND NOT THAT THY WHOLE BODY SHOULD BE CAST INTO HELL", "subset": "test_other", "task_type": "understanding", "prediction": "no doubt no doubt returned mr lilburne but if thy right eye offend thee pluck it out and cast it from thee for it is profitable for thee that one of thy members should perish and not that thy whole body should be cast into hell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0042.flac", "answer": "A MAN OF GIANT SIZE AND HERCULEAN STRENGTH HAD LAID ASIDE HIS PIPE AND SLOWLY RISING TO HIS FEET SEIZED THE SCOUNDREL IN HIS POWERFUL GRASP", "subset": "test_other", "task_type": "understanding", "prediction": "a man of giant size and herculean strength had laid aside his pipe and slowly rising to his feet seized the scoundrel in his powerful grasp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0006.flac", "answer": "YES SHE ANSWERED THAT LITTLE GROUP YONDER A YOUNG MINISTER AND HIS WIFE AND CHILD I SUPPOSE", "subset": "test_other", "task_type": "understanding", "prediction": "yes she answered that little group yonder a young minister and his wife and child i suppose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0043.flac", "answer": "LET ME GO YELLED WARD MAKING A DESPERATE EFFORT TO FREE HIS ARMS", "subset": "test_other", "task_type": "understanding", "prediction": "let me go yelled ward making a desperate effort to free his arms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0047.flac", "answer": "YET THERE WAS GAMBLING AGAIN THE SECOND NIGHT BETWEEN WARD AND SEVERAL OTHERS OF HIS PROFESSION", "subset": "test_other", "task_type": "understanding", "prediction": "yet there was gambling again the second night between ward and several others of his profession", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0057.flac", "answer": "IT WAS THE LAST GAME OF CARDS FOR THAT TRIP", "subset": "test_other", "task_type": "understanding", "prediction": "it was the last game of cards for that trip", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0061.flac", "answer": "AND HOW WONDERFULLY HE HAS ANSWERED OUR PETITIONS", "subset": "test_other", "task_type": "understanding", "prediction": "and how wonderfully he has answered our petitions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8280/266249/8280-266249-0015.flac", "answer": "ONE DROP OF NICOTINE EXTRACT OF TOBACCO PLACED ON THE TONGUE OF A DOG WILL KILL HIM IN A MINUTE THE HUNDREDTH PART OF A GRAIN PICKED UNDER THE SKIN OF A MAN'S ARM WILL PRODUCE NAUSEA AND FAINTING", "subset": "test_other", "task_type": "understanding", "prediction": "one drop of nicotine extracted tobacco placed on the tongue of a dog will kill him in a minute the hundredth part of a grain pricked under the skin of a man s arm will produce nausea and fainting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0020.flac", "answer": "THE CONSTITUENT ASSEMBLY WILL NOT DARE TO BREAK WITH THE WILL OF THE PEOPLE", "subset": "test_other", "task_type": "understanding", "prediction": "the constituent assembly will not dare to break with the will of the people", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0012.flac", "answer": "WHEREUPON THE OLD EXECUTIVE COMMITTEE LEFT THE HALL", "subset": "test_other", "task_type": "understanding", "prediction": "whereupon the old executive committee left the hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2840, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0001.flac", "answer": "THE COLDS AND RHEUMATISM OF THE RAINY MONTHS VANISHED", "subset": "test_other", "task_type": "understanding", "prediction": "the colds and rheumatism of the rainy months vanished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2841, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0013.flac", "answer": "DOWN WITH HIM THEY SHRIEKED", "subset": "test_other", "task_type": "understanding", "prediction": "down with him they shrieked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2842, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0027.flac", "answer": "BUT THE PRESENT MOVEMENT IS INTERNATIONAL AND THAT IS WHY IT IS INVINCIBLE", "subset": "test_other", "task_type": "understanding", "prediction": "but the present movement is international and that is why it is invincible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2843, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0029.flac", "answer": "A NEW HUMANITY WILL BE BORN OF THIS WAR", "subset": "test_other", "task_type": "understanding", "prediction": "a new humanity will be born of this war", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2844, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0017.flac", "answer": "BY DECLARING THE ASSEMBLY EXTRAORDINARY CONFERENCE IT HAD BEEN PLANNED TO BLOCK THE REELECTION OF THE EXECUTIVE COMMITTEE", "subset": "test_other", "task_type": "understanding", "prediction": "by declaring the assembly extraordinary conference it had been planned to block the reelection of the executive committee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2845, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0021.flac", "answer": "FOLLOWED HIM LENIN LISTENED TO NOW WITH ABSORBING INTENSITY", "subset": "test_other", "task_type": "understanding", "prediction": "followed him lenin listened to now with absorbing intensity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2846, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0028.flac", "answer": "THE WILL OF MILLIONS OF WORKERS IS NOW CONCENTRATED IN THIS HALL", "subset": "test_other", "task_type": "understanding", "prediction": "the wheel of millions of workers is now concentrated in the hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2847, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0010.flac", "answer": "THESE MEN ESPECIALLY WELCOMED THE CALL TO A CONGRESS OF PEASANTS", "subset": "test_other", "task_type": "understanding", "prediction": "this man has specially welcomed the call to a congress of peasants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2848, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0007.flac", "answer": "YOU CALL YOURSELVES THE PEOPLE OF RUSSIA BUT YOU'RE NOT THE PEOPLE OF RUSSIA", "subset": "test_other", "task_type": "understanding", "prediction": "you call yourselves the people of russia but you are not the people of russia", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2849, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0025.flac", "answer": "HE SPOKE TO THE RUMP CONVENTION", "subset": "test_other", "task_type": "understanding", "prediction": "he spoke to the rum convention", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2850, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0000.flac", "answer": "EVEN THE SUN CAME OUT PALE AND WATERY AT NOON", "subset": "test_other", "task_type": "understanding", "prediction": "even the sun came out pale and watery at noon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2851, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0003.flac", "answer": "WELL DIDN'T THEY SHOOT US ONE MAN EXHIBITED HIS ARM IN A SLING", "subset": "test_other", "task_type": "understanding", "prediction": "well didn t they shoot us one man exhibited his arm in a sling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2852, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0030.flac", "answer": "I GREET YOU WITH THE CHRISTENING OF A NEW RUSSIAN LIFE AND FREEDOM", "subset": "test_other", "task_type": "understanding", "prediction": "i greet you with the christianizing of a new russian life and freedom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2853, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0004.flac", "answer": "HAVEN'T I GOT SOMETHING TO REMEMBER THEM BY THE DEVILS", "subset": "test_other", "task_type": "understanding", "prediction": "havent i got something to remember them by the devils", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2854, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0009.flac", "answer": "WE KNOW WHAT THE PEASANTS WILL SAY AREN'T THEY WORKINGMEN LIKE OURSELVES", "subset": "test_other", "task_type": "understanding", "prediction": "we know what the peasants will say arent they working men like ourselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2855, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0005.flac", "answer": "WHO ARE YOU TO DESTROY THE LEGAL GOVERNMENT WHO IS LENIN A GERMAN", "subset": "test_other", "task_type": "understanding", "prediction": "who are you to destroy the legal government who is lenin a german", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2856, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0002.flac", "answer": "ASKED A WORKER LAST SUNDAY YOU DID IT WHEN THE YUNKERS", "subset": "test_other", "task_type": "understanding", "prediction": "asked a worker last sunday you did it when the young girls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2857, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0024.flac", "answer": "HE KNEW THAT AN AGREEMENT WITH THE BOLSHEVIKI WAS BEING DISCUSSED BUT HE DID NOT KNOW THAT IT HAD BEEN CONCLUDED", "subset": "test_other", "task_type": "understanding", "prediction": "he knew that an agreement with the bolsheviki was being discussed but he did not know that it had been concluded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2858, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0019.flac", "answer": "ON THE TWENTY SEVENTH OCCURRED THE DEBATE ON THE LAND QUESTION WHICH REVEALED THE DIFFERENCES BETWEEN THE AGRARIAN PROGRAMME OF THE BOLSHEVIKI AND THE LEFT SOCIALIST REVOLUTIONARIES", "subset": "test_other", "task_type": "understanding", "prediction": "on the twenty seventh occurred the debate on the land question which revealed the differences between the agrarian programme of the bolsheviki and the left socialist revolutionaries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2859, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0022.flac", "answer": "THE FIRST STAGE WAS THE CRUSHING OF AUTOCRACY AND THE CRUSHING OF THE POWER OF THE INDUSTRIAL CAPITALISTS AND LAND OWNERS WHOSE INTERESTS ARE CLOSELY RELATED", "subset": "test_other", "task_type": "understanding", "prediction": "the first stage was the crushing of autocracy and the crushing of the power of the industrial capitalist and the landowners whose interests are closely related", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2860, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0016.flac", "answer": "MEANWHILE THE QUESTION OF THE STATUS OF THE EXECUTIVE COMMITTEE WAS AGITATING ALL MINDS", "subset": "test_other", "task_type": "understanding", "prediction": "meanwhile the question of the status of the executive committee was agitating all minds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2861, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0011.flac", "answer": "THESE LAST WERE THE YOUNG GENERATION WHO HAD BEEN SERVING IN THE ARMY", "subset": "test_other", "task_type": "understanding", "prediction": "this last were the young generation who had been serving in the army", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2862, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0014.flac", "answer": "FEARFUL TUMULT CRIES DOWN WITH THE BOLSHEVIKI", "subset": "test_other", "task_type": "understanding", "prediction": "fearful tumult cries down with the bolsheviki", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2863, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0026.flac", "answer": "THE VILLAGES WILL SAVE US IN THE END", "subset": "test_other", "task_type": "understanding", "prediction": "the villages will save us in the end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2864, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0018.flac", "answer": "BUT THIS WORKED BOTH WAYS THE LEFT SOCIALIST REVOLUTIONISTS DECIDED THAT IF THE CONGRESS HAD NO POWER OVER THE EXECUTIVE COMMITTEE THEN THE EXECUTIVE COMMITTEE HAD NO POWER OVER THE CONGRESS", "subset": "test_other", "task_type": "understanding", "prediction": "but this worked both ways the left socialist revolutionist decided that if the congress had no power over the executive committee then the executive committee had no power over the congress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2865, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0006.flac", "answer": "WHO ARE YOU A COUNTER REVOLUTIONIST A PROVOCATOR THEY BELLOWED AT HIM", "subset": "test_other", "task_type": "understanding", "prediction": "who are you a counter revolutionist a provocateur they belabored at him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2866, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0023.flac", "answer": "THE DUMAS AND ZEMSTVOS WERE DROPPED", "subset": "test_other", "task_type": "understanding", "prediction": "the dumas and zamstovs were dropped", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2867, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0008.flac", "answer": "THE PEASANTS ARE THE PEOPLE OF RUSSIA WAIT UNTIL THE PEASANTS", "subset": "test_other", "task_type": "understanding", "prediction": "the peasants are the people of russia wait until the peasants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2868, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6938/70848/6938-70848-0015.flac", "answer": "UPON MY RETURN I VISITED SMOLNY NO SUCH ACCUSATION WAS MADE AGAINST ME THERE AFTER A BRIEF CONVERSATION I LEFT AND THAT'S ALL LET ANY ONE PRESENT MAKE SUCH AN ACCUSATION", "subset": "test_other", "task_type": "understanding", "prediction": "upon my return i visited smolny no such accusation was made against me there after a brief conversation i left and that is all let anyone present make such an accusation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2869, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0013.flac", "answer": "FINALLY GOT OUR ORDERS FOR YOU IT'S MERCURY", "subset": "test_other", "task_type": "understanding", "prediction": "finally got our orders for you its mercury", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2870, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0002.flac", "answer": "ONLY GORDON AND SHEILA WERE LEFT", "subset": "test_other", "task_type": "understanding", "prediction": "only gordon and sheila were left", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2871, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0003.flac", "answer": "CREDIT HAD BEEN ESTABLISHED AGAIN AND THE BUSINESSES WERE OPEN", "subset": "test_other", "task_type": "understanding", "prediction": "credit had been established again and the businesses were open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2872, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0008.flac", "answer": "HE REACHED AUTOMATICALLY FOR THE GLASS OF ETHER NEEDLED BEER", "subset": "test_other", "task_type": "understanding", "prediction": "he reached automatically for the glass of ether needled beer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2873, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0022.flac", "answer": "HE GRABBED GORDON'S HAND AND WADDLED DOWN THE LANDING PLANK IZZY SHOOK HIS HEAD", "subset": "test_other", "task_type": "understanding", "prediction": "he grabbed gordon s hand and waddled down the landing plank izzie shook his head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2874, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0020.flac", "answer": "DID YOU THINK WE'D LET YOU GO WITHOUT SEEING YOU OFF COBBER HE ASKED", "subset": "test_other", "task_type": "understanding", "prediction": "did you think wed let you go without seeing you off cobb he asked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2875, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0012.flac", "answer": "THERE WAS A GRIN ON THE OTHER'S FACE", "subset": "test_other", "task_type": "understanding", "prediction": "there was a grin on the other s face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2876, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0017.flac", "answer": "THERE'S A ROCKET WAITING TO TRANSSHIP YOU TO THE MOON ON THE WAY TO MERCURY RIGHT NOW GORDON SIGHED", "subset": "test_other", "task_type": "understanding", "prediction": "there is a rocket waiting to tranship you to the moon on the way to mercury right now gordon sighed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2877, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0019.flac", "answer": "BUT HIS OLD EYES WERE GLINTING", "subset": "test_other", "task_type": "understanding", "prediction": "but his old eyes were glinting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2878, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0014.flac", "answer": "WE SENT TWENTY OTHERS THE SAME WAY AND THEY FAILED", "subset": "test_other", "task_type": "understanding", "prediction": "we sent twenty others the same way and they failed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2879, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0000.flac", "answer": "THERE WAS A MAN COMING FROM EARTH ON A SECOND SHIP WHO WOULD SEE HIM", "subset": "test_other", "task_type": "understanding", "prediction": "there was a man coming from earth on a second ship who would see him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2880, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0004.flac", "answer": "GORDON CAME TO A ROW OF TEMPORARY BUBBLES INDIVIDUAL DWELLINGS BUILT LIKE THE DOME BUT OPAQUE FOR PRIVACY", "subset": "test_other", "task_type": "understanding", "prediction": "gordon came to a row of temporary bubbles individual dwellings built like the dome but opaque for privacy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2881, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0010.flac", "answer": "THAT'S MARS GORDON ECHOED THE OTHER'S COMMENT WHY DON'T YOU PULL OFF THE PLANET FATS YOU COULD GO BACK TO EARTH I'D GUESS THE OTHER NODDED", "subset": "test_other", "task_type": "understanding", "prediction": "that s mars gordon echoed the other s comment why don't you pull off the planet fats you could go back to earth i d guess the other nodded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2882, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0011.flac", "answer": "GUESS A MAN GETS USED TO ANYTHING HELL MAYBE I CAN HIRE SOME BUMS TO SIT AROUND AND WHOOP IT UP WHEN THE SHIPS COME IN AND BILL THIS AS A REAL OLD MARTIAN DEN OF SIN", "subset": "test_other", "task_type": "understanding", "prediction": "guess a man gets used to anything hell maybe i can hire some bums to sit around and whoop it up when the ships come in and bill this as a real old martian den of sin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2883, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0007.flac", "answer": "FATS PLACE WAS STILL OPEN THOUGH THE CROOKED TABLES HAD BEEN REMOVED GORDON DROPPED TO A STOOL SLIPPING OFF HIS HELMET", "subset": "test_other", "task_type": "understanding", "prediction": "fats place was still open though the crooked tables had been removed gordon dropped to a stool slipping off his helmet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2884, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0021.flac", "answer": "I I OH DRAT IT I'M GETTING OLD IZZY YOU TELL HIM", "subset": "test_other", "task_type": "understanding", "prediction": "aye aye oh drat it i am getting old is he you tell him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2885, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0018.flac", "answer": "AND I'VE PAID HER THE PAY WE OWE YOU FROM THE TIME YOU BEGAN USING YOUR BADGE SHE'S OUT SHOPPING", "subset": "test_other", "task_type": "understanding", "prediction": "and i paid her the pay we owe you from the time you began using your badge she is out shopping", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2886, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0005.flac", "answer": "THEY HAD BEEN LUCKY", "subset": "test_other", "task_type": "understanding", "prediction": "they had been lucky", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2887, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0015.flac", "answer": "LET'S SAY YOU'VE SHIFTED SOME OF THE MISERY AROUND A BIT AND GIVEN THEM A CHANCE TO DO BETTER", "subset": "test_other", "task_type": "understanding", "prediction": "lets say youve shifted some of the misery around a bit and given them a chance to do better", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2888, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0016.flac", "answer": "YOU CAN'T STAY HERE", "subset": "test_other", "task_type": "understanding", "prediction": "you cant stay here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2889, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0009.flac", "answer": "THOUGHT YOU'D BE IN THE CHIPS", "subset": "test_other", "task_type": "understanding", "prediction": "thought you d be in the chips", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2890, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0001.flac", "answer": "THE LITTLE PUBLISHER WAS BACK AT THE CRUSADER AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "the little publisher was back at the crusader again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2891, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117029/8131-117029-0006.flac", "answer": "SCHULBERG'S VOLUNTEERS WERE OFFICIAL NOW", "subset": "test_other", "task_type": "understanding", "prediction": "schulberg s volunteers were official now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2892, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0011.flac", "answer": "JENKINS THE OTHER COP HAD BEEN HOLDING THE WALLET", "subset": "test_other", "task_type": "understanding", "prediction": "jenkins the other cop had been holding the wallet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2893, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0012.flac", "answer": "MUST OF BEEN MAKING A BIG CONTACT IN SOMETHING FIFTY FIFTY", "subset": "test_other", "task_type": "understanding", "prediction": "must have been making a big contact in something fifty fifty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2894, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0022.flac", "answer": "GORDON HAD HEARD OF THE FRIENDLY INTEREST CHARGED ON THE SIDE HERE BUT HE SHOOK HIS HEAD WRONG IZZY", "subset": "test_other", "task_type": "understanding", "prediction": "gordon had heard of the friendly interest charged on the side here but he shook his head wrong asie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2895, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0030.flac", "answer": "AND IF ANY OF THE OTHER COPS HAD PRIVATE RACKETS OF THEIR OWN IZZY WAS UNDOUBTEDLY THE MAN TO FIND IT OUT AND USE THE INFORMATION WITH A BEAT SUCH AS THAT EVEN GOING HALVES AND WITH ALL THE GRAFT TO THE UPPER BRACKETS HE'D STILL BE ABLE TO MAKE HIS PILE IN A MATTER OF MONTHS", "subset": "test_other", "task_type": "understanding", "prediction": "and if any of the other cops had private rackets of their own izzy was undoubtedly the man to find it out and use the information with a beat such as that even going halves and with all the graft at the upper brackets he would still be able to make his pile in a matter of months", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2896, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0016.flac", "answer": "LIKE THIS SOCIAL CALL GORDON ASKED HIM", "subset": "test_other", "task_type": "understanding", "prediction": "like this social call gordon asked him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2897, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0029.flac", "answer": "THE LITTLE GUY KNEW MARS AS FEW OTHERS DID APPARENTLY FROM ALL SIDES", "subset": "test_other", "task_type": "understanding", "prediction": "the little guy knew mars as few others did apparently from all sides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2898, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0008.flac", "answer": "ONE LOOK WAS ENOUGH THE WORK PAPERS HAD THE TELLTALE OVER THICKENING OF THE SIGNATURE THAT HAD SHOWED UP ON OTHER PAPERS OBVIOUSLY FORGERIES", "subset": "test_other", "task_type": "understanding", "prediction": "one look was enough the work papers had the telltale over thickening of the signature they had showed up on other papers obviously forgeries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2899, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0031.flac", "answer": "THE CAPTAIN LOOKED COMPLETELY BEATEN AS HE CAME INTO THE ROOM AND DROPPED ONTO THE BENCH", "subset": "test_other", "task_type": "understanding", "prediction": "the captain looked completely beaten as he came into the room and dropped onto the bench", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2900, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0019.flac", "answer": "ELEVEN HUNDRED FIFTY CREDITS", "subset": "test_other", "task_type": "understanding", "prediction": "eleven hundred fifty credits", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2901, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0015.flac", "answer": "WHATEVER COMES TO HAND GOV'NOR", "subset": "test_other", "task_type": "understanding", "prediction": "whatever comes to hand guvner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2902, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0005.flac", "answer": "YOU CAN'T DO IT TO ME", "subset": "test_other", "task_type": "understanding", "prediction": "you cant do it to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2903, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0020.flac", "answer": "YOU DIDN'T PAY UP YOUR PLEDGE TO THE CAMPAIGN FUND SO I HADDA FILL IN", "subset": "test_other", "task_type": "understanding", "prediction": "you did n t pay up your pledge to the captain fund so i had to fill in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2904, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0026.flac", "answer": "HE PULLED OUT THE BILLS AND HANDED THEM OVER", "subset": "test_other", "task_type": "understanding", "prediction": "he pulled out the bills and handed them over", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2905, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0003.flac", "answer": "GORDON HIT THE SIGNAL SWITCH AND THE MARSPEAKER LET OUT A SHRILL WHISTLE", "subset": "test_other", "task_type": "understanding", "prediction": "gordon hit the signal switch and the mars speaker let out a shrill whistle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2906, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0000.flac", "answer": "IT WAS NIGHT OUTSIDE AND THE PHOSPHOR BULBS AT THE CORNERS GLOWED DIMLY GIVING HIM BARELY ENOUGH LIGHT BY WHICH TO LOCATE THE WAY TO THE EXTEMPORIZED PRECINCT HOUSE", "subset": "test_other", "task_type": "understanding", "prediction": "it was night outside and the phosphor bulbs at the corners glowed dimly giving him barely enough light by which to locate the way to the extemporized precinct house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2907, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0028.flac", "answer": "THE KID POCKETED THE MONEY CHEERFULLY NODDING", "subset": "test_other", "task_type": "understanding", "prediction": "the kid pocketed the money cheerfully nodding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2908, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0017.flac", "answer": "THE LITTLE MAN SHOOK HIS HEAD HIS ANCIENT EIGHTEEN YEAR OLD FACE TURNING SOBER NOPE", "subset": "test_other", "task_type": "understanding", "prediction": "the little man shook his head his ancient eighteen year old face turning sober no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2909, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0014.flac", "answer": "WHEN GORDON AND JENKINS CAME BACK MURDOCH TOSSED THE MONEY TO THEM SPLIT IT", "subset": "test_other", "task_type": "understanding", "prediction": "when gordon and jenkins came back murdock tossed the money to them split it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2910, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0013.flac", "answer": "THERE MUST HAVE BEEN OVER TWO THOUSAND CREDITS IN THE WALLET", "subset": "test_other", "task_type": "understanding", "prediction": "there must have been over two thousand credits in the wallet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2911, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0021.flac", "answer": "A THOUSAND INTEREST AT TEN PER CENT A WEEK STANDARD RIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "a thousand interest at ten per cent a week standard right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2912, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0010.flac", "answer": "WHEN IT WAS OVER THE TWO PICKED UP THEIR WHIMPERING CAPTIVE", "subset": "test_other", "task_type": "understanding", "prediction": "when it was over the two picked up their whimpering captive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2913, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0002.flac", "answer": "AND THE SLOW DOUBTFUL RESPECT ON THE FACES OF THE CITIZENS AS THEY NODDED TO HIM WAS EVEN MORE PROOF THAT HALEY'S SYSTEM WAS WORKING", "subset": "test_other", "task_type": "understanding", "prediction": "and the slow doubtful respect on the faces of the citizens as they nodded to him was even more proof that haley system was working", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2914, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0018.flac", "answer": "YOU OWE ME SOME BILLS GOV'NOR", "subset": "test_other", "task_type": "understanding", "prediction": "you owe me some bills guvner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2915, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0006.flac", "answer": "I'M REFORMED I'M GOING STRAIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "i am reformed i am going straight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2916, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0023.flac", "answer": "HUH IZZY TURNED IT OVER AND SHOOK HIS HEAD", "subset": "test_other", "task_type": "understanding", "prediction": "haw as he turned it over and shook his head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2917, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0027.flac", "answer": "THANKS IZZY THANKS YOURSELF", "subset": "test_other", "task_type": "understanding", "prediction": "thanks izzie thanks yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2918, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0009.flac", "answer": "SOME TURNED AWAY AS GORDON AND THE OTHER COP WENT TO WORK BUT MOST OF THEM WEREN'T SQUEAMISH", "subset": "test_other", "task_type": "understanding", "prediction": "some turned away as gordon and the other cop went to work but most of them weren t squeamish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2919, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0025.flac", "answer": "FOR A SECOND IZZY'S FACE WENT BLANK THEN HE CHUCKLED", "subset": "test_other", "task_type": "understanding", "prediction": "for a second izzy s face went blank then he chuckled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2920, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0004.flac", "answer": "GUNS SUDDENLY SEEMED TO BE FLOURISHING EVERYWHERE", "subset": "test_other", "task_type": "understanding", "prediction": "guns suddenly seemed to be flourishing everywhere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2921, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0007.flac", "answer": "YOU DAMNED COPS CAN'T O'NEILL WAS BLUBBERING", "subset": "test_other", "task_type": "understanding", "prediction": "you damned cops can t o neill was blubbering", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2922, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0032.flac", "answer": "GO ON ACCEPT DAMN IT", "subset": "test_other", "task_type": "understanding", "prediction": "go on accept damn it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2923, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0001.flac", "answer": "IT HAD PROBABLY BEEN YEARS SINCE ANY HAD DARED RISK IT AFTER THE SUN WENT DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "it had probably been years since any had dared risk it after the sun went down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2924, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117017/8131-117017-0024.flac", "answer": "NOW SHOW ME WHERE I SIGNED ANY AGREEMENT SAYING I'D PAY YOU BACK", "subset": "test_other", "task_type": "understanding", "prediction": "now show me where i signed any agreement saying i would pay you back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2925, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0013.flac", "answer": "HE PICKED OUT FIVE OF THE MEN INCLUDING GORDON YOU FIVE WILL COME WITH ME", "subset": "test_other", "task_type": "understanding", "prediction": "he picked out five of the men including gordon you five will come with me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2926, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0021.flac", "answer": "MOVING IN TWO GROUPS OF THREES AT OPPOSITE SIDES OF THE STREET THEY BEGAN THEIR BEAT", "subset": "test_other", "task_type": "understanding", "prediction": "moving in two groups of threes at opposite sides of the street they began their beat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2927, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0003.flac", "answer": "THE STONEWALL GANG NUMBERED PERHAPS FIVE HUNDRED", "subset": "test_other", "task_type": "understanding", "prediction": "the stonewall gang numbered perhaps five hundred", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2928, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0001.flac", "answer": "BUT MARSPORT HAD FLOURISHED ENOUGH TO KILL IT OFF", "subset": "test_other", "task_type": "understanding", "prediction": "but marsport had flourished enough to kill it off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2929, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0000.flac", "answer": "CAPTAIN MURDOCH", "subset": "test_other", "task_type": "understanding", "prediction": "captain murdock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2930, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0015.flac", "answer": "BRUCE GORDON GRINNED SLOWLY AS HE SWUNG THE STICK AND MURDOCH'S EYES FELL ON HIM EARTH COP", "subset": "test_other", "task_type": "understanding", "prediction": "bruce gordon grinned slowly as he swung the stick and murdock s eyes fell on him earth cop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2931, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0002.flac", "answer": "SOME OF MARS LAWS DATED FROM THE TIME WHEN LAW ENFORCEMENT HAD BEEN HAMPERED BY LACK OF MEN RATHER THAN BY THE TYPE OF MEN", "subset": "test_other", "task_type": "understanding", "prediction": "some of mars laws dated from the time when law enforcement had been hampered by lack of men rather than by the type of men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2932, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0012.flac", "answer": "THE FIRST MAN MAKING A SHAKEDOWN WILL GET THE SAME TREATMENT WE'RE GOING TO USE ON THE STONEWALL BOYS YOU'LL GET DOUBLE PAY HERE AND YOU CAN LIVE ON IT", "subset": "test_other", "task_type": "understanding", "prediction": "the first man making a shake down will get the same treatment we are going to use on the stonewall boys you will get double pay here and you can live on it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2933, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0005.flac", "answer": "THEY WERE SAFE FROM PROTECTION RACKETEERS THERE NONE BOTHERED TO COME SO FAR OUT", "subset": "test_other", "task_type": "understanding", "prediction": "they were safe from protection racketeers there none bothered to come so far out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2934, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0046.flac", "answer": "BRUCE GORDON GRIMACED I'VE GOT A YELLOW TICKET FROM SECURITY", "subset": "test_other", "task_type": "understanding", "prediction": "bruce gordon grimaced i have got a yellow ticket from security", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2935, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0051.flac", "answer": "NO YOU'RE A FIRSTER HE CAN'T LOSE", "subset": "test_other", "task_type": "understanding", "prediction": "no you are a firster he cant lose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2936, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0014.flac", "answer": "THE REST OF YOU CAN TEAM UP ANY WAY YOU WANT TONIGHT PICK ANY ROUTE THAT'S OPEN OKAY MEN LET'S GO", "subset": "test_other", "task_type": "understanding", "prediction": "the rest of you can team up any way you want tonight pick any route that is open okay men lets go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2937, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0027.flac", "answer": "HE BROUGHT HIM TO THE GROUND WITH A SINGLE BLOW ACROSS THE KIDNEYS", "subset": "test_other", "task_type": "understanding", "prediction": "he brought him to the ground with a single blow across the kidneys", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2938, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0026.flac", "answer": "THE OTHER FOUR COPS HAD COME IN RELUCTANTLY", "subset": "test_other", "task_type": "understanding", "prediction": "the other four cops had come in reluctantly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2939, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0061.flac", "answer": "BUT THERE PROBABLY WOULDN'T BE TIME FOR IT IF MAYOR WAYNE WAS RE ELECTED", "subset": "test_other", "task_type": "understanding", "prediction": "but there probably wouldnt be time for it if mayor wayne was reelected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2940, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0006.flac", "answer": "THE SHOPKEEPERS AND SOME OF THE LESS UNFORTUNATE PEOPLE THERE HAD PROTESTED LOUD ENOUGH TO REACH CLEAR BACK TO EARTH", "subset": "test_other", "task_type": "understanding", "prediction": "the shopkeepers and some of the less unfortunate people there had protested loud enough to reach clear back to earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2941, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0049.flac", "answer": "NOBODY WANTS HIM EXCEPT A GANG OF CROOKS AND THOSE IN POWER", "subset": "test_other", "task_type": "understanding", "prediction": "nobody wants him except a gang of crooks and those in power", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2942, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0059.flac", "answer": "IT WASN'T EXACTLY LEGAL BUT NOTHING WAS HERE", "subset": "test_other", "task_type": "understanding", "prediction": "it wasnt exactly legal but nothing was here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2943, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0042.flac", "answer": "BUT THE CAPTAIN STIRRED FINALLY SIGHING", "subset": "test_other", "task_type": "understanding", "prediction": "but the captain stirred finally sighing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2944, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0060.flac", "answer": "THIS COULD LEAD TO ABUSES AS HE'D SEEN ON EARTH", "subset": "test_other", "task_type": "understanding", "prediction": "this could lead to abuses as he had seen on earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2945, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0007.flac", "answer": "CAPTAIN MURDOCH WAS AN UNKNOWN FACTOR AND NOW WAS ASKING FOR MORE MEN", "subset": "test_other", "task_type": "understanding", "prediction": "captain murdock was an unknown factor and now was asking for more men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2946, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0050.flac", "answer": "EVER SEE A MARTIAN ELECTION", "subset": "test_other", "task_type": "understanding", "prediction": "ever see a martian election", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2947, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0044.flac", "answer": "BUT THE STONEWALL GANG IS BACKING WAYNE", "subset": "test_other", "task_type": "understanding", "prediction": "but the stonewall gang is backing wayne", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2948, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0023.flac", "answer": "GORDON FELT THE SOLID PLEASURE OF THE FINELY TURNED CLUB IN HIS HANDS", "subset": "test_other", "task_type": "understanding", "prediction": "gordon felt the solid pleasure of the finely turned club in his hands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2949, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0011.flac", "answer": "YOUR JOB IS TO PROTECT THE CITIZENS HERE AND THAT MEANS EVERYONE NOT BREAKING THE LAWS WHETHER YOU FEEL LIKE IT OR NOT NO GRAFT", "subset": "test_other", "task_type": "understanding", "prediction": "your job is to protect the citizens here and that means everyone not breaking the laws whether you feel like it or not no graft", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2950, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0022.flac", "answer": "THERE WAS NO CHANCE TO SAVE THE CITIZEN WHO WAS DYING FROM LACK OF AIR", "subset": "test_other", "task_type": "understanding", "prediction": "there was no chance to save the citizen who was dying from lack of air", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2951, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0031.flac", "answer": "IF THEY TRIED TO RUN THEY WERE HIT FROM BEHIND IF THEY STOOD STILL THEY WERE CLUBBED CAREFULLY", "subset": "test_other", "task_type": "understanding", "prediction": "if they tried to run they were hit from behind if they stood still they were clubbed carefully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2952, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0037.flac", "answer": "IF HE SHOULD TURN UP DEAD I'LL KNOW YOU BOYS ARE RESPONSIBLE AND I'LL FIND YOU", "subset": "test_other", "task_type": "understanding", "prediction": "if he should turn up dead i ll know you boys are responsible and i ll find you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2953, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0041.flac", "answer": "GET A STRETCHER AND TAKE HIM WHEREVER HE BELONGS HE ORDERED", "subset": "test_other", "task_type": "understanding", "prediction": "get a stretcher and take him wherever he belongs he ordered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2954, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0035.flac", "answer": "COLONEL THEY'D KILL ME I DON'T KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "colonel theyd kill me i don t know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2955, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0020.flac", "answer": "THERE WAS A CRUDE LIGHTING SYSTEM HERE PUT UP BY THE CITIZENS AT THE FRONT OF EACH BUILDING A DIM PHOSPHOR BULB GLOWED WHEN DARKNESS FELL THEY WOULD HAVE NOTHING ELSE TO SEE BY", "subset": "test_other", "task_type": "understanding", "prediction": "there was a crude lighting system here put up by the citizens at the front of each building a dim phosphor bulb glowed when darkness fell they would have nothing else to see by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2956, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0034.flac", "answer": "I WANT THE NAME OF EVERY MAN IN THE GANG YOU CAN REMEMBER HE TOLD THE MAN", "subset": "test_other", "task_type": "understanding", "prediction": "i want the name of every man in the gang you can remember he told the man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2957, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0057.flac", "answer": "BUT YOU GOT EARTH IDEAS OF THE STUFF LIKE I HAD ONCE", "subset": "test_other", "task_type": "understanding", "prediction": "but you got earth ideas of the stuff like i had once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2958, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0055.flac", "answer": "COST EM MORE BUT THEY'D BE RESPECTABLE", "subset": "test_other", "task_type": "understanding", "prediction": "cost em more but they d be respectable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2959, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0040.flac", "answer": "IN THE THIRD ONE BRUCE GORDON SPOTTED ONE OF THE MEN WHO'D BEEN BEATEN BEFORE", "subset": "test_other", "task_type": "understanding", "prediction": "and the third one bruce gordon spotted one of the men who had been beaten before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2960, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0033.flac", "answer": "THE CAPTAIN'S FACE WAS AS SICK AS GORDON FELT", "subset": "test_other", "task_type": "understanding", "prediction": "the captain s face was as sick as gordon s felt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2961, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0009.flac", "answer": "GORDON REPORTED FOR WORK WITH A SENSE OF THE BOTTOM FALLING OUT MIXED WITH A VAGUE RELIEF", "subset": "test_other", "task_type": "understanding", "prediction": "gordon reported for work with a sense of the bottom falling out mixed with a vague relief", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2962, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0004.flac", "answer": "EVEN DERELICTS AND FAILURES HAD TO EAT THERE WERE STORES AND SHOPS THROUGHOUT THE DISTRICT WHICH EKED OUT SOME KIND OF A MARGINAL LIVING", "subset": "test_other", "task_type": "understanding", "prediction": "even derelicts and failures had to eat there were stores and shops throughout the district which eked out some kind of a marginal living", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2963, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0010.flac", "answer": "I'VE GOT A FREE HAND AND WE'RE GOING TO RUN THIS THE WAY WE WOULD ON EARTH", "subset": "test_other", "task_type": "understanding", "prediction": "i have got a free hand and we are going to run this the way we would on earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2964, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0019.flac", "answer": "NOBODY HAD TRIED TO GET IN TOUCH WITH HIM", "subset": "test_other", "task_type": "understanding", "prediction": "nobody had tried to get in touch with him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2965, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0053.flac", "answer": "IT FITTED WITH THE DIRE PREDICTIONS OF SECURITY AND WITH THE SPYING GORDON WAS GOING TO DO ACCORDING TO THEM", "subset": "test_other", "task_type": "understanding", "prediction": "yet fitted with the dyer predictions of security and with the spying gordon was going to do according to them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2966, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0029.flac", "answer": "TO FIND A PHONE AND CALL THE WAGON", "subset": "test_other", "task_type": "understanding", "prediction": "to find a phone and call the wagon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2967, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0052.flac", "answer": "AND THEN HELL IS GOING TO POP AND THIS WHOLE PLANET MAY BE BLOWN WIDE OPEN", "subset": "test_other", "task_type": "understanding", "prediction": "and then hell is going to pop and this whole planet may be blown wide open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2968, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0036.flac", "answer": "MURDOCH TOOK HIS NOD AS EVIDENCE ENOUGH AND TURNED TO THE WRETCHED TOUGHS", "subset": "test_other", "task_type": "understanding", "prediction": "murdock took his nod as evidence enough and turned to the wretched toughs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2969, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0048.flac", "answer": "WHAT MAKES YOU THINK WAYNE WILL BE RE ELECTED", "subset": "test_other", "task_type": "understanding", "prediction": "what makes you think wayne will be reelected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2970, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0054.flac", "answer": "HE WAS GETTING EVEN FATTER NOW THAT HE WAS EATING BETTER FOOD FROM THE FAIR RESTAURANT AROUND THE CORNER", "subset": "test_other", "task_type": "understanding", "prediction": "he was getting even fatter now that he was eating better food from the fair restaurant around the corner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2971, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0018.flac", "answer": "HE BEGAN WONDERING ABOUT SECURITY THEN", "subset": "test_other", "task_type": "understanding", "prediction": "he began wondering about security then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2972, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0016.flac", "answer": "TWO YEARS GORDON ADMITTED", "subset": "test_other", "task_type": "understanding", "prediction": "two years gordon admitted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2973, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0024.flac", "answer": "GORDON'S EYES POPPED AT THAT", "subset": "test_other", "task_type": "understanding", "prediction": "gordon s eyes popped at that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2974, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0008.flac", "answer": "THE PRESSURE WAS ENOUGH TO GET THEM FOR HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the pressure was enough to get them for him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2975, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0038.flac", "answer": "TROUBLE BEGAN BREWING SHORTLY AFTER THOUGH", "subset": "test_other", "task_type": "understanding", "prediction": "trouble began brewing shortly after though", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2976, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0025.flac", "answer": "HE SWALLOWED THE SENTIMENT HIS OWN CLUB WAS MOVING NOW", "subset": "test_other", "task_type": "understanding", "prediction": "he swallowed the sentiment his own club was moving now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2977, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0058.flac", "answer": "THE GROUPS GREW MORE EXPERIENCED AND MURDOCH WAS TRAINING A NEW SQUAD EVERY NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "the groups grew more experienced and murdock was training a new squad every night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2978, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0017.flac", "answer": "FOR A SECOND GORDON CURSED HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "for a second gordon cursed himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2979, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0030.flac", "answer": "WE'RE NOT USING WAGONS MURDOCH TOLD HIM LINE THEM UP", "subset": "test_other", "task_type": "understanding", "prediction": "were not using wagons murdock told him line them up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2980, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0039.flac", "answer": "MURDOCH SENT ONE OF THE MEN TO PICK UP A SECOND SQUAD OF SIX AND THEN A THIRD", "subset": "test_other", "task_type": "understanding", "prediction": "murdoch sent one of the men to pick up a second squad of six and then a third", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2981, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0056.flac", "answer": "BECAUSE IZZY IS ALWAYS HONEST ACCORDING TO HOW HE SEES IT", "subset": "test_other", "task_type": "understanding", "prediction": "because iZZy is always honest according to how he sees it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2982, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0032.flac", "answer": "MURDOCH INDICATED ONE WHO STOOD WITH HIS SHOULDERS SHAKING AND TEARS RUNNING DOWN HIS CHEEKS", "subset": "test_other", "task_type": "understanding", "prediction": "murdock indicated one who stood with his shoulder shaking and tears running down his cheeks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2983, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0047.flac", "answer": "MURDOCH BLINKED HE DROPPED HIS EYES SLOWLY", "subset": "test_other", "task_type": "understanding", "prediction": "murdock blinked he dropped his eyes slowly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2984, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0043.flac", "answer": "NO THE COPS THEY'RE GIVING ME WE'RE COVERED GORDON", "subset": "test_other", "task_type": "understanding", "prediction": "no the cops are giving me were covered gordon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2985, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0045.flac", "answer": "BUT IT'S GOING TO BE TOUGH ON THEM", "subset": "test_other", "task_type": "understanding", "prediction": "but it is going to be tough on them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2986, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8131/117016/8131-117016-0028.flac", "answer": "THEY ROUNDED UP THE MEN OF THE GANG AND ONE OF THE COPS STARTED OFF", "subset": "test_other", "task_type": "understanding", "prediction": "they rounded up the men of the gang and one of the cops started off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2987, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0007.flac", "answer": "IT IS EASY ENOUGH WITH THE CHILD YOU WILL CARRY HER OUT", "subset": "test_other", "task_type": "understanding", "prediction": "it is easy enough with the child you will carry her out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2988, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0021.flac", "answer": "WHAT COFFIN WHAT ADMINISTRATION", "subset": "test_other", "task_type": "understanding", "prediction": "what coffin what administration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2989, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0053.flac", "answer": "I SHALL FOLLOW THAT IS MY BUSINESS", "subset": "test_other", "task_type": "understanding", "prediction": "i shall follow that is my business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2990, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0044.flac", "answer": "WHAT DOES NOT A MAN UNDERGO FOR THE SAKE OF A CURE", "subset": "test_other", "task_type": "understanding", "prediction": "what does not a man undergo for the sake of a cure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2991, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0006.flac", "answer": "THAT'S WHERE THE DIFFICULTY LIES", "subset": "test_other", "task_type": "understanding", "prediction": "that is where the difficulty lies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2992, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0027.flac", "answer": "HOW LONG IS THE COFFIN SIX FEET", "subset": "test_other", "task_type": "understanding", "prediction": "how long is the coffin six feet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2993, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0034.flac", "answer": "WHO SPREADS THE PALL OVER IT", "subset": "test_other", "task_type": "understanding", "prediction": "who spreads the pall over it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2994, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0041.flac", "answer": "BAH IMPOSSIBLE TO TAKE A HAMMER AND DRIVE SOME NAILS IN A PLANK", "subset": "test_other", "task_type": "understanding", "prediction": "bah impossible to take a hammer and drive some nails in a plank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2995, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0004.flac", "answer": "EVERYTHING IS ARRANGED AND NOTHING IS SAID FAUCHELEVENT", "subset": "test_other", "task_type": "understanding", "prediction": "everything is ranged and nothing is said fauchelevent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2996, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0045.flac", "answer": "TO HAVE HIMSELF NAILED UP IN A CASE AND CARRIED OFF LIKE A BALE OF GOODS TO LIVE FOR A LONG TIME IN A BOX TO FIND AIR WHERE THERE IS NONE TO ECONOMIZE HIS BREATH FOR HOURS TO KNOW HOW TO STIFLE WITHOUT DYING THIS WAS ONE OF JEAN VALJEAN'S GLOOMY TALENTS", "subset": "test_other", "task_type": "understanding", "prediction": "to have himself nailed up in a case and carried off like a bale of goods to live for a long time in a box to find air where there is none to economize his breath for hours to know how to stifle without dying this was one of jean valjean s gloomy talents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2997, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0033.flac", "answer": "WHO NAILS UP THE COFFIN I DO", "subset": "test_other", "task_type": "understanding", "prediction": "who nails up the coffin i do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2998, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0018.flac", "answer": "AND THEN THAT THERE WAS ANOTHER THE EMPTY COFFIN", "subset": "test_other", "task_type": "understanding", "prediction": "and then that there was another the empty coffin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2999, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0014.flac", "answer": "THEN HE EXPLAINED TO JEAN VALJEAN THAT THIS WAS HIS RECOMPENSE FOR A SERVICE WHICH HE FAUCHELEVENT WAS TO RENDER TO THE COMMUNITY", "subset": "test_other", "task_type": "understanding", "prediction": "then he explained to jean valjean that this was his recompense for a service which he fauchelevent was to render to the community", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3000, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0020.flac", "answer": "ASKED JEAN VALJEAN FAUCHELEVENT REPLIED", "subset": "test_other", "task_type": "understanding", "prediction": "asked jean valjean fauchelevent replied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3001, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0030.flac", "answer": "HAVE YOU THE KEYS TO THOSE TWO DOORS", "subset": "test_other", "task_type": "understanding", "prediction": "have you the keys to those two doors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3002, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0024.flac", "answer": "AND I ADD AND FATHER MADELEINE IS BURIED AH", "subset": "test_other", "task_type": "understanding", "prediction": "and i add and father madeline is buried ah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3003, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0009.flac", "answer": "FAUCHELEVENT GRUMBLED MORE TO HIMSELF THAN TO JEAN VALJEAN", "subset": "test_other", "task_type": "understanding", "prediction": "fauchelevent grumbled more to himself than to jean valjean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3004, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0000.flac", "answer": "THE STRIDES OF A LAME MAN ARE LIKE THE OGLING GLANCES OF A ONE EYED MAN THEY DO NOT REACH THEIR GOAL VERY PROMPTLY", "subset": "test_other", "task_type": "understanding", "prediction": "the strides of a lame man are like the ogling glances of a one eyed man they do not reach their goal very promptly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3005, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0011.flac", "answer": "JEAN VALJEAN STARED HIM STRAIGHT IN THE EYE AND THOUGHT THAT HE WAS RAVING", "subset": "test_other", "task_type": "understanding", "prediction": "jean valjean stared him straight in the eye and thought that he was raving", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3006, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0002.flac", "answer": "JEAN VALJEAN HAD PLACED HER NEAR THE FIRE", "subset": "test_other", "task_type": "understanding", "prediction": "jean valjean had placed her near the fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3007, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0046.flac", "answer": "YOU SURELY MUST HAVE A GIMLET YOU WILL MAKE A FEW HOLES HERE AND THERE AROUND MY MOUTH AND YOU WILL NAIL THE TOP PLANK ON LOOSELY GOOD AND WHAT IF YOU SHOULD HAPPEN TO COUGH OR TO SNEEZE", "subset": "test_other", "task_type": "understanding", "prediction": "you surely must have a gimlet you will make a few holes here and there around my mouth and you will nail the top plank on loosely good and what if you should happen to cough or to sneeze", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3008, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0022.flac", "answer": "FAUCHELEVENT WHO WAS SEATED SPRANG UP AS THOUGH A BOMB HAD BURST UNDER HIS CHAIR YOU", "subset": "test_other", "task_type": "understanding", "prediction": "fauchelevent who was seated sprang up as though a bomb had burst under his chair you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3009, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0023.flac", "answer": "YOU KNOW FAUCHELEVENT WHAT YOU HAVE SAID MOTHER CRUCIFIXION IS DEAD", "subset": "test_other", "task_type": "understanding", "prediction": "you know franche levant what you have said mother crucifixion is dead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3010, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0043.flac", "answer": "ANY MAN WHO HAS BEEN A PRISONER UNDERSTANDS HOW TO CONTRACT HIMSELF TO FIT THE DIAMETER OF THE ESCAPE", "subset": "test_other", "task_type": "understanding", "prediction": "any man who has been a prisoner understands how to contract himself to fit the diameter of the escape", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3011, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0001.flac", "answer": "COSETTE HAD WAKED UP", "subset": "test_other", "task_type": "understanding", "prediction": "cosette had waked up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3012, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0017.flac", "answer": "THAT HE FAUCHELEVENT WAS TO NAIL UP THE COFFIN IN THE CELL RAISE THE STONE IN THE CHAPEL AND LOWER THE CORPSE INTO THE VAULT", "subset": "test_other", "task_type": "understanding", "prediction": "that he fauchelevent was to nail up the coffin in the cell raise the stone in the chapel and lower the corpse into the vault", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3013, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0047.flac", "answer": "A MAN WHO IS MAKING HIS ESCAPE DOES NOT COUGH OR SNEEZE", "subset": "test_other", "task_type": "understanding", "prediction": "a man who is making his escape does not cough or sneeze", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3014, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0048.flac", "answer": "WHO IS THERE WHO HAS NOT SAID TO A CAT DO COME IN", "subset": "test_other", "task_type": "understanding", "prediction": "who is there who has not said to a cat do come in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3015, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0005.flac", "answer": "I HAVE PERMISSION TO BRING YOU IN BUT BEFORE BRINGING YOU IN YOU MUST BE GOT OUT", "subset": "test_other", "task_type": "understanding", "prediction": "i have permission to bring you in but before bringing you in you must be got out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3016, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0028.flac", "answer": "IT IS A CHAMBER ON THE GROUND FLOOR WHICH HAS A GRATED WINDOW OPENING ON THE GARDEN WHICH IS CLOSED ON THE OUTSIDE BY A SHUTTER AND TWO DOORS ONE LEADS INTO THE CONVENT THE OTHER INTO THE CHURCH WHAT CHURCH", "subset": "test_other", "task_type": "understanding", "prediction": "it is a chamber on the ground floor which has a grated window opening on the garden which is closed on the outside by a shutter and two doors one leads into the convent the other into the church a what church", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3017, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0025.flac", "answer": "YOU ARE NOT LIKE OTHER MEN FATHER MADELEINE", "subset": "test_other", "task_type": "understanding", "prediction": "you are not like other men father madelin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3018, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0010.flac", "answer": "YOU UNDERSTAND FATHER MADELEINE THE GOVERNMENT WILL NOTICE IT", "subset": "test_other", "task_type": "understanding", "prediction": "you understand father madelin the government will notice it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3019, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0037.flac", "answer": "ABOUT THREE O'CLOCK IN THE AFTERNOON", "subset": "test_other", "task_type": "understanding", "prediction": "about three o clock in the afternoon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3020, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0012.flac", "answer": "FAUCHELEVENT WENT ON", "subset": "test_other", "task_type": "understanding", "prediction": "fouchon went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3021, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0008.flac", "answer": "AND SHE WILL HOLD HER TONGUE I ANSWER FOR THAT", "subset": "test_other", "task_type": "understanding", "prediction": "and she will hold her tongue i answer for that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3022, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0050.flac", "answer": "BUT JEAN VALJEAN'S COOLNESS PREVAILED OVER HIM IN SPITE OF HIMSELF HE GRUMBLED", "subset": "test_other", "task_type": "understanding", "prediction": "but jean valjean s coolness prevailed over him in spite of himself he grumbled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3023, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0016.flac", "answer": "THAT THE PRIORESS AND THE VOCAL MOTHERS INTENDED TO FULFIL THE WISH OF THE DECEASED", "subset": "test_other", "task_type": "understanding", "prediction": "that the prioress and the vocal mothers intended to fulfil a wish of the deceased", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3024, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0057.flac", "answer": "THAT IS SETTLED FATHER FAUCHELEVENT ALL WILL GO WELL", "subset": "test_other", "task_type": "understanding", "prediction": "that is settled father fauchelevent all will go well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3025, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0040.flac", "answer": "FAUCHELEVENT RECOILED AND CRACKED HIS FINGER JOINTS BUT THAT IS IMPOSSIBLE", "subset": "test_other", "task_type": "understanding", "prediction": "first levin recoiled and cracked his finger joints but that is impossible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3026, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0042.flac", "answer": "JEAN VALJEAN HAD BEEN IN WORSE STRAITS THAN THIS", "subset": "test_other", "task_type": "understanding", "prediction": "jean valjean had been in worse straits than this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3027, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0031.flac", "answer": "NO I HAVE THE KEY TO THE DOOR WHICH COMMUNICATES WITH THE CONVENT THE PORTER HAS THE KEY TO THE DOOR WHICH COMMUNICATES WITH THE CHURCH", "subset": "test_other", "task_type": "understanding", "prediction": "no i have the key to the door which communicates with the convent the porter has the key to the door which communicates with the church", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3028, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0038.flac", "answer": "I SHALL BE HUNGRY I WILL BRING YOU SOMETHING", "subset": "test_other", "task_type": "understanding", "prediction": "i shall be hungry i will bring you something", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3029, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0003.flac", "answer": "YOU WILL WAIT FOR ME AT A LADY'S HOUSE I SHALL COME TO FETCH YOU", "subset": "test_other", "task_type": "understanding", "prediction": "you will wait for me at a lady s house i shall come to fetch ye", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3030, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0055.flac", "answer": "THE PRIEST SAYS THE PRAYERS MAKES THE SIGN OF THE CROSS SPRINKLES THE HOLY WATER AND TAKES HIS DEPARTURE", "subset": "test_other", "task_type": "understanding", "prediction": "the priest as the prayers makes the sign of the cross sprinkles the holy water and takes his departure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3031, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0013.flac", "answer": "IT IS TO MORROW THAT I AM TO BRING YOU IN THE PRIORESS EXPECTS YOU", "subset": "test_other", "task_type": "understanding", "prediction": "it is to morrow that i am to bring you in the prioress expects you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3032, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0032.flac", "answer": "ONLY TO ALLOW THE UNDERTAKER'S MEN TO ENTER WHEN THEY COME TO GET THE COFFIN", "subset": "test_other", "task_type": "understanding", "prediction": "only to allow the undertakers men to enter when they come to get the coffin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3033, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0019.flac", "answer": "WHAT IS THAT EMPTY COFFIN", "subset": "test_other", "task_type": "understanding", "prediction": "what is that empty coffin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3034, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0056.flac", "answer": "ONE OF TWO THINGS WILL HAPPEN HE WILL EITHER BE SOBER OR HE WILL NOT BE SOBER", "subset": "test_other", "task_type": "understanding", "prediction": "one of two things will happen he will either be sober or he will not be sober", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3035, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0049.flac", "answer": "THE OVER PRUDENT CATS AS THEY ARE AND BECAUSE THEY ARE CATS SOMETIMES INCUR MORE DANGER THAN THE AUDACIOUS", "subset": "test_other", "task_type": "understanding", "prediction": "the over prudent cats as they are and because they are cats sometimes incur more danger than the audacious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3036, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0052.flac", "answer": "AN OLD FELLOW OF THE OLD SCHOOL THE GRAVE DIGGER PUTS THE CORPSES IN THE GRAVE AND I PUT THE GRAVE DIGGER IN MY POCKET", "subset": "test_other", "task_type": "understanding", "prediction": "an old fellow of the old school the gravedigger puts the corpses in the grave and i put the gravedigger in my pocket", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3037, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0029.flac", "answer": "THE CHURCH IN THE STREET THE CHURCH WHICH ANY ONE CAN ENTER", "subset": "test_other", "task_type": "understanding", "prediction": "the church in the street the church which any one can enter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3038, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0039.flac", "answer": "YOU CAN COME AND NAIL ME UP IN THE COFFIN AT TWO O'CLOCK", "subset": "test_other", "task_type": "understanding", "prediction": "you can come and nail me up in the coffin at two o clock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3039, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0015.flac", "answer": "THAT THE NUN WHO HAD DIED THAT MORNING HAD REQUESTED TO BE BURIED IN THE COFFIN WHICH HAD SERVED HER FOR A BED AND INTERRED IN THE VAULT UNDER THE ALTAR OF THE CHAPEL", "subset": "test_other", "task_type": "understanding", "prediction": "that the nun who had died that morning had requested to be buried in the coffin which had served her for a bed and interred in the vault under the altar of the chapel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3040, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0035.flac", "answer": "NOT ANOTHER MAN EXCEPT THE POLICE DOCTOR CAN ENTER THE DEAD ROOM THAT IS EVEN WRITTEN ON THE WALL", "subset": "test_other", "task_type": "understanding", "prediction": "not another man except the police doctor can enter the dead room that is even written on the wall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3041, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0054.flac", "answer": "THE HEARSE HALTS THE UNDERTAKER'S MEN KNOT A ROPE AROUND YOUR COFFIN AND LOWER YOU DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "the hearse halts the undertaker s men knot a rope around your coffin and lower you down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3042, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0026.flac", "answer": "THIS OFFERS THE MEANS BUT GIVE ME SOME INFORMATION IN THE FIRST PLACE", "subset": "test_other", "task_type": "understanding", "prediction": "this offers the means but give me some information in the first place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3043, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0051.flac", "answer": "IF YOU ARE SURE OF COMING OUT OF THE COFFIN ALL RIGHT I AM SURE OF GETTING YOU OUT OF THE GRAVE", "subset": "test_other", "task_type": "understanding", "prediction": "if you are sure of coming out of the coffin all right i am sure of getting you out of the grave", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3044, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168670/3764-168670-0036.flac", "answer": "COULD YOU HIDE ME IN THAT ROOM TO NIGHT WHEN EVERY ONE IS ASLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "could you hide me in that room tonight when every one is asleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3045, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0003.flac", "answer": "BEHIND IT CAME AN OLD MAN IN THE GARMENTS OF A LABORER WHO LIMPED ALONG", "subset": "test_other", "task_type": "understanding", "prediction": "behind it came an old man in the garments of a laborer who limped along", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3046, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0035.flac", "answer": "THE GRAVE DIGGER WALKED ON IN FRONT OF HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the gravedigger walked on in front of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3047, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0042.flac", "answer": "YOU ARE A PEASANT I AM A PARISIAN", "subset": "test_other", "task_type": "understanding", "prediction": "you are a peasant i am a parisian", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3048, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0046.flac", "answer": "FORTUNATELY THE SOIL WHICH WAS LIGHT AND WET WITH THE WINTER RAINS CLOGGED THE WHEELS AND RETARDED ITS SPEED", "subset": "test_other", "task_type": "understanding", "prediction": "fortunately the soil which was light and wet with the winter rains clogged the wheels and retarded its speed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3049, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0048.flac", "answer": "BUT HE HAD REVERSES HE HAD LOSSES ON CHANGE I WAS OBLIGED TO RENOUNCE THE PROFESSION OF AUTHOR BUT I AM STILL A PUBLIC WRITER", "subset": "test_other", "task_type": "understanding", "prediction": "but he had reverses he had losses on change i was obliged to renounce the profession of author but i am still a public writer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3050, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0016.flac", "answer": "JEAN VALJEAN'S COMPOSURE WAS ONE OF THOSE POWERFUL TRANQUILLITIES WHICH ARE CONTAGIOUS", "subset": "test_other", "task_type": "understanding", "prediction": "jean valjean s composure was one of those powerful tranquillities which are contagious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3051, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0009.flac", "answer": "THE INTERMENT OF MOTHER CRUCIFIXION IN THE VAULT UNDER THE ALTAR THE EXIT OF COSETTE THE INTRODUCTION OF JEAN VALJEAN TO THE DEAD ROOM ALL HAD BEEN EXECUTED WITHOUT DIFFICULTY AND THERE HAD BEEN NO HITCH LET US REMARK IN PASSING THAT THE BURIAL OF MOTHER CRUCIFIXION UNDER THE ALTAR OF THE CONVENT IS A PERFECTLY VENIAL OFFENCE IN OUR SIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "the interment of mother crucifixion in the vault under the altar the exit of cosette the introduction of jean valjean into the dead room all had been executed without difficulty and there had been no hitch let us remark in passing that the burial of mother crucifixion under the altar of the convent is a perfectly venial offence in our sight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3052, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0013.flac", "answer": "MAKE AS MANY LAWS AS YOU PLEASE MEN BUT KEEP THEM FOR YOURSELVES", "subset": "test_other", "task_type": "understanding", "prediction": "make as many laws as you please men but keep them for yourselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3053, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0001.flac", "answer": "THIS HEARSE CONTAINED A COFFIN COVERED WITH A WHITE CLOTH OVER WHICH SPREAD A LARGE BLACK CROSS LIKE A HUGE CORPSE WITH DROOPING ARMS", "subset": "test_other", "task_type": "understanding", "prediction": "this hearse contained a coffin covered with a white cloth over which spread a large black cross like a huge corpse with drooping arms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3054, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0030.flac", "answer": "DO YOU KNOW WHO LITTLE FATHER LENOIR IS HE IS A JUG OF RED WINE", "subset": "test_other", "task_type": "understanding", "prediction": "do you know who little father lenoir is he is a jug of red wine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3055, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0008.flac", "answer": "TO BE BURIED IN PERE LACHAISE IS EQUIVALENT TO HAVING FURNITURE OF MAHOGANY IT IS RECOGNIZED AS ELEGANT", "subset": "test_other", "task_type": "understanding", "prediction": "to be buried in pere la chaise is equivalent to having furniture of mahogany it is recognized as elegant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3056, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0031.flac", "answer": "BUT YOU ARE A JOLLY FELLOW TOO", "subset": "test_other", "task_type": "understanding", "prediction": "but you are a jolly fellow too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3057, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0004.flac", "answer": "THE GRAVE DIGGERS BEING THUS BOUND TO SERVICE IN THE EVENING IN SUMMER AND AT NIGHT IN WINTER IN THIS CEMETERY THEY WERE SUBJECTED TO A SPECIAL DISCIPLINE", "subset": "test_other", "task_type": "understanding", "prediction": "the grave diggers being thus bound to service in the evening in summer and at night in winter in this cemetery they were subjected to a special discipline", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3058, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0036.flac", "answer": "FAUCHELEVENT PASSED THE UNEXPECTED GRIBIER ONCE MORE IN REVIEW", "subset": "test_other", "task_type": "understanding", "prediction": "foucheville passed the unexpected cribier once more in review", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3059, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0051.flac", "answer": "HERE A REMARK BECOMES NECESSARY", "subset": "test_other", "task_type": "understanding", "prediction": "here a remark becomes necessary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3060, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0049.flac", "answer": "SO YOU ARE NOT A GRAVE DIGGER THEN", "subset": "test_other", "task_type": "understanding", "prediction": "so you are not a gravedigger then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3061, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0024.flac", "answer": "YOU I", "subset": "test_other", "task_type": "understanding", "prediction": "you i", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3062, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0047.flac", "answer": "MY FATHER WAS A PORTER AT THE PRYTANEUM TOWN HALL", "subset": "test_other", "task_type": "understanding", "prediction": "my father was a porter at the prytaneum town hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3063, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0012.flac", "answer": "IN THE CLOISTER WHAT IS CALLED THE GOVERNMENT IS ONLY AN INTERMEDDLING WITH AUTHORITY AN INTERFERENCE WHICH IS ALWAYS QUESTIONABLE", "subset": "test_other", "task_type": "understanding", "prediction": "in the cloister what is called the government is only an intermeddling with authority an interference which is always questionable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3064, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0043.flac", "answer": "FAUCHELEVENT THOUGHT I AM LOST", "subset": "test_other", "task_type": "understanding", "prediction": "frochon thought i am lost", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3065, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0052.flac", "answer": "FAUCHELEVENT WHATEVER HIS ANGUISH OFFERED A DRINK BUT HE DID NOT EXPLAIN HIMSELF ON ONE POINT WHO WAS TO PAY", "subset": "test_other", "task_type": "understanding", "prediction": "a fauchelevent whatever his anguish offered a drink but he did not explain himself on one point who was to pay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3066, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0050.flac", "answer": "RETURNED FAUCHELEVENT CLUTCHING AT THIS BRANCH FEEBLE AS IT WAS", "subset": "test_other", "task_type": "understanding", "prediction": "returned vaucherlevent clutching at this branch feeble as it was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3067, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0006.flac", "answer": "DAMPNESS WAS INVADING IT THE FLOWERS WERE DESERTING IT", "subset": "test_other", "task_type": "understanding", "prediction": "dampness was invading it the flowers were deserting it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3068, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0026.flac", "answer": "FAUCHELEVENT HAD EXPECTED ANYTHING BUT THIS THAT A GRAVE DIGGER COULD DIE", "subset": "test_other", "task_type": "understanding", "prediction": "fortunovant had expected anything but this that a grave digger could die", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3069, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0038.flac", "answer": "SO FATHER MESTIENNE IS DEAD", "subset": "test_other", "task_type": "understanding", "prediction": "but so father mestienne is dead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3070, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0053.flac", "answer": "THE GRAVE DIGGER WENT ON WITH A SUPERIOR SMILE", "subset": "test_other", "task_type": "understanding", "prediction": "the gravedigger went on with a superior smile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3071, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0054.flac", "answer": "ONE MUST EAT", "subset": "test_other", "task_type": "understanding", "prediction": "one must eat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3072, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0002.flac", "answer": "A MOURNING COACH IN WHICH COULD BE SEEN A PRIEST IN HIS SURPLICE AND A CHOIR BOY IN HIS RED CAP FOLLOWED", "subset": "test_other", "task_type": "understanding", "prediction": "a mourning coach in which could be seen a priest in his surplice and a choir boy in his red cap followed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3073, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0007.flac", "answer": "THE BOURGEOIS DID NOT CARE MUCH ABOUT BEING BURIED IN THE VAUGIRARD IT HINTED AT POVERTY PERE LACHAISE IF YOU PLEASE", "subset": "test_other", "task_type": "understanding", "prediction": "the bourgeois did not care much about being buried in the vaugirard it hinted at poverty per lachaise if you please", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3074, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0037.flac", "answer": "FAUCHELEVENT WHO WAS ILLITERATE BUT VERY SHARP UNDERSTOOD THAT HE HAD TO DEAL WITH A FORMIDABLE SPECIES OF MAN WITH A FINE TALKER HE MUTTERED", "subset": "test_other", "task_type": "understanding", "prediction": "fauchelevent who was illiterate but very sharp understood that he had to deal with a formidable species of man with a fine talker he muttered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3075, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0044.flac", "answer": "THEY WERE ONLY A FEW TURNS OF THE WHEEL DISTANT FROM THE SMALL ALLEY LEADING TO THE NUNS CORNER", "subset": "test_other", "task_type": "understanding", "prediction": "they were only a few turns of the wheel distant from the small alley leading to the nuns corner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3076, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0045.flac", "answer": "AND HE ADDED WITH THE SATISFACTION OF A SERIOUS MAN WHO IS TURNING A PHRASE WELL", "subset": "test_other", "task_type": "understanding", "prediction": "and he added with the satisfaction of a serious man who is turning a phrase well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3077, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0000.flac", "answer": "ON THE FOLLOWING DAY AS THE SUN WAS DECLINING THE VERY RARE PASSERS BY ON THE BOULEVARD DU MAINE PULLED OFF THEIR HATS TO AN OLD FASHIONED HEARSE ORNAMENTED WITH SKULLS CROSS BONES AND TEARS", "subset": "test_other", "task_type": "understanding", "prediction": "on the following day as the sun was declining the very rare passers by on the boulevard du menin pulled off their hats to an old fashioned hearse ornamented with skulls crossbones and tears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3078, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0014.flac", "answer": "A PRINCE IS NOTHING IN THE PRESENCE OF A PRINCIPLE", "subset": "test_other", "task_type": "understanding", "prediction": "a prince is nothing in the presence of a principle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3079, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0022.flac", "answer": "THE MAN REPLIED THE GRAVE DIGGER", "subset": "test_other", "task_type": "understanding", "prediction": "the man replied the gravedigger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3080, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0019.flac", "answer": "HE DID WHAT HE LIKED WITH HIM HE MADE HIM DANCE ACCORDING TO HIS WHIM", "subset": "test_other", "task_type": "understanding", "prediction": "he did what he liked with him he made him dance according to his whim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3081, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0023.flac", "answer": "THE GRAVE DIGGER YES", "subset": "test_other", "task_type": "understanding", "prediction": "the grave digger yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3082, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0010.flac", "answer": "IT IS ONE OF THE FAULTS WHICH RESEMBLE A DUTY", "subset": "test_other", "task_type": "understanding", "prediction": "it is one of the faults which resemble a duty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3083, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0033.flac", "answer": "THE MAN REPLIED", "subset": "test_other", "task_type": "understanding", "prediction": "the man replied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3084, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0025.flac", "answer": "FATHER MESTIENNE IS THE GRAVE DIGGER HE WAS", "subset": "test_other", "task_type": "understanding", "prediction": "father mestienne is the grave digger he was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3085, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0028.flac", "answer": "HE HAD HARDLY THE STRENGTH TO STAMMER", "subset": "test_other", "task_type": "understanding", "prediction": "he had hardly the strength to stammer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3086, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0034.flac", "answer": "HE LIMPED MORE OUT OF ANXIETY THAN FROM INFIRMITY", "subset": "test_other", "task_type": "understanding", "prediction": "he limped more out of anxiety than from infirmity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3087, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0029.flac", "answer": "BUT HE PERSISTED FEEBLY FATHER MESTIENNE IS THE GRAVE DIGGER", "subset": "test_other", "task_type": "understanding", "prediction": "but he persisted feebly father mestienne is the gravedigger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3088, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0027.flac", "answer": "IT IS TRUE NEVERTHELESS THAT GRAVE DIGGERS DO DIE THEMSELVES", "subset": "test_other", "task_type": "understanding", "prediction": "it is true nevertheless that gravediggers do die themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3089, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0032.flac", "answer": "ARE YOU NOT COMRADE WE'LL GO AND HAVE A DRINK TOGETHER PRESENTLY", "subset": "test_other", "task_type": "understanding", "prediction": "are you not comrade we will go and have a drink together presently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3090, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0039.flac", "answer": "THE MAN REPLIED COMPLETELY", "subset": "test_other", "task_type": "understanding", "prediction": "the man replied completely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3091, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0005.flac", "answer": "THESE GATES THEREFORE SWUNG INEXORABLY ON THEIR HINGES AT THE INSTANT WHEN THE SUN DISAPPEARED BEHIND THE DOME OF THE INVALIDES", "subset": "test_other", "task_type": "understanding", "prediction": "these gates therefore swung inexorably on their hinges at the instant when the sun disappeared behind the dome of the invalides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3092, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0015.flac", "answer": "FAUCHELEVENT LIMPED ALONG BEHIND THE HEARSE IN A VERY CONTENTED FRAME OF MIND", "subset": "test_other", "task_type": "understanding", "prediction": "fauchelevent limped along behind the hearse in a very contented frame of mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3093, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0040.flac", "answer": "THE GOOD GOD CONSULTED HIS NOTE BOOK WHICH SHOWS WHEN THE TIME IS UP IT WAS FATHER MESTIENNE'S TURN FATHER MESTIENNE DIED", "subset": "test_other", "task_type": "understanding", "prediction": "the good god consulted his notebook which shows when the time is up it was father mestien s turn father mestien died", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3094, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0011.flac", "answer": "THE NUNS HAD COMMITTED IT NOT ONLY WITHOUT DIFFICULTY BUT EVEN WITH THE APPLAUSE OF THEIR OWN CONSCIENCES", "subset": "test_other", "task_type": "understanding", "prediction": "the nuns had committed it not only without difficulty but even with the applause of their own consciences", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3095, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0018.flac", "answer": "HE PLAYED WITH FATHER MESTIENNE", "subset": "test_other", "task_type": "understanding", "prediction": "he played with father mestienne", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3096, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0017.flac", "answer": "WHAT REMAINED TO BE DONE WAS A MERE NOTHING", "subset": "test_other", "task_type": "understanding", "prediction": "what remained to be done was a mere nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3097, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0041.flac", "answer": "STAMMERED FAUCHELEVENT IT IS MADE", "subset": "test_other", "task_type": "understanding", "prediction": "stammered fauchelevent it is made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3098, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0021.flac", "answer": "HE WAS A SORT OF LABORING MAN WHO WORE A WAISTCOAT WITH LARGE POCKETS AND CARRIED A MATTOCK UNDER HIS ARM", "subset": "test_other", "task_type": "understanding", "prediction": "he was a sort of labouring man who wore a waistcoat with large pockets and carried a mattock under his arm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3099, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3764/168671/3764-168671-0020.flac", "answer": "THE PERMISSION FOR INTERMENT MUST BE EXHIBITED", "subset": "test_other", "task_type": "understanding", "prediction": "the permission for interment must be exhibited", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0002.flac", "answer": "HE WAS CURIOUS ABOUT THAT BLACK HEADED COUSIN OF OL MISTAH BUZZARD VERY CURIOUS INDEED", "subset": "test_other", "task_type": "understanding", "prediction": "he was curious about that black headed cousin of old mr buzzard very curious indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0017.flac", "answer": "THEY LIKE TO CHOKE THAT NO COUNT BUZZARD TO DEATH", "subset": "test_other", "task_type": "understanding", "prediction": "they d like to choke that no count buzzer to death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0020.flac", "answer": "IT WAS JUST AS GOOD AS ONE OF GRANDFATHER FROG'S", "subset": "test_other", "task_type": "understanding", "prediction": "it was just as good as one of grandfather frog s", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0018.flac", "answer": "WHEN HE GET HOME HE TRY AN TRY TO BRUSH THAT SOOT OFF BUT IT DONE GET INTO THE SKIN AN IT STAY THERE", "subset": "test_other", "task_type": "understanding", "prediction": "when he get home he try and try to brush the soot off but it done get into the skin and it stay there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0013.flac", "answer": "WHY HE JES STRETCH HIS FOOL HAID AS FAR DOWN THAT CHIMNEY AS HE CAN AN LISTEN AN LISTEN", "subset": "test_other", "task_type": "understanding", "prediction": "why he just stretch his fool head as far down the chimney as he can and listen and listen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0012.flac", "answer": "IT WAS ON A LIL OL HOUSE A LIL OL TUMBLE DOWN HOUSE", "subset": "test_other", "task_type": "understanding", "prediction": "it was on a little old house a little old tumble down house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0019.flac", "answer": "A LITTLE SIGH OF SATISFACTION WENT AROUND THE CIRCLE OF LISTENERS", "subset": "test_other", "task_type": "understanding", "prediction": "a little sigh of satisfaction went round the circle of listeners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0015.flac", "answer": "WILL YO' ALLS PLEASE SPEAK A LIL LOUDER HE HOLLER DOWN THE CHIMNEY JES LIKE THAT", "subset": "test_other", "task_type": "understanding", "prediction": "will you all please speak a little louder he hollered down the chimney just like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0011.flac", "answer": "ONE DAY THIS NO COUNT TRIFLING COUSIN OF GRANDPAP BUZZARD GET COLD IN HIS FEET", "subset": "test_other", "task_type": "understanding", "prediction": "one day this no count trifling cousin of grand pop buzzard get cold in his feet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0001.flac", "answer": "THIS SOUNDED LIKE ANOTHER STORY", "subset": "test_other", "task_type": "understanding", "prediction": "this sounded like another story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0010.flac", "answer": "SO WE UNS SIT ON THE CHIMNEY TOPS WHENEVER OL JACK FROST GETS TO STRAYING DOWN WHERE HE HAVE NO BUSINESS", "subset": "test_other", "task_type": "understanding", "prediction": "so we uns set on the chimney tops whenever old jack frost gets to straying down where he have no business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0014.flac", "answer": "BUT HE DON'T MIND THAT", "subset": "test_other", "task_type": "understanding", "prediction": "but he dont mind that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0004.flac", "answer": "PLEASE MISTER BUZZARD PLEASE TELL US THE STORY HE BEGGED", "subset": "test_other", "task_type": "understanding", "prediction": "please mr buzzard please tell us the story he begged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0000.flac", "answer": "OL MISTAH BUZZARD GRINNED", "subset": "test_other", "task_type": "understanding", "prediction": "old mr buzzard grinned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0007.flac", "answer": "LIKE MOST NO COUNT PEOPLE HE USED TO MAKE A REGULAR NUISANCE OF HISSELF POKING HIS NOSE INTO EV'YBODY'S BUSINESS AND NEVER TENDING TO HIS OWN", "subset": "test_other", "task_type": "understanding", "prediction": "like most no count people he used to make a regular nuisance of himself poking his nose into everybodys business and never attending to his own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0005.flac", "answer": "NOW OL MISTAH BUZZARD IS NATURALLY GOOD NATURED AND ACCOMMODATING AND WHEN PETER BEGGED SO HARD HE JUST COULDN'T FIND IT IN HIS HEART TO REFUSE", "subset": "test_other", "task_type": "understanding", "prediction": "now old mr buzzard is naturally good natured and accommodating and when peter begged so hard he just could n t find it in his heart to refuse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0008.flac", "answer": "WASN'T ANYTHING GOING ON THAT THIS TRIFLING MEMBER OF THE BUZZARD FAM'LY DIDN'T FIND OUT ABOUT AND MEDDLE IN HE COULD ASK MO QUESTIONS THAN PETER RABBIT CAN AN ANYBODY THAT CAN DO THAT HAS GOT TO ASK A LOT", "subset": "test_other", "task_type": "understanding", "prediction": "wasn t anything going on that this trifling member of the buzzard family didn t find out about and meddle in he could ask more questions than peter rabbit can and anybody that can do that has got to ask a lot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0006.flac", "answer": "WAY BACK IN THE DAYS WHEN GRANDPAP BUZZARD HAD HIS LIL FALLING OUT WITH OL KING EAGLE AND DONE FLY SO HIGH HE SCO'TCH THE FEATHERS OFFEN HIS HAID HE HAD A COUSIN DID GRANDPAP BUZZARD AND THIS COUSIN WAS JES NATURALLY LAZY AND NO COUNT", "subset": "test_other", "task_type": "understanding", "prediction": "way back in the days when grandpa buzzard had his little falling out with old king eagle and done fly so high he scorched the feathers off'n his head he had a cousin did grandpa buzzard and this cousin was just naturally lazy and no count", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0009.flac", "answer": "EVERYBODY LOOKED AT PETER AND LAUGHED", "subset": "test_other", "task_type": "understanding", "prediction": "everybody looked at peter and laughed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0016.flac", "answer": "YES SAH SHE SHO'LY WAS PLUMB SCARED", "subset": "test_other", "task_type": "understanding", "prediction": "yas sah she shoaly was plum scared", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/182399/3997-182399-0003.flac", "answer": "ANYWAY HE WOULD FIND OUT", "subset": "test_other", "task_type": "understanding", "prediction": "anyway he would find out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0028.flac", "answer": "LOOK HERE PRUDENCE DO YOU KNOW WHAT HE WANTS SAID MARGUERITE", "subset": "test_other", "task_type": "understanding", "prediction": "look here prudence do you know what he wants said marguerite", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0001.flac", "answer": "YOU IN THE WAY MARGUERITE BUT HOW", "subset": "test_other", "task_type": "understanding", "prediction": "you in the way marguerite but how", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0019.flac", "answer": "IT MEANS LITTLE ENOUGH TO THEM THAT WE SHOULD HAVE TEN LOVERS EXTRA AS LONG AS THEY GET DRESSES OR A BRACELET OUT OF THEM AND THAT THEY CAN DRIVE IN OUR CARRIAGE FROM TIME TO TIME OR COME TO OUR BOX AT THE THEATRE", "subset": "test_other", "task_type": "understanding", "prediction": "it means little enough to them that we should have ten lovers extra as long as they get dresses or a bracelet out of them and that they can drive in our carriage from time to time or come to our box at the theatre", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0006.flac", "answer": "BECAUSE I AM WATCHED AND THE LEAST SUSPICION MIGHT DO ME THE GREATEST HARM", "subset": "test_other", "task_type": "understanding", "prediction": "because i am watched and the least suspicion might do me the greatest harm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0004.flac", "answer": "MY DEAR PRUDENCE I ANSWERED YOU DO NOT KNOW WHAT YOU ARE SAYING", "subset": "test_other", "task_type": "understanding", "prediction": "my dear prudence i answered you do not know what you are saying", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0011.flac", "answer": "WELL GOOD HEAVENS THE MEANS WERE EASY ENOUGH TO GUESS", "subset": "test_other", "task_type": "understanding", "prediction": "well good heavens the means were easy enough to guess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0008.flac", "answer": "IF THERE WERE ANY OTHER I WOULD TELL YOU FOR WE ARE NOT TO HAVE ANY SECRETS FROM ONE ANOTHER NOW", "subset": "test_other", "task_type": "understanding", "prediction": "if there were any other i would tell you for we are not to have any secrets from one another now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0005.flac", "answer": "YES BUT BESIDES NOT WISHING TO PUT YOU OUT I WAS SURE THAT IF YOU CAME AS FAR AS MY DOOR YOU WOULD WANT TO COME UP AND AS I COULD NOT LET YOU I DID NOT WISH TO LET YOU GO AWAY BLAMING ME FOR SAYING NO", "subset": "test_other", "task_type": "understanding", "prediction": "yes but besides not wishing to put you out i was sure that if you came as far as my door you would want to come up and as i could not let you i did not wish to let you go away blaming me for saying no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0003.flac", "answer": "DURING THIS REMARK MARGUERITE LOOKED AT ME ATTENTIVELY", "subset": "test_other", "task_type": "understanding", "prediction": "during this remark marguerite looked at me attentively", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0007.flac", "answer": "IS THAT REALLY THE ONLY REASON", "subset": "test_other", "task_type": "understanding", "prediction": "is that really the only reason", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0010.flac", "answer": "I FANCIED FOR A MOMENT THAT I MIGHT GIVE MYSELF THAT HAPPINESS FOR SIX MONTHS YOU WOULD NOT HAVE IT YOU INSISTED ON KNOWING THE MEANS", "subset": "test_other", "task_type": "understanding", "prediction": "i fancied for a moment that i might give myself that happiness for six months you would not have it you insisted on knowing the means", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0002.flac", "answer": "WELL YOU MIGHT HAVE HAD A WOMAN HERE SAID PRUDENCE AND IT WOULD HARDLY HAVE BEEN AMUSING FOR HER TO SEE TWO MORE ARRIVE", "subset": "test_other", "task_type": "understanding", "prediction": "well you might have had a woman here said prudence and it would hardly have been amusing for her to see two more arrive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0009.flac", "answer": "HONESTLY DO YOU CARE FOR ME A LITTLE A GREAT DEAL", "subset": "test_other", "task_type": "understanding", "prediction": "honestly do you care for me a little a great deal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0030.flac", "answer": "ONE HAS TO BUT HE WANTS MORE THAN THAT WHAT THEN", "subset": "test_other", "task_type": "understanding", "prediction": "one has to but he wants more than that what then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0029.flac", "answer": "HE WANTS YOU TO FORGIVE HIM", "subset": "test_other", "task_type": "understanding", "prediction": "he wants you to forgive him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0021.flac", "answer": "I THOUGHT I COULD ACCEPT THE LIFE WHICH HE OFFERED ME BUT WHAT WOULD YOU HAVE", "subset": "test_other", "task_type": "understanding", "prediction": "i thought i could accept the life which he offered me but what would you have", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0025.flac", "answer": "MARGUERITE DREW THE LETTER FROM HER BOSOM AND HANDING IT TO ME WITH A SMILE OF INFINITE SWEETNESS SAID", "subset": "test_other", "task_type": "understanding", "prediction": "marguerite drew the letter from her bosom and handing it to me with a smile of infinite sweetness said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0012.flac", "answer": "I LISTENED AND I GAZED AT MARGUERITE WITH ADMIRATION", "subset": "test_other", "task_type": "understanding", "prediction": "i listened and i gazed at marguerite with admiration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0023.flac", "answer": "MARGUERITE TIRED OUT WITH THIS LONG CONFESSION THREW HERSELF BACK ON THE SOFA AND TO STIFLE A SLIGHT COUGH PUT UP HER HANDKERCHIEF TO HER LIPS AND FROM THAT TO HER EYES", "subset": "test_other", "task_type": "understanding", "prediction": "marguerite tired out with this long confession threw herself back on the sofa and to stifle a slight cough put up her handkerchief to her lips and from that to her eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0015.flac", "answer": "WE ARE NOT ALLOWED TO HAVE HEARTS UNDER PENALTY OF BEING HOOTED DOWN AND OF RUINING OUR CREDIT", "subset": "test_other", "task_type": "understanding", "prediction": "we are not allowed to have hearts under penalty of being hooted down and of ruining our credit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0018.flac", "answer": "NEVER DO THEY GIVE YOU ADVICE WHICH IS NOT LUCRATIVE", "subset": "test_other", "task_type": "understanding", "prediction": "never do they give you advice which is not lucrative", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0016.flac", "answer": "WE NO LONGER BELONG TO OURSELVES", "subset": "test_other", "task_type": "understanding", "prediction": "we no longer belong to ourselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0017.flac", "answer": "WE STAND FIRST IN THEIR SELF ESTEEM LAST IN THEIR ESTEEM", "subset": "test_other", "task_type": "understanding", "prediction": "we stand first in their self esteem last in their esteem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0014.flac", "answer": "TRULY SHE CONTINUED WE POOR CREATURES OF CHANCE HAVE FANTASTIC DESIRES AND INCONCEIVABLE LOVES", "subset": "test_other", "task_type": "understanding", "prediction": "truly she continued we poor creatures of chance have fantastic desire and inconceivable loves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0024.flac", "answer": "MARGUERITE DO WITH ME AS YOU WILL I AM YOUR SLAVE YOUR DOG BUT IN THE NAME OF HEAVEN TEAR UP THE LETTER WHICH I WROTE TO YOU AND DO NOT MAKE ME LEAVE YOU TO MORROW IT WOULD KILL ME", "subset": "test_other", "task_type": "understanding", "prediction": "marguerite do with me as you will i am your slave your dog but in the name of heaven tear up the letter which i wrote to you and do not make me leave you to morrow it would kill me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0000.flac", "answer": "I HAVE NOT COME TO HINDER YOU FROM LEAVING PARIS", "subset": "test_other", "task_type": "understanding", "prediction": "i have not come to hinder you from leaving paris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0026.flac", "answer": "HERE IT IS I HAVE BROUGHT IT BACK", "subset": "test_other", "task_type": "understanding", "prediction": "here it is i have brought it back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0031.flac", "answer": "I EMBRACED MARGUERITE UNTIL SHE WAS ALMOST STIFLED", "subset": "test_other", "task_type": "understanding", "prediction": "i embraced marguerite until she was almost stifled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0013.flac", "answer": "WHEN I THOUGHT THAT THIS MARVELLOUS CREATURE WHOSE FEET I HAD ONCE LONGED TO KISS WAS WILLING TO LET ME TAKE MY PLACE IN HER THOUGHTS MY PART IN HER LIFE AND THAT I WAS NOT YET CONTENT WITH WHAT SHE GAVE ME I ASKED IF MAN'S DESIRE HAS INDEED LIMITS WHEN SATISFIED AS PROMPTLY AS MINE HAD BEEN IT REACHED AFTER SOMETHING FURTHER", "subset": "test_other", "task_type": "understanding", "prediction": "when i thought that this marvellous creature whose feet i had once longed to kiss was willing to let me take my place in her thoughts my part in her life and that i was not yet content with what she gave me i asked if man s desire had indeed limits when satisfied as promptly as mine had been it reached after something further", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0027.flac", "answer": "I TORE THE LETTER INTO FRAGMENTS AND KISSED WITH TEARS THE HAND THAT GAVE IT TO ME", "subset": "test_other", "task_type": "understanding", "prediction": "i tore the letter into fragments and kissed with tears the hand that gave it to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0022.flac", "answer": "WHAT I LOVED IN YOU WAS NOT THE MAN WHO WAS BUT THE MAN WHO WAS GOING TO BE", "subset": "test_other", "task_type": "understanding", "prediction": "what i loved in you was not the man who was but the man who was going to be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180297/3997-180297-0020.flac", "answer": "SUCH A MAN I FOUND IN THE DUKE BUT THE DUKE IS OLD AND OLD AGE NEITHER PROTECTS NOR CONSOLES", "subset": "test_other", "task_type": "understanding", "prediction": "such a man i found in the duke but the duke is old and old age neither protects nor consoles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0021.flac", "answer": "MY WHOLE BEING WAS EXALTED INTO JOY AT THE MEMORY OF THE WORDS WE HAD EXCHANGED DURING THAT FIRST NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "my whole being was exalted into joy at the memory of the words we had exchanged during that first night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0031.flac", "answer": "YOU STILL LOVE ME CAN YOU ASK", "subset": "test_other", "task_type": "understanding", "prediction": "you still love me can you ask", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0023.flac", "answer": "COME DURING THE THIRD ENTR'ACTE", "subset": "test_other", "task_type": "understanding", "prediction": "come during the third entrant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0022.flac", "answer": "HERE ARE MY ORDERS TO NIGHT AT THE VAUDEVILLE", "subset": "test_other", "task_type": "understanding", "prediction": "here are my orders tonight at the vaudeville", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0008.flac", "answer": "THE MORE A GIRL BELIEVES IN GOODNESS THE MORE EASILY WILL SHE GIVE WAY IF NOT TO HER LOVER AT LEAST TO LOVE FOR BEING WITHOUT MISTRUST SHE IS WITHOUT FORCE AND TO WIN HER LOVE IS A TRIUMPH THAT CAN BE GAINED BY ANY YOUNG MAN OF FIVE AND TWENTY SEE HOW YOUNG GIRLS ARE WATCHED AND GUARDED", "subset": "test_other", "task_type": "understanding", "prediction": "the more a girl believes in goodness the more isli will she give way if not to her lover at least to love for being without mistrust she is without force and to win her love is a triumph that can be gained by any young man of five and twenty see how young girls are watched and guarded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0015.flac", "answer": "IT IS THE SAME WITH THESE UNHAPPY WOMEN WHEN THEY LOVE SERIOUSLY", "subset": "test_other", "task_type": "understanding", "prediction": "this is the same with these unhappy women when they love seriously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0030.flac", "answer": "WHERE AT HOME", "subset": "test_other", "task_type": "understanding", "prediction": "where at home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0011.flac", "answer": "THEY LOVE BY PROFESSION AND NOT BY INSTINCT", "subset": "test_other", "task_type": "understanding", "prediction": "they love by profession and not by instinct", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0014.flac", "answer": "IN ORDER TO DISTURB THE LABOURERS IN THE FIELD WAS ONE DAY DEVOURED BY A WOLF BECAUSE THOSE WHOM HE HAD SO OFTEN DECEIVED NO LONGER BELIEVED IN HIS CRIES FOR HELP", "subset": "test_other", "task_type": "understanding", "prediction": "in order to disturb the laborers in the fields was one day devoured by a wolf because those whom he had so often deceived no longer believed in his cries for help", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0020.flac", "answer": "HOW WHY", "subset": "test_other", "task_type": "understanding", "prediction": "how why", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0006.flac", "answer": "IT SEEMED TO ME AS IF THIS SLEEPING CITY BELONGED TO ME I SEARCHED MY MEMORY FOR THE NAMES OF THOSE WHOSE HAPPINESS I HAD ONCE ENVIED AND I COULD NOT RECALL ONE WITHOUT FINDING MYSELF THE HAPPIER", "subset": "test_other", "task_type": "understanding", "prediction": "it seems to me as if this sleeping city belongs to me i searched my memory for the names of those whose happiness i had once envied and i could not recall one without finding myself the happier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0000.flac", "answer": "THE DUKE COMES EVERY MORNING THEY WILL TELL HIM WHEN HE COMES THAT I AM ASLEEP AND PERHAPS HE WILL WAIT UNTIL I WAKE", "subset": "test_other", "task_type": "understanding", "prediction": "the duke comes every morning they will tell him when he comes that i am asleep and perhaps he will wait until i awake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0027.flac", "answer": "DID SHE LOVE ME ENOUGH TO BELIEVE THAT THE MORE BEAUTIFUL SHE LOOKED THE HAPPIER I SHOULD BE", "subset": "test_other", "task_type": "understanding", "prediction": "does she love me enough to believe that the more beautiful she looks the happier i should be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0012.flac", "answer": "WHEN A CREATURE WHO HAS ALL HER PAST TO REPROACH HERSELF WITH IS TAKEN ALL AT ONCE BY A PROFOUND SINCERE IRRESISTIBLE LOVE OF WHICH SHE HAD NEVER FELT HERSELF CAPABLE WHEN SHE HAS CONFESSED HER LOVE HOW ABSOLUTELY THE MAN WHOM SHE LOVES DOMINATES HER", "subset": "test_other", "task_type": "understanding", "prediction": "when a creature who has all her past to reproach herself with is taken all at once by a profound sincere irresistible love of which she had never felt herself capable when she has confessed her love how absolutely the man whom she loves dominates her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0018.flac", "answer": "WHEN I REACHED HOME I WAS IN A STATE OF MAD GAIETY", "subset": "test_other", "task_type": "understanding", "prediction": "when i reached home i was in a state of mad gaiety", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0007.flac", "answer": "EDUCATION FAMILY FEELING THE SENSE OF DUTY THE FAMILY ARE STRONG SENTINELS BUT THERE ARE NO SENTINELS SO VIGILANT AS NOT TO BE DECEIVED BY A GIRL OF SIXTEEN TO WHOM NATURE BY THE VOICE OF THE MAN SHE LOVES GIVES THE FIRST COUNSELS OF LOVE ALL THE MORE ARDENT BECAUSE THEY SEEM SO PURE", "subset": "test_other", "task_type": "understanding", "prediction": "education family feeling the sense of duty the family are strong sentinels but there are no sentinels so vigilant as not to be deceived by a girl of sixteen to whom nature by the voice of the man she loves gives the first counsel of love all the more ardent because they seem so pure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0004.flac", "answer": "I DON'T KNOW HOW IT IS BUT IT SEEMS TO ME AS IF I DO", "subset": "test_other", "task_type": "understanding", "prediction": "i don t know how it is but it seems to me as if i do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0005.flac", "answer": "NOW GO I CAN'T KEEP MY EYES OPEN", "subset": "test_other", "task_type": "understanding", "prediction": "now go i can t keep my eyes open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0003.flac", "answer": "THERE ARE BOLTS ON THE DOOR WRETCH", "subset": "test_other", "task_type": "understanding", "prediction": "there are bolts in the door wretch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0032.flac", "answer": "BECAUSE YOU DON'T LIKE SEEING HIM", "subset": "test_other", "task_type": "understanding", "prediction": "because you dont like seeing him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0010.flac", "answer": "WITH THEM THE BODY HAS WORN OUT THE SOUL THE SENSES HAVE BURNED UP THE HEART DISSIPATION HAS BLUNTED THE FEELINGS", "subset": "test_other", "task_type": "understanding", "prediction": "with them the body has worn out the soul the senses have burned up the heart dissipation has blunted the feelings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0013.flac", "answer": "THEY KNOW NOT WHAT PROOF TO GIVE", "subset": "test_other", "task_type": "understanding", "prediction": "they know not what proof to give", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0033.flac", "answer": "NONETHELESS I WAS VERY UNHAPPY ALL THE REST OF THE EVENING AND WENT AWAY VERY SADLY AFTER HAVING SEEN PRUDENCE THE COUNT AND MARGUERITE GET INTO THE CARRIAGE WHICH WAS WAITING FOR THEM AT THE DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "none the less i was very unhappy all the rest of the evening and went away very sadly after having seen prudence the count and marguerite get into the carriage which was waiting for them at the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0019.flac", "answer": "THE WOMAN BECOMES THE MAN'S MISTRESS AND LOVES HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the woman becomes the man s mistress and loves him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0029.flac", "answer": "YOU SHOULD GO TO BED SHE REPLIED WITH THAT IRONICAL AIR WHICH WENT SO WELL WITH HER DELICATE AND WITTY FACE", "subset": "test_other", "task_type": "understanding", "prediction": "you should go to bed she replied with that ironic air which went so well with her delicate and witty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0002.flac", "answer": "WELL DO IT FOR ME FOR I SWEAR TO YOU THAT I DON'T LOVE YOU AS THE OTHERS HAVE LOVED YOU", "subset": "test_other", "task_type": "understanding", "prediction": "well do it for me for i swear to you that i dont love you as the others have loved you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0025.flac", "answer": "ONLY ONE REMAINED EMPTY THE STAGE BOX", "subset": "test_other", "task_type": "understanding", "prediction": "only one remains empty the stage box", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0001.flac", "answer": "YES BUT IF I SHOULD ALREADY ASK FOR SOMETHING WHAT", "subset": "test_other", "task_type": "understanding", "prediction": "yes but if i should already ask for something what", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0026.flac", "answer": "AT THE BEGINNING OF THE THIRD ACT I HEARD THE DOOR OF THE BOX ON WHICH MY EYES HAD BEEN ALMOST CONSTANTLY FIXED OPEN AND MARGUERITE APPEARED", "subset": "test_other", "task_type": "understanding", "prediction": "at the beginning of the third act i heard the door of the box on which my eyes had been almost constantly fixed open and marguerite appeared", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0024.flac", "answer": "THE BOXES FILLED ONE AFTER ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "the boxes filled one after another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0017.flac", "answer": "BUT TO RETURN TO THE FIRST DAY OF MY LIAISON", "subset": "test_other", "task_type": "understanding", "prediction": "but to return to the first day of my liaison", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0016.flac", "answer": "BUT WHEN THE MAN WHO INSPIRES THIS REDEEMING LOVE IS GREAT ENOUGH IN SOUL TO RECEIVE IT WITHOUT REMEMBERING THE PAST WHEN HE GIVES HIMSELF UP TO IT WHEN IN SHORT HE LOVES AS HE IS LOVED THIS MAN DRAINS AT ONE DRAUGHT ALL EARTHLY EMOTIONS AND AFTER SUCH A LOVE HIS HEART WILL BE CLOSED TO EVERY OTHER", "subset": "test_other", "task_type": "understanding", "prediction": "but when the man who inspires this redeeming love is great enough in soul to receive it without remembering the past when he gives himself up to it when in short he loves as he is loved this man drains at one draught all earthly emotions and after such a love his heart will be closed to every other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0028.flac", "answer": "WHAT IS THE MATTER WITH YOU TO NIGHT SAID MARGUERITE RISING AND COMING TO THE BACK OF THE BOX AND KISSING ME ON THE FOREHEAD", "subset": "test_other", "task_type": "understanding", "prediction": "what is the matter with you to night said marguerite rising and coming to the back of the box and kissing me on the forehead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3997/180294/3997-180294-0009.flac", "answer": "THEN HOW SURELY MUST THEY DESIRE THE WORLD WHICH IS HIDDEN FROM THEM HOW SURELY MUST THEY FIND IT TEMPTING HOW SURELY MUST THEY LISTEN TO THE FIRST VOICE WHICH COMES TO TELL ITS SECRETS THROUGH THEIR BARS AND BLESS THE HAND WHICH IS THE FIRST TO RAISE A CORNER OF THE MYSTERIOUS VEIL", "subset": "test_other", "task_type": "understanding", "prediction": "then how surely must they desire the world which is hidden from them how surely must they find it tempting how surely must they listen to the first voice which comes to tell its secrets through their bars and bless the hand which is the first to raise a corner of the mystery veil", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0068.flac", "answer": "I SOMETIMES THINK I SHALL BE MOPED WI SORROW EVEN IN THE CITY OF GOD IF FATHER IS NOT THERE", "subset": "test_other", "task_type": "understanding", "prediction": "i sometimes think i shall be moped with sorrow even in the city of god if father is not there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0029.flac", "answer": "THERE WERE SEVERAL OTHER SIGNS OF SOMETHING WRONG ABOUT MISSUS HALE", "subset": "test_other", "task_type": "understanding", "prediction": "there were several other signs of something wrong about mrs hale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0075.flac", "answer": "I WILL COME TO MORROW SAID MARGARET", "subset": "test_other", "task_type": "understanding", "prediction": "i will come to morrow said margaret", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0042.flac", "answer": "BUT FOR A MINUTE OR TWO SHE DID NOT SPEAK", "subset": "test_other", "task_type": "understanding", "prediction": "but for a minute or two she did not speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0008.flac", "answer": "HIS FATHER DYING IN MISERABLE CIRCUMSTANCES", "subset": "test_other", "task_type": "understanding", "prediction": "his father dying in miserable circumstances", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0003.flac", "answer": "I REALLY LIKED THAT ACCOUNT OF HIMSELF BETTER THAN ANYTHING ELSE HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "i really liked that account of himself better than anything else he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0010.flac", "answer": "HIS FATHER SPECULATED WILDLY FAILED AND THEN KILLED HIMSELF BECAUSE HE COULD NOT BEAR THE DISGRACE", "subset": "test_other", "task_type": "understanding", "prediction": "his father speculated wildly failed and then killed himself because he could not bear the disgrace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0084.flac", "answer": "WHY I WOULD APPLY TO SOME GOOD HOUSE MOTHER TO RECOMMEND ME ONE KNOWN TO HERSELF OR HER SERVANTS", "subset": "test_other", "task_type": "understanding", "prediction": "well i i would apply to some good housemother to recommend me one known to herself or her servants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0051.flac", "answer": "THE SHARPNESS IN HER EYE TURNED TO A WISTFUL LONGING AS SHE MET MARGARET'S SOFT AND FRIENDLY GAZE", "subset": "test_other", "task_type": "understanding", "prediction": "the sharpness in her eye turned to a wistful longing as she met margaret s soft and friendly gaze", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0022.flac", "answer": "JUST AS SHE WAS LEAVING THE ROOM SHE HESITATED SHE WAS INCLINED TO MAKE AN ACKNOWLEDGMENT WHICH SHE THOUGHT WOULD PLEASE HER FATHER BUT WHICH TO BE FULL AND TRUE MUST INCLUDE A LITTLE ANNOYANCE", "subset": "test_other", "task_type": "understanding", "prediction": "just as she was leaving the room she hesitated she was inclined to make an acknowledgment which she thought would please her father but which to be full and true must include a little annoyance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0004.flac", "answer": "HIS STATEMENT OF HAVING BEEN A SHOP BOY WAS THE THING I LIKED BEST OF ALL", "subset": "test_other", "task_type": "understanding", "prediction": "his statement of having been a shop boy was the thing i liked best of all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0064.flac", "answer": "BUT HOO'S COME AT LAST AND HOO'S WELCOME AS LONG AS HOO'LL KEEP FROM PREACHING ON WHAT HOO KNOWS NOUGHT ABOUT", "subset": "test_other", "task_type": "understanding", "prediction": "but who s come at last an who s welcome as long as who ll keep from preaching on what who knows nought about", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0061.flac", "answer": "I BELIEVE WHAT I SEE AND NO MORE", "subset": "test_other", "task_type": "understanding", "prediction": "i believe what i see and no more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0040.flac", "answer": "I'M BETTER IN NOT BEING TORN TO PIECES BY COUGHING O'NIGHTS BUT I'M WEARY AND TIRED O MILTON AND LONGING TO GET AWAY TO THE LAND O BEULAH AND WHEN I THINK I'M FARTHER AND FARTHER OFF MY HEART SINKS AND I'M NO BETTER I'M WORSE", "subset": "test_other", "task_type": "understanding", "prediction": "i am better in not being torn to pieces by coughing o nights but i am weary and tired o milton and longing to get away to the land of boola and when i think i am farther and farther off my heart sinks and i am no better i am worse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0006.flac", "answer": "I DON'T THINK MISTER HALE YOU HAVE DONE QUITE RIGHT IN INTRODUCING SUCH A PERSON TO US WITHOUT TELLING US WHAT HE HAD BEEN", "subset": "test_other", "task_type": "understanding", "prediction": "i don think mr hale you have done quite right in introducing such a person to us without telling us what he had been", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0019.flac", "answer": "NOT VICIOUS HE NEVER SAID THAT", "subset": "test_other", "task_type": "understanding", "prediction": "not vicious he never said that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0086.flac", "answer": "THE MOTHER OF WHOM HE SPOKE TO US SAID MARGARET", "subset": "test_other", "task_type": "understanding", "prediction": "the mother of whom he spoke to us said margaret", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0015.flac", "answer": "HOW TAINTED ASKED HER FATHER", "subset": "test_other", "task_type": "understanding", "prediction": "how tainted asked her father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0031.flac", "answer": "ONCE MARGARET HAD GONE INTO THE CHAMBER SOON AFTER DIXON LEFT IT AND FOUND HER MOTHER ON HER KNEES AND AS MARGARET STOLE OUT SHE CAUGHT A FEW WORDS WHICH WERE EVIDENTLY A PRAYER FOR STRENGTH AND PATIENCE TO ENDURE SEVERE BODILY SUFFERING", "subset": "test_other", "task_type": "understanding", "prediction": "once margaret had gone into the chamber soon after dixon left it and found her mother on her knees and as margaret stole out she caught a few words which were evidently a prayer for strength and patience to endure severe bodily suffering", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0027.flac", "answer": "I DON'T SET HIM UP FOR A HERO OR ANYTHING OF THAT KIND", "subset": "test_other", "task_type": "understanding", "prediction": "i don t set him up for a hero or anything of that kind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0083.flac", "answer": "WHAT WOULD YOU DO PAPA HOW WOULD YOU SET ABOUT IT", "subset": "test_other", "task_type": "understanding", "prediction": "what would you do papa how would you set about it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0053.flac", "answer": "YO'LL NOT BE DAUNTED IF FATHER'S AT HOME AND SPEAKS A BIT GRUFFISH AT FIRST", "subset": "test_other", "task_type": "understanding", "prediction": "you will not be daunted if father is at home and speaks a bit gruffish at first", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0045.flac", "answer": "BESSY WAS SILENT IN HER TURN FOR A MINUTE OR TWO THEN SHE REPLIED", "subset": "test_other", "task_type": "understanding", "prediction": "bessie was silent in her turn for a minute or two then she replied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0066.flac", "answer": "BUT THE GIRL ONLY PLEADED THE MORE WITH MARGARET", "subset": "test_other", "task_type": "understanding", "prediction": "but the girl only pleaded the more with margaret", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0047.flac", "answer": "BUT WHAT WAS IT", "subset": "test_other", "task_type": "understanding", "prediction": "but what was it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0090.flac", "answer": "SHE SOUNDED TO BE SUCH A CAREFUL ECONOMICAL PERSON THAT I SHOULD LIKE ANY ONE OUT OF THE SAME FAMILY", "subset": "test_other", "task_type": "understanding", "prediction": "she sounded to be such a careful economical person that i should like any one out of the same family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0036.flac", "answer": "ONE AFTERNOON SHE MET BESSY HIGGINS IN THE STREET AND STOPPED TO SPEAK TO HER", "subset": "test_other", "task_type": "understanding", "prediction": "one afternoon she met bessie higgins in the street and stopped to speak to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0021.flac", "answer": "MARGARET WAS COLLECTING HER MOTHER'S WORKING MATERIALS AND PREPARING TO GO TO BED", "subset": "test_other", "task_type": "understanding", "prediction": "margaret was collecting her mother s working materials and preparing to go to bed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0020.flac", "answer": "IMPROVIDENT AND SELF INDULGENT WERE HIS WORDS", "subset": "test_other", "task_type": "understanding", "prediction": "improvident and self indulgent were his words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0074.flac", "answer": "I'LL GO TO BED IT'S BEST PLACE BUT CATCHING AT MARGARET'S GOWN YO'LL COME AGAIN I KNOW YO WILL BUT JUST SAY IT", "subset": "test_other", "task_type": "understanding", "prediction": "i ll go to bed its best place but catching at margaret s gown you ll come again i know you will but just say it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0011.flac", "answer": "ALL HIS FORMER FRIENDS SHRUNK FROM THE DISCLOSURES THAT HAD TO BE MADE OF HIS DISHONEST GAMBLING WILD HOPELESS STRUGGLES MADE WITH OTHER PEOPLE'S MONEY TO REGAIN HIS OWN MODERATE PORTION OF WEALTH", "subset": "test_other", "task_type": "understanding", "prediction": "all his former friends shrunk from the disclosures that had to be made of his dishonest gambling wild hopeless struggles made with other people s money to regain his own moderate portion of wealth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0093.flac", "answer": "TAKE NOTICE THAT IS NOT MY KIND OF HAUGHTINESS PAPA IF I HAVE ANY AT ALL WHICH I DON'T AGREE TO THOUGH YOU'RE ALWAYS ACCUSING ME OF IT", "subset": "test_other", "task_type": "understanding", "prediction": "take notice that this is not my kind of haughtiness papa if i have any at all which i don t agree to though you re always accusing me of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0069.flac", "answer": "THE FEVERISH COLOUR CAME INTO HER CHEEK AND THE FEVERISH FLAME INTO HER EYE", "subset": "test_other", "task_type": "understanding", "prediction": "the feverish colour came into her cheeks and the feverish flame into her eye", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0023.flac", "answer": "HOWEVER OUT IT CAME", "subset": "test_other", "task_type": "understanding", "prediction": "however out it came", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0043.flac", "answer": "AT LAST SHE SAID IN A LOW VOICE", "subset": "test_other", "task_type": "understanding", "prediction": "at last she said in a low voice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0030.flac", "answer": "SHE AND DIXON HELD MYSTERIOUS CONSULTATIONS IN HER BEDROOM FROM WHICH DIXON WOULD COME OUT CRYING AND CROSS AS WAS HER CUSTOM WHEN ANY DISTRESS OF HER MISTRESS CALLED UPON HER SYMPATHY", "subset": "test_other", "task_type": "understanding", "prediction": "she and dixon held mysterious consultations in a bedroom from which dixon would come out crying and cross as was her custom when any distress of her mistress called upon her sympathy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0007.flac", "answer": "I REALLY WAS VERY MUCH AFRAID OF SHOWING HIM HOW MUCH SHOCKED I WAS AT SOME PARTS OF WHAT HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "i really was very much afraid of showing him how much shocked i was at some parts of what he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0002.flac", "answer": "YOU DON'T MEAN THAT YOU THOUGHT ME SO SILLY", "subset": "test_other", "task_type": "understanding", "prediction": "you dont mean that you thought me so silly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0014.flac", "answer": "SO THEY LEFT MILTON", "subset": "test_other", "task_type": "understanding", "prediction": "so they left milton", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0037.flac", "answer": "WELL BESSY HOW ARE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "well bessie how are you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0018.flac", "answer": "AND THE POOR MEN AROUND HIM THEY WERE POOR BECAUSE THEY WERE VICIOUS OUT OF THE PALE OF HIS SYMPATHIES BECAUSE THEY HAD NOT HIS IRON NATURE AND THE CAPABILITIES THAT IT GIVES HIM FOR BEING RICH", "subset": "test_other", "task_type": "understanding", "prediction": "and the poor men around him they were poor because they were vicious out of the pale of his sympathies because they had not his iron nature and the capabilities that it gives him for being rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0039.flac", "answer": "NOT EXACTLY REPLIED MARGARET SMILING", "subset": "test_other", "task_type": "understanding", "prediction": "not exactly replied margaret smiling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0046.flac", "answer": "NOUGHT WORSE THAN MANY OTHERS I RECKON", "subset": "test_other", "task_type": "understanding", "prediction": "not worse than many others i reckon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0065.flac", "answer": "IT'S SIMPLE AND NOT FAR TO FETCH NOR HARD TO WORK", "subset": "test_other", "task_type": "understanding", "prediction": "its simple and not far to fetch nor hard to work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0041.flac", "answer": "MARGARET TURNED ROUND TO WALK ALONGSIDE OF THE GIRL IN HER FEEBLE PROGRESS HOMEWARD", "subset": "test_other", "task_type": "understanding", "prediction": "margaret turned around to walk alongside of the girl in her feeble progress homeward", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0026.flac", "answer": "PERSONALLY AS YOU CALL IT AND ALL", "subset": "test_other", "task_type": "understanding", "prediction": "personally as you call it and all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0055.flac", "answer": "GASPED BESSY AT LAST", "subset": "test_other", "task_type": "understanding", "prediction": "gasped bessie at last", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0005.flac", "answer": "YOU WHO WERE ALWAYS ACCUSING PEOPLE OF BEING SHOPPY AT HELSTONE", "subset": "test_other", "task_type": "understanding", "prediction": "you who were always accusing people of being shoppy at helston", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0089.flac", "answer": "PERHAPS SHE MAY HAVE A RELATION WHO MIGHT SUIT US AND BE GLAD OF OUR PLACE", "subset": "test_other", "task_type": "understanding", "prediction": "perhaps she may have a relation who might suit us and be glad of our place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0009.flac", "answer": "WHY IT MIGHT HAVE BEEN IN THE WORKHOUSE", "subset": "test_other", "task_type": "understanding", "prediction": "why it might have been in the workhouse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0060.flac", "answer": "BUT SURELY SAID MARGARET FACING ROUND YOU BELIEVE IN WHAT I SAID THAT GOD GAVE HER LIFE AND ORDERED WHAT KIND OF LIFE IT WAS TO BE", "subset": "test_other", "task_type": "understanding", "prediction": "but surely said margaret facing round you believe in what i said that god gave her life and ordered what kind of life it was to be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0067.flac", "answer": "DON'T THINK HARDLY ON HIM HE'S A GOOD MAN HE IS", "subset": "test_other", "task_type": "understanding", "prediction": "dont think hardly on him he is a good man he is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0078.flac", "answer": "HAVE YOU MET WITH A SERVANT DEAR", "subset": "test_other", "task_type": "understanding", "prediction": "have you met with a servant do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0082.flac", "answer": "I MAY BE THE CINDERELLA TO PUT ON THE SLIPPER AFTER ALL", "subset": "test_other", "task_type": "understanding", "prediction": "i may be the cinderella to put on the slipper after all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0059.flac", "answer": "NOW I'LL NOT HAVE MY WENCH PREACHED TO", "subset": "test_other", "task_type": "understanding", "prediction": "now i ll not have my wench preached to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0071.flac", "answer": "SHE PUT HER HAND TO IT AND BECAME GHASTLY PALE", "subset": "test_other", "task_type": "understanding", "prediction": "she put her hand to it and became ghastly pale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0025.flac", "answer": "AND I DO SAID HER FATHER LAUGHING", "subset": "test_other", "task_type": "understanding", "prediction": "and i do said her father laughing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0094.flac", "answer": "I DON'T KNOW POSITIVELY THAT IT IS HERS EITHER BUT FROM LITTLE THINGS I HAVE GATHERED FROM HIM I FANCY SO", "subset": "test_other", "task_type": "understanding", "prediction": "i don t know positively that it is hers either but from little things i have gathered from him i fancy sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0056.flac", "answer": "BESSY TOOK A LONG AND FEVERISH DRAUGHT AND THEN FELL BACK AND SHUT HER EYES", "subset": "test_other", "task_type": "understanding", "prediction": "bessie took a long and feverish draught and then fell back and shut her eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0062.flac", "answer": "THAT'S WHAT I BELIEVE YOUNG WOMAN", "subset": "test_other", "task_type": "understanding", "prediction": "that is what i believe young woman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0038.flac", "answer": "BETTER AND NOT BETTER IF YO KNOW WHAT THAT MEANS", "subset": "test_other", "task_type": "understanding", "prediction": "better and not better if you know what that means", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0076.flac", "answer": "MARGARET WENT AWAY VERY SAD AND THOUGHTFUL", "subset": "test_other", "task_type": "understanding", "prediction": "margaret went away very sad and thoughtful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0087.flac", "answer": "MISSUS THORNTON THE ONLY MOTHER HE HAS I BELIEVE SAID MISTER HALE QUIETLY", "subset": "test_other", "task_type": "understanding", "prediction": "mr thornton the only mother he has i believe said mr hale quietly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0048.flac", "answer": "YOU KNOW I'M A STRANGER HERE SO PERHAPS I'M NOT SO QUICK AT UNDERSTANDING WHAT YOU MEAN AS IF I'D LIVED ALL MY LIFE AT MILTON", "subset": "test_other", "task_type": "understanding", "prediction": "you know i am a stranger here so perhaps i am not so quick at understanding what you mean as if i had lived all my life in milton", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0058.flac", "answer": "REMEMBER WHO GAVE IT YOU AND MADE IT WHAT IT IS", "subset": "test_other", "task_type": "understanding", "prediction": "remember who gave it to you and made it what it is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0079.flac", "answer": "NO MAMMA THAT ANNE BUCKLEY WOULD NEVER HAVE DONE", "subset": "test_other", "task_type": "understanding", "prediction": "no mamma that ann buckley would never have done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0085.flac", "answer": "VERY GOOD BUT WE MUST FIRST CATCH OUR HOUSE MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "very good but we must first catch our house mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0033.flac", "answer": "SHE LAY AWAKE VERY LONG THIS NIGHT PLANNING HOW TO LESSEN THE EVIL INFLUENCE OF THEIR MILTON LIFE ON HER MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "she lay awake very long this night planning how to lessen the evil influence of the milton life on her mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0077.flac", "answer": "SHE WAS LATE FOR TEA AT HOME", "subset": "test_other", "task_type": "understanding", "prediction": "she was late for tea at home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0081.flac", "answer": "EVERYBODY ELSE HAS HAD THEIR TURN AT THIS GREAT DIFFICULTY NOW LET ME TRY", "subset": "test_other", "task_type": "understanding", "prediction": "everybody else has had their turn at this great difficulty now let me try", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0088.flac", "answer": "I SHALL LIKE TO SEE HER SHE MUST BE AN UNCOMMON PERSON HER MOTHER ADDED", "subset": "test_other", "task_type": "understanding", "prediction": "i shall like to see her she must be an uncommon person her mother added", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0092.flac", "answer": "I AM SURE AT ANY RATE SHE WOULD NOT LIKE STRANGERS TO KNOW ANYTHING ABOUT IT", "subset": "test_other", "task_type": "understanding", "prediction": "i am sure at any rate she would not like strangers to know anything about it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0034.flac", "answer": "A SERVANT TO GIVE DIXON PERMANENT ASSISTANCE SHOULD BE GOT IF SHE GAVE UP HER WHOLE TIME TO THE SEARCH AND THEN AT ANY RATE HER MOTHER MIGHT HAVE ALL THE PERSONAL ATTENTION SHE REQUIRED AND HAD BEEN ACCUSTOMED TO HER WHOLE LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "a servant to give dixon permanent assistance should be got if she gave up the whole time to the search and then at any rate her mother might have all the personal attentions she required and had been accustomed to her whole life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0063.flac", "answer": "I DON'T BELIEVE ALL I HEAR NO NOT BY A BIG DEAL", "subset": "test_other", "task_type": "understanding", "prediction": "i don t believe all i hear no not by a big deal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0091.flac", "answer": "MY DEAR SAID MISTER HALE ALARMED PRAY DON'T GO OFF ON THAT IDEA", "subset": "test_other", "task_type": "understanding", "prediction": "my dear said mr hale alarmed pray do not go off on that idea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0013.flac", "answer": "AT LEAST NO FRIEND CAME FORWARDS IMMEDIATELY AND MISSUS THORNTON IS NOT ONE I FANCY TO WAIT TILL TARDY KINDNESS COMES TO FIND HER OUT", "subset": "test_other", "task_type": "understanding", "prediction": "at least no friend came forwards immediately and mr thornton is not one i fancy to wait till tardy kindness comes to find her out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0024.flac", "answer": "PAPA I DO THINK MISTER THORNTON A VERY REMARKABLE MAN BUT PERSONALLY I DON'T LIKE HIM AT ALL", "subset": "test_other", "task_type": "understanding", "prediction": "papa i do think mr thornton a very remarkable man but personally i don't like him at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0049.flac", "answer": "I HAD FORGOTTEN WHAT I SAID FOR THE TIME CONTINUED MARGARET QUIETLY", "subset": "test_other", "task_type": "understanding", "prediction": "i had forgotten what i said for the time continued margaret quietly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0012.flac", "answer": "NO ONE CAME FORWARDS TO HELP THE MOTHER AND THIS BOY", "subset": "test_other", "task_type": "understanding", "prediction": "no one came forwards to help the mother and this boy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0080.flac", "answer": "SUPPOSE I TRY SAID MISTER HALE", "subset": "test_other", "task_type": "understanding", "prediction": "spos i try said mr hale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0016.flac", "answer": "OH PAPA BY THAT TESTING EVERYTHING BY THE STANDARD OF WEALTH", "subset": "test_other", "task_type": "understanding", "prediction": "oh papa by that testing everything by the standard of wealth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0070.flac", "answer": "BUT YOU WILL BE THERE FATHER YOU SHALL OH MY HEART", "subset": "test_other", "task_type": "understanding", "prediction": "but you will be there father you shall oh my heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0017.flac", "answer": "WHEN HE SPOKE OF THE MECHANICAL POWERS HE EVIDENTLY LOOKED UPON THEM ONLY AS NEW WAYS OF EXTENDING TRADE AND MAKING MONEY", "subset": "test_other", "task_type": "understanding", "prediction": "when he spoke of the mechanical powers he evidently looked upon them only as new ways of extending trade and making money", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0057.flac", "answer": "MARGARET BENT OVER AND SAID BESSY DON'T BE IMPATIENT WITH YOUR LIFE WHATEVER IT IS OR MAY HAVE BEEN", "subset": "test_other", "task_type": "understanding", "prediction": "margaret bent over her and said bessie dont be impatient with your life whatever it is or may have been", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0035.flac", "answer": "VISITING REGISTER OFFICES SEEING ALL MANNER OF UNLIKELY PEOPLE AND VERY FEW IN THE LEAST LIKELY ABSORBED MARGARET'S TIME AND THOUGHTS FOR SEVERAL DAYS", "subset": "test_other", "task_type": "understanding", "prediction": "visiting register offices seeing all manner of unlikely people and very few in the least likely absorbed margaret s time and thoughts for several days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0072.flac", "answer": "MARGARET HELD HER IN HER ARMS AND PUT THE WEARY HEAD TO REST UPON HER BOSOM", "subset": "test_other", "task_type": "understanding", "prediction": "margaret held her in her arms and put the weary head to rest upon her bosom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0054.flac", "answer": "BUT NICHOLAS WAS NOT AT HOME WHEN THEY ENTERED", "subset": "test_other", "task_type": "understanding", "prediction": "but nicholas was not at home when they entered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0044.flac", "answer": "BESSY DO YOU WISH TO DIE", "subset": "test_other", "task_type": "understanding", "prediction": "bessie do you wish to die", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0032.flac", "answer": "BUT THOUGH SHE RECEIVED CARESSES AND FOND WORDS BACK AGAIN IN SUCH PROFUSION AS WOULD HAVE GLADDENED HER FORMERLY YET SHE FELT THAT THERE WAS A SECRET WITHHELD FROM HER AND SHE BELIEVED IT BORE SERIOUS REFERENCE TO HER MOTHER'S HEALTH", "subset": "test_other", "task_type": "understanding", "prediction": "but though she received caresses and fond words back again in such profusion as would have gladdened her formerly yet she felt that there was a secret withheld from her and she believed it bore serious reference to her mother s health", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0000.flac", "answer": "THERE'S IRON THEY SAY IN ALL OUR BLOOD AND A GRAIN OR TWO PERHAPS IS GOOD BUT HIS HE MAKES ME HARSHLY FEEL HAS GOT A LITTLE TOO MUCH OF STEEL ANON", "subset": "test_other", "task_type": "understanding", "prediction": "there is iron they say in all our blood and a grain or two perhaps is good but his he makes me harshly feel has got a little too much of steel anon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0095.flac", "answer": "THEY CARED TOO LITTLE TO ASK IN WHAT MANNER HER SON HAD SPOKEN ABOUT HER", "subset": "test_other", "task_type": "understanding", "prediction": "they cared too little to ask in what manner her son had spoken about her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0001.flac", "answer": "MARGARET SAID MISTER HALE AS HE RETURNED FROM SHOWING HIS GUEST DOWNSTAIRS I COULD NOT HELP WATCHING YOUR FACE WITH SOME ANXIETY WHEN MISTER THORNTON MADE HIS CONFESSION OF HAVING BEEN A SHOP BOY", "subset": "test_other", "task_type": "understanding", "prediction": "margaret said mr hale as he returned from showing his guests downstairs i could not help watching your face with some anxiety when mr thornton made his confession of having been a shop boy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0050.flac", "answer": "I SHOULD HAVE THOUGHT OF IT AGAIN WHEN I WAS LESS BUSY MAY I GO WITH YOU NOW", "subset": "test_other", "task_type": "understanding", "prediction": "i should have thought of it again when i was less busy may i go with you now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0028.flac", "answer": "BUT GOOD NIGHT CHILD", "subset": "test_other", "task_type": "understanding", "prediction": "but good night child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0052.flac", "answer": "AS THEY TURNED UP INTO A SMALL COURT OPENING OUT OF A SQUALID STREET BESSY SAID", "subset": "test_other", "task_type": "understanding", "prediction": "as they turned up into a small court opening out into a squalid street bessie said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1688/142285/1688-142285-0073.flac", "answer": "PRESENTLY THE SPASM THAT FORESHADOWED DEATH HAD PASSED AWAY AND BESSY ROUSED HERSELF AND SAID", "subset": "test_other", "task_type": "understanding", "prediction": "presently the spasm that foreshadowed death had passed away and bessie roused herself and said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0024.flac", "answer": "FIVE A PART OF THIS ETHEREAL SOLUTION IS POURED INTO A WATCH GLASS AND ALLOWED TO EVAPORATE", "subset": "test_other", "task_type": "understanding", "prediction": "five a part of this ethereal solution is poured into a watch glass and allowed to evaporate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0011.flac", "answer": "IN USING THE ELASTIC STOMACH TUBE SOME FLUID SHOULD BE INTRODUCED INTO THE STOMACH BEFORE ATTEMPTING TO EMPTY IT OR A PORTION OF THE MUCOUS MEMBRANE MAY BE SUCKED INTO THE APERTURE", "subset": "test_other", "task_type": "understanding", "prediction": "in using the elastic stomach tube some fluid should be introduced into the stomach before attempting to empty it or a portion of the mucous membrane may be sucked into the aperture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0002.flac", "answer": "HE SHOULD NOTICE THE POSITION AND TEMPERATURE OF THE BODY THE CONDITION OF RIGOR MORTIS MARKS OF VIOLENCE APPEARANCE OF LIPS AND MOUTH", "subset": "test_other", "task_type": "understanding", "prediction": "he should notice the position and temperature of the body the condition of rigor mortis marks of violence appearance of lips and mouth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0015.flac", "answer": "NOTICE THE SMELL COLOUR AND GENERAL APPEARANCE OF THE MATTER SUBMITTED FOR EXAMINATION", "subset": "test_other", "task_type": "understanding", "prediction": "notice the smell colour and general appearance of the matter submitted for examination", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0023.flac", "answer": "SEPARATE THE ETHEREAL SOLUTION AND EVAPORATE", "subset": "test_other", "task_type": "understanding", "prediction": "separate the ethereal solution and evaporate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0010.flac", "answer": "TICKLING THE FAUCES WITH A FEATHER MAY EXCITE VOMITING", "subset": "test_other", "task_type": "understanding", "prediction": "tickling the fauces with a feather may excite vomiting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0009.flac", "answer": "APOMORPHINE IS NOT ALLIED IN PHYSIOLOGICAL ACTION TO MORPHINE AND MAY BE GIVEN IN CASES OF NARCOTIC POISONING", "subset": "test_other", "task_type": "understanding", "prediction": "epomorphin is not allied in physiological action to morphin and may be given in cases of narcotic poisoning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0026.flac", "answer": "BOIL THE FINELY DIVIDED SUBSTANCE WITH ABOUT ONE EIGHTH ITS BULK OF PURE HYDROCHLORIC ACID ADD FROM TIME TO TIME POTASSIC CHLORATE UNTIL THE SOLIDS ARE REDUCED TO A STRAW YELLOW FLUID", "subset": "test_other", "task_type": "understanding", "prediction": "boy the finely divided substance with about one eighth its bulk of pure hydrochloric acid add from time to time potassic chloride until the solids are reduced to a straw yellow fluid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0000.flac", "answer": "IF CALLED TO A CASE SUPPOSED OR SUSPECTED TO BE ONE OF POISONING THE MEDICAL MAN HAS TWO DUTIES TO PERFORM TO SAVE THE PATIENT'S LIFE AND TO PLACE HIMSELF IN A POSITION TO GIVE EVIDENCE IF CALLED ON TO DO SO", "subset": "test_other", "task_type": "understanding", "prediction": "if called to a case supposed a suspected to be one of poisoning the medical man has two duties to perform to save the patients life and to place himself in a position to give evidence if called on to do so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0003.flac", "answer": "IN MAKING A POST MORTEM EXAMINATION THE ALIMENTARY CANAL SHOULD BE REMOVED AND PRESERVED FOR FURTHER INVESTIGATION", "subset": "test_other", "task_type": "understanding", "prediction": "in making a post mortem examination the alimentary canal should be removed and preserved for further investigation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0006.flac", "answer": "IN A CASE OF ATTEMPTED SUICIDE BY POISONING IS IT THE DUTY OF THE DOCTOR TO INFORM THE POLICE", "subset": "test_other", "task_type": "understanding", "prediction": "in a case of attempted suicide by poisoning is it the duty of the doctor to inform the police", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0013.flac", "answer": "ANTIDOTES ARE USUALLY GIVEN HYPODERMICALLY OR IF BY MOUTH IN THE FORM OF TABLETS", "subset": "test_other", "task_type": "understanding", "prediction": "antidotes are usually given hypodermically or if the mouth in the form of tablets", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0007.flac", "answer": "THE BEST EMETIC IS THAT WHICH IS AT HAND", "subset": "test_other", "task_type": "understanding", "prediction": "the best amadoc is that which is at hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0017.flac", "answer": "THIS PROCESS IS BASED UPON THE PRINCIPLE THAT THE SALTS OF THE ALKALOIDS ARE SOLUBLE IN ALCOHOL AND WATER AND INSOLUBLE IN ETHER", "subset": "test_other", "task_type": "understanding", "prediction": "this process is based upon the principle that the salts of the alkaloids are soluble in alcohol and water and insoluble in ether", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0016.flac", "answer": "FOR THE SEPARATION OF AN ALKALOID THE FOLLOWING IS THE PROCESS OF STAS OTTO", "subset": "test_other", "task_type": "understanding", "prediction": "for the separation of an alkaloid the following is the process of staarz otto", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0004.flac", "answer": "THE GUT AND THE GULLET BEING CUT ACROSS BETWEEN THESE LIGATURES THE STOMACH MAY BE REMOVED ENTIRE WITHOUT SPILLING ITS CONTENTS", "subset": "test_other", "task_type": "understanding", "prediction": "the gut and the gallblad being cut across between these ligatures the stomach may be removed entire without spilling its contents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0014.flac", "answer": "IN THE ABSENCE OF A HYPODERMIC SYRINGE THE REMEDY MAY BE GIVEN BY THE RECTUM", "subset": "test_other", "task_type": "understanding", "prediction": "in the absence of a hypodermic syringe the remedy may be given by the rectum", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0020.flac", "answer": "THE RESIDUE MAY BE SET ASIDE FOR THE DETECTION OF THE METALLIC POISONS IF SUSPECTED EXPEL THE ALCOHOL BY CAREFUL EVAPORATION", "subset": "test_other", "task_type": "understanding", "prediction": "the residue may be set aside for the detection of the metallic poisons if suspected expel the alcohol by careful evaporation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0012.flac", "answer": "THE TUBE SHOULD BE EXAMINED TO SEE THAT IT IS NOT BROKEN OR CRACKED AS ACCIDENTS HAVE HAPPENED FROM NEGLECTING THIS PRECAUTION", "subset": "test_other", "task_type": "understanding", "prediction": "the tube should be examined to see that it is not broken or cracked as accidents have happened from neglecting this precaution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0022.flac", "answer": "EVAPORATE THE FILTRATE TO A SYRUP AND EXTRACT WITH SUCCESSIVE PORTIONS OF ABSOLUTE ALCOHOL", "subset": "test_other", "task_type": "understanding", "prediction": "evaporate the filtrate to a syrup and extract with successive portions of absolute alcohol", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0025.flac", "answer": "TO PURIFY IT ADD A SMALL QUANTITY OF DILUTE SULPHURIC ACID AND AFTER EVAPORATING TO THREE QUARTERS OF ITS BULK ADD A SATURATED SOLUTION OF CARBONATE OF POTASH OR SODA", "subset": "test_other", "task_type": "understanding", "prediction": "to purify it add a small quantity of dilute sulphuric acid and after evaporating to three quarters of its bulk add a saturated solution of carbonate of potash or soda", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0019.flac", "answer": "TWO COOL THE MIXTURE AND FILTER WASH THE RESIDUE WITH STRONG ALCOHOL AND MIX THE FILTRATES", "subset": "test_other", "task_type": "understanding", "prediction": "two cool the mixture and filter wash the residue with strong alcohol and mix the filtrates", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0008.flac", "answer": "THE DOSE FOR AN ADULT IS TEN MINIMS", "subset": "test_other", "task_type": "understanding", "prediction": "the dose for an adult is ten minims", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0027.flac", "answer": "THE RESIDUE OF THE MATERIAL AFTER DIGESTION WITH HYDROCHLORIC ACID AND POTASSIUM CHLORATE MAY HAVE TO BE EXAMINED FOR SILVER LEAD AND BARIUM", "subset": "test_other", "task_type": "understanding", "prediction": "the residue of the material after digestion with hydrochloric acid and potassium chlorate may have to be examined for silver lead and barium", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0005.flac", "answer": "IF THE MEDICAL PRACTITIONER IS IN DOUBT ON ANY POINT HE SHOULD OBTAIN TECHNICAL ASSISTANCE FROM SOMEONE WHO HAS PAID ATTENTION TO THE SUBJECT", "subset": "test_other", "task_type": "understanding", "prediction": "if the medical practitioner is in doubt on any point he should obtain technical assistance from someone who has paid attention to the subject", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0018.flac", "answer": "THE PURE ALKALOIDS WITH THE EXCEPTION OF MORPHINE IN ITS CRYSTALLINE FORM ARE SOLUBLE IN ETHER", "subset": "test_other", "task_type": "understanding", "prediction": "the pure alkaloids with the exception of morphine in its crystalline form are soluble in ether", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0021.flac", "answer": "ON THE EVAPORATION OF THE ALCOHOL THE RESINOUS AND FATTY MATTERS SEPARATE", "subset": "test_other", "task_type": "understanding", "prediction": "on the evaporation of the alcohol the resinous and fatty matters separate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/15444/1998-15444-0001.flac", "answer": "HE SHOULD MAKE INQUIRIES AS TO SYMPTOMS AND TIME AT WHICH FOOD OR MEDICINE WAS LAST TAKEN", "subset": "test_other", "task_type": "understanding", "prediction": "he should make inquiries as to symptoms and time at which food or medicine was last taken", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0006.flac", "answer": "HE LOOKED ABOUT HIM AND KNEW THAT HE DID NOT AT ALL KNOW WHERE HE WAS", "subset": "test_other", "task_type": "understanding", "prediction": "he looked about him and knew that he did not at all know where he was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0028.flac", "answer": "GET IT WROTE DOWN THEN DONE", "subset": "test_other", "task_type": "understanding", "prediction": "get it wrote down then done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0045.flac", "answer": "STEP OUT SONNY OR WE'LL NEVER GET THERE THIS SIDE CHRISTMAS", "subset": "test_other", "task_type": "understanding", "prediction": "step out sanny or we ll never get there this side of christmas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0042.flac", "answer": "YOU ARE GOOD SAID DICKIE I DO LIKE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "you are good said dickie i do like you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0032.flac", "answer": "I SEE THAT THERE IN A BOOK SAID DICKIE CHARMED", "subset": "test_other", "task_type": "understanding", "prediction": "i see that there in the book said dick at shemmed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0041.flac", "answer": "IF YOU'RE CLEAN THEY SAY HONEST POVERTY AN IF YOU'RE DIRTY THEY SAY SERVE YOU RIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "if you are clean they say honest poverty and if you are dirty they say serve you right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0019.flac", "answer": "I WOULDN'T GO OME NOT IF I WAS YOU SAID THE MAN", "subset": "test_other", "task_type": "understanding", "prediction": "i wouldnt go ome not if air was you said the man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0043.flac", "answer": "I KNOW YOU WILL SAID DICKIE WITH ENTHUSIASM I KNOW OW GOOD YOU ARE", "subset": "test_other", "task_type": "understanding", "prediction": "i know you will said dickie with enthusiasm i know how good you are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0001.flac", "answer": "PERUSAL SAID THE PAWNBROKER THAT'S THE WAY TO PERNOUNCE IT", "subset": "test_other", "task_type": "understanding", "prediction": "perusal said the pawnbroker that is the way to pronounce it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0040.flac", "answer": "SOME BLOKES THINK IT PAYS TO BE DIRTY BUT IT DON'T", "subset": "test_other", "task_type": "understanding", "prediction": "some folks think it pays to be dirty but it dont", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0004.flac", "answer": "WHEN DICKIE CAME DOWN HIS AUNT SLIGHTLY SLAPPED HIM AND HE TOOK THE HALFPENNY AND LIMPED OFF OBEDIENTLY", "subset": "test_other", "task_type": "understanding", "prediction": "when dicky came down his aunt slightly slapped him and he took the halfpenny and limped off obediently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0022.flac", "answer": "WELL THAT'LL SHOW YOU THE SORT OF MAN I AM", "subset": "test_other", "task_type": "understanding", "prediction": "well that will show you the sort of man i am", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0031.flac", "answer": "THEY COULD PUT A MAN AWAY FOR LESS THAN THAT", "subset": "test_other", "task_type": "understanding", "prediction": "they could put a man away for less than that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0000.flac", "answer": "A THOUSAND BLESSINGS FROM A GRATEFUL HEART", "subset": "test_other", "task_type": "understanding", "prediction": "a thousand blessings from a grateful heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0013.flac", "answer": "AND THIS IS THE PRETTIEST PLACE EVER I SEE", "subset": "test_other", "task_type": "understanding", "prediction": "and this is the prettiest place ever i see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0034.flac", "answer": "WILD ONES AIN'T ALF THE SIZE I LAY", "subset": "test_other", "task_type": "understanding", "prediction": "wide ones and a half the size i lay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0008.flac", "answer": "WHEN HE SAID AVE I BIN ASLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "when he said ever been asleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0029.flac", "answer": "THEN HE FOLDED IT AND PUT IT IN HIS POCKET", "subset": "test_other", "task_type": "understanding", "prediction": "then he folded it and put it in his pocket", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0021.flac", "answer": "I AIN'T IT YER HAVE I LIKE WHAT YER AUNT DO", "subset": "test_other", "task_type": "understanding", "prediction": "i andent yer have i like what yer andent to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0025.flac", "answer": "A BIRD PAUSED IN ITS FLIGHT ON A BRANCH QUITE CLOSE AND CLUNG THERE SWAYING", "subset": "test_other", "task_type": "understanding", "prediction": "a bird paused in its flight on a branch quite close and clung there swaying", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0011.flac", "answer": "WHEN IT WAS OVER THE MAN ASKED DICKIE IF HE COULD WALK A LITTLE WAY AND WHEN DICKIE SAID HE COULD THEY SET OUT IN THE MOST FRIENDLY WAY SIDE BY SIDE", "subset": "test_other", "task_type": "understanding", "prediction": "when it was over the men asked dickie if he could walk a little way and when dickie said he could they set out in the most friendly way side by side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0046.flac", "answer": "WELL YOU'LL KNOW ALL ABOUT IT PRESENTLY", "subset": "test_other", "task_type": "understanding", "prediction": "well youll know all about it presently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0036.flac", "answer": "AH SAID DICKIE AND A FULL SILENCE FELL BETWEEN THEM", "subset": "test_other", "task_type": "understanding", "prediction": "ah said diggie and a full silence fell between them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0026.flac", "answer": "HE TOOK OUT OF HIS POCKET A NEW ENVELOPE A NEW SHEET OF PAPER AND A NEW PENCIL READY SHARPENED BY MACHINERY", "subset": "test_other", "task_type": "understanding", "prediction": "he took out of his pocket a new envelope a new sheet of paper and a new pencil ready sharpened by machinery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0005.flac", "answer": "HE HAD NEVER SEEN ONE BEFORE AND IT INTERESTED HIM EXTREMELY", "subset": "test_other", "task_type": "understanding", "prediction": "he had never seen one before and it interested him extremely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0044.flac", "answer": "BLESS ME SAID MISTER BEALE UNCOMFORTABLY WELL THERE", "subset": "test_other", "task_type": "understanding", "prediction": "bless me said mr beale uncomfortably well there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0033.flac", "answer": "HE REWARD THE WAKE THE LAST OF THE ENGLISH AND I WUNNERED WHAT IT STOOD FOR", "subset": "test_other", "task_type": "understanding", "prediction": "he reward the wake the last of the english and i wunnot what it stood for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0016.flac", "answer": "AIN'T BAD WHEN SHE'S IN A GOOD TEMPER", "subset": "test_other", "task_type": "understanding", "prediction": "and bad when she is in a good temper", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0015.flac", "answer": "SHE WAS WAITIN FOR THE WOOD TO BOIL THE KETTLE WHEN I COME OUT MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "she was waiting for the water to boil the kettle when i came out mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0002.flac", "answer": "HIS BOOKS TOLD HIM THAT TREASURE IS BEST HIDDEN UNDER LOOSE BOARDS UNLESS OF COURSE YOUR HOUSE HAS A SECRET PANEL WHICH HIS HAD NOT", "subset": "test_other", "task_type": "understanding", "prediction": "his books told him that treasure is best hidden under loose boards and as of course your house has a secret panel which his had not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0010.flac", "answer": "NOT EXACKLY SAID THE MAN BUT IT'S ALL RIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "not exactly said the man but it is all right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0017.flac", "answer": "THAT AIN'T WHAT SHE'LL BE IN WHEN YOU GETS BACK", "subset": "test_other", "task_type": "understanding", "prediction": "that ain what you ll be in when you gets back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0014.flac", "answer": "I SHALL CATCH IT A FAIR TREAT AS IT IS", "subset": "test_other", "task_type": "understanding", "prediction": "i shall catch it a fair treat as it is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0007.flac", "answer": "WHAT'S UP MATEY LOST YOUR WAY DICKIE EXPLAINED", "subset": "test_other", "task_type": "understanding", "prediction": "what s up matey lost your way dicky explained", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0039.flac", "answer": "SO YOU SHALL SAID MISTER BEALE A REG'LER WASH ALL OVER THIS VERY NIGHT I ALWAYS LIKE A WASH MESELF", "subset": "test_other", "task_type": "understanding", "prediction": "so you shall said mr beale a reglar wash all over this very night i always like a wash myself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0027.flac", "answer": "AN I ASKS YOU LET ME COME ALONGER YOU GOT THAT", "subset": "test_other", "task_type": "understanding", "prediction": "an i ask you let me come alonger you got that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0024.flac", "answer": "THE SUN SHOT LONG GOLDEN BEAMS THROUGH THE GAPS IN THE HEDGE", "subset": "test_other", "task_type": "understanding", "prediction": "the sun shot long golden beams through the gaps in the hedge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0012.flac", "answer": "AND THE TEA AND ALL AN THE EGG", "subset": "test_other", "task_type": "understanding", "prediction": "and the tea and all and the egg", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0037.flac", "answer": "THAT WAS CHARMING BUT IT WAS PLEASANT TOO TO WASH THE MUD OFF ON THE WET GRASS", "subset": "test_other", "task_type": "understanding", "prediction": "it was charming but it was pleasant too to rush the madoff on the wet grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0035.flac", "answer": "ADVENTURES I SHOULD THINK SO", "subset": "test_other", "task_type": "understanding", "prediction": "adventures i should think so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0003.flac", "answer": "HE GOT IT UP AND PUSHED HIS TREASURES AS FAR IN AS HE COULD ALONG THE ROUGH CRUMBLY SURFACE OF THE LATH AND PLASTER", "subset": "test_other", "task_type": "understanding", "prediction": "he got it up and pushed his treasures as far in as he could along the rough crumbly surface of the lath and plaster", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0038.flac", "answer": "DICKIE ALWAYS REMEMBERED THAT MOMENT", "subset": "test_other", "task_type": "understanding", "prediction": "dickie always remembered that moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0018.flac", "answer": "I GOT TO STICK IT SAID DICKIE SADLY I'D BEST BE GETTING HOME", "subset": "test_other", "task_type": "understanding", "prediction": "i got a stickered said dickie sadly i d best be getting home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0030.flac", "answer": "NOW WE'RE SQUARE HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "now we are square he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0023.flac", "answer": "THE MAN'S MANNER WAS SO KIND AND HEARTY THE WHOLE ADVENTURE WAS SO WONDERFUL AND NEW IS IT COUNTRY WHERE YOU GOING", "subset": "test_other", "task_type": "understanding", "prediction": "the man s manner was so kind and hearty the whole adventure was so wonderful and new is it country where you are going", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0020.flac", "answer": "NO SAID DICKIE OH NO NO I NEVER", "subset": "test_other", "task_type": "understanding", "prediction": "no said dicky oh no no i never", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29454/1998-29454-0009.flac", "answer": "HERE WE ARE SAID THE MAN", "subset": "test_other", "task_type": "understanding", "prediction": "here we are said the man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0033.flac", "answer": "SEE THAT BLOKE JUST NOW SAID MISTER BEALE YUSS SAID DICKIE", "subset": "test_other", "task_type": "understanding", "prediction": "see that bloke just now said mr beale yes said diggy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0035.flac", "answer": "IF ANY ONE ARSTS YOU IF YOU EVER SEE IM YOU NEVER SET EYES ON IM IN ALL YOUR BORN NOT TO REMEMBER IM", "subset": "test_other", "task_type": "understanding", "prediction": "if any one asks you if you ever see him you never set eyes on him in all your born not to remember him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0005.flac", "answer": "THEY'RE ONLY WEEDS SAID BEALE", "subset": "test_other", "task_type": "understanding", "prediction": "they are only weeds said beale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0039.flac", "answer": "WHAT'S THAT THERE SAID DICKIE", "subset": "test_other", "task_type": "understanding", "prediction": "what s that there said dickie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0034.flac", "answer": "WELL YOU NEVER SEE IM", "subset": "test_other", "task_type": "understanding", "prediction": "well you never see em", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0026.flac", "answer": "THE NIGHT IS FULL OF INTERESTING LITTLE SOUNDS THAT WILL NOT AT FIRST LET YOU SLEEP THE RUSTLE OF LITTLE WILD THINGS IN THE HEDGES THE BARKING OF DOGS IN DISTANT FARMS THE CHIRP OF CRICKETS AND THE CROAKING OF FROGS", "subset": "test_other", "task_type": "understanding", "prediction": "the night is full of interesting little sounds that will not at first let you sleep the rustle of little white things in the hedges the barking of dogs in distant farms the chirp of crickets and the croaking of frogs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0002.flac", "answer": "TELL YER WHAT MATE LOOKS TO ME AS IF I'D TOOK A FANCY TO YOU", "subset": "test_other", "task_type": "understanding", "prediction": "tell you what mate looks to me as if i took a fancy to you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0011.flac", "answer": "OW'M I TO WHEEL THE BLOOMIN PRAM IF YOU GOES ON LIKE AS IF YOU WAS A BAG OF EELS", "subset": "test_other", "task_type": "understanding", "prediction": "ow am i to weear the room and pram if yer goes on like as if yer was a peck o eels", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0008.flac", "answer": "SEE IM CROST THE ROAD THERE SEE HIM", "subset": "test_other", "task_type": "understanding", "prediction": "see him crossed the road there see him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0028.flac", "answer": "BLESSED IF I EVER SEE SUCH A NIPPER HE SAID OVER AND OVER AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "blest if i ever see such a nipper he said over and over again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0009.flac", "answer": "HOW BEAUTIFUL SAID DICKIE WRIGGLING WITH DELIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "how beautiful said dickie wriggling with delight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0024.flac", "answer": "BUT YOU SAID THE BED WITH THE GREEN CURTAINS URGED DICKIE", "subset": "test_other", "task_type": "understanding", "prediction": "but you said the bed was the green curtains urged dickie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0019.flac", "answer": "YOU STICK TO THAT SAID BEALE RADIANT WITH DELIGHT YOU'RE A FAIR MASTERPIECE YOU ARE YOU EARNED IT HONEST IF EVER A KID DONE", "subset": "test_other", "task_type": "understanding", "prediction": "you stick to that said beer radiant with delight you are a fair masterpiece you are you earned it honest if ever a kid done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0007.flac", "answer": "HI THERE GOES A RABBIT", "subset": "test_other", "task_type": "understanding", "prediction": "hi there goes a rabbit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0027.flac", "answer": "THE NEW GAME OF BEGGING AND INVENTING STORIES TO INTEREST THE PEOPLE FROM WHOM IT WAS WORTH WHILE TO BEG WENT ON GAILY DAY BY DAY AND WEEK BY WEEK AND DICKIE BY CONSTANT PRACTICE GREW SO CLEVER AT TAKING HIS PART IN THE ACTING THAT MISTER BEALE WAS QUITE DAZED WITH ADMIRATION", "subset": "test_other", "task_type": "understanding", "prediction": "the new game of begging and inventing stories to interest the people from whom it was worth while to beg went on gaily day by day and week by week and dickie by constant practice grew so clever taking his part in the acting that mr beale was quite dazed with admiration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0025.flac", "answer": "WHICH THIS AIN'T NOT BY NO MEANS", "subset": "test_other", "task_type": "understanding", "prediction": "which this ant not by no means", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0022.flac", "answer": "REMEMBER THAT NEITHER OF THEM KNEW ANY BETTER", "subset": "test_other", "task_type": "understanding", "prediction": "remember that neither of them knew any better", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0016.flac", "answer": "OH WELL DONE LITTLE UN SAID MISTER BEALE TO HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "oh well done little one said mr beale to himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0013.flac", "answer": "THAT'S ALL RIGHT SAID MISTER BEALE AWKWARDLY", "subset": "test_other", "task_type": "understanding", "prediction": "that is all right said mr beale awkwardly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0018.flac", "answer": "NO I NEVER SAID DICKIE ERE'S THE STEEVER", "subset": "test_other", "task_type": "understanding", "prediction": "no i never said dickie yes the steamer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0038.flac", "answer": "THEY DID NOT STAY THERE BUT WALKED OUT ACROSS THE DOWNS WHERE THE SKYLARKS WERE SINGING AND ON A DIP OF THE DOWNS CAME UPON GREAT STONE WALLS AND TOWERS VERY STRONG AND GRAY", "subset": "test_other", "task_type": "understanding", "prediction": "they did not stay there but walked out across the downs where the skylarks were singing and on a dip of the downs came upon great stone walls and towers very strong and grey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0023.flac", "answer": "TO THE ELDER TRAMP LIES AND BEGGING WERE NATURAL MEANS OF LIVELIHOOD", "subset": "test_other", "task_type": "understanding", "prediction": "to the idle tramp lies and begging were natural means of livelihood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0015.flac", "answer": "POOR LITTLE MAN SAID THE LADY YOU MISS YOUR MOTHER DON'T YOU", "subset": "test_other", "task_type": "understanding", "prediction": "poor little man said the lady you miss your mother dont you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0029.flac", "answer": "CLEVER AS A TRAINDAWG E IS AN ALL OUTER IS OWN EAD", "subset": "test_other", "task_type": "understanding", "prediction": "clever as a train dog he is and all out of his own head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0021.flac", "answer": "PLEASE DO NOT BE TOO SHOCKED", "subset": "test_other", "task_type": "understanding", "prediction": "please do not be too shocked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0012.flac", "answer": "I LIKE YOU NEXTER MY OWN DADDY AND MISTER BAXTER NEXT DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "i like you next to my own daddy and mr bex the next door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0014.flac", "answer": "DICKIE QUICK TO IMITATE TOUCHED HIS", "subset": "test_other", "task_type": "understanding", "prediction": "dickie quick to imitate touched his", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0020.flac", "answer": "THEY WENT ON UP THE HILL AS HAPPY AS ANY ONE NEED WISH TO BE", "subset": "test_other", "task_type": "understanding", "prediction": "they went on up the hill as happy as anyone need wish to be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0001.flac", "answer": "WHAT'S ALL THAT THERE DICKIE ASKED POINTING TO THE ODD KNOBBLY BUNDLES OF ALL SORTS AND SHAPES TIED ON TO THE PERAMBULATOR'S FRONT", "subset": "test_other", "task_type": "understanding", "prediction": "what on that there dicky asked pointing to the odd knobby bundles of all sorts and shapes tied on to the perambulator front", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0031.flac", "answer": "I OPE E'S CLEVER ENOUGH TO DO WOT E'S TOLD KEEP IS MUG SHUT THAT'S ALL", "subset": "test_other", "task_type": "understanding", "prediction": "i hope he is clever enough to do what he is told give us maksha that is all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0004.flac", "answer": "OH LOOK SAID DICKIE THE FLOWERS", "subset": "test_other", "task_type": "understanding", "prediction": "oh look said diggie the flowers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0030.flac", "answer": "I AIN'T SURE AS I ADN'T BETTER STICK TO THE ROAD AND KEEP AWAY FROM OLD ANDS LIKE YOU JIM", "subset": "test_other", "task_type": "understanding", "prediction": "i an sure as i adent better stick to the road and keep away from old anes like you jim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0037.flac", "answer": "NOR WAS IT SUNDAY ON WHICH THEY TOOK A REST AND WASHED THEIR SHIRTS ACCORDING TO MISTER BEALE'S RULE OF LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "nor was it sunday on which they took a rest and washed their shirts according to mr beale s rule of life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0017.flac", "answer": "THE TWO TRAVELLERS WERE LEFT FACING EACH OTHER THE RICHER BY A PENNY AND OH WONDERFUL GOOD FORTUNE A WHOLE HALF CROWN", "subset": "test_other", "task_type": "understanding", "prediction": "the two travellers were left facing each other the richer by a penny and oh wonderful good fortune a whole half crown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0032.flac", "answer": "IF E'S STRAIGHT E'LL DO FOR ME AND IF HE AIN'T I'LL DO FOR IM SEE", "subset": "test_other", "task_type": "understanding", "prediction": "if he strayed he ll do for me and if he andt i ll do for him see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0000.flac", "answer": "THE SINGING AND LAUGHING WENT ON LONG AFTER HE HAD FALLEN ASLEEP AND IF LATER IN THE EVENING THERE WERE LOUD VOICED ARGUMENTS OR QUARRELS EVEN DICKIE DID NOT HEAR THEM", "subset": "test_other", "task_type": "understanding", "prediction": "the singing and laughing went on long after he had fallen asleep and if later in the evening there were loud voiced arguments or quarrels even dickie did not hear them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0006.flac", "answer": "BUT I SHALL HAVE THEM WHILE THEY'RE ALIVE SAID DICKIE AS HE HAD SAID TO THE PAWNBROKER ABOUT THE MOONFLOWERS", "subset": "test_other", "task_type": "understanding", "prediction": "but i shall have them while they are alive said dickie as he had said to the pawnbroker about the moonflowers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0010.flac", "answer": "THIS LIFE OF THE RABBIT AS DESCRIBED BY MISTER BEALE WAS THE CHILD'S FIRST GLIMPSE OF FREEDOM I'D LIKE TO BE A RABBIT", "subset": "test_other", "task_type": "understanding", "prediction": "this life of the rabbit as described by mr beale was the child s first glimpse of freedom i d like to be a rabbit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0036.flac", "answer": "DICKIE WAS FULL OF QUESTIONS BUT MISTER BEALE HAD NO ANSWERS FOR THEM", "subset": "test_other", "task_type": "understanding", "prediction": "dickie was full of questions but mr beale had no answers for them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/1998/29455/1998-29455-0003.flac", "answer": "SWELP ME HE SAID HELPLESSLY", "subset": "test_other", "task_type": "understanding", "prediction": "swab me he said helplessly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0009.flac", "answer": "YOUNG VANE FALLING UPON THIS PAPER OF NOTES DEEMED THE MATTER OF THE UTMOST IMPORTANCE AND IMMEDIATELY COMMUNICATED IT TO PYM WHO NOW PRODUCED THE PAPER BEFORE THE HOUSE OF COMMONS", "subset": "test_other", "task_type": "understanding", "prediction": "young vane falling upon this paper of notes deemed the matter of the utmost importance and immediately communicated it to pym who now produced the paper before the house of commons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0004.flac", "answer": "WHERE THE TOKEN BY WHICH I SHOULD DISCOVER IT", "subset": "test_other", "task_type": "understanding", "prediction": "wear the token by which i shall discover it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0011.flac", "answer": "YOUR MAJESTY HAVING TRIED THE AFFECTIONS OF YOUR PEOPLE YOU ARE ABSOLVED AND LOOSE FROM ALL RULES OF GOVERNMENT AND MAY DO WHAT POWER WILL ADMIT", "subset": "test_other", "task_type": "understanding", "prediction": "your majesty having tried the affections of your people you are absolved and loose from all rules of government and may do what power will admit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0000.flac", "answer": "THE COMMONS ALSO VOTED THAT THE NEW CREATED PEERS OUGHT TO HAVE NO VOICE IN THIS TRIAL BECAUSE THE ACCUSATION BEING AGREED TO WHILE THEY WERE COMMONERS THEIR CONSENT TO IT WAS IMPLIED WITH THAT OF ALL THE COMMONS OF ENGLAND", "subset": "test_other", "task_type": "understanding", "prediction": "the commons also voted that the new created peers ought to have no voice in this trial because the accusation being agreed to while they were commoners their consent to it was implied with that of all the commons of england", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0005.flac", "answer": "IT IS NOW FULL TWO HUNDRED AND FORTY YEARS SINCE TREASONS WERE DEFINED AND SO LONG HAS IT BEEN SINCE ANY MAN WAS TOUCHED TO THIS EXTENT UPON THIS CRIME BEFORE MYSELF", "subset": "test_other", "task_type": "understanding", "prediction": "it is now a full two hundred and forty years since treasons were defined and so long has it been since any man was touched to this extent upon this crime before myself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0010.flac", "answer": "THE KING PROPOSES THIS DIFFICULTY BUT HOW CAN I UNDERTAKE OFFENSIVE WAR IF I HAVE NO MORE MONEY", "subset": "test_other", "task_type": "understanding", "prediction": "the king proposes this difficulty but how can i undertake offensive war if i have no more money", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0008.flac", "answer": "MY LORDS I HAVE NOW TROUBLED YOUR LORDSHIPS A GREAT DEAL LONGER THAN I SHOULD HAVE DONE", "subset": "test_other", "task_type": "understanding", "prediction": "my lords i have now troubled your lordships a great deal longer than i should have done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0001.flac", "answer": "IN THE GOVERNMENT OF IRELAND HIS ADMINISTRATION HAD BEEN EQUALLY PROMOTIVE OF HIS MASTER'S INTEREST AND THAT OF THE SUBJECTS COMMITTED TO HIS CARE", "subset": "test_other", "task_type": "understanding", "prediction": "in the government of ireland his administration had been equally promotive of his master s interest and that of the subjects committed to his care", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0003.flac", "answer": "THE COURT WHICH CONSISTED OF THE CHIEF OFFICERS OF THE ARMY FOUND THE CRIME TO BE CAPITAL AND CONDEMNED THAT NOBLEMAN TO LOSE HIS HEAD", "subset": "test_other", "task_type": "understanding", "prediction": "the court which consisted of the chief officials of the army found the crime to be capital and condemned that nobleman to lose his head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0006.flac", "answer": "LET US NOT TO OUR OWN DESTRUCTION AWAKE THOSE SLEEPING LIONS BY RATTLING UP A COMPANY OF OLD RECORDS WHICH HAVE LAIN FOR SO MANY AGES BY THE WALL FORGOTTEN AND NEGLECTED", "subset": "test_other", "task_type": "understanding", "prediction": "let us not to our own destruction awake those sleeping lions by rattling up a company of old records which have lain for so many ages by the wall forgotten and neglected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0007.flac", "answer": "HOWEVER THESE GENTLEMEN AT THE BAR SAY THEY SPEAK FOR THE COMMONWEALTH AND THEY BELIEVE SO YET UNDER FAVOR IT IS I WHO IN THIS PARTICULAR SPEAK FOR THE COMMONWEALTH", "subset": "test_other", "task_type": "understanding", "prediction": "however these gentlemen at the bar say they speak for the commonwealth and they believe so yet under favour it is i who in this particular speak for the commonwealth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/274364/8188-274364-0002.flac", "answer": "THE CASE OF LORD MOUNTNORRIS OF ALL THOSE WHICH WERE COLLECTED WITH SO MUCH INDUSTRY IS THE MOST FLAGRANT AND THE LEAST EXCUSABLE", "subset": "test_other", "task_type": "understanding", "prediction": "the case of lord montnorris of all those which were collected with so much industry is the most flagrant and the least excusable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0051.flac", "answer": "ANNIE COLCHESTER IS YOUR ROOMFELLOW IS SHE NOT SHE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "any coldchister is your roomfellow is she not she said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0014.flac", "answer": "BUT DON'T LOCK ME OUT PLEASE ANNIE", "subset": "test_other", "task_type": "understanding", "prediction": "but dont lock me out please annie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0009.flac", "answer": "YOU FRET ME BEYOND ENDURANCE", "subset": "test_other", "task_type": "understanding", "prediction": "you fret me beyond endurance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0056.flac", "answer": "THE GIRL WHO BREAKS THE RULES HAS TO BE PUNISHED", "subset": "test_other", "task_type": "understanding", "prediction": "the girl who breaks the rules has to be punished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0026.flac", "answer": "THAT'S JUST IT JANE THAT IS WHAT FRIGHTENS ME SHE REFUSES TO COME", "subset": "test_other", "task_type": "understanding", "prediction": "that is just it jane that is what frightens me she refuses to come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0005.flac", "answer": "IT BURNED AS IF WITH FEVER", "subset": "test_other", "task_type": "understanding", "prediction": "it burned as if with fever", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0011.flac", "answer": "LESLIE WAS JUST CLOSING THE DOOR BEHIND HER WHEN ANNIE CALLED AFTER HER", "subset": "test_other", "task_type": "understanding", "prediction": "leslie was just closing the door behind her when annie called after her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0039.flac", "answer": "MARJORIE AND EILEEN WERE CLOSE TO HER", "subset": "test_other", "task_type": "understanding", "prediction": "marjorie and eileen were close to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0013.flac", "answer": "HAVE THE GOODNESS TO FIND IT AND PUT IT BACK", "subset": "test_other", "task_type": "understanding", "prediction": "have the goodness to find it and put it back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0016.flac", "answer": "JANE HERIOT'S VOICE WAS HEARD IN THE PASSAGE", "subset": "test_other", "task_type": "understanding", "prediction": "jane harriotts voice was heard in the passage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0002.flac", "answer": "I'M NOT COMING SAID ANNIE", "subset": "test_other", "task_type": "understanding", "prediction": "i am not coming said annie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0003.flac", "answer": "EVERY STUDENT IS TO BE IN EAST HALL AT HALF PAST EIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "every student is to be in east hall at half past eight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0021.flac", "answer": "YOU SEE ALL THE GIRLS EXCEPT EILEEN AND MARJORIE LAUGH AT HER AND THAT SEEMS TO ME TO MAKE HER WORSE", "subset": "test_other", "task_type": "understanding", "prediction": "you see all the girls except eileen and marjorie laugh at her and that seems to me to make her worse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0001.flac", "answer": "IMMEDIATELY AFTER DINNER THAT EVENING LESLIE RAN UP TO HER ROOM TO MAKE PREPARATIONS FOR HER VISIT TO EAST HALL", "subset": "test_other", "task_type": "understanding", "prediction": "immediately after dinner that evening leslie ran up to her room to make preparations for her visit to east hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0055.flac", "answer": "EXCUSES MAKE NO DIFFERENCE", "subset": "test_other", "task_type": "understanding", "prediction": "excuses make no difference", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0052.flac", "answer": "I SEE BY YOUR FACE MISS GILROY THAT YOU ARE DISTRESSED ABOUT SOMETHING ARE YOU KEEPING ANYTHING BACK", "subset": "test_other", "task_type": "understanding", "prediction": "i see by your face missus gilroy that you are distressed about something are you keeping anything back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0053.flac", "answer": "I AM AFRAID I AM REPLIED LESLIE DISTRESS NOW IN HER TONE", "subset": "test_other", "task_type": "understanding", "prediction": "i am afraid i am replied lizzie distressed now in her tone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0025.flac", "answer": "I BELIEVE POOR ANNIE IS DREADFULLY UNHAPPY", "subset": "test_other", "task_type": "understanding", "prediction": "i believe poor annie is dreadfully unhappy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0004.flac", "answer": "IT DOESN'T MATTER REPLIED ANNIE WHETHER IT IS AN ORDER OR NOT I'M NOT COMING SAY NOTHING ABOUT ME PLEASE", "subset": "test_other", "task_type": "understanding", "prediction": "it does n not matter replied annie whether it is an order or not i am not coming say nothing about me please", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0015.flac", "answer": "OH I WON'T LOCK YOU OUT SHE SAID BUT I MUST HAVE THE KEY", "subset": "test_other", "task_type": "understanding", "prediction": "oh i won t lock you out she said but i must have the key", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0022.flac", "answer": "SOME DAY JANE YOU MUST SEE HER", "subset": "test_other", "task_type": "understanding", "prediction": "someday jane you must see her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0048.flac", "answer": "AFTER THE ADDRESS THE GIRLS THEMSELVES WERE ENCOURAGED TO SPEAK AND A VERY ANIMATED DISCUSSION FOLLOWED", "subset": "test_other", "task_type": "understanding", "prediction": "after the address the girls themselves were encouraged to speak and a very animated discussion followed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0043.flac", "answer": "YOU ASK SHE CONTINUED", "subset": "test_other", "task_type": "understanding", "prediction": "you ask she continued", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0031.flac", "answer": "DO COME ANNIE DO", "subset": "test_other", "task_type": "understanding", "prediction": "do come annie do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0042.flac", "answer": "AM I MY BROTHER'S KEEPER", "subset": "test_other", "task_type": "understanding", "prediction": "am i my brother s keeper", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0006.flac", "answer": "YOU DON'T KNOW WHAT A TRIAL IT IS FOR ME TO HAVE YOU HERE", "subset": "test_other", "task_type": "understanding", "prediction": "you dont know what a trial it is for me to have you here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0023.flac", "answer": "IF YOU ARE IN LONDON DURING THE SUMMER YOU MUST COME AND PAY US A VISIT WILL YOU", "subset": "test_other", "task_type": "understanding", "prediction": "if you are in london during the summer you must come and pay us a visit will you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0020.flac", "answer": "OH I SHALL NEVER DO THAT REPLIED LESLIE", "subset": "test_other", "task_type": "understanding", "prediction": "oh i shall never do that replied lizzie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0046.flac", "answer": "ALL MEN ARE YOUR BROTHERS", "subset": "test_other", "task_type": "understanding", "prediction": "all men are your brothers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0012.flac", "answer": "I TOOK IT OUT SAID LESLIE TOOK IT OUT", "subset": "test_other", "task_type": "understanding", "prediction": "i took it out said leslie took it out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0045.flac", "answer": "THE WORLD SAYS NO I AM NOT BUT GOD SAYS YES YOU ARE", "subset": "test_other", "task_type": "understanding", "prediction": "the world saith no i am not but god saith yes you are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0033.flac", "answer": "BUT MARJORIE AND EILEEN HAD ALREADY DEPARTED AND LESLIE AND JANE FOUND THEMSELVES AMONG THE LAST STUDENTS TO ARRIVE AT THE GREAT EAST HALL", "subset": "test_other", "task_type": "understanding", "prediction": "but marjorie and eileen had already departed and leslie and jane found themselves among the last students to arrive at the great east hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0037.flac", "answer": "HEAR HEAR AND ONCE AGAIN HEAR", "subset": "test_other", "task_type": "understanding", "prediction": "here here and once again here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0041.flac", "answer": "THE NAMES OF PROPOSED MEMBERS ARE TO BE SUBMITTED TO ME BEFORE THIS DAY WEEK", "subset": "test_other", "task_type": "understanding", "prediction": "the names of the proposed members are to be submitted to me before this day week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0024.flac", "answer": "THAT IS IF YOU CARE TO CONFIDE IN ME", "subset": "test_other", "task_type": "understanding", "prediction": "that is if you care to confide in me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0035.flac", "answer": "THEN A ROLL CALL WAS GONE THROUGH BY ONE OF THE TUTORS THE ONLY ABSENTEE WAS ANNIE COLCHESTER", "subset": "test_other", "task_type": "understanding", "prediction": "then a roll call was gone through by one of the tutors the only absentee was enni colchester", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0029.flac", "answer": "I AM SURE SHE IS ILL SHE WORKS TOO HARD AND SHE BUT THERE I DON'T KNOW THAT I OUGHT TO SAY ANY MORE", "subset": "test_other", "task_type": "understanding", "prediction": "i am sure she is ill she works too hard and she but there i do not know that i ought to say any more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0054.flac", "answer": "I MUST SEE HER MYSELF EARLY IN THE MORNING AND I AM QUITE SURE THAT NOTHING WILL SATISFY MISS LAUDERDALE EXCEPT A VERY AMPLE APOLOGY AND A FULL EXPLANATION OF THE REASON WHY SHE ABSENTED HERSELF", "subset": "test_other", "task_type": "understanding", "prediction": "i must see her myself early in the morning and i am quite sure that nothing will satisfy miss lauderdale except a very ample apology and a full explanation of the reason why she absented herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0044.flac", "answer": "GOD ANSWERS TO EACH OF YOU YOU ARE", "subset": "test_other", "task_type": "understanding", "prediction": "god answers to each of you you are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0008.flac", "answer": "I KNOW YOU DON'T QUITE MEAN WHAT YOU SAY SAID LESLIE BUT OF COURSE IF YOU REALLY WISH ME", "subset": "test_other", "task_type": "understanding", "prediction": "i know you do not quite mean what you say said leslie but of course if you really wish me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0049.flac", "answer": "IT WAS PAST TEN O'CLOCK WHEN SHE LEFT THE HALL", "subset": "test_other", "task_type": "understanding", "prediction": "it was past ten o clock when she left the hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0017.flac", "answer": "AS SHE WALKED DOWN THE CORRIDOR SHE HEARD IT BEING TURNED IN THE LOCK", "subset": "test_other", "task_type": "understanding", "prediction": "as she walked down the corridor she heard it being turned in the lock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0000.flac", "answer": "THE GUILD OF SAINT ELIZABETH", "subset": "test_other", "task_type": "understanding", "prediction": "the guild of saint elizabeth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0018.flac", "answer": "WHAT CAN THIS MEAN SHE SAID TO HERSELF", "subset": "test_other", "task_type": "understanding", "prediction": "what can this mean she said to herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0010.flac", "answer": "WRAPPING A PRETTY BLUE SHAWL ROUND HER HEAD AND SHOULDERS SHE TURNED TO ANNIE", "subset": "test_other", "task_type": "understanding", "prediction": "wrapping a pretty blue shawl around her hidden shoulders she turned to annie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0007.flac", "answer": "I WANT TO BE ALONE GO", "subset": "test_other", "task_type": "understanding", "prediction": "i want to be alone go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0030.flac", "answer": "I'LL WAIT FOR YOU HERE SAID LESLIE", "subset": "test_other", "task_type": "understanding", "prediction": "i will wait for you here said leslie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0038.flac", "answer": "SHE UTTERED HER STRANGE REMARK STANDING UP", "subset": "test_other", "task_type": "understanding", "prediction": "she uttered a stray remark standing up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0019.flac", "answer": "OH I WON'T PRESS YOU REPLIED JANE", "subset": "test_other", "task_type": "understanding", "prediction": "oh i won t press you replied jane", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0057.flac", "answer": "I WILL TELL HER", "subset": "test_other", "task_type": "understanding", "prediction": "i will tell her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0050.flac", "answer": "JUST AS SHE WAS DOING SO MISS FRERE CAME UP", "subset": "test_other", "task_type": "understanding", "prediction": "just as she was doing so miss frere came up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0034.flac", "answer": "MISS LAUDERDALE WAS STANDING WITH THE OTHER TUTORS AND PRINCIPALS OF THE DIFFERENT HALLS ON A RAISED PLATFORM", "subset": "test_other", "task_type": "understanding", "prediction": "miss lauderdale was standing with the other tutors and principals of the different halls on a raised platform", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0040.flac", "answer": "I WILL TALK WITH YOU BELLE ACHESON PRESENTLY SHE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "i will talk with you bell archson presently she said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0047.flac", "answer": "FOR ALL WHO SIN ALL WHO SUFFER YOU ARE TO A CERTAIN EXTENT RESPONSIBLE", "subset": "test_other", "task_type": "understanding", "prediction": "for all who sin all who suffer you are to a certain extent responsible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0027.flac", "answer": "REFUSES TO COME SHE CRIED", "subset": "test_other", "task_type": "understanding", "prediction": "refuses to come she cried", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0032.flac", "answer": "SCARCELY LIKELY REPLIED LESLIE SHE TOLD ME SHE WAS DETERMINED NOT TO COME TO THE MEETING", "subset": "test_other", "task_type": "understanding", "prediction": "scarcely likely replied leslie she told me she was determined not to come to the meeting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0028.flac", "answer": "SHE WILL GET INTO AN AWFUL SCRAPE", "subset": "test_other", "task_type": "understanding", "prediction": "she will get into an awful scrape", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269290/8188-269290-0036.flac", "answer": "THE PHYSICAL PART OF YOUR TRAINING AND ALSO THE MENTAL PART ARE ABUNDANTLY SUPPLIED IN THIS GREAT HOUSE OF LEARNING SHE CONTINUED BUT THE SPIRITUAL PART IT SEEMS TO ME OUGHT NOW TO BE STRENGTHENED", "subset": "test_other", "task_type": "understanding", "prediction": "the physical part of your training and also the mental part are abundantly supplied in this great house of learning she continued but the spiritual part it seems to me ought now to be strengthened", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0005.flac", "answer": "WHY YOU WILL BE PARTING FROM ME YOU KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "why you will be parting from me you know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0049.flac", "answer": "CAN'T YOU MANAGE WITH A CANDLE JUST FOR ONCE", "subset": "test_other", "task_type": "understanding", "prediction": "cant you manage with a candle just for once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0024.flac", "answer": "I MUST GO INTO THE GROUNDS THE AIR IS STIFLING", "subset": "test_other", "task_type": "understanding", "prediction": "i must go into the grounds the air is stifling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0010.flac", "answer": "I MUST PASS IN HONORS IF I DON'T I SHALL DIE", "subset": "test_other", "task_type": "understanding", "prediction": "i must pass in honours if i doent i shall die", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0007.flac", "answer": "IT IS THIS IF BY ANY CHANCE YOU DON'T LEAVE SAINT WODE'S ANNIE I HOPE YOU WILL ALLOW ME TO BE YOUR ROOMFELLOW AGAIN NEXT TERM", "subset": "test_other", "task_type": "understanding", "prediction": "it is this if by any chance you do not leave st wode s annie i hope you will allow me to be your roomfellow again next term", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0040.flac", "answer": "DON'T TALK TO ME LESLIE DON'T SAY A SINGLE WORD", "subset": "test_other", "task_type": "understanding", "prediction": "dont talk to me leslie dont say a single word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0013.flac", "answer": "JANE HERIOT STOOD WITHOUT", "subset": "test_other", "task_type": "understanding", "prediction": "jane harriet stood without", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0033.flac", "answer": "LESLIE LEFT THE ROOM BUT SHE HAD SCARCELY GONE A DOZEN PACES DOWN THE CORRIDOR BEFORE SHE MET ANNIE RETURNING", "subset": "test_other", "task_type": "understanding", "prediction": "leslie left the room but she had scarcely gone a dozen paces down the corridor before she met annie returning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0018.flac", "answer": "HER FACE GREW SUDDENLY WHITE AS DEATH WHAT IS IT DEAR", "subset": "test_other", "task_type": "understanding", "prediction": "her face grew suddenly white as death what is it dear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0045.flac", "answer": "DRINK THAT SHE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "drink that she said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0029.flac", "answer": "NOW I REMEMBER SHE GOT A LETTER WHICH UPSET HER VERY MUCH AND WENT OUT", "subset": "test_other", "task_type": "understanding", "prediction": "now i remember she got a letter which upset her very much and went out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0030.flac", "answer": "LESLIE WENT TO THE WINDOW AND FLUNG IT OPEN SHE PUT HER HEAD OUT AND TRIED TO PEER INTO THE DARKNESS BUT THE MOON HAD ALREADY SET AND SHE COULD NOT SEE MORE THAN A COUPLE OF YARDS IN FRONT OF HER", "subset": "test_other", "task_type": "understanding", "prediction": "leslie went to the window and flung it open she put her head out and tried to peer into the darkness but the moon had already set and she could not see more than a couple of yards in front of her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0008.flac", "answer": "SAID ANNIE A FLASH OF LIGHT COMING INTO HER EYES AND THEN LEAVING THEM", "subset": "test_other", "task_type": "understanding", "prediction": "said annie a flash of light coming into her eyes and then leaving them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0004.flac", "answer": "WHAT DO YOU MEAN REPLIED LESLIE", "subset": "test_other", "task_type": "understanding", "prediction": "what do you mean replied rizzliff", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0037.flac", "answer": "DON'T BEGIN WHAT DO YOU MEAN", "subset": "test_other", "task_type": "understanding", "prediction": "dont begin what do you mean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0054.flac", "answer": "TIRED OUT LESLIE HERSELF DROPPED ASLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "tired out leslie herself dropped asleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0015.flac", "answer": "LESLIE THANKED HER AND EAGERLY GRASPED THE LITTLE PARCEL", "subset": "test_other", "task_type": "understanding", "prediction": "leslie thanked her and eagerly grasped the little parcel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0043.flac", "answer": "NOW DRINK THIS AT ONCE SHE SAID IN A VOICE OF AUTHORITY IF YOU REALLY WISH TO SLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "now drink this at once she said in a voice of authority if you really wish to sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0035.flac", "answer": "SHE DID NOT TAKE THE LEAST NOTICE OF LESLIE BUT GOING INTO THE ROOM SHUT THE DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "she did not take the least notice of leslie but going into the room shut the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0048.flac", "answer": "SHE GOT INTO BED AS SHE SPOKE AND WRAPPED THE CLOTHES TIGHTLY ROUND HER", "subset": "test_other", "task_type": "understanding", "prediction": "she got into bed as she spoke and wrapped the clothes tightly round her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0017.flac", "answer": "HERE IS A LETTER FOR YOU ANNIE CRIED LESLIE", "subset": "test_other", "task_type": "understanding", "prediction": "here is a letter for you annie cried leslie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0036.flac", "answer": "DON'T BEGIN SAID ANNIE", "subset": "test_other", "task_type": "understanding", "prediction": "dont begin said annie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0006.flac", "answer": "I WON'T BE THE CONSTANT WORRY AND PLAGUE OF YOUR LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "i won t be the constant worry and plague of your life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0019.flac", "answer": "I HAVE BEEN STARVING OR RATHER I HAVE BEEN THIRSTING", "subset": "test_other", "task_type": "understanding", "prediction": "i have been starving or rather i have been thirsting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0055.flac", "answer": "ANNIE IS THAT YOU SHE CALLED OUT", "subset": "test_other", "task_type": "understanding", "prediction": "annie is that you she called out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0038.flac", "answer": "I MEAN THAT I DON'T WANT YOU TO BEGIN TO ASK QUESTIONS", "subset": "test_other", "task_type": "understanding", "prediction": "i mean that i don t want you to begin to ask questions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0026.flac", "answer": "I SHALL GO I KNOW A WAY", "subset": "test_other", "task_type": "understanding", "prediction": "i shall go i know a way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0052.flac", "answer": "ANNIE'S MANNER WAS VERY MYSTERIOUS", "subset": "test_other", "task_type": "understanding", "prediction": "annie s manner was very mysterious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0002.flac", "answer": "HER TASTES ALL LAY IN THIS DIRECTION HER IDEA BEING BY AND BY TO FOLLOW HER MOTHER'S PROFESSION OF JOURNALISM FOR WHICH SHE ALREADY SHOWED CONSIDERABLE APTITUDE", "subset": "test_other", "task_type": "understanding", "prediction": "her tastes all lay in this direction her idea being by and by to follow her mother s profession of journalism for which she already showed considerable aptitude", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0057.flac", "answer": "OH THIS WILL KILL ME MY HEART WILL BREAK THIS WILL KILL ME", "subset": "test_other", "task_type": "understanding", "prediction": "oh this will kill me my heart will break this will kill me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0000.flac", "answer": "ANNIE COLCHESTER HAD BEGUN TO MAKE FRIENDS WITH LESLIE", "subset": "test_other", "task_type": "understanding", "prediction": "any colchester had begun to make prints with leslie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0032.flac", "answer": "WHAT CAN SHE BE DOING OUT BY HERSELF", "subset": "test_other", "task_type": "understanding", "prediction": "what can she be doing out by herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0003.flac", "answer": "SHE HAD NO IDEA OF ALLOWING HERSELF TO BREAK DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "she had no idea of allowing herself to break down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0009.flac", "answer": "BUT SHE ADDED ABRUPTLY YOU SPEAK OF SOMETHING WHICH MUST NOT TAKE PLACE", "subset": "test_other", "task_type": "understanding", "prediction": "but she added abruptly you speak of something which must not take place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0047.flac", "answer": "I AM SLEEPY I SHALL SLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "i am sleepy i shall sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0046.flac", "answer": "DO YOU WANT TO KILL ME DON'T TALK ANY MORE", "subset": "test_other", "task_type": "understanding", "prediction": "do you want to kill me don t talk any more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0012.flac", "answer": "LESLIE OPENED THE DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "leslie opened the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0044.flac", "answer": "ANNIE STARED VACANTLY AT THE COCOA THEN SHE UTTERED A LAUGH", "subset": "test_other", "task_type": "understanding", "prediction": "enni stared vacantly at the cocoa then she uttered a laugh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0041.flac", "answer": "I SHALL GO OFF TO SLEEP THAT IS ALL I CARE FOR", "subset": "test_other", "task_type": "understanding", "prediction": "i shall go off to sleep that is all i care for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0051.flac", "answer": "SHE TURNED OFF THE LIGHT AND LIT A CANDLE WHICH SHE PUT BEHIND HER SCREEN THEN PREPARED TO GET INTO BED", "subset": "test_other", "task_type": "understanding", "prediction": "she turned off the light and lit a candle which she put behind her screen then prepared to get into bed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0022.flac", "answer": "LESLIE SEATED HERSELF WITH HER BACK TO HER COMPANION AND OPENED HER OWN LETTERS", "subset": "test_other", "task_type": "understanding", "prediction": "lisbeth seated herself with her back to her companion and opened her own letters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0027.flac", "answer": "JUST AFTER MIDNIGHT SHE ROSE WITH A SIGH TO PREPARE FOR BED", "subset": "test_other", "task_type": "understanding", "prediction": "just after midnight she rose with a sigh to prepare for bed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0042.flac", "answer": "DON'T SAID ANNIE", "subset": "test_other", "task_type": "understanding", "prediction": "dont said annie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0016.flac", "answer": "HER EYES SHONE WITH PLEASURE AT THE ANTICIPATION OF THE DELIGHTFUL TIME SHE WOULD HAVE REVELING IN THE HOME NEWS THE OTHER LETTER WAS DIRECTED TO ANNIE COLCHESTER", "subset": "test_other", "task_type": "understanding", "prediction": "her eyes shone with pleasure at the anticipation of the delightful time she would have revelling in the home news the other letter was directed to eddy colchester", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0039.flac", "answer": "I WALKED UP AND DOWN AS FAST AS EVER I COULD OUTSIDE IN ORDER TO MAKE MYSELF SLEEPY", "subset": "test_other", "task_type": "understanding", "prediction": "i walked up and down as fast as ever i could outside in order to make myself sleepy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0034.flac", "answer": "ANNIE'S EYES WERE VERY BRIGHT HER CHEEKS WERE NO LONGER PALE AND THERE WAS A BRILLIANT COLOR IN THEM", "subset": "test_other", "task_type": "understanding", "prediction": "annie s eyes were very bright her cheeks were no longer pale and there was a brilliant color in them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0023.flac", "answer": "DON'T NOTICE ME REPLIED ANNIE", "subset": "test_other", "task_type": "understanding", "prediction": "dont notice me replied annie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0031.flac", "answer": "SHE IS A VERY QUEER ERRATIC CREATURE AND THAT LETTER THERE WAS BAD NEWS IN THAT LETTER", "subset": "test_other", "task_type": "understanding", "prediction": "she is a very queer erratic creature and that letter there was bad news in that letter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0025.flac", "answer": "BUT THEY ARE JUST SHUTTING UP", "subset": "test_other", "task_type": "understanding", "prediction": "but they are just shutting up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0053.flac", "answer": "ANNIE DID NOT MEAN TO CONFIDE IN ANYONE THAT NIGHT AND THE KINDEST THING WAS TO LEAVE HER ALONE", "subset": "test_other", "task_type": "understanding", "prediction": "annie did not mean to confine any one that night and the kindest thing was to leave her alone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0011.flac", "answer": "A FEW MOMENTS LATER THERE CAME A TAP AT THE DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "a few moments later there came a tap at the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0028.flac", "answer": "SHE LOOKED ROUND THE ROOM", "subset": "test_other", "task_type": "understanding", "prediction": "she looked round the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0014.flac", "answer": "THESE LETTERS HAVE JUST COME FOR YOU AND ANNIE COLCHESTER SHE SAID AND AS I WAS COMING UPSTAIRS I THOUGHT I WOULD LEAVE THEM WITH YOU", "subset": "test_other", "task_type": "understanding", "prediction": "these letters have just come for you and annie colchester she said and as i was coming upstairs i thought i would leave them with you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0050.flac", "answer": "CERTAINLY SAID LESLIE", "subset": "test_other", "task_type": "understanding", "prediction": "certainly said leslie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0021.flac", "answer": "I AM TRULY GLAD IT HAS COME", "subset": "test_other", "task_type": "understanding", "prediction": "i am truly glad it has come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0056.flac", "answer": "THERE WAS NO REPLY BUT THE SOUND OF HURRYING STEPS CAME QUICKER AND QUICKER NOW AND THEN THEY WERE INTERRUPTED BY A GROAN", "subset": "test_other", "task_type": "understanding", "prediction": "there was no reply but the sound of hurrying steps came quicker and quicker now and then they were interrupted by a groan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0020.flac", "answer": "WELL READ IT IN PEACE SAID LESLIE I WON'T DISTURB YOU", "subset": "test_other", "task_type": "understanding", "prediction": "well read it in peace said lennoxley i won t disturb you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8188/269288/8188-269288-0001.flac", "answer": "LESLIE DETERMINED TO TRY FOR HONORS IN ENGLISH LANGUAGE AND LITERATURE", "subset": "test_other", "task_type": "understanding", "prediction": "leslie determined to try for honors in english language and literature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0006.flac", "answer": "WHAT A QUEER DREAM HE THOUGHT TO HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "what a queer dream he thought to himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0032.flac", "answer": "NO I CAN'T PART WITH THAT HA HA HA LAUGHED THE BOY JEERINGLY", "subset": "test_other", "task_type": "understanding", "prediction": "no i can not part with that ha ha ha laughed the boy jeeringly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0016.flac", "answer": "HULLO HE SAID WHO ARE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "hullo he said who are you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0048.flac", "answer": "BIT OF A MIDDY FED ON SALT TACK AND WEEVILLY BISCUIT TALK OF GIVING ME ROPE'S END", "subset": "test_other", "task_type": "understanding", "prediction": "bit of a middy fed on a salt tack and weevily biscuit talk of giving me ropes end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0033.flac", "answer": "BUT I'LL YES I'LL GIVE YOU A GUINEA IF YOU WILL LET ME OUT", "subset": "test_other", "task_type": "understanding", "prediction": "but ill yes ill give you a guinea if you will let me out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0022.flac", "answer": "THINK I DON'T KNOW YOU MISTER ORFICER", "subset": "test_other", "task_type": "understanding", "prediction": "think i don t know you mr orfeuer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0011.flac", "answer": "NO HE WAS NOT DREAMING FOR HE WAS LOOKING OUT ON THE SEA OVER WHICH A FAINT MIST HUNG LIKE WREATHS OF SMOKE", "subset": "test_other", "task_type": "understanding", "prediction": "no he was not dreaming for he was looking out on the sea over which a faint mist hung like wreaths of smoke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0013.flac", "answer": "ONCE OUT OF THAT ROOM HE COULD RAN AND BY DAYLIGHT THE SMUGGLERS DARE NOT HUNT HIM DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "once out of that room he could ram and by daylight the smugglers dare not hunt him down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0007.flac", "answer": "BUT HOW QUEER FOR MISTER GURR TO BE TALKING LIKE THAT TO ANDREW TEAL THE BOY WHO HELPED THE COOK", "subset": "test_other", "task_type": "understanding", "prediction": "but how queer for mr gurr to be talking like that to andrew teal the boy who helped the cook", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0035.flac", "answer": "BE QUICK THERE'S A GOOD FELLOW I WANT TO GET AWAY AT ONCE", "subset": "test_other", "task_type": "understanding", "prediction": "be quick there is a good fellow i want to get away at once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0034.flac", "answer": "GUINEA SAID THE BOY THINK I'D DO IT FOR A GUINEA WELL THEN TWO", "subset": "test_other", "task_type": "understanding", "prediction": "guinea said the boy think i ll do it for a guinea well then two", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0024.flac", "answer": "BEEN PLAYING THE SPY THAT'S WHAT YOU'VE BEEN DOING WHO LOCKED YOU IN", "subset": "test_other", "task_type": "understanding", "prediction": "been playing the spy that is what you have been doing who locked you in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0000.flac", "answer": "SURE YOU'VE LOOKED ROUND EVERYWHERE BOY YES FATHER QUITE", "subset": "test_other", "task_type": "understanding", "prediction": "sure you looked round everywhere boy yes father quite", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0047.flac", "answer": "WHY I COULD TIE YOU UP IN A KNOT AND HEAVE YOU OFF THE CLIFF ANY DAY WHAT A GAME", "subset": "test_other", "task_type": "understanding", "prediction": "why i could tie you up in a knot and heave you off the cliff any day what a game", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0030.flac", "answer": "THE RESULT WAS NOT VERY SATISFACTORY BUT SUFFICIENTLY SO TO MAKE HIM ESSAY THE BAR OF THE WINDOW ONCE MORE PRODUCING A GRATING EAR ASSAILING SOUND AS HE FOUND THAT NOW HE DID MAKE A LITTLE IMPRESSION SO LITTLE THOUGH THAT THE PROBABILITY WAS IF HE KEPT ON WORKING WELL FOR TWENTY FOUR HOURS HE WOULD NOT GET THROUGH", "subset": "test_other", "task_type": "understanding", "prediction": "the result was not very satisfactory but sufficiently so to make him essay the bar of the window once more producing a grating ear assailing sound as he found that now he did make a little impression so little though that the probability was if he kept on working well for twenty four hours he would not get through", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0041.flac", "answer": "ARCHY CHECKED HIMSELF AND THE BOY LAUGHED", "subset": "test_other", "task_type": "understanding", "prediction": "archie checked himself and the boy laughed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0049.flac", "answer": "ONCE MORE WILL YOU COME AND LET ME OUT NO", "subset": "test_other", "task_type": "understanding", "prediction": "once more will you come and let me out no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0039.flac", "answer": "I TOLD YOU A FISHER BOY CRIED ARCHY IMPATIENTLY BUT TRYING NOT TO OFFEND HIS VISITOR WHO POSSESSED THE POWER OF CONFERRING FREEDOM BY SPEAKING SHARPLY", "subset": "test_other", "task_type": "understanding", "prediction": "i told you a fisher boy cried archie impatiently but trying not to offend his visitor who possessed the power of conferring freedom by speaking sharply", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0012.flac", "answer": "WHAT DID THEY SAY FALSE ALARM TELL SIR RISDON THEY WOULD CLEAR ALL AWAY TO NIGHT SEE IF ANYTHING HAD BEEN LEFT ABOUT LOBSTER BOAT", "subset": "test_other", "task_type": "understanding", "prediction": "what did they say false alarm tell servants then they would clear all away to night see if anything had been left about lobster boat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0004.flac", "answer": "TELL HIM NOT TO BE UNEASY TIS ALL RIGHT AND I'LL HAVE EVERYTHING CLEAR AWAY TO NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "tell him not to be uneasy tis all right and i ll have everything cleared away to night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0005.flac", "answer": "THE DULL SOUND OF DEPARTING STEPS AND A LOW WHISTLING SOUND COMING DOWN THROUGH THE SKYLIGHT WINDOW INTO THE CABIN WHERE ARCHY RAYSTOKE LAY WITH HIS HEAVY EYELIDS PRESSED DOWN BY SLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "the dull sound of departing steps and a low whistling sound coming down through the skylight window into the cabin where archie ray strokor lay with his heavy eyelids pressed down by sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0036.flac", "answer": "NOT YOU ONLY A SHAM", "subset": "test_other", "task_type": "understanding", "prediction": "not you only a sham", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0018.flac", "answer": "I SAW YOU LAST NIGHT AND WONDERED WHOSE BOY YOU WAS", "subset": "test_other", "task_type": "understanding", "prediction": "i saw you last night and wondered whose boy you was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0014.flac", "answer": "OH THOSE BARS HE MENTALLY EXCLAIMED AND HE WAS ADVANCING TOWARD THEM WHEN JUST AS HE DREW NEAR THERE WAS A RUSTLING NOISE UNDER THE WINDOW A COUPLE OF HANDS SEIZED THE BARS THERE WAS A SCRATCHING OF BOOT TOES AGAINST STONE WORK AND RAM'S FACE APPEARED TO GAZE INTO THE ROOM BY INTENTION BUT INTO THE ASTONISHED COUNTENANCE OF THE YOUNG MIDSHIPMAN INSTEAD", "subset": "test_other", "task_type": "understanding", "prediction": "oh those bars he mentally exclaimed and he was advancing towards them when just as he drew near there was a rustling noise under the window a couple of hands seized the bars there was a scratching of boot toes against stonework and ramms face appeared to gaze into the room by intention but into the astonished countenance of the young midshipman instead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0029.flac", "answer": "HE DIVIDED THE PAINT AND PRODUCED A FEW SQUEAKS AND GRATING SOUNDS AS HE REALISED THAT THE ATTEMPT WAS MADNESS", "subset": "test_other", "task_type": "understanding", "prediction": "he divided the paint and produced a few squeaks and grating sounds as he realized that the attempt was madness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0001.flac", "answer": "I'M GOING HOME TO BREAKFAST", "subset": "test_other", "task_type": "understanding", "prediction": "i am going home to breakfast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0025.flac", "answer": "ARCHY STEPPED BACK TO THE DOOR LISTENING BUT THERE WAS NOT A SOUND", "subset": "test_other", "task_type": "understanding", "prediction": "archie stepped back to the door listening but there was not a sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0042.flac", "answer": "IT WAS YOUR TURN YESTERDAY IT'S MINE TO DAY WHAT A GAME", "subset": "test_other", "task_type": "understanding", "prediction": "it was your turn yesterday it is mine today what a game", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0002.flac", "answer": "SHALL I COME TOO FATHER NO", "subset": "test_other", "task_type": "understanding", "prediction": "shall i come too father no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0003.flac", "answer": "STOP HERE TILL SIR RISDON COMES DOWN AND TELL HIM I'M VERY SORRY THAT WE SHOULD HAVE CLEARED OUT LAST NIGHT ONLY A BORN FOOL SAW JERRY NANDY'S LOBSTER BOAT COMING INTO THE COVE AND CAME RUNNING TO SAY IT WAS A PARTY FROM THE CUTTER YES FATHER", "subset": "test_other", "task_type": "understanding", "prediction": "stop here till sir risdon comes down and tell him i am very sorry that we should have cleared out last night only a born fool saw jerry and andy s lobster boat coming into the cove and came running to say it was a party from the cutter yes father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0010.flac", "answer": "AND I'M HUNGRY TOO TIME I WAS UP I SUPPOSE", "subset": "test_other", "task_type": "understanding", "prediction": "and i am hungry too time i was up i suppose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0019.flac", "answer": "IT WAS YOU FATHER KICKED FOR SHIRKING AND MY WELL I HARDLY KNOWED YOU", "subset": "test_other", "task_type": "understanding", "prediction": "it was you father kicked for shirking and my well i hardly knowed you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0028.flac", "answer": "A HAPPY INSPIRATION HAD COME AND PLACING ONE HAND UPON HIS BREAST HE THRUST IN THE OTHER GAVE A TUG AND DREW OUT HIS LITTLE CURVED DIRK GLANCED AT THE EDGE RAN TO THE WINDOW AND BEGAN TO CUT AT ONE OF THE BARS LABOUR IN VAIN", "subset": "test_other", "task_type": "understanding", "prediction": "a happy inspiration had come and placing one hand upon his chest he thrust in the other gave a tug and drew out his little curved dirk glanced at the edge ran to the window and began to cut at one of the bars labour in vain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0009.flac", "answer": "THERE WAS AN INTERVAL OF THINKING OVER THIS KNOTTY QUESTION DURING WHICH THE LOW WHISTLING WENT ON", "subset": "test_other", "task_type": "understanding", "prediction": "there was an interval of thinking over this knotty question during which the low whistling went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0037.flac", "answer": "WHY YOUR CLOTHES DON'T FIT YOU AND YOUR CAP'S PUT ON ALL SKEW REW", "subset": "test_other", "task_type": "understanding", "prediction": "why your clothes dont fit you and your cap is put on all scuro", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0026.flac", "answer": "HE HAS GONE TO GIVE THE ALARM THOUGHT THE PRISONER AND HE LOOKED EXCITEDLY ROUND FOR A WAY OF ESCAPE", "subset": "test_other", "task_type": "understanding", "prediction": "he has gone to give the alarm thought the prisoner and he looked excitedly round for a way of escape", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0045.flac", "answer": "RAM SHOWED HIS WHITE TEETH AS HE BURST OUT WITH A LONG LOW FIT OF LAUGHTER", "subset": "test_other", "task_type": "understanding", "prediction": "ram showed his white teeth as he burst out with a long low fit of laughter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0038.flac", "answer": "NEVER MIND ABOUT THAT LET ME OUT OF THIS PLACE", "subset": "test_other", "task_type": "understanding", "prediction": "never mind about that let me out of this place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0015.flac", "answer": "RAM WAS THE FIRST TO RECOVER FROM HIS SURPRISE", "subset": "test_other", "task_type": "understanding", "prediction": "ram was the first to recover from his surprise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0044.flac", "answer": "I SAY YOU DO LOOK A RUM UN JUST LIKE A BIG MONKEY IN A SHOW", "subset": "test_other", "task_type": "understanding", "prediction": "i say you do look like a rummin just like a big monkey in a show", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0020.flac", "answer": "NONSENSE", "subset": "test_other", "task_type": "understanding", "prediction": "nonsense", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0050.flac", "answer": "TO HIS ASTONISHMENT THE BOY DID NOT FLINCH BUT THRUST HIS OWN ARMS THROUGH PLACING THEM ABOUT THE MIDDY'S WAIST CLENCHING HIS HANDS BEHIND AND UTTERING A SHARP WHISTLE", "subset": "test_other", "task_type": "understanding", "prediction": "to his astonishment the boy did not flinch but thrust his own arms through placing them about the middy s waist clenching his hand behind and uttering a sharp whistle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0027.flac", "answer": "NOTHING BUT THE CHIMNEY PRESENTED ITSELF", "subset": "test_other", "task_type": "understanding", "prediction": "nothing but the chimney presented itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0008.flac", "answer": "AND WHY DID ANDY CALL MISTER GURR FATHER", "subset": "test_other", "task_type": "understanding", "prediction": "and why did andy call mr gurr father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0046.flac", "answer": "YOU ROPE'S END ME HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "you rope send me he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0040.flac", "answer": "NOT YOU LOOK LIKE A WILD BEAST IN A CAGE LIKE A MONKEY YOU INSOLENT", "subset": "test_other", "task_type": "understanding", "prediction": "not you look like a wild beast in a cage like a monkey you insolent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0043.flac", "answer": "YOU LAUGHED AND FLEERED AT ME WHEN I WAS ON THE CUTTER'S DECK", "subset": "test_other", "task_type": "understanding", "prediction": "you laughed and fleered at me when i was on the cutter s deck", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0023.flac", "answer": "WON'T DO SAID RAM QUICKLY I KNOW YOU", "subset": "test_other", "task_type": "understanding", "prediction": "wont do said rem quickly i know you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0021.flac", "answer": "WON'T DO SAID RAM GRINNING", "subset": "test_other", "task_type": "understanding", "prediction": "wont do said ram grinning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0031.flac", "answer": "BUT AT THE END OF FIVE MINUTES HE STOPPED AND THRUST BACK THE DIRK INTO ITS SHEATH", "subset": "test_other", "task_type": "understanding", "prediction": "but at the end of five minutes he stopped and thrust back the dirk into its sheath", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96592/7902-96592-0017.flac", "answer": "GO ROUND AND OPEN THE DOOR I WAS SHUT IN LAST NIGHT BY MISTAKE", "subset": "test_other", "task_type": "understanding", "prediction": "go round and open the door i was shut in last night by mistake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0012.flac", "answer": "NO WAIT ANOTHER HALF HOUR", "subset": "test_other", "task_type": "understanding", "prediction": "no wait another half hour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0019.flac", "answer": "WHAT FOR THERE AREN'T A PUBLIC HOUSE FOR TEN MILES DIDN'T MEAN THAT", "subset": "test_other", "task_type": "understanding", "prediction": "what for there aren t a public house for ten miles didn t mean that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0027.flac", "answer": "HE SWUNG ROUND WALKED AFT AND BEGAN SWEEPING THE SHORE AGAIN WITH HIS GLASS WHILE THE MASTER AND DICK EXCHANGED GLANCES WHICH MEANT A GREAT DEAL", "subset": "test_other", "task_type": "understanding", "prediction": "he swung round walked aft and began sweeping the shore again with his glass while the master and dick exchanged glances which meant a great deal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0021.flac", "answer": "HOPPING ABOUT LIKE A CAT ON HOT BRICKS", "subset": "test_other", "task_type": "understanding", "prediction": "hopping about like a cat on hot bricks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0011.flac", "answer": "I'M GETTING VERY ANXIOUS ABOUT MISTER RAYSTOKE START AT ONCE SIR", "subset": "test_other", "task_type": "understanding", "prediction": "i am getting very anxious about mr raistruk start at once sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0032.flac", "answer": "STEADY MY LADS STEADY CRIED THE MASTER KEEP STROKE AND THEN HE BEGAN TO MAKE PLANS AS TO HIS FIRST PROCEEDINGS ON GETTING ASHORE", "subset": "test_other", "task_type": "understanding", "prediction": "steady my lads steady cried the master keep stroke and then he began to make plans as to his first proceedings on getting ashore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0030.flac", "answer": "NOW MISTER GURR HE SAID I'M ONLY GOING TO SAY ONE THING TO YOU IN THE WAY OF INSTRUCTIONS YES SIR", "subset": "test_other", "task_type": "understanding", "prediction": "now mr gurr he said i am only going to say one thing to you in the way of instructions yes sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0023.flac", "answer": "BEG PARDON DIDN'T MEAN NOWT SIR SAID THE SAILOR TOUCHING HIS FORELOCK", "subset": "test_other", "task_type": "understanding", "prediction": "beg pardon didn t mean nout sir said the sailor touching his forelock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0014.flac", "answer": "THEN I MUST REQUEST THAT YOU WILL NOT MAKE IT AGAIN VERY TRUE", "subset": "test_other", "task_type": "understanding", "prediction": "then i must request that you will not make it again very true", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0022.flac", "answer": "NOW THEN WHY DO YOU WANT TO GO ASHORE", "subset": "test_other", "task_type": "understanding", "prediction": "now then why do you want to go ashore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0015.flac", "answer": "AWK WARD MISTER GURR AWKWARD", "subset": "test_other", "task_type": "understanding", "prediction": "awkward mr gurr awkward", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0001.flac", "answer": "YES SIR BUT HE MAY TURN UP ON THE CLIFF AT ANY MOMENT", "subset": "test_other", "task_type": "understanding", "prediction": "yes sir but he may turn up on the cliff at any moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0007.flac", "answer": "YOU DON'T THINK MISTER GURR THAT THEY WOULD DARE TO INJURE HIM IF HE WAS SO UNLUCKY AS TO BE CAUGHT", "subset": "test_other", "task_type": "understanding", "prediction": "you dont think mr gurr that they would dare to injure him if he was so unlucky as to be caught", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0031.flac", "answer": "BEG PARDON SIR SAID THE MASTER DEPRECATINGLY", "subset": "test_other", "task_type": "understanding", "prediction": "beg pardon sir said the master deprecatingly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0026.flac", "answer": "KEEP A SHARP LOOK OUT ON THE CLIFF TO SEE IF MISTER RAYSTOKE IS MAKING SIGNALS FOR A BOAT", "subset": "test_other", "task_type": "understanding", "prediction": "keep a sharp lookout on the cliff to see if mr ray stroke is making signals for a boat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0017.flac", "answer": "SAY AWK WARD IN FUTURE NOT AWK'ARD", "subset": "test_other", "task_type": "understanding", "prediction": "say awkward in the future not uckward", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0028.flac", "answer": "AT LAST THE LITTLE LIEUTENANT COULD BEAR THE ANXIETY NO LONGER", "subset": "test_other", "task_type": "understanding", "prediction": "at last the little lieutenant could bear the anxiety no longer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0003.flac", "answer": "THAT'S RIGHT OF COURSE WELL ARMED", "subset": "test_other", "task_type": "understanding", "prediction": "that is right of course well armed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0004.flac", "answer": "SOON AS THE SIGNAL COMES WE SHALL PUSH OFF", "subset": "test_other", "task_type": "understanding", "prediction": "soon as the signal comes we shall push off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0009.flac", "answer": "CERTAINLY SIR SMUGGLERS ARE SMUGGLERS INDEED", "subset": "test_other", "task_type": "understanding", "prediction": "certainly sir smugglers are smugglers indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0000.flac", "answer": "SEEMED IN GOOD SPIRITS LAST NIGHT MISTER GURR EH", "subset": "test_other", "task_type": "understanding", "prediction": "seemed in good spirits last night mr gurr eh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0025.flac", "answer": "NO WAIT", "subset": "test_other", "task_type": "understanding", "prediction": "no wait", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0008.flac", "answer": "WELL SIR SAID THE MASTER HESITATING SMUGGLERS ARE SMUGGLERS", "subset": "test_other", "task_type": "understanding", "prediction": "well sir said the master hesitating smugglers are smugglers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0013.flac", "answer": "VERY ILL ADVISED THING TO DO", "subset": "test_other", "task_type": "understanding", "prediction": "very ill advised thing to do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0006.flac", "answer": "SO SHALL WE YET SIR", "subset": "test_other", "task_type": "understanding", "prediction": "so shall we yes sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0029.flac", "answer": "PIPE AWAY THE MEN TO THAT BOAT THERE HE SAID AND AS THE CREW SPRANG IN", "subset": "test_other", "task_type": "understanding", "prediction": "pipe away the men to that boat there he said and as the crew sprang in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0005.flac", "answer": "AWKWARD BIT O COUNTRY SIR SIX MILES ROW BEFORE YOU CAN FIND A PLACE TO LAND", "subset": "test_other", "task_type": "understanding", "prediction": "awkward bit of country sir six miles row before you can find a place to land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0016.flac", "answer": "YES SIR OF COURSE", "subset": "test_other", "task_type": "understanding", "prediction": "yes sir of course", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0018.flac", "answer": "I MEAN ALL ALONE BY MYSELF SIR", "subset": "test_other", "task_type": "understanding", "prediction": "i mean all alone by myself sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0024.flac", "answer": "YES SIR SAID THE MAN HUMBLY SHALL I GO AT ONCE SIR", "subset": "test_other", "task_type": "understanding", "prediction": "yes sir said the man humbly shall i go at once sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0002.flac", "answer": "YES MEN QUITE READY YES SIR", "subset": "test_other", "task_type": "understanding", "prediction": "yes men quite ready yes sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0010.flac", "answer": "BEG PARDON SIR DIDN'T MEAN ANY HARM", "subset": "test_other", "task_type": "understanding", "prediction": "beg pardon sir didn t mean any harm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96594/7902-96594-0020.flac", "answer": "THEN WHAT DID YOU MEAN SPEAK OUT AND DON'T DO THE DOUBLE SHUFFLE ALL OVER MY CLEAN DECK NO SIR", "subset": "test_other", "task_type": "understanding", "prediction": "then what did you mean speak out and don t do the double shuffle all over my clean deck no sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0023.flac", "answer": "BUT THERE WAS NO CHANCE FOR HIS BODY THERE THE HEAD WOULD NOT GO FIRST", "subset": "test_other", "task_type": "understanding", "prediction": "but there was no chance for his body there and the head would not go first", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0012.flac", "answer": "FOR IT SUDDENLY OCCURRED TO HIM THAT HE WAS NOT ONLY A PRISONER BUT A PRISONER IN THE POWER OF A VERY RECKLESS SET OF PEOPLE WHO WOULD STOP AT NOTHING", "subset": "test_other", "task_type": "understanding", "prediction": "for it suddenly occurred to him that he was not only a prisoner but a prisoner in the power of a very reckless set of people who would stop at nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0010.flac", "answer": "COLD WATER CAME ON THIS IDEA DIRECTLY AS HE RECALLED THE FACT THAT THE DARKNESS WAS INTENSE AND CELIA COULD NOT HAVE SEEN HIM", "subset": "test_other", "task_type": "understanding", "prediction": "cold water came on this idea directly as he recalled the fact that the darkness was intense and celia could not have seen him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0024.flac", "answer": "A FELLOW WHO WAS SHUT UP IN PRISON FOR LIFE MIGHT DO IT HE SAID BUT NOT IN A CASE LIKE THIS", "subset": "test_other", "task_type": "understanding", "prediction": "a fellow who was shut up in prison for life might do it he said but not in a case like this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0000.flac", "answer": "I AM FROM THE CUTTER LYING OFF THE COAST", "subset": "test_other", "task_type": "understanding", "prediction": "i am from the cutter lying off the coast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0007.flac", "answer": "THEN AS ARCHY STOOD IN THE DARK LITERALLY AGHAST WITH ASTONISHMENT HE HEARD THE FAINT RUSTLING ONCE MORE AND AGAIN ALL WAS SILENT", "subset": "test_other", "task_type": "understanding", "prediction": "then as archie stood in the dark literally aghast with astonishment he heard the faint rustling once more and again all was silent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0015.flac", "answer": "TO DO THIS HE MUST SCHEME LIE HID TILL MORNING THEN MAKE FOR THE NEAREST POINT AND SIGNAL FOR HELP UNLESS A BOAT'S CREW WERE ALREADY SEARCHING FOR HIM HOW TO ESCAPE", "subset": "test_other", "task_type": "understanding", "prediction": "to do this he must scheme lie hid till morning then make for the nearest point and signal for help unless a boats crew were already searching for him how to escape", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0022.flac", "answer": "HE WENT AND TRIED TO FORCE HIS HEAD THROUGH RECALLING AS HE DID THAT WHERE A PERSON'S HEAD WOULD GO THE REST OF THE BODY WOULD PASS", "subset": "test_other", "task_type": "understanding", "prediction": "he went and tried to force his head through recalling as he did that where a person s head would go the rest of the body would pass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0006.flac", "answer": "PRAY PRAY SAY YOU WILL NOT ARCHY WAS SILENT", "subset": "test_other", "task_type": "understanding", "prediction": "pray pray say you will not archie was silent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0003.flac", "answer": "I WISH YOU WOULD BELIEVE ME THAT I AM IN AS GREAT TROUBLE ABOUT IT AS YOU ARE", "subset": "test_other", "task_type": "understanding", "prediction": "i wish you would believe me that i am in as great trouble about it as you are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0004.flac", "answer": "THAT MY FATHER SIR RISDON GRAEME HAS SMUGGLED GOODS HERE", "subset": "test_other", "task_type": "understanding", "prediction": "that my father sir risdon graham has smuggled goods here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0008.flac", "answer": "HE LAUGHED BUT IT WAS A CURIOUS KIND OF LAUGH FULL OF VEXATION INJURED AMOUR PROPRE AS THE FRENCH CALL OUR LOVE OF OUR OWN DIGNITY OF WHICH ARCHIBALD RAYSTOKE IN THE FULL FLUSH OF HIS YOUNG BELIEF IN HIS IMPORTANCE AS A BRITISH OFFICER HAD A PRETTY GOOD STOCK", "subset": "test_other", "task_type": "understanding", "prediction": "he laughed but it was a curious kind of laugh full of vexation injured amour propre as the french call our love of our own dignity of which archibald ray stroke in the full flush of his young belief in his importance as a british officer had a pretty good stock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0005.flac", "answer": "HE COULD NOT HELP IT HE HATES THE SMUGGLERS YOU SHALL NOT TELL", "subset": "test_other", "task_type": "understanding", "prediction": "he could not help it he hates the smugglers you shall not tell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0002.flac", "answer": "AND AND YOU HAVE NOT FOUND OUT ANYTHING CAME IN QUICK FRIGHTENED TONES", "subset": "test_other", "task_type": "understanding", "prediction": "and and you have not found out anything came in quick frightened tones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0017.flac", "answer": "NEXT MOMENT AS HE FELT HIS WAY ABOUT HIS HAND TOUCHED AN OLD FASHIONED MARBLE MANTELPIECE FIREPLACE CHIMNEY", "subset": "test_other", "task_type": "understanding", "prediction": "next moment as he felt his way about his hand touched an old fashioned marble mantelpiece fireplace chimney", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0009.flac", "answer": "IT ALL COMES OF DRESSING UP IN THIS STUPID WAY LIKE A ROUGH FISHER LAD", "subset": "test_other", "task_type": "understanding", "prediction": "and all comes of dressing up in this stupid way like a rough fisher lad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0014.flac", "answer": "THE KICK HE HAD RECEIVED WAS A FORETASTE OF WHAT HE MIGHT EXPECT AND AFTER A LITTLE CONSIDERATION HE CAME TO THE CONCLUSION THAT HIS DUTY WAS TO ESCAPE AND GET BACK TO THE CUTTER AS QUICKLY AS HE COULD", "subset": "test_other", "task_type": "understanding", "prediction": "the kick he had received was a foretaste of what he might expect and after a little consideration he came to the conclusion that his duty was to escape and get back to the cutter as quickly as he could", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0013.flac", "answer": "NO HE THOUGHT TO HIMSELF I DON'T BELIEVE THEY WOULD KILL ME BUT THEY WOULD KNOCK ME ABOUT", "subset": "test_other", "task_type": "understanding", "prediction": "no he thought to himself i don t believe they would kill me but they would knock me about", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0016.flac", "answer": "THE WINDOW WAS BARRED BUT HE WENT TO IT AND TRIED THE BARS ONE BY ONE TO FIND THEM ALL SOLIDLY FITTED INTO THE STONE SILL", "subset": "test_other", "task_type": "understanding", "prediction": "the window was barred but he went to it and tried the bars one by one to find them all solidly fitted into the stone sill", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0001.flac", "answer": "DON'T CRY HE SAID I WAS OBLIGED TO COME", "subset": "test_other", "task_type": "understanding", "prediction": "dont cry he said i was obliged to come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0020.flac", "answer": "SYMPATHY AND PITY FOR THE DWELLERS IN THE HOZE WERE COMPLETELY GONE NOW AND HE SET HIS TEETH FAST AND MENTALLY CALLED HIMSELF A WEAK IDIOT FOR EVER THINKING ABOUT SUCH PEOPLE", "subset": "test_other", "task_type": "understanding", "prediction": "sympathy and pity for the dwellers in the hoes were completely gone now and he set his teeth fast and mentally called himself a weak idiot for ever thinking about such people", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0018.flac", "answer": "YES IF OTHER WAYS FAILED HE COULD ESCAPE UP THE CHIMNEY", "subset": "test_other", "task_type": "understanding", "prediction": "yes if other ways failed he could escape up the chimney", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0019.flac", "answer": "NO THAT WAS TOO BAD HE COULD NOT DO THAT", "subset": "test_other", "task_type": "understanding", "prediction": "no that was too bad he cannot do that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0011.flac", "answer": "I'LL SOON SHOW THEM THAT I AM NOT GOING TO BE PLAYED WITH", "subset": "test_other", "task_type": "understanding", "prediction": "ill soon show them that i am not going to be played with", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96591/7902-96591-0021.flac", "answer": "A NARROW TABLE AGAINST THE WALL IN TWO PLACES", "subset": "test_other", "task_type": "understanding", "prediction": "a narrow table against the wall in two places", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0002.flac", "answer": "WHAT CHUCKED HIM OFF YONDER", "subset": "test_other", "task_type": "understanding", "prediction": "what tracked him off yonder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0017.flac", "answer": "I DUNNO MUTTERED DICK AND A MAN CAN'T BE SURE", "subset": "test_other", "task_type": "understanding", "prediction": "i dunno muttered dick and a man can t be sure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0019.flac", "answer": "A LAD LOOKING LIKE A COMMON SAILOR AND WEARING A RED CAP NO SAID SIR RISDON", "subset": "test_other", "task_type": "understanding", "prediction": "a lad looking like a common sailor and wearing a red cap no said sir risdon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0001.flac", "answer": "MISTER RAYSTOKE SIR DON'T BE A FOOL", "subset": "test_other", "task_type": "understanding", "prediction": "mr raystoke sir don t be a fool", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0006.flac", "answer": "I HOPE NOT DICK I HOPE NOT BUT SMUGGLERS DON'T STAND AT ANYTHING SOMETIMES", "subset": "test_other", "task_type": "understanding", "prediction": "i hope not dick i hope not but smugglers don't stand at anything sometimes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0009.flac", "answer": "BOY BOUT SEVENTEEN WITH A RED CAP NO SIR INDEED I'VE NOT", "subset": "test_other", "task_type": "understanding", "prediction": "boy about seventeen with a red cap no sir indeed i have not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0003.flac", "answer": "GURR GLANCED ROUND TO SEE IF THE MEN WERE LOOKING AND THEN SAID RATHER HUSKILY BUT KINDLY", "subset": "test_other", "task_type": "understanding", "prediction": "gerr glanced round to see if the men were looking and then said rather huskily but kindly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0013.flac", "answer": "THE MAN SHOOK HIS HEAD AND STARED AS IF HE DIDN'T HALF UNDERSTAND THE DRIFT OF WHAT WAS SAID", "subset": "test_other", "task_type": "understanding", "prediction": "the man shook his head and stared as if he did n t half understand the drift of what was said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0007.flac", "answer": "I DO ASSURE YOU THERE'S NOTHING HERE BUT WHAT YOU MAY SEE", "subset": "test_other", "task_type": "understanding", "prediction": "i do assure you there is nothing here but what you may see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0023.flac", "answer": "SIR RISDON WAS SILENT", "subset": "test_other", "task_type": "understanding", "prediction": "sir richmond was silent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0005.flac", "answer": "SAY MESTER GURR SIR WHICH THANKFUL I AM TO YOU FOR SPEAKING SO BUT YOU DON'T REALLY THINK AS HE HAS COME TO HARM", "subset": "test_other", "task_type": "understanding", "prediction": "say mr gursuer which thankful i am for you for speaking so but you do not really think as he has come to harm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0021.flac", "answer": "BEG PARDON SIR BUT CAN YOU AS A GENTLEMAN ASSURE ME THAT HE IS NOT HERE CERTAINLY SAID SIR RISDON", "subset": "test_other", "task_type": "understanding", "prediction": "beg pardon sir but can you as a gentleman assure me that he is not here certainly said sir risdon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0012.flac", "answer": "I SAID A LAD BOUT SEVENTEEN IN A RED CAP LIKE YOURS SAID GURR VERY SHORTLY", "subset": "test_other", "task_type": "understanding", "prediction": "i said a lad about seventeen in a red cap like yours said gurr very shortly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0004.flac", "answer": "AH EJACULATED DICK SADLY", "subset": "test_other", "task_type": "understanding", "prediction": "ah ejaculated dick sadly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0015.flac", "answer": "EH I SAY WHERE'S YOUR MASTER", "subset": "test_other", "task_type": "understanding", "prediction": "eh i say where is your master", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0022.flac", "answer": "SURELY CRIED SIR RISDON EXCITEDLY", "subset": "test_other", "task_type": "understanding", "prediction": "surely cried sir gisborne excitedly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0016.flac", "answer": "GURR TURNED AWAY IMPATIENTLY AGAIN AND SIGNING TO HIS MEN TO FOLLOW THEY ALL BEGAN TO TRAMP UP THE STEEP TRACK LEADING TOWARD THE HOZE WITH THE RABBITS SCUTTLING AWAY AMONG THE FURZE AND SHOWING THEIR WHITE COTTONY TAILS FOR A MOMENT AS THEY DARTED DOWN INTO THEIR HOLES", "subset": "test_other", "task_type": "understanding", "prediction": "gurr turned away impatiently again and signing to his men to follow they all began to tramp up the steep track leading toward the houghes with the rabbits scuttling away among the furze and showing their white cottony tails for a moment as they darted down into their holes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0014.flac", "answer": "HERE MY LAD WHERE'S YOUR MASTER", "subset": "test_other", "task_type": "understanding", "prediction": "here my lad where is your master", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0020.flac", "answer": "I HAVE SEEN NO ONE ANSWERING TO THE DESCRIPTION HERE", "subset": "test_other", "task_type": "understanding", "prediction": "i have seen no one answering to the description here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0010.flac", "answer": "DON'T KNOW AS HE HAS BEEN SEEN ABOUT HERE DO YOU SAID GURR LOOKING AT HER SEARCHINGLY NO SIR", "subset": "test_other", "task_type": "understanding", "prediction": "dont know as he has been seen about here do you said the girl looking at her searchingly no sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0024.flac", "answer": "LADY GRAEME LOOKED GHASTLY", "subset": "test_other", "task_type": "understanding", "prediction": "lady graham looked ghastly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0011.flac", "answer": "IF SHE KNEW EVIL HAD COME TO THE POOR LAD HER FACE WOULD TELL TALES LIKE PRINT", "subset": "test_other", "task_type": "understanding", "prediction": "if she knew evil had come to the poor lad her face would tell tales like print", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0000.flac", "answer": "SAY MESTER GURR SAID DICK AFTER ONE OF THESE SEARCHES HE WOULDN'T RUN AWAY WHAT", "subset": "test_other", "task_type": "understanding", "prediction": "say mr girk said dick after one of these searches he wouldnt run away what", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0025.flac", "answer": "YOU DO NOT KNOW NO", "subset": "test_other", "task_type": "understanding", "prediction": "you do not know no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0018.flac", "answer": "GURR SALUTED AND STATED HIS BUSINESS WHILE THE BARONET WHO HAD TURNED SALLOWER AND MORE CAREWORN THAN HIS LOT DREW A BREATH FULL OF RELIEF ONE OF YOUR SHIP BOYS HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "gur saluted and stated his business while the baronet who had turned sallow and more careworn than his lot drew a breath of full relief one of your ship boys he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7902/96595/7902-96595-0008.flac", "answer": "IF YOU'D LET ME FINISH YOU'D KNOW SAID GURR GRUFFLY ONE OF OUR BOYS IS MISSING SEEN HIM UP HERE", "subset": "test_other", "task_type": "understanding", "prediction": "if you let me finish you would know said gregg roughly one of our boys is missing seen him up here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0019.flac", "answer": "BUT THERE IS MAJESTY AND THERE IS NO MIGHT SAVE IN ALLAH THE GLORIOUS THE GREAT", "subset": "test_other", "task_type": "understanding", "prediction": "but there is majesty and there is no might save in allah the glorious the great", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0007.flac", "answer": "NOW SLEEPING UNDER THESE TREES WERE MANY APES WHICH WHEN THEY SAW US ROSE AND FLED FROM US AND SWARMED UP AMONG THE BRANCHES WHEREUPON MY COMPANIONS BEGAN TO PELT THEM WITH WHAT THEY HAD IN THEIR BAGS AND THE APES FELL TO PLUCKING OF THE FRUIT OF THE TREES AND CASTING THEM AT THE FOLK", "subset": "test_other", "task_type": "understanding", "prediction": "now sleeping under these trees were many apes which when they saw us rose and fled from us and swarmed up among the branches whereupon my companions began to pelt them with what they had in their bags and the apes fell to plucking of the fruit of the trees and casting them at the folk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0005.flac", "answer": "THEN HE CARRIED ME TO THE BEACH WHERE I FILLED MY BAG WITH PEBBLES LARGE AND SMALL AND PRESENTLY WE SAW A COMPANY OF FOLK ISSUE FROM THE TOWN EACH BEARING A BAG LIKE MINE FILLED WITH PEBBLES", "subset": "test_other", "task_type": "understanding", "prediction": "then he carried me to the beach where i filled my bag with pebbles large and small and presently we saw a company of folk issue from the town each bearing a bag like mine filled with pebbles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0008.flac", "answer": "WE WEIGHED ANCHOR AND SHAHRAZAD PERCEIVED THE DAWN OF DAY AND CEASED SAYING HER PERMITTED SAY", "subset": "test_other", "task_type": "understanding", "prediction": "we weighed anchor and shahrazad perceived the dawn of day and ceased saying her permitted say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0006.flac", "answer": "TO THESE HE COMMITTED ME COMMENDING ME TO THEIR CARE AND SAYING THIS MAN IS A STRANGER SO TAKE HIM WITH YOU AND TEACH HIM HOW TO GATHER THAT HE MAY GET HIS DAILY BREAD AND YOU WILL EARN YOUR REWARD AND RECOMPENSE IN HEAVEN", "subset": "test_other", "task_type": "understanding", "prediction": "to these he committed me commending me to their care and saying this man is a stranger so take him with you and teach him how to gather that he may get his daily bread and you will earn your reward and recompense in heaven", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0018.flac", "answer": "EACH THAT DIED WE WASHED AND SHROUDED IN SOME OF THE CLOTHES AND LINEN CAST ASHORE BY THE TIDES AND AFTER A LITTLE THE REST OF MY FELLOWS PERISHED ONE BY ONE TILL I HAD BURIED THE LAST OF THE PARTY AND ABODE ALONE ON THE ISLAND WITH BUT A LITTLE PROVISION LEFT I WHO WAS WONT TO HAVE SO MUCH", "subset": "test_other", "task_type": "understanding", "prediction": "each that died we washed and shrouded in some of the clothes and linen cast ashore by the tides and after little the rest of my fellows perished one by one till i had buried the last of the party and abode alone on the island with but a little provision left i who was wont to have so much", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0016.flac", "answer": "PRESENTLY THE SHIP STRUCK THE MOUNTAIN AND BROKE UP AND ALL AND EVERYTHING ON BOARD OF HER WERE PLUNGED INTO THE SEA", "subset": "test_other", "task_type": "understanding", "prediction": "presently the ship struck the mountain and broke up and all and everything on board of her were plunged into the sea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0015.flac", "answer": "HAPLY AMONGST YOU IS ONE RIGHTEOUS WHOSE PRAYERS THE LORD WILL ACCEPT", "subset": "test_other", "task_type": "understanding", "prediction": "happily amongst you is one righteous whose prayers the lord will accept", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0012.flac", "answer": "AFTER WHICH I RETURNED TO MY OLD MERRY WAY OF LIFE AND FORGOT ALL I HAD SUFFERED IN THE GREAT PROFIT AND GAIN I HAD MADE", "subset": "test_other", "task_type": "understanding", "prediction": "after which i returned to my old merry way of life and forgot all i had suffered in the great profit and gain i had made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0010.flac", "answer": "AND CEASED NOT SAILING TILL WE ARRIVED SAFELY AT BASSORAH", "subset": "test_other", "task_type": "understanding", "prediction": "and ceased not sailing till we arrived safely at busarah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0000.flac", "answer": "THEN I TOOK UP A GREAT STONE FROM AMONG THE TREES AND COMING UP TO HIM SMOTE HIM THEREWITH ON THE HEAD WITH ALL MY MIGHT AND CRUSHED IN HIS SKULL AS HE LAY DEAD DRUNK", "subset": "test_other", "task_type": "understanding", "prediction": "then i took up a great stone from among the trees and coming up to him smote him therewith on the head with all my might and crushed in his skull as he lay dead drunk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0003.flac", "answer": "UPON THIS HE BROUGHT ME A COTTON BAG AND GIVING IT TO ME SAID TAKE THIS BAG AND FILL IT WITH PEBBLES FROM THE BEACH AND GO FORTH WITH A COMPANY OF THE TOWNSFOLK TO WHOM I WILL GIVE A CHARGE RESPECTING THEE", "subset": "test_other", "task_type": "understanding", "prediction": "upon this he bought me a cotton bag and giving it to me said take this bag and fill it with pebbles from the beach and go forth with a company of the townsfolk to whom i will give a charge respecting thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0011.flac", "answer": "THERE I ABODE A LITTLE AND THEN WENT ON TO BAGHDAD WHERE I ENTERED MY QUARTER AND FOUND MY HOUSE AND FOREGATHERED WITH MY FAMILY AND SALUTED MY FRIENDS WHO GAVE ME JOY OF MY SAFE RETURN AND I LAID UP ALL MY GOODS AND VALUABLES IN MY STOREHOUSES", "subset": "test_other", "task_type": "understanding", "prediction": "there i abode a little and then went on to baghdad where i entered my quarter and found my house and forgathered with my family and saluted my friends who gave me joy of my safe return and i laid up all my goods and valuables in my storehouses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0017.flac", "answer": "BUT IT BURNETH IN THEIR BELLIES SO THEY CAST IT UP AGAIN AND IT CONGEALETH ON THE SURFACE OF THE WATER WHEREBY ITS COLOR AND QUANTITIES ARE CHANGED AND AT LAST THE WAVES CAST IT ASHORE AND THE TRAVELLERS AND MERCHANTS WHO KNOW IT COLLECT IT AND SELL IT", "subset": "test_other", "task_type": "understanding", "prediction": "but it burneth in their bellies so they cast it up again and it congealeth on the surface of the water whereby its colour and quantities are changed and at last the waves cast it ashore and the travellers and merchants who know it collect it and sell it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0002.flac", "answer": "HEARING THIS I WAS SORE TROUBLED REMEMBERING WHAT I HAD BEFORE SUFFERED FROM THE APE KIND", "subset": "test_other", "task_type": "understanding", "prediction": "hearing this i was sore troubled remembering what i had before suffered from the ape kind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0004.flac", "answer": "DO AS THEY DO AND BELIKE THOU SHALT GAIN WHAT MAY FURTHER THY RETURN VOYAGE TO THY NATIVE LAND", "subset": "test_other", "task_type": "understanding", "prediction": "do as they do and belike thou shalt gain what may further thy return voyage to thy native land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0014.flac", "answer": "HERE I FOUND A GREAT SHIP READY FOR SEA AND FULL OF MERCHANTS AND NOTABLES WHO HAD WITH THEM GOODS OF PRICE SO I EMBARKED MY BALES THEREIN", "subset": "test_other", "task_type": "understanding", "prediction": "here i found a great ship ready for sea and full of merchants and notables who had with them goods of price so i embarked my bales therein", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0009.flac", "answer": "WHEN IT WAS THE FIVE HUNDRED AND FIFTY NINTH NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "when it was the five hundred and fifty ninth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0013.flac", "answer": "NEXT MORNING AS SOON AS IT WAS LIGHT HE PRAYED THE DAWN PRAYER AND AFTER BLESSING MOHAMMED THE CREAM OF ALL CREATURES BETOOK HIMSELF TO THE HOUSE OF SINDBAD THE SEAMAN AND WISHED HIM A GOOD DAY", "subset": "test_other", "task_type": "understanding", "prediction": "next morning as soon as it was light he prayed the dawn prayer and after blessing mahomet the cream of all creatures betook himself to the house of sindbad the seaman and wished him a good day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75788/7018-75788-0001.flac", "answer": "BEHOLD A SHIP WAS MAKING FOR THE ISLAND THROUGH THE DASHING SEA AND CLASHING WAVES", "subset": "test_other", "task_type": "understanding", "prediction": "behold a ship was making for the island through the dashing sea and clashing waves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0031.flac", "answer": "WHEN SUDDENLY A VIOLENT SQUALL OF WIND AROSE AND SMOTE THE SHIP WHICH ROSE OUT OF THE WATER AND SETTLED UPON A GREAT REEF THE HAUNT OF SEA MONSTERS WHERE IT BROKE UP AND FELL ASUNDER INTO PLANKS AND ALL AND EVERYTHING ON BOARD WERE PLUNGED INTO THE SEA", "subset": "test_other", "task_type": "understanding", "prediction": "when suddenly a violent squall of wind arose and smote the ship which rose out of the water and settled upon a great reef the haunt of sea monsters where it broke up and fell asunder into planks and all and everything on board were plunged into the sea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0027.flac", "answer": "SO HAVING MADE UP MY MIND I PACKED UP IN BALES A QUANTITY OF PRECIOUS STUFFS SUITED FOR SEA TRADE AND REPAIRED WITH THEM FROM BAGHDAD CITY TO BASSORAH TOWN WHERE I FOUND A SHIP READY FOR SEA AND IN HER A COMPANY OF CONSIDERABLE MERCHANTS", "subset": "test_other", "task_type": "understanding", "prediction": "so having made up my mind i packed up in bales a quantity of precious stuffs suited for sea trade and repaired with them from bagdad city to bassorah town where i found a ship ready for sea and in her a company of considerable merchants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0023.flac", "answer": "WHEN IT WAS THE FIVE HUNDRED AND SIXTY THIRD NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "when it was the five hundred and sixty third night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0006.flac", "answer": "BUT I WAS DELIGHTED AT MY ESCAPE FROM THE RIVER", "subset": "test_other", "task_type": "understanding", "prediction": "but i was delighted at my escape from the river", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0007.flac", "answer": "WHEN THEY SAW I UNDERSTOOD THEM NOT AND MADE THEM NO ANSWER ONE OF THEM CAME FORWARD AND SAID TO ME IN ARABIC PEACE BE WITH THEE O MY BROTHER", "subset": "test_other", "task_type": "understanding", "prediction": "when they saw i understood them not and made them no answer one of them came forward and said to me in arabic peace be with thee o my brother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0026.flac", "answer": "KNOW O COMPANY THAT AFTER MY RETURN FROM MY SIXTH VOYAGE WHICH BROUGHT ME ABUNDANT PROFIT I RESUMED MY FORMER LIFE IN ALL POSSIBLE JOYANCE AND ENJOYMENT AND MIRTH AND MAKING MERRY DAY AND NIGHT AND I TARRIED SOME TIME IN THIS SOLACE AND SATISFACTION TILL MY SOUL BEGAN ONCE MORE TO LONG TO SAIL THE SEAS AND SEE FOREIGN COUNTRIES AND COMPANY WITH MERCHANTS AND HEAR NEW THINGS", "subset": "test_other", "task_type": "understanding", "prediction": "know o company that after my return from my sixth voyage which brought me abundant profit i resumed my former life in all possible joyance and enjoyment and mirth and making merry day and night and i tarried some time in this solace and satisfaction till my soul began once more to long to sail the seas and see foreign countries and company with merchants and hear new things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0000.flac", "answer": "WHEN IT WAS THE FIVE HUNDRED AND SIXTY FIRST NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "when it was the five hundred and sixty first night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0003.flac", "answer": "I ROWED MY CONVEYANCE INTO THE PLACE WHICH WAS INTENSELY DARK AND THE CURRENT CARRIED THE RAFT WITH IT DOWN THE UNDERGROUND CHANNEL", "subset": "test_other", "task_type": "understanding", "prediction": "i rowed my conveyance into the place which was intensely dark and the current carried me the raft with it down the underground channel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0029.flac", "answer": "THIS HE SET IN A SAUCER WETTED WITH A LITTLE WATER AND AFTER WAITING A SHORT TIME SMELT AND TASTED IT AND THEN HE TOOK OUT OF THE CHEST A BOOKLET WHEREIN HE READ AWHILE AND SAID WEEPING KNOW O YE PASSENGERS THAT IN THIS BOOK IS A MARVELLOUS MATTER DENOTING THAT WHOSO COMETH HITHER SHALL SURELY DIE WITHOUT HOPE OF ESCAPE FOR THAT THIS OCEAN IS CALLED THE SEA OF THE CLIME OF THE KING WHEREIN IS THE SEPULCHRE OF OUR LORD SOLOMON SON OF DAVID ON BOTH BE PEACE", "subset": "test_other", "task_type": "understanding", "prediction": "this he set in a saucer wetted with a little water and after waiting a short time smelt and tasted it and then he took out of the chest a booklet wherein he read awhile and said weeping know o ye passengers that in this book is a marvellous matter denoting that whoso come hither shall surely die without hope of escape for that this ocean is called the sea of the clime of the king wherein is the sepulchre of our lord solomon son of david on both be peace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0022.flac", "answer": "I WILL TELL YOU THE STORY OF MY SEVENTH AND LAST VOYAGE WHICH IS STILL MORE WONDROUS AND MARVELLOUS THAN THAT OF THE FIRST SIX", "subset": "test_other", "task_type": "understanding", "prediction": "i will tell you the story of my seventh and last voyage which is still more wondrous and marvellous than that of the first six", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0017.flac", "answer": "HE ASKED ME WHENCE THEY CAME AND I SAID TO HIM BY ALLAH O COMMANDER OF THE FAITHFUL I KNOW NOT THE NAME OF THE CITY NOR THE WAY THITHER", "subset": "test_other", "task_type": "understanding", "prediction": "he asked me whence they came and i said to him by allah o commander of the faithful i know not the name of the city nor the way thither", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0014.flac", "answer": "QUOTH HE THOU ART THINE OWN MASTER YET IF IT BE THY WILL TO ABIDE WITH US ON OUR HEAD AND EYES BE IT FOR THOU GLADDENEST US WITH THY COMPANY", "subset": "test_other", "task_type": "understanding", "prediction": "quoth he thou art thine own master yet if it be thy will to abide with us on our head and eyes be it for thou gladdenest us with thy company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0009.flac", "answer": "I ANSWERED FOR ALLAH'S SAKE O MY LORD ERE I SPEAK GIVE ME SOMEWHAT TO EAT FOR I AM STARVING AND AFTER ASK ME WHAT THOU WILT", "subset": "test_other", "task_type": "understanding", "prediction": "i answered for allahs sake o my lord ere i speak give me somewhat to eat for i am starving and after ask me what thou wilt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0004.flac", "answer": "AND I THREW MYSELF DOWN UPON MY FACE ON THE RAFT BY REASON OF THE NARROWNESS OF THE CHANNEL WHILST THE STREAM CEASED NOT TO CARRY ME ALONG KNOWING NOT NIGHT FROM DAY FOR THE EXCESS OF THE GLOOM WHICH ENCOMPASSED ME ABOUT AND MY TERROR AND CONCERN FOR MYSELF LEST I SHOULD PERISH", "subset": "test_other", "task_type": "understanding", "prediction": "and i threw myself down upon my face on the raft by reason of the narrowness of the channel whilst the stream ceased not to carry me along knowing not night from day for the excess of the gloom which encompassed me about in my terror and concern for myself lest i should perish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0012.flac", "answer": "SO I CONSORTED WITH THE CHIEF OF THE ISLANDERS AND THEY PAID ME THE UTMOST RESPECT", "subset": "test_other", "task_type": "understanding", "prediction": "so i consorted with the chief of the islanders and they paid me the utmost respect", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0021.flac", "answer": "SUCH THEN O MY BROTHERS IS THE HISTORY OF WHAT BEFEL ME IN MY SIXTH VOYAGE AND TO MORROW INSHALLAH", "subset": "test_other", "task_type": "understanding", "prediction": "such then o my brothers is the history of what befell me in my sixth voyage and to morrow inshallah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0024.flac", "answer": "SHE SAID IT HATH REACHED ME O AUSPICIOUS KING THAT WHEN SINDBAD THE SEAMAN HAD RELATED THE HISTORY OF WHAT BEFEL HIM IN HIS SIXTH VOYAGE AND ALL THE COMPANY HAD DISPERSED SINDBAD THE LANDSMAN WENT HOME AND SLEPT AS OF WONT", "subset": "test_other", "task_type": "understanding", "prediction": "she said it hath reached me o auspicious king that when sindbad the seaman had related the history of what befell him in his sixth voyage and all the company had dispersed sindbad the landsman went home and slept as of wont", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0025.flac", "answer": "THE SEVENTH VOYAGE OF SINDBAD THE SEAMAN", "subset": "test_other", "task_type": "understanding", "prediction": "the seventh voyage of sindbad the seaman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0018.flac", "answer": "FOR STATE PROCESSIONS A THRONE IS SET FOR HIM UPON A HUGE ELEPHANT ELEVEN CUBITS HIGH AND UPON THIS HE SITTETH HAVING HIS GREAT LORDS AND OFFICERS AND GUESTS STANDING IN TWO RANKS ON HIS RIGHT HAND AND ON HIS LEFT", "subset": "test_other", "task_type": "understanding", "prediction": "for state processions a throne is set for him upon a huge elephant eleven cubits high and upon this he sitteth having his great lords and officers and guests standing in two ranks on his right hand and on his left", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0019.flac", "answer": "HIS LETTER HATH SHOWN ME THIS AND AS FOR THE MIGHTINESS OF HIS DOMINION THOU HAST TOLD US WHAT THOU HAST EYE WITNESSED", "subset": "test_other", "task_type": "understanding", "prediction": "his letter hath shown me this and as for the mightiness of his dominion thou hast told us what thou hast eyewitnessed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0011.flac", "answer": "SHE SAID IT HATH REACHED ME O AUSPICIOUS KING THAT SINDBAD THE SEAMAN CONTINUED WHEN I LANDED AND FOUND MYSELF AMONGST THE INDIANS AND ABYSSINIANS AND HAD TAKEN SOME REST THEY CONSULTED AMONG THEMSELVES AND SAID TO ONE ANOTHER THERE IS NO HELP FOR IT BUT WE CARRY HIM WITH US AND PRESENT HIM TO OUR KING THAT HE MAY ACQUAINT HIM WITH HIS ADVENTURES", "subset": "test_other", "task_type": "understanding", "prediction": "she said it hath reached me o auspicious king that sinbad the seaman continued when i landed and found myself amongst the indians and abyssinians and had taken some rest they consulted among themselves and said to one another there is no help for it but we carry him with us and present him to our king that he may acquaint him with his adventures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0002.flac", "answer": "LAND AFTER LAND SHALT THOU SEEK AND FIND BUT NO OTHER LIFE ON THY WISH SHALL WAIT FRET NOT THY SOUL IN THY THOUGHTS O NIGHT ALL WOES SHALL END OR SOONER OR LATE", "subset": "test_other", "task_type": "understanding", "prediction": "land after land shalt thou see confined but no other life on thy wish shall wait fret not thy soul in thy thoughts a knight all woes shall end or sooner or late", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0016.flac", "answer": "THEN I TOOK LEAVE OF HIM AND OF ALL MY INTIMATES AND ACQUAINTANCES IN THE ISLAND AND EMBARKED WITH THE MERCHANTS AFORESAID", "subset": "test_other", "task_type": "understanding", "prediction": "then i took leave of him and of all my intimates and acquaintances in the island and embarked with the merchants aforesaid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0001.flac", "answer": "THEN SIGHING FOR MYSELF I SET TO WORK COLLECTING A NUMBER OF PIECES OF CHINESE AND COMORIN ALOES WOOD AND I BOUND THEM TOGETHER WITH ROPES FROM THE WRECKAGE THEN I CHOSE OUT FROM THE BROKEN UP SHIPS STRAIGHT PLANKS OF EVEN SIZE AND FIXED THEM FIRMLY UPON THE ALOES WOOD MAKING ME A BOAT RAFT A LITTLE NARROWER THAN THE CHANNEL OF THE STREAM AND I TIED IT TIGHTLY AND FIRMLY AS THOUGH IT WERE NAILED", "subset": "test_other", "task_type": "understanding", "prediction": "then signed for myself i set to work collecting a number of pieces of chinese and cormorant alloys wood and i bound them together with ropes from the wreckage then i chose out from the broken up ships straight planks of even size and fixed them firmly upon the alloys wood making me a boat raft a little narrower than the channel of the stream and i tied it tightly and firmly as though it were nailed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0015.flac", "answer": "BY ALLAH O MY LORD ANSWERED I THOU HAST INDEED OVERWHELMED ME WITH THY FAVOURS AND WELL DOINGS BUT I WEARY FOR A SIGHT OF MY FRIENDS AND FAMILY AND NATIVE COUNTRY", "subset": "test_other", "task_type": "understanding", "prediction": "by allah o my lord answered i thou hast indeed overwhelmed me with thy favours and well doings but i weary for a sight of my friends and family and native country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0008.flac", "answer": "O MY BROTHER ANSWERED HE WE ARE HUSBANDMEN AND TILLERS OF THE SOIL WHO CAME OUT TO WATER OUR FIELDS AND PLANTATIONS AND FINDING THEE ASLEEP ON THIS RAFT LAID HOLD OF IT AND MADE IT FAST BY US AGAINST THOU SHOULDST AWAKE AT THY LEISURE", "subset": "test_other", "task_type": "understanding", "prediction": "o my brother answered he we are husbandmen and tillers of the soil who came out to water our fields and plantations and finding thee asleep on this raft laid hold of it and made it fast by us against thou shouldst awake at thy leisure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0005.flac", "answer": "WHEN I AWOKE AT LAST I FOUND MYSELF IN THE LIGHT OF HEAVEN AND OPENING MY EYES I SAW MYSELF IN A BROAD STREAM AND THE RAFT MOORED TO AN ISLAND IN THE MIDST OF A NUMBER OF INDIANS AND ABYSSINIANS", "subset": "test_other", "task_type": "understanding", "prediction": "when i awoke at last i found myself in the light of heaven and opening my eyes i saw myself in a broad stream and the raft moored to an island in the midst of a number of indians and abyssinians", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0028.flac", "answer": "BUT THE CAPTAIN AROSE AND TIGHTENING HIS GIRDLE TUCKED UP HIS SKIRTS AND AFTER TAKING REFUGE WITH ALLAH FROM SATAN THE STONED CLOMB TO THE MAST HEAD WHENCE HE LOOKED OUT RIGHT AND LEFT AND GAZING AT THE PASSENGERS AND CREW FELL TO BUFFETING HIS FACE AND PLUCKING OUT HIS BEARD", "subset": "test_other", "task_type": "understanding", "prediction": "but the captain arose and tightening his girdle tucked up his skirts and after taking refuge with allah from satan the stoned climbed to the mast head whence he looked out right and left and gazing at the passengers and crew felt he buffeted his face and plucked out his beard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0030.flac", "answer": "A SECOND FISH MADE ITS APPEARANCE THAN WHICH WE HAD SEEN NAUGHT MORE MONSTROUS", "subset": "test_other", "task_type": "understanding", "prediction": "a second fish made its appearance and which we had seen naught more monstrous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0010.flac", "answer": "WHEN IT WAS THE FIVE HUNDRED AND SIXTY SECOND NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "when it was the five hundred and sixty second night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0013.flac", "answer": "SO I ROSE WITHOUT STAY OR DELAY AND KISSED THE KING'S HAND AND ACQUAINTED HIM WITH MY LONGING TO SET OUT WITH THE MERCHANTS FOR THAT I PINED AFTER MY PEOPLE AND MINE OWN LAND", "subset": "test_other", "task_type": "understanding", "prediction": "so i rose without stay or delay and kissed the king s hand and acquainted him with my longing tis set out with the merchants for that i pined after my people and my known land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7018/75789/7018-75789-0020.flac", "answer": "PRESENTLY MY FRIENDS CAME TO ME AND I DISTRIBUTED PRESENTS AMONG MY FAMILY AND GAVE ALMS AND LARGESSE AFTER WHICH I YIELDED MYSELF TO JOYANCE AND ENJOYMENT MIRTH AND MERRY MAKING AND FORGOT ALL THAT I HAD SUFFERED", "subset": "test_other", "task_type": "understanding", "prediction": "presently my friends came to me and i distributed presents among my family and gave alms and largess after which i yielded myself to joyance and enjoyment mirth and merrymaking and forgot all that i had suffered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0074.flac", "answer": "IT FOLLOWS THAT THERE COULD NOT HAVE BEEN ANY INTELLIGENCE ANY DESIGN BACK OF MATTER AND FORCE", "subset": "test_other", "task_type": "understanding", "prediction": "it followed that there could not have been any intelligence any design back of matter and force", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0051.flac", "answer": "THEY HATED PLEASURE", "subset": "test_other", "task_type": "understanding", "prediction": "they hated pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0088.flac", "answer": "NATURE PRODUCES WITHOUT PURPOSE SUSTAINS WITHOUT INTENTION AND DESTROYS WITHOUT THOUGHT", "subset": "test_other", "task_type": "understanding", "prediction": "nature produces without purpose sustains without intention and destroys without thought", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0012.flac", "answer": "HOW CAN WE ACCOUNT FOR THE WILD BEASTS THAT DEVOUR HUMAN BEINGS FOR THE FANGED SERPENTS WHOSE BITE IS DEATH", "subset": "test_other", "task_type": "understanding", "prediction": "how can we account for the wild beasts that devour human beings for the fanged serpents whose bite is death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0097.flac", "answer": "IT IS FAR BETTER TO BE FREE TO LEAVE THE FORTS AND BARRICADES OF FEAR TO STAND ERECT AND FACE THE FUTURE WITH A SMILE", "subset": "test_other", "task_type": "understanding", "prediction": "it is far better to be free to leave the forts and barricades of fear to stand erect and face the future with a smile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0093.flac", "answer": "THIS CANNOT BE DONE BY TALK OR EXAMPLE", "subset": "test_other", "task_type": "understanding", "prediction": "this cannot be done by talk or example", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0087.flac", "answer": "FAILURE SEEMS TO BE THE TRADEMARK OF NATURE WHY", "subset": "test_other", "task_type": "understanding", "prediction": "failure seems to be the trademark of nature why", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0048.flac", "answer": "COULD THESE COUNTRIES HAVE BEEN WORSE WITHOUT RELIGION", "subset": "test_other", "task_type": "understanding", "prediction": "could these countries have been worse without religion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0096.flac", "answer": "POVERTY AND CRIME WILL BE CHILDLESS", "subset": "test_other", "task_type": "understanding", "prediction": "poverty and crime will be childless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0028.flac", "answer": "HE HAS TRIED THAT ROAD AND KNOWS THAT IT IS THE WRONG ROAD", "subset": "test_other", "task_type": "understanding", "prediction": "he has tried that road and knows that it is the wrong road", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0089.flac", "answer": "MUST THE WORLD FOREVER REMAIN THE VICTIM OF IGNORANT PASSION", "subset": "test_other", "task_type": "understanding", "prediction": "must the world forever remain the victim of ignorant passion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0007.flac", "answer": "IS HE RESPONSIBLE FOR THE CENTURIES OF SLAVERY FOR THE BACKS THAT HAVE BEEN SCARRED WITH THE LASH FOR THE BABES THAT HAVE BEEN SOLD FROM THE BREASTS OF MOTHERS FOR THE FAMILIES THAT HAVE BEEN SEPARATED AND DESTROYED", "subset": "test_other", "task_type": "understanding", "prediction": "is he responsible for the centuries of slavery for the backs that have been scarred with the lash for the babes that have been sold from the breasts of mothers for the families that have been separated and destroyed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0019.flac", "answer": "CAN WE SAY THAT HIS MERCY ENDURETH FOREVER", "subset": "test_other", "task_type": "understanding", "prediction": "can we say that his mercy endureth forever", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0004.flac", "answer": "WHY DID HE CREATE THE DEFORMED AND HELPLESS WHY DID HE CREATE THE CRIMINAL THE IDIOTIC THE INSANE", "subset": "test_other", "task_type": "understanding", "prediction": "why did he create the deformed and helpless why did he create the criminal the idiotic the insane", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0070.flac", "answer": "I HAVE A THEORY AND I HAVE FOUR CORNER STONES", "subset": "test_other", "task_type": "understanding", "prediction": "i have a theory and i have four cornerstones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0068.flac", "answer": "THE STRUCTURE MUST HAVE A BASEMENT", "subset": "test_other", "task_type": "understanding", "prediction": "the structure must have a basement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0030.flac", "answer": "THE POWER THAT WORKS FOR RIGHTEOUSNESS HAS TAUGHT THE CHILD A LESSON", "subset": "test_other", "task_type": "understanding", "prediction": "the power that works for righteousness had taught the child a lesson", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0090.flac", "answer": "WHY SHOULD MEN AND WOMEN HAVE CHILDREN THAT THEY CANNOT TAKE CARE OF CHILDREN THAT ARE BURDENS AND CURSES WHY", "subset": "test_other", "task_type": "understanding", "prediction": "why should men and women have children that they cannot take care of children that are a burden and curses why", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0035.flac", "answer": "THEY ARE REGARDED AS GOOD THAT IS TO SAY AS MORAL", "subset": "test_other", "task_type": "understanding", "prediction": "they are regarded as good that is to say as moral", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0083.flac", "answer": "FOR THOUSANDS OF YEARS MEN AND WOMEN HAVE BEEN TRYING TO REFORM THE WORLD", "subset": "test_other", "task_type": "understanding", "prediction": "for thousands of years men and women have been trying to reform the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0091.flac", "answer": "PASSION IS AND ALWAYS HAS BEEN DEAF", "subset": "test_other", "task_type": "understanding", "prediction": "passion is and always has been death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0064.flac", "answer": "CAN WE CURE DISEASE BY SUPPLICATION", "subset": "test_other", "task_type": "understanding", "prediction": "can we cure disease by supplication", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0075.flac", "answer": "I SAY WHAT I THINK", "subset": "test_other", "task_type": "understanding", "prediction": "i say what i think", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0001.flac", "answer": "WHETHER HE WAS THE CREATOR OF YOURSELF AND MYSELF", "subset": "test_other", "task_type": "understanding", "prediction": "whether he was the creator of yourself and myself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0015.flac", "answer": "FEAR BUILDS THE ALTAR AND OFFERS THE SACRIFICE", "subset": "test_other", "task_type": "understanding", "prediction": "fear builds the altar and offers the sacrifice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0032.flac", "answer": "IT IS INSISTED BY THESE THEOLOGIANS AND BY MANY OF THE SO CALLED PHILOSOPHERS THAT THIS MORAL SENSE THIS SENSE OF DUTY OF OBLIGATION WAS IMPORTED AND THAT CONSCIENCE IS AN EXOTIC", "subset": "test_other", "task_type": "understanding", "prediction": "it is insisted by these theologians and by many of the so called philosophers that this moral sense this sense of duty of obligation was imported and that conscience is an exotic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0018.flac", "answer": "CAN WE SAY THAT HE CARED FOR THE CHILDREN OF MEN", "subset": "test_other", "task_type": "understanding", "prediction": "can we say that he cared for the children of men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0017.flac", "answer": "LIPS RELIGIOUS AND FEARFUL TREMBLINGLY REPEAT THIS PASSAGE THOUGH HE SLAY ME YET WILL I TRUST HIM", "subset": "test_other", "task_type": "understanding", "prediction": "lips religious and fearful tremblingly repeat this passage though he slay me yet will i trust him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0031.flac", "answer": "IT IS A RESULT", "subset": "test_other", "task_type": "understanding", "prediction": "it is a result", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0037.flac", "answer": "THE GREATEST OF HUMAN BEINGS HAS SAID CONSCIENCE IS BORN OF LOVE", "subset": "test_other", "task_type": "understanding", "prediction": "the greatest of human beings had said conscience is born of love", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0034.flac", "answer": "THEY ARE PRAISED ADMIRED AND RESPECTED", "subset": "test_other", "task_type": "understanding", "prediction": "they are praised admired and respected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0029.flac", "answer": "A CHILD CHARMED BY THE BEAUTY OF THE FLAME GRASPS IT WITH ITS DIMPLED HAND", "subset": "test_other", "task_type": "understanding", "prediction": "a child charmed by the beauty of the flame grasped it with his dimpled hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0092.flac", "answer": "LAW CAN PUNISH BUT IT CAN NEITHER REFORM CRIMINALS NOR PREVENT CRIME", "subset": "test_other", "task_type": "understanding", "prediction": "law can punish but it can neither reform criminals nor prevent crime", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0036.flac", "answer": "THE MEMBERS WHO ADD TO THE MISERY OF THE FAMILY THE TRIBE OR THE NATION ARE CONSIDERED BAD MEMBERS", "subset": "test_other", "task_type": "understanding", "prediction": "the members who add to the misery of the family the tribe or the nation are considered bad members", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0080.flac", "answer": "WE NOW KNOW IF WE KNOW ANYTHING THAT THE UNIVERSE IS NATURAL AND THAT MEN AND WOMEN HAVE BEEN NATURALLY PRODUCED", "subset": "test_other", "task_type": "understanding", "prediction": "we now know if we know anything that the universe is natural and that men and women have been naturally produced", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0055.flac", "answer": "LET ME REFER TO JUST ONE FACT SHOWING THE INFLUENCE OF A BELIEF IN THE BIBLE ON HUMAN BEINGS", "subset": "test_other", "task_type": "understanding", "prediction": "Let me refer to just one fact showing the influence of a belief in the Bible on human beings.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0094.flac", "answer": "THIS IS THE SOLUTION OF THE WHOLE QUESTION", "subset": "test_other", "task_type": "understanding", "prediction": "this is the solution of the whole question", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0022.flac", "answer": "OUGHT THE SUPERIOR RACES TO THANK GOD THAT THEY ARE NOT THE INFERIOR", "subset": "test_other", "task_type": "understanding", "prediction": "all the superior race to thank god that they are not the inferior", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0054.flac", "answer": "THE PURITAN BELIEVED THE BIBLE TO BE THE WORD OF GOD AND THIS BELIEF HAS ALWAYS MADE THOSE WHO HELD IT CRUEL AND WRETCHED", "subset": "test_other", "task_type": "understanding", "prediction": "the puritan believed the bible to be the word of god and this belief has always made those who held it cruel and wretched", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0010.flac", "answer": "DID HE ALLOW TYRANTS TO SHED THE BLOOD OF PATRIOTS", "subset": "test_other", "task_type": "understanding", "prediction": "did he allow tyrants to shed the blood of patriots", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0023.flac", "answer": "MOST PEOPLE CLING TO THE SUPERNATURAL", "subset": "test_other", "task_type": "understanding", "prediction": "most people cling to the supernatural", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0052.flac", "answer": "THEY MUFFLED ALL THE BELLS OF GLADNESS", "subset": "test_other", "task_type": "understanding", "prediction": "they muffled all the bells of gladness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0071.flac", "answer": "THE FIRST STONE IS THAT MATTER SUBSTANCE CANNOT BE DESTROYED CANNOT BE ANNIHILATED", "subset": "test_other", "task_type": "understanding", "prediction": "the first stone is that matter substance cannot be destroyed cannot be annihilated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0086.flac", "answer": "THEY LIVE BY FRAUD AND VIOLENCE AND BEQUEATH THEIR VICES TO THEIR CHILDREN", "subset": "test_other", "task_type": "understanding", "prediction": "they live by fraud and violence and bequeath their vices to their children", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0049.flac", "answer": "COULD THEY HAVE BEEN WORSE HAD THEY HAD ANY OTHER RELIGION THAN CHRISTIANITY", "subset": "test_other", "task_type": "understanding", "prediction": "could they have been worse had they had any other religion than christianity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0002.flac", "answer": "WHETHER ANY PRAYER WAS EVER ANSWERED", "subset": "test_other", "task_type": "understanding", "prediction": "whether any prayer was ever answered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0033.flac", "answer": "WE LIVE TOGETHER IN FAMILIES TRIBES AND NATIONS", "subset": "test_other", "task_type": "understanding", "prediction": "we live together in families tribes and nations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0067.flac", "answer": "WE MUST HAVE CORNER STONES", "subset": "test_other", "task_type": "understanding", "prediction": "we must have corn the stones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0077.flac", "answer": "THAT WHICH HAS NOT HAPPENED COULD NOT", "subset": "test_other", "task_type": "understanding", "prediction": "that which has not happened could not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0025.flac", "answer": "WHAT IS THIS POWER", "subset": "test_other", "task_type": "understanding", "prediction": "what is this power", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0072.flac", "answer": "IF THESE CORNER STONES ARE FACTS IT FOLLOWS AS A NECESSITY THAT MATTER AND FORCE ARE FROM AND TO ETERNITY THAT THEY CAN NEITHER BE INCREASED NOR DIMINISHED", "subset": "test_other", "task_type": "understanding", "prediction": "if these cornerstones are facts it follows as a necessity that matter and force are from and to eternity that they can neither be increased nor diminished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0061.flac", "answer": "RELIGION HAS NEVER MADE MAN FREE", "subset": "test_other", "task_type": "understanding", "prediction": "religion has never made men free", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0040.flac", "answer": "A MAN PUTS HIMSELF IN THE PLACE OF ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "a man puts himself in the place of another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0053.flac", "answer": "THE RELIGION OF THE PURITAN WAS AN UNADULTERATED CURSE", "subset": "test_other", "task_type": "understanding", "prediction": "the religion of the puritan was an unadulterated curse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0066.flac", "answer": "RELIGION RESTS ON THE IDEA THAT NATURE HAS A MASTER AND THAT THIS MASTER WILL LISTEN TO PRAYER THAT THIS MASTER PUNISHES AND REWARDS THAT HE LOVES PRAISE AND FLATTERY AND HATES THE BRAVE AND FREE", "subset": "test_other", "task_type": "understanding", "prediction": "religion rests on the idea that nature has a master and that this master will listen to prayer that this master punishes and rewards that he loves praise and flattery and hates the brave and free", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0058.flac", "answer": "HAS THE BIBLE MADE THE PEOPLE OF GEORGIA KIND AND MERCIFUL", "subset": "test_other", "task_type": "understanding", "prediction": "has the bible made the people of georgia kind and merciful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0079.flac", "answer": "WE NOW KNOW THAT OUR FIRST PARENTS WERE NOT FOREIGNERS", "subset": "test_other", "task_type": "understanding", "prediction": "we now know that our first parents were not foreigners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0038.flac", "answer": "AS PEOPLE ADVANCE THE REMOTE CONSEQUENCES ARE PERCEIVED", "subset": "test_other", "task_type": "understanding", "prediction": "as people advance the remote consequences are perceived", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0056.flac", "answer": "THE QUEEN RECEIVED THE BIBLE KISSED IT AND PLEDGED HERSELF TO DILIGENTLY READ THEREIN", "subset": "test_other", "task_type": "understanding", "prediction": "the queen received the bible kissed it and pledged herself to diligently read therein", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0042.flac", "answer": "MAN JUDGES HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "man judges himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0045.flac", "answer": "HAS CHRISTIANITY DONE GOOD", "subset": "test_other", "task_type": "understanding", "prediction": "has christianity done good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0013.flac", "answer": "HOW CAN WE ACCOUNT FOR A WORLD WHERE LIFE FEEDS ON LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "how can we account for a world where life feeds on life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0020.flac", "answer": "DO WE PROVE HIS GOODNESS BY SHOWING THAT HE HAS OPENED THE EARTH AND SWALLOWED THOUSANDS OF HIS HELPLESS CHILDREN OR THAT WITH THE VOLCANOES HE HAS OVERWHELMED THEM WITH RIVERS OF FIRE", "subset": "test_other", "task_type": "understanding", "prediction": "do we prove his goodness by showing that he hath opened the earth and swallowed thousands of his helpless children or that with the volcanoes he hath overwhelmed them with rivers of fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0027.flac", "answer": "A MAN WISHING TO GO TO A CERTAIN PLACE COMES TO WHERE THE ROAD DIVIDES", "subset": "test_other", "task_type": "understanding", "prediction": "a man wishing to go to a certain place comes to where the road divides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0008.flac", "answer": "IS THIS GOD RESPONSIBLE FOR RELIGIOUS PERSECUTION FOR THE INQUISITION FOR THE THUMB SCREW AND RACK AND FOR ALL THE INSTRUMENTS OF TORTURE", "subset": "test_other", "task_type": "understanding", "prediction": "is this god responsible for religious persecution for the inquisition for the thumbscrew and rack and for all the instruments of torture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0006.flac", "answer": "IS HE RESPONSIBLE FOR ALL THE WARS THAT HAVE BEEN WAGED FOR ALL THE INNOCENT BLOOD THAT HAS BEEN SHED", "subset": "test_other", "task_type": "understanding", "prediction": "is he responsible for all the wars that have been waged for all the innocent blood that has been shed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0047.flac", "answer": "WHAT HAS RELIGION DONE FOR HUNGARY OR AUSTRIA", "subset": "test_other", "task_type": "understanding", "prediction": "what has religion done for hungary or austria", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0084.flac", "answer": "WHY HAVE THE REFORMERS FAILED", "subset": "test_other", "task_type": "understanding", "prediction": "why have the reformers failed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0095.flac", "answer": "THIS FREES WOMAN", "subset": "test_other", "task_type": "understanding", "prediction": "this frees women", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0081.flac", "answer": "WE KNOW THE PATHS THAT LIFE HAS TRAVELED", "subset": "test_other", "task_type": "understanding", "prediction": "we know the paths that life has travelled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0003.flac", "answer": "WHY DID HE CREATE THE INTELLECTUALLY INFERIOR", "subset": "test_other", "task_type": "understanding", "prediction": "why did he create the intellectually inferior", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0046.flac", "answer": "WHEN THE CHURCH HAD CONTROL WERE MEN MADE BETTER AND HAPPIER", "subset": "test_other", "task_type": "understanding", "prediction": "when the church had control were men made better and happier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0063.flac", "answer": "ARE CHRISTIANS MORE TEMPERATE NEARER VIRTUOUS NEARER HONEST THAN SAVAGES", "subset": "test_other", "task_type": "understanding", "prediction": "are christians more temperate nearer virtuous nearer honest than savages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0014.flac", "answer": "DID INFINITE WISDOM INTENTIONALLY PRODUCE THE MICROSCOPIC BEASTS THAT FEED UPON THE OPTIC NERVE THINK OF BLINDING A MAN TO SATISFY THE APPETITE OF A MICROBE", "subset": "test_other", "task_type": "understanding", "prediction": "did infinite wisdom intentionally produce the microscopic beasts that feed upon the optic nerve think of blinding a man to satisfy the appetite of a microbe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0011.flac", "answer": "CAN WE CONCEIVE OF A DEVIL BASE ENOUGH TO PREFER HIS ENEMIES TO HIS FRIENDS", "subset": "test_other", "task_type": "understanding", "prediction": "can we conceive of a devil base enough to prefer his enemies to his friends", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0057.flac", "answer": "IN OTHER WORDS IT WAS JUST AS FIENDISH JUST AS INFAMOUS AS THE CATHOLIC SPIRIT", "subset": "test_other", "task_type": "understanding", "prediction": "in other words it was just as fiendish just as infamous as the catholic spirit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0065.flac", "answer": "CAN WE RECEIVE VIRTUE OR HONOR AS ALMS", "subset": "test_other", "task_type": "understanding", "prediction": "can we receive virtue or honor as alms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0021.flac", "answer": "WAS THERE GOODNESS WAS THERE WISDOM IN THIS", "subset": "test_other", "task_type": "understanding", "prediction": "was there goodness was there wisdom in this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0073.flac", "answer": "IT FOLLOWS THAT NOTHING HAS BEEN OR CAN BE CREATED THAT THERE NEVER HAS BEEN OR CAN BE A CREATOR", "subset": "test_other", "task_type": "understanding", "prediction": "it follows that nothing hath been or can be created that there never hath been or can be a creator", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0039.flac", "answer": "THE IMAGINATION IS CULTIVATED", "subset": "test_other", "task_type": "understanding", "prediction": "the imagination is cultivated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0000.flac", "answer": "AFTERWARD IT WAS SUPPOSED THAT HE WAS SATISFIED WITH THE BLOOD OF OXEN LAMBS AND DOVES AND THAT IN EXCHANGE FOR OR ON ACCOUNT OF THESE SACRIFICES THIS GOD GAVE RAIN SUNSHINE AND HARVEST", "subset": "test_other", "task_type": "understanding", "prediction": "afterward it was supposed that he was satisfied with the blood of oxen lambs and doves and that in exchange for or in account of these sacrifices this god gave rain sunshine and harvest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0059.flac", "answer": "RELIGION HAS BEEN TRIED AND IN ALL COUNTRIES IN ALL TIMES HAS FAILED", "subset": "test_other", "task_type": "understanding", "prediction": "religion has been tried and in all countries in all times has failed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0044.flac", "answer": "MAN HAS DECEIVED HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "man has deceived himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0043.flac", "answer": "IN ALL THIS THERE IS NOTHING SUPERNATURAL", "subset": "test_other", "task_type": "understanding", "prediction": "in all this there is nothing supernatural", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0016.flac", "answer": "FEAR ERECTS THE CATHEDRAL AND BOWS THE HEAD OF MAN IN WORSHIP", "subset": "test_other", "task_type": "understanding", "prediction": "fear erects the cathedral and bows the head of man in worship", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0085.flac", "answer": "THEY DEPEND ON THE LORD ON LUCK AND CHARITY", "subset": "test_other", "task_type": "understanding", "prediction": "they depend on the lot on luck and charity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0041.flac", "answer": "THE SENSE OF DUTY BECOMES STRONGER MORE IMPERATIVE", "subset": "test_other", "task_type": "understanding", "prediction": "the sense of duty becomes stronger more imperative", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0024.flac", "answer": "IF THEY GIVE UP ONE GOD THEY IMAGINE ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "if they give up one god they imagine another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0076.flac", "answer": "EVERY EVENT HAS PARENTS", "subset": "test_other", "task_type": "understanding", "prediction": "every event has parents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0005.flac", "answer": "ARE THE FAILURES UNDER OBLIGATION TO THEIR CREATOR", "subset": "test_other", "task_type": "understanding", "prediction": "are the failures under obligation to their creator", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0009.flac", "answer": "DID THIS GOD ALLOW THE CRUEL AND VILE TO DESTROY THE BRAVE AND VIRTUOUS", "subset": "test_other", "task_type": "understanding", "prediction": "did this god allow the cruel and vile to destroy the brave and virtuous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0078.flac", "answer": "IN THE INFINITE CHAIN THERE IS AND THERE CAN BE NO BROKEN NO MISSING LINK", "subset": "test_other", "task_type": "understanding", "prediction": "in the infinite chain there is and there can be no broken no missing link", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0069.flac", "answer": "IF WE BUILD WE MUST BEGIN AT THE BOTTOM", "subset": "test_other", "task_type": "understanding", "prediction": "if we build we must begin at the bottom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0082.flac", "answer": "WE KNOW THE FOOTSTEPS OF ADVANCE THEY HAVE BEEN TRACED", "subset": "test_other", "task_type": "understanding", "prediction": "we know the footsteps of advance they have been traced", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0050.flac", "answer": "WHAT DID CHRISTIANITY DO FOR THEM", "subset": "test_other", "task_type": "understanding", "prediction": "what did christianity do for them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0026.flac", "answer": "MAN ADVANCES AND NECESSARILY ADVANCES THROUGH EXPERIENCE", "subset": "test_other", "task_type": "understanding", "prediction": "man advances and necessarily advances through experience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0060.flac", "answer": "RELIGION HAS ALWAYS BEEN THE ENEMY OF SCIENCE OF INVESTIGATION AND THOUGHT", "subset": "test_other", "task_type": "understanding", "prediction": "religion has always been the enemy of science of investigation and thought", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5764/299665/5764-299665-0062.flac", "answer": "IT HAS NEVER MADE MAN MORAL TEMPERATE INDUSTRIOUS AND HONEST", "subset": "test_other", "task_type": "understanding", "prediction": "it hath never made man moral temperate industrious and honest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0004.flac", "answer": "SHE COULD NOT DEFEND HERSELF AGAINST A RICH ADMIRATION A KIND OF TENDERNESS OF ENVY OF ANY ONE WHO HAD BEEN SO HAPPY AS TO HAVE THAT OPPORTUNITY", "subset": "test_other", "task_type": "understanding", "prediction": "she could not defend herself against a rich admiration a kind of tenderness of envy of any one who had been so happy as to have that opportunity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0011.flac", "answer": "SHE WAS PERFECTLY SAFE AFTER WRITING TO BASIL RANSOM AND INDEED IT WAS DIFFICULT TO SEE WHAT HE COULD HAVE DONE TO HER EXCEPT THANK HER HE WAS ONLY EXCEPTIONALLY SUPERLATIVE FOR HER LETTER AND ASSURE HER THAT HE WOULD COME AND SEE HER THE FIRST TIME HIS BUSINESS HE WAS BEGINNING TO GET A LITTLE SHOULD TAKE HIM TO BOSTON", "subset": "test_other", "task_type": "understanding", "prediction": "she was perfectly safe after writing to basil ransome and indeed it was difficult to see what he could have done to her except thank her he was only exceptionally superlative for her letter and assure her that he would come and see her the first time his business he was beginning to get a little should take him to boston", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0010.flac", "answer": "SHE HAD ERECTED IT INTO A SORT OF RULE OF CONDUCT THAT WHENEVER SHE SAW A RISK SHE WAS TO TAKE IT AND SHE HAD FREQUENT HUMILIATIONS AT FINDING HERSELF SAFE AFTER ALL", "subset": "test_other", "task_type": "understanding", "prediction": "she had erected it into a sort of rule of conduct that whenever she saw a risk she was to take it and she had frequent humiliations at finding herself saved after all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0013.flac", "answer": "OF ALL THINGS IN THE WORLD CONTENTION WAS MOST SWEET TO HER THOUGH WHY IT IS HARD TO IMAGINE FOR IT ALWAYS COST HER TEARS HEADACHES A DAY OR TWO IN BED ACUTE EMOTION AND IT WAS VERY POSSIBLE BASIL RANSOM WOULD NOT CARE TO CONTEND", "subset": "test_other", "task_type": "understanding", "prediction": "of all things in the world contention was most sweet to her though why it is hard to imagine for it always cost her tears headaches a day or two in bed acute emotion and it was very possible basil ransome would not care to contend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0002.flac", "answer": "RANSOM WAS PLEASED WITH THE VISION OF THAT REMEDY IT MUST BE REPEATED THAT HE WAS VERY PROVINCIAL", "subset": "test_other", "task_type": "understanding", "prediction": "ransom was pleased with the vision of that remedy it must be repeated that he was very provincial", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0006.flac", "answer": "THE STATE OF MISSISSIPPI SEEMED TO HIM THE STATE OF DESPAIR SO HE SURRENDERED THE REMNANTS OF HIS PATRIMONY TO HIS MOTHER AND SISTERS AND AT NEARLY THIRTY YEARS OF AGE ALIGHTED FOR THE FIRST TIME IN NEW YORK IN THE COSTUME OF HIS PROVINCE WITH FIFTY DOLLARS IN HIS POCKET AND A GNAWING HUNGER IN HIS HEART", "subset": "test_other", "task_type": "understanding", "prediction": "the state of mississippi seemed to him the state of despair so he surrendered the remnants of his patrimony to his mother and sisters and at nearly thirty years of age alighted for the first time in new york in the costume of his province with fifty dollars in his pocket and a gnawing hunger in his heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0007.flac", "answer": "IT WAS IN THE FEMALE LINE AS BASIL RANSOM HAD WRITTEN IN ANSWERING HER LETTER WITH A GOOD DEAL OF FORM AND FLOURISH HE SPOKE AS IF THEY HAD BEEN ROYAL HOUSES", "subset": "test_other", "task_type": "understanding", "prediction": "it was in the female line as bales and ransom had written in answering her letter with a good deal of form and flourish he spoke as if they had been royal houses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0005.flac", "answer": "HIS FAMILY WAS RUINED THEY HAD LOST THEIR SLAVES THEIR PROPERTY THEIR FRIENDS AND RELATIONS THEIR HOME HAD TASTED OF ALL THE CRUELTY OF DEFEAT", "subset": "test_other", "task_type": "understanding", "prediction": "his family was ruined they had lost their slaves their property their friends and relations their home had tasted of all the cruelty of defeat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0003.flac", "answer": "HE WAS SORRY FOR HER BUT HE SAW IN A FLASH THAT NO ONE COULD HELP HER THAT WAS WHAT MADE HER TRAGIC", "subset": "test_other", "task_type": "understanding", "prediction": "he was sorry for her but he saw in a flash that no one could help her that was what made her tragic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0012.flac", "answer": "HE WAS TOO SIMPLE TOO MISSISSIPPIAN FOR THAT SHE WAS ALMOST DISAPPOINTED", "subset": "test_other", "task_type": "understanding", "prediction": "he was too simple too mississippi an for that she was almost disappointed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0001.flac", "answer": "THE WOMEN HE HAD HITHERTO KNOWN HAD BEEN MAINLY OF HIS OWN SOFT CLIME AND IT WAS NOT OFTEN THEY EXHIBITED THE TENDENCY HE DETECTED AND CURSORILY DEPLORED IN MISSUS LUNA'S SISTER", "subset": "test_other", "task_type": "understanding", "prediction": "the women he had hitherto known had been mainly of his own soft clime and it was not often they exhibited the tendency he detected and cursorily deplored in mrs luna s sister", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0000.flac", "answer": "POOR RANSOM ANNOUNCED THIS FACT TO HIMSELF AS IF HE HAD MADE A GREAT DISCOVERY BUT IN REALITY HE HAD NEVER BEEN SO BOEOTIAN AS AT THAT MOMENT", "subset": "test_other", "task_type": "understanding", "prediction": "poor ransome announced this fact to himself as if he had made a great discovery but in reality he had never been so boeotian as at that moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0008.flac", "answer": "IF IT HAD BEEN POSSIBLE TO SEND MISSUS RANSOM MONEY OR EVEN CLOTHES SHE WOULD HAVE LIKED THAT BUT SHE HAD NO MEANS OF ASCERTAINING HOW SUCH AN OFFERING WOULD BE TAKEN", "subset": "test_other", "task_type": "understanding", "prediction": "if it had been possible to send mrs ransome money or even clothes she would have liked that but she had no means of ascertaining how such a offering would be taken", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63241/6128-63241-0009.flac", "answer": "OLIVE HAD A FEAR OF EVERYTHING BUT HER GREATEST FEAR WAS OF BEING AFRAID", "subset": "test_other", "task_type": "understanding", "prediction": "olive had a fear of everything but her greatest fear was of being afraid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0018.flac", "answer": "ARE YOU VERY AMBITIOUS YOU LOOK AS IF YOU WERE", "subset": "test_other", "task_type": "understanding", "prediction": "are you very ambitious you look as if you were", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0021.flac", "answer": "BESIDES OLIVE DIDN'T WANT HER IN BOSTON AND DIDN'T GO THROUGH THE FORM OF SAYING SO", "subset": "test_other", "task_type": "understanding", "prediction": "besides olive didn t want her in boston and didn t go through the form of saying so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0016.flac", "answer": "SHE HATES IT SHE WOULD LIKE TO ABOLISH IT", "subset": "test_other", "task_type": "understanding", "prediction": "she hates it she would like to abolish it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0015.flac", "answer": "NO I HAVEN'T BEEN ANYWHERE", "subset": "test_other", "task_type": "understanding", "prediction": "no i haven t been anywhere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0014.flac", "answer": "HAVE YOU BEEN IN EUROPE", "subset": "test_other", "task_type": "understanding", "prediction": "have you been in europe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0006.flac", "answer": "THOSE OF BASIL RANSOM WERE DARK DEEP AND GLOWING HIS HEAD HAD A CHARACTER OF ELEVATION WHICH FAIRLY ADDED TO HIS STATURE IT WAS A HEAD TO BE SEEN ABOVE THE LEVEL OF A CROWD ON SOME JUDICIAL BENCH OR POLITICAL PLATFORM OR EVEN ON A BRONZE MEDAL", "subset": "test_other", "task_type": "understanding", "prediction": "those of basil ramsden were dark deep and glowing his head had a character of elevation which fairly added to his stature it was a head to be seen above the level of a crowd on some judicial bench or political platform or even on a bronze medal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0022.flac", "answer": "THAT WAS ONE COMFORT WITH OLIVE SHE NEVER WENT THROUGH ANY FORMS", "subset": "test_other", "task_type": "understanding", "prediction": "that was one comfort with olive she never went through any forms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0017.flac", "answer": "THIS LAST REMARK HE MADE AT A VENTURE FOR HE HAD NATURALLY NOT DEVOTED ANY SUPPOSITION WHATEVER TO MISSUS LUNA", "subset": "test_other", "task_type": "understanding", "prediction": "this last remark he made at a venture for he had naturally not devoted any supposition whatever to mrs lena", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0026.flac", "answer": "I SHALL BE BACK VERY LATE WE ARE GOING TO A THEATRE PARTY THAT'S WHY WE DINE SO EARLY", "subset": "test_other", "task_type": "understanding", "prediction": "i shall be back very late we are going to a theatre party that is why we dined so early", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0013.flac", "answer": "SHE WAS ATTRACTIVE AND IMPERTINENT ESPECIALLY THE LATTER", "subset": "test_other", "task_type": "understanding", "prediction": "she was attractive and impertinent especially the latter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0000.flac", "answer": "THE GENTLEMAN HAD NOT EVEN NEEDED TO SIT DOWN TO BECOME INTERESTED APPARENTLY HE HAD TAKEN UP THE VOLUME FROM A TABLE AS SOON AS HE CAME IN AND STANDING THERE AFTER A SINGLE GLANCE ROUND THE APARTMENT HAD LOST HIMSELF IN ITS PAGES", "subset": "test_other", "task_type": "understanding", "prediction": "the gentleman had not even needed to sit down to become interested apparently he had taken up the volume from a table as soon as he came in and standing there after a single glance round the apartment had lost himself in its pages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0020.flac", "answer": "ONE DIDN'T EVEN KNOW WHAT ONE HAD COME BACK FOR", "subset": "test_other", "task_type": "understanding", "prediction": "one didn t even know what one had come back for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0005.flac", "answer": "IN SPITE OF THIS DECORATION THE YOUNG MAN LOOKED POOR AS POOR AS A YOUNG MAN COULD LOOK WHO HAD SUCH A FINE HEAD AND SUCH MAGNIFICENT EYES", "subset": "test_other", "task_type": "understanding", "prediction": "in spite of this decoration the young man looked poor as poor as a young man could look who had such a fine head and such magnificent eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0011.flac", "answer": "IF YOU ARE GOING TO DINE WITH HER YOU HAD BETTER KNOW IT OH MURDER", "subset": "test_other", "task_type": "understanding", "prediction": "if you are going to dine with her you had better know it oh murder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0025.flac", "answer": "HE OBSERVED THAT MISS CHANCELLOR'S HAND WAS AT ONCE COLD AND LIMP SHE MERELY PLACED IT IN HIS WITHOUT EXERTING THE SMALLEST PRESSURE", "subset": "test_other", "task_type": "understanding", "prediction": "he observed that miss chancellor s hand was at once cold and limp she merely placed it in his without exerting the smallest pressure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3840, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0003.flac", "answer": "JUST AS I AM THE VISITOR INQUIRED PRESENTING HIMSELF WITH RATHER A WORK A DAY ASPECT", "subset": "test_other", "task_type": "understanding", "prediction": "just as i am the visitor inquired presenting himself with rather a workaday aspect", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3841, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0004.flac", "answer": "HE WAS TALL AND LEAN AND DRESSED THROUGHOUT IN BLACK HIS SHIRT COLLAR WAS LOW AND WIDE AND THE TRIANGLE OF LINEN A LITTLE CRUMPLED EXHIBITED BY THE OPENING OF HIS WAISTCOAT WAS ADORNED BY A PIN CONTAINING A SMALL RED STONE", "subset": "test_other", "task_type": "understanding", "prediction": "he was tall and lean and dressed throughout in black his shirt collar was low and wide and the triangle of linen a little crumpled exhibited by the opening of his waistcoat was adorned by a pin containing a small red stone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3842, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0001.flac", "answer": "THAT HAS AN UNFLATTERING SOUND FOR ME SAID THE YOUNG MAN", "subset": "test_other", "task_type": "understanding", "prediction": "that has an unflattering sound for me said the young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3843, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0008.flac", "answer": "AND YET THE READER WHO LIKES A COMPLETE IMAGE WHO DESIRES TO READ WITH THE SENSES AS WELL AS WITH THE REASON IS ENTREATED NOT TO FORGET THAT HE PROLONGED HIS CONSONANTS AND SWALLOWED HIS VOWELS THAT HE WAS GUILTY OF ELISIONS AND INTERPOLATIONS WHICH WERE EQUALLY UNEXPECTED AND THAT HIS DISCOURSE WAS PERVADED BY SOMETHING SULTRY AND VAST SOMETHING ALMOST AFRICAN IN ITS RICH BASKING TONE SOMETHING THAT SUGGESTED THE TEEMING EXPANSE OF THE COTTON FIELD", "subset": "test_other", "task_type": "understanding", "prediction": "and yet the reader who likes a complete image who desires to read with the senses as well as with the reason is entreated not to forget that he prolonged his consonants and swallowed his vowels that he was guilty of elisions and interpolations which were equally unexpected and that his discourse was pervaded by something sultry and vast something almost african in its rich basking tone something that suggested the teeming expanse of the cotton field", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3844, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0010.flac", "answer": "WELL SO IT IS THEY ARE ALL WITCHES AND WIZARDS MEDIUMS AND SPIRIT RAPPERS AND ROARING RADICALS", "subset": "test_other", "task_type": "understanding", "prediction": "well so it is they are all witches and wizards mediums and spirit rappers and roaring radicals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3845, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0002.flac", "answer": "SHE IS WILLING TO RISK THAT", "subset": "test_other", "task_type": "understanding", "prediction": "she is willing to risk that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3846, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0012.flac", "answer": "HE LOOKED AT MISSUS LUNA WITH INTELLIGENT INCREDULITY", "subset": "test_other", "task_type": "understanding", "prediction": "He looked at Mrs. Luna, with intelligent incredulity.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3847, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0023.flac", "answer": "SHE STOOD THERE LOOKING CONSCIOUSLY AND RATHER SERIOUSLY AT MISTER RANSOM A SMILE OF EXCEEDING FAINTNESS PLAYED ABOUT HER LIPS IT WAS JUST PERCEPTIBLE ENOUGH TO LIGHT UP THE NATIVE GRAVITY OF HER FACE", "subset": "test_other", "task_type": "understanding", "prediction": "she stood there looking consciously and rather seriously at mr ransome a smile of exceeding faintness played about her lips it was just perceptible enough to light up the native gravity of her face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3848, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0007.flac", "answer": "THESE THINGS THE EYES ESPECIALLY WITH THEIR SMOULDERING FIRE MIGHT HAVE INDICATED THAT HE WAS TO BE A GREAT AMERICAN STATESMAN OR ON THE OTHER HAND THEY MIGHT SIMPLY HAVE PROVED THAT HE CAME FROM CAROLINA OR ALABAMA", "subset": "test_other", "task_type": "understanding", "prediction": "these things the eyes especially with their smouldering fire might have indicated that he was to be a great american statesman or on the other hand they might simply have proved that he came from carolina or alabama", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3849, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0024.flac", "answer": "HER VOICE WAS LOW AND AGREEABLE A CULTIVATED VOICE AND SHE EXTENDED A SLENDER WHITE HAND TO HER VISITOR WHO REMARKED WITH SOME SOLEMNITY HE FELT A CERTAIN GUILT OF PARTICIPATION IN MISSUS LUNA'S INDISCRETION THAT HE WAS INTENSELY HAPPY TO MAKE HER ACQUAINTANCE", "subset": "test_other", "task_type": "understanding", "prediction": "her voice was low and agreeable a cultivated voice and she extended a slender white hand to her visitor who remarked with some solemnity he felt a certain guilt of participation in mrs luna s indiscretion that he was intensely happy to make her acquaintance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3850, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0009.flac", "answer": "AND HE TOOK UP HIS HAT VAGUELY A SOFT BLACK HAT WITH A LOW CROWN AND AN IMMENSE STRAIGHT BRIM", "subset": "test_other", "task_type": "understanding", "prediction": "and he took up his hat vaguely a soft black hat with a low crown and an immense straight brim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3851, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0019.flac", "answer": "AND MISSUS LUNA ADDED THAT NOW SHE WAS BACK SHE DIDN'T KNOW WHAT SHE SHOULD DO", "subset": "test_other", "task_type": "understanding", "prediction": "and mrs luna added that now she was back she did not know what she should do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3852, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63240/6128-63240-0027.flac", "answer": "MISSUS LUNA'S FAMILIARITY EXTENDED EVEN TO HER SISTER SHE REMARKED TO MISS CHANCELLOR THAT SHE LOOKED AS IF SHE WERE GOT UP FOR A SEA VOYAGE", "subset": "test_other", "task_type": "understanding", "prediction": "mrs loonos familiarity extended even to her sister she remarked to miss chancellor that she looked as if she were got up for a sea voyage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3853, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0014.flac", "answer": "I LOOK AFTER THE DETAILS AS WELL AS THE BIG CURRENTS MISSUS FARRINDER ADDED IN A TONE AS EXPLANATORY AS COULD BE EXPECTED OF SUCH A WOMAN AND WITH A SMILE OF WHICH THE SWEETNESS WAS THRILLING TO HER LISTENER", "subset": "test_other", "task_type": "understanding", "prediction": "and look after the details as well as the big currents mrs farinder added in a tone as explanatory as could be expected of such a woman and with a smile of which the sweetness was thrilling to her listener", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3854, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0000.flac", "answer": "MISS CHANCELLOR HERSELF HAD THOUGHT SO MUCH ON THE VITAL SUBJECT WOULD NOT SHE MAKE A FEW REMARKS AND GIVE THEM SOME OF HER EXPERIENCES", "subset": "test_other", "task_type": "understanding", "prediction": "miss chancellor herself hath thought so much on the vital subject would not she make a few remarks and give them some of her experiences", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3855, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0011.flac", "answer": "IF IT BE NECESSARY WE ARE PREPARED TO TAKE CERTAIN STEPS TO CONCILIATE THE SHRINKING", "subset": "test_other", "task_type": "understanding", "prediction": "if it be necessary we are prepared to take certain steps to conciliate the shrinking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3856, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0018.flac", "answer": "THE UNHAPPINESS OF WOMEN", "subset": "test_other", "task_type": "understanding", "prediction": "the unhappiness of women", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3857, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0020.flac", "answer": "THIS WAS THE ONLY SACRED CAUSE THIS WAS THE GREAT THE JUST REVOLUTION IT MUST TRIUMPH IT MUST SWEEP EVERYTHING BEFORE IT IT MUST EXACT FROM THE OTHER THE BRUTAL BLOOD STAINED RAVENING RACE THE LAST PARTICLE OF EXPIATION", "subset": "test_other", "task_type": "understanding", "prediction": "this was the only sacred cause this was the great the just revolution it was triumph it was sweeping everything before it it must exact from the other the brutal bloodstained ravening race the last particle of expiation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3858, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0002.flac", "answer": "PERHAPS SHE COULD SPEAK FOR THEM MORE THAN FOR SOME OTHERS", "subset": "test_other", "task_type": "understanding", "prediction": "perhaps she could speak for them more than for some others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3859, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0013.flac", "answer": "RAISE THE STANDARD AMONG THEM AND BRING ME A THOUSAND NAMES", "subset": "test_other", "task_type": "understanding", "prediction": "raise the standard among them and bring me your thousand names", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3860, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0016.flac", "answer": "I WANT TO BE NEAR TO THEM TO HELP THEM", "subset": "test_other", "task_type": "understanding", "prediction": "i want to be near to them to help them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3861, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0007.flac", "answer": "SHE WISHED TO WORK IN ANOTHER FIELD SHE HAD LONG BEEN PREOCCUPIED WITH THE ROMANCE OF THE PEOPLE", "subset": "test_other", "task_type": "understanding", "prediction": "she wished to work in another field she had long been preoccupied with the romance of the people", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3862, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0023.flac", "answer": "WHEN MISS BIRDSEYE APPROACHED IT TRANSFIGURED HER FAMILIAR HER COMICAL SHAPE AND MADE THE POOR LITTLE HUMANITARY HACK SEEM ALREADY A MARTYR", "subset": "test_other", "task_type": "understanding", "prediction": "when miss birdseye approached it transfigured her familiar her comical shape and made the poor little humanitairy hack seem already a martyr", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3863, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0003.flac", "answer": "WITH HER IMMENSE SYMPATHY FOR REFORM SHE FOUND HERSELF SO OFTEN WISHING THAT REFORMERS WERE A LITTLE DIFFERENT", "subset": "test_other", "task_type": "understanding", "prediction": "with her immense sympathy for reform she found herself so often wishing that reformers were a little different", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3864, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0015.flac", "answer": "SAID OLIVE CHANCELLOR WITH A FACE WHICH SEEMED TO PLEAD FOR A REMISSION OF RESPONSIBILITY", "subset": "test_other", "task_type": "understanding", "prediction": "said olive chancellor with a face which seemed to plead for a remission of responsibility", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3865, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0010.flac", "answer": "OLIVE CHANCELLOR WONDERED HOW MISSUS FARRINDER WOULD TREAT THAT BRANCH OF THE QUESTION", "subset": "test_other", "task_type": "understanding", "prediction": "olive chancellor wondered how mrs thryngdoe would treat that branch of the question", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3866, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0008.flac", "answer": "THIS MIGHT SEEM ONE OF THE MOST ACCESSIBLE OF PLEASURES BUT IN POINT OF FACT SHE HAD NOT FOUND IT SO", "subset": "test_other", "task_type": "understanding", "prediction": "this might seem one of the most accessible of pleasures but in point of fact she had not found it so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3867, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0004.flac", "answer": "OLIVE HATED TO HEAR THAT FINE AVENUE TALKED ABOUT AS IF IT WERE SUCH A REMARKABLE PLACE AND TO LIVE THERE WERE A PROOF OF WORLDLY GLORY", "subset": "test_other", "task_type": "understanding", "prediction": "olive hated to hear that fine avenue talked about as if it were such a remarkable place and to live there were a proof of worldly glory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3868, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0001.flac", "answer": "HOW DID THE LADIES ON BEACON STREET FEEL ABOUT THE BALLOT", "subset": "test_other", "task_type": "understanding", "prediction": "how did the ladies on beacon street feel about the ballot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3869, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0017.flac", "answer": "IT WAS ONE THING TO CHOOSE FOR HERSELF BUT NOW THE GREAT REPRESENTATIVE OF THE ENFRANCHISEMENT OF THEIR SEX FROM EVERY FORM OF BONDAGE HAD CHOSEN FOR HER", "subset": "test_other", "task_type": "understanding", "prediction": "it was one thing to choose for herself but now the great representative of the enfranchisement of their sex from every form of bondage had chosen for her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3870, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0006.flac", "answer": "SHE KNEW HER PLACE IN THE BOSTON HIERARCHY AND IT WAS NOT WHAT MISSUS FARRINDER SUPPOSED SO THAT THERE WAS A WANT OF PERSPECTIVE IN TALKING TO HER AS IF SHE HAD BEEN A REPRESENTATIVE OF THE ARISTOCRACY", "subset": "test_other", "task_type": "understanding", "prediction": "she knew her place in the boston hierarchy and it was not what mrs farinder supposed so that there was a want of perspective in talking to her as if she had been a representative of the aristocracy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3871, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0024.flac", "answer": "OLIVE CHANCELLOR LOOKED AT HER WITH LOVE REMEMBERED THAT SHE HAD NEVER IN HER LONG UNREWARDED WEARY LIFE HAD A THOUGHT OR AN IMPULSE FOR HERSELF", "subset": "test_other", "task_type": "understanding", "prediction": "olive chancellor looked at her with love remembered that she had never in her long unrewarded weary life had a thought or an impulse for herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3872, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0005.flac", "answer": "ALL SORTS OF INFERIOR PEOPLE LIVED THERE AND SO BRILLIANT A WOMAN AS MISSUS FARRINDER WHO LIVED AT ROXBURY OUGHT NOT TO MIX THINGS UP", "subset": "test_other", "task_type": "understanding", "prediction": "all sorts of inferior people with that and so brilliant a woman as mrs farinder who lived at braxby ought not to mix things up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3873, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0021.flac", "answer": "THEY WOULD BE NAMES OF WOMEN WEAK INSULTED PERSECUTED BUT DEVOTED IN EVERY PULSE OF THEIR BEING TO THE CAUSE AND ASKING NO BETTER FATE THAN TO DIE FOR IT", "subset": "test_other", "task_type": "understanding", "prediction": "there would be names of women weak insulted persecuted but devoted in every pulse of their being to the cause and asking no better fate than to die for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3874, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0009.flac", "answer": "CHARLIE WAS A YOUNG MAN IN A WHITE OVERCOAT AND A PAPER COLLAR IT WAS FOR HIM IN THE LAST ANALYSIS THAT THEY CARED MUCH THE MOST", "subset": "test_other", "task_type": "understanding", "prediction": "charlie was a young man in a wide overcoat and a paper collar it was for him in the last analysis that they cared much the most", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3875, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0022.flac", "answer": "IT WAS NOT CLEAR TO THIS INTERESTING GIRL IN WHAT MANNER SUCH A SACRIFICE AS THIS LAST WOULD BE REQUIRED OF HER BUT SHE SAW THE MATTER THROUGH A KIND OF SUNRISE MIST OF EMOTION WHICH MADE DANGER AS ROSY AS SUCCESS", "subset": "test_other", "task_type": "understanding", "prediction": "it was not clear to this interesting girl in what manner such a sacrifice as this last would be required of her that she solved the matter through a kind of sunrise mist of imagination which made danger as rosy as success", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3876, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0012.flac", "answer": "OUR MOVEMENT IS FOR ALL IT APPEALS TO THE MOST DELICATE LADIES", "subset": "test_other", "task_type": "understanding", "prediction": "our movement is for all it appeals to the most delicate ladies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3877, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0019.flac", "answer": "THEY WERE HER SISTERS THEY WERE HER OWN AND THE DAY OF THEIR DELIVERY HAD DAWNED", "subset": "test_other", "task_type": "understanding", "prediction": "they were her sisters they were her own and the day of their delivery had dawned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3878, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6128/63244/6128-63244-0025.flac", "answer": "SHE HAD BEEN CONSUMED BY THE PASSION OF SYMPATHY IT HAD CRUMPLED HER INTO AS MANY CREASES AS AN OLD GLAZED DISTENDED GLOVE", "subset": "test_other", "task_type": "understanding", "prediction": "she had been consumed by the passion of sympathy it had crumpled her into as many creases as an old glazed distended glove", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3879, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0032.flac", "answer": "THOUGH SO LOUD A DENIAL IS WRITTEN ON YOUR FACE I PERSIST IN MY CONVICTION AND THAT NO IDLE DELUSION ENSNARES ME I CAN PROVE", "subset": "test_other", "task_type": "understanding", "prediction": "though so loud a denial is written on your face i persist in my conviction and that no idle delusion and snazz me i can prove", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3880, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0031.flac", "answer": "HOW INDIFFERENT YOU LOOK BUT I TELL YOU HER DEEP BLUE EYES FLASHED AS SHE SPOKE THAT SO LONG AS YOU WERE STILL A GENUINE CREATING ARTIST THE CASE WAS DIFFERENT", "subset": "test_other", "task_type": "understanding", "prediction": "how indifferent you look but i tell you her deep blue eyes flashed as she spoke that so long as you were still a genuine creating artist the case was different", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3881, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0029.flac", "answer": "A WOMAN WHO YEARNS FOR THE REGARD OF ALL MEN AND MAKES LOVE A TOY EASILY LESSENS THE DEMANDS SHE IMPOSES UPON INDIVIDUALS", "subset": "test_other", "task_type": "understanding", "prediction": "a woman who yearns for the regard of all men and makes love a toy easily lessens the demands she imposes upon individuals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3882, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0018.flac", "answer": "THE THREE MOST TRUSTWORTHY ONES ARE HERE AMYNTAS THE LEECH CHRYSIPPUS AND THE ADMIRABLE PROCLUS", "subset": "test_other", "task_type": "understanding", "prediction": "the three most trustworthy ones are here amyntas the leag chrysippus and the admirable proclus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3883, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0000.flac", "answer": "WHEN HE CAME FROM THE BATH PROCLUS VISITED HIM AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "when he came from the bath proclus visited him again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3884, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0004.flac", "answer": "THE BANQUET WAS TO BEGIN IN A FEW HOURS YET HE COULD NOT LET THE DAY PASS WITHOUT SEEING DAPHNE AND TELLING HER THE WORDS OF THE ORACLE", "subset": "test_other", "task_type": "understanding", "prediction": "the banquet was to begin in a few hours yet he could not let the day pass without seeing daphne and telling her the words of the oracle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3885, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0025.flac", "answer": "THE ROYAL LADY HAD INQUIRED ABOUT HIM AND HIS SUFFERINGS WITH ALMOST SISTERLY INTEREST AND ALTHEA EAGERLY CONFIRMED THE STATEMENT", "subset": "test_other", "task_type": "understanding", "prediction": "the royal lady had inquired about him and his sufferings with almost sisterly interest and althea eagerly confirmed the statement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3886, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0030.flac", "answer": "ONLY EVEN THOUGH LOVE HAS WHOLLY DISAPPEARED SHE STILL CLAIMS CONSIDERATION AND ALTHEA DID NOT WISH TO LOSE HERMON'S REGARD", "subset": "test_other", "task_type": "understanding", "prediction": "only even though love has wholly disappeared she still claims consideration and althea did not wish to lose hermon s regard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3887, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0006.flac", "answer": "SINCE HIS RETURN FROM THE ORACLE THE FEAR THAT THE RESCUED DEMETER MIGHT YET BE THE WORK OF MYRTILUS HAD AGAIN MASTERED HIM", "subset": "test_other", "task_type": "understanding", "prediction": "since his return from the oracle the fear that the rescued demeter might yet be the work of myrtilus had again mastered him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3888, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0002.flac", "answer": "SHE WOULD APPEAR HERSELF AT DESSERT AND THE BANQUET MUST THEREFORE BEGIN AT AN UNUSUALLY EARLY HOUR", "subset": "test_other", "task_type": "understanding", "prediction": "she would appear herself at dessert and the banquet must therefore begin at an unusually early hour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3889, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0005.flac", "answer": "HE LONGED WITH ARDENT YEARNING FOR THE SOUND OF HER VOICE AND STILL MORE TO UNBURDEN HIS SORELY TROUBLED SOUL TO HER", "subset": "test_other", "task_type": "understanding", "prediction": "he longed with ardent yearning for the sound of her voice and still more to unburden his sorely troubled soul to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3890, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0019.flac", "answer": "LET US HOPE THAT YOU WILL MAKE THIS THREE LEAVED CLOVER THE LUCK PROMISING FOUR LEAVED ONE", "subset": "test_other", "task_type": "understanding", "prediction": "let us hope that you will make this three leaved clover the luck promising four leaved one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3891, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0007.flac", "answer": "THE APPROVAL AS WELL AS THE DOUBTS WHICH IT AROUSED IN OTHERS STRENGTHENED HIS OPINION ALTHOUGH EVEN NOW HE COULD NOT SUCCEED IN BRINGING IT INTO HARMONY WITH THE FACTS", "subset": "test_other", "task_type": "understanding", "prediction": "the approval as well as the doubts which had arisen in others strengthened his opinion although even now he could not succeed in bringing it into harmony with the facts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3892, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0012.flac", "answer": "TRUE AN INTERESTING CONVERSATION STILL HAD POWER TO CHARM HIM BUT OFTEN DURING ITS CONTINUANCE THE FULL CONSCIOUSNESS OF HIS MISFORTUNE FORCED ITSELF UPON HIS MIND FOR THE MAJORITY OF THE SUBJECTS DISCUSSED BY THE ARTISTS CAME TO THEM THROUGH THE MEDIUM OF SIGHT AND REFERRED TO NEW CREATIONS OF ARCHITECTURE SCULPTURE AND PAINTING FROM WHOSE ENJOYMENT HIS BLINDNESS DEBARRED HIM", "subset": "test_other", "task_type": "understanding", "prediction": "true an interesting conversation still had power to charm him but often during its continuance the full consciousness of his misfortune forced itself upon his mind for the majority of the subjects discussed by the artists came to them through the medium of sight and referred to new creations of architecture sculpture and painting from whose enjoyment his blindness debarred him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3893, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0020.flac", "answer": "YOUR UNCLE TOO HAS OFTEN WITH PRAISEWORTHY GENEROSITY HELPED ARSINOE IN MANY AN EMBARRASSMENT", "subset": "test_other", "task_type": "understanding", "prediction": "your uncle too has often with praiseworthy generosity helped arsinoe in many an embarrassment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3894, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0011.flac", "answer": "THE PLACE BY HERMON'S SIDE WHICH ALTHEA HAD CHOSEN FOR HERSELF WOULD THEN BE GIVEN UP TO ARSINOE", "subset": "test_other", "task_type": "understanding", "prediction": "the place by hermon's side which alethea had chosen for herself would then be given up to arsenal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3895, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0022.flac", "answer": "WHEN HE DID FINALLY SUMMON YOU HE SAID THINGS WHICH MUST HAVE WOUNDED YOU", "subset": "test_other", "task_type": "understanding", "prediction": "when he did finally summon you he said things which must have wounded you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3896, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0027.flac", "answer": "THE RHODIAN WAS JUST BEGINNING TO PRAISE ARSINOE ALSO AS A SPECIAL FRIEND AND CONNOISSEUR OF THE SCULPTOR'S ART WHEN CRATES HERMON'S FELLOW STUDENT ASKED THE BLIND ARTIST IN BEHALF OF HIS BEAUTIFUL COMPANION WHY HIS DEMETER WAS PLACED UPON A PEDESTAL WHICH TO OTHERS AS WELL AS HIMSELF SEEMED TOO HIGH FOR THE SIZE OF THE STATUE", "subset": "test_other", "task_type": "understanding", "prediction": "the rhodian was just beginning to praise arsinoe also as a special friend and connoisseur of the sculptor s art when crates hermon s fellow student asked the blind artist in behalf of his beautiful companion why his demeter was placed upon a pedestal which to others as well as himself seemed too high for the size of the statue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3897, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0017.flac", "answer": "WE WOMEN ARE ONLY AS OLD AS WE LOOK AND THE LEECHES AND TIRING WOMEN OF THIS BEAUTY OF FORTY PRACTISE ARTS WHICH GIVE HER THE APPEARANCE OF TWENTY FIVE YET PERHAPS THE KING VALUES HER INTELLECT MORE THAN HER PERSON AND THE WISDOM OF A HUNDRED SERPENTS IS CERTAINLY UNITED IN THIS WOMAN'S HEAD", "subset": "test_other", "task_type": "understanding", "prediction": "we women are only as old as we look and the leeches and tire women of this beauty of forty practise arts which give her the appearance of twenty five yet perhaps the king values her intellect more than her person and the wisdom of a hundred serpents is certainly united in this woman s head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3898, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0003.flac", "answer": "SO THE ARTIST FOUND HIMSELF OBLIGED TO RELINQUISH HIS OPPOSITION", "subset": "test_other", "task_type": "understanding", "prediction": "so the artist found himself obliged to relinquish his opposition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3899, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0033.flac", "answer": "IT WAS NAY IT COULD HAVE BEEN NOTHING ELSE THAT VERY SPIDER", "subset": "test_other", "task_type": "understanding", "prediction": "it was nay it could have been nothing else that very spider", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3900, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0016.flac", "answer": "THE KING'S SISTER THE OBJECT OF HIS LOVE CRIED HERMON INCREDULOUSLY", "subset": "test_other", "task_type": "understanding", "prediction": "the king s sister the object of his love cried hermon incredulously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3901, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0023.flac", "answer": "THAT IS GOING TOO FAR REPLIED HERMON", "subset": "test_other", "task_type": "understanding", "prediction": "that is going too far replied hermann", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3902, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0013.flac", "answer": "A STRANGER OUT OF HIS OWN SPHERE HE FELT CHILLED AMONG THESE CLOSELY UNITED MEN AND WOMEN TO WHOM NO TIE BOUND HIM SAVE THE PRESENCE OF THE SAME HOST", "subset": "test_other", "task_type": "understanding", "prediction": "a stranger out of his own sphere he felt chilled among these closely united men and women to whom no tie bound him save the presence of the same host", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3903, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0015.flac", "answer": "HIS SON HAD BEEN THIS ROYAL DAME'S FIRST HUSBAND AND SHE HAD DESERTED HIM TO MARRY LYSIMACHUS THE AGED KING OF THRACE", "subset": "test_other", "task_type": "understanding", "prediction": "his son had been the royal dame s first husband and she had deserted him to marry lysimachus the aged king of thrace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3904, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0026.flac", "answer": "HERMON LISTENED TO THE PAIR IN SILENCE", "subset": "test_other", "task_type": "understanding", "prediction": "her mom listened to the parents silence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3905, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0009.flac", "answer": "HITHERTO THE MERCHANT HAD BEEN INDUCED IT IS TRUE TO ADVANCE LARGE SUMS OF MONEY TO THE QUEEN BUT THE LOYAL DEVOTION WHICH HE SHOWED TO HER ROYAL HUSBAND HAD RENDERED IT IMPOSSIBLE TO GIVE HIM EVEN A HINT OF THE CONSPIRACY", "subset": "test_other", "task_type": "understanding", "prediction": "hitherto the merchant had been induced it is true to advance large sums of money to the queen but the loyal devotion which he showed to her royal husband had rendered it impossible to give him even a hint of the conspiracy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3906, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0024.flac", "answer": "HE WINKED AT HER AND MADE A SIGNIFICANT GESTURE AS HE SPOKE AND THEN INFORMED THE BLIND ARTIST HOW GRACIOUSLY ARSINOE HAD REMEMBERED HIM WHEN SHE HEARD OF THE REMEDY BY WHOSE AID MANY A WONDERFUL CURE OF BLIND EYES HAD BEEN MADE IN RHODES", "subset": "test_other", "task_type": "understanding", "prediction": "he winked at her and made a significant gesture as he spoke and then informed the blind artist how graciously arsinoe had remembered him when she heard of the remedy by whose aid many a wonderful cure of blind eye had been made in rhodes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3907, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0008.flac", "answer": "THEN HE WENT DIRECTLY TO THE NEIGHBOURING PALACE THE QUEEN MIGHT HAVE APPEARED ALREADY AND IT WOULD NOT DO TO KEEP HER WAITING", "subset": "test_other", "task_type": "understanding", "prediction": "then he went directly to the neighbouring palace the queen might have appeared already and it would not do to keep her waiting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3908, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0014.flac", "answer": "CRATES HAD REALLY BEEN INVITED IN ORDER TO WIN HIM OVER TO THE QUEEN'S CAUSE BUT CHARMING FAIR HAIRED NICO HAD BEEN COMMISSIONED BY THE CONSPIRATORS TO PERSUADE HIM TO SING ARSINOE'S PRAISES AMONG HIS PROFESSIONAL ASSOCIATES", "subset": "test_other", "task_type": "understanding", "prediction": "crates had really been invited in order to win him over to the queen s cause but charming fair haired nico had been commissioned by the conspirators to persuade him to sing arsinoe s praises among his professional associates", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3909, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0021.flac", "answer": "HOW LONG HE KEPT YOU WAITING FOR THE FIRST WORD CONCERNING A WORK WHICH JUSTLY TRANSPORTED THE WHOLE CITY WITH DELIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "how long he kept you waiting from the first word concerning a work which justly transported the whole city with delight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3910, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0028.flac", "answer": "YET WHAT MATTERED IT EVEN IF THESE MISERABLE PEOPLE CONSIDERED THEMSELVES DECEIVED AND POINTED THE FINGER OF SCORN AT HIM", "subset": "test_other", "task_type": "understanding", "prediction": "yet what mattered it even if these miserable people considered themselves deceived and pointed the finger of scorn at him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3911, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0001.flac", "answer": "BUT HERMON WAS NOT IN THE MOOD TO SHARE A JOYOUS REVEL AND HE FRANKLY SAID SO ALTHOUGH IMMEDIATELY AFTER HIS RETURN HE HAD ACCEPTED THE INVITATION TO THE FESTIVAL WHICH THE WHOLE FELLOWSHIP OF ARTISTS WOULD GIVE THE FOLLOWING DAY IN HONOUR OF THE SEVENTIETH BIRTHDAY OF THE OLD SCULPTOR EUPHRANOR", "subset": "test_other", "task_type": "understanding", "prediction": "but hermann was not in the mood to share a joyous revel and he frankly said so although immediately after his return he had accepted the invitation to the festival which the whole fellowship of artists would give the following day in honor of the seventieth birthday of the old sculptor euphrainer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3912, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24317/5484-24317-0010.flac", "answer": "WHEN HERMON ENTERED THE RESIDENCE OF THE GRAMMATEUS IN THE PALACE THE GUESTS HAD ALREADY ASSEMBLED", "subset": "test_other", "task_type": "understanding", "prediction": "when hermon entered the residence of the grammateus in the palace the guests had already assembled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3913, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0003.flac", "answer": "WHAT PLEASURE HAD LIFE TO OFFER HIM THE BLIND MAN WHO WAS ALREADY DEAD TO HIS ART", "subset": "test_other", "task_type": "understanding", "prediction": "what pleasure had life to offer him the blind man who was already dead to his art", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3914, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0034.flac", "answer": "THE EGYPTIAN OBEYED AND HIS MASTER CROSSED THE WIDE SPACE STREWN WITH SAND AND APPROACHED THE STAGE WHICH HAD BEEN ERECTED FOR THE FESTAL PERFORMANCES EVEN HAD HIS EYES RETAINED THE POWER OF SIGHT HIS BLOOD WAS COURSING SO WILDLY THROUGH HIS VEINS THAT HE MIGHT PERHAPS HAVE BEEN UNABLE TO DISTINGUISH THE STATUES AROUND HIM AND THE THOUSANDS OF SPECTATORS WHO CROWDED CLOSELY TOGETHER RICHLY GARLANDED THEIR CHEEKS GLOWING WITH ENTHUSIASM SURROUNDED THE ARENA HERMON", "subset": "test_other", "task_type": "understanding", "prediction": "the egyptian obeyed and his master crossed the wide space strewn with sand and approached the stage which had been erected for the festal performances even had his eyes retained the power of sight his blood was coursing so wildly through his veins that he might perhaps have been unable to distinguish the statues around him and the thousands of spectators who crowded closely together richly garlanded their cheeks glowing with enthusiasm surrounded the arena hermann", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3915, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0006.flac", "answer": "WHATEVER MIGHT AWAIT HIM HE DESIRED NO BETTER FATE", "subset": "test_other", "task_type": "understanding", "prediction": "whatever might await him he desired no better fate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3916, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0028.flac", "answer": "HE HIMSELF ON THE WAY TO EXPOSE HIMSELF TO THE MALICE AND MOCKERY OF THE WHOLE CITY", "subset": "test_other", "task_type": "understanding", "prediction": "he himself on the way to expose himself to the malice and mockery of the whole city", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3917, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0008.flac", "answer": "BUT IF HE WERE DESTINED TO MEET HIS MYRTILUS AND HIS MOTHER IN THE WORLD BEYOND THE GRAVE WHAT HAD HE NOT TO TELL THEM HOW SURE HE WAS OF FINDING A JOYFUL RECEPTION THERE FROM BOTH", "subset": "test_other", "task_type": "understanding", "prediction": "but if he were destined to meet his bertolus and his mother in the world beyond the grave what had he not to tell them how sure he was of finding a joyful reception there from both", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3918, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0002.flac", "answer": "WAS HE TO BE LED TO THE EXECUTIONER'S BLOCK", "subset": "test_other", "task_type": "understanding", "prediction": "was he to be led to the executioners block", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3919, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0013.flac", "answer": "LASTLY WITH EARNEST WARMTH SHE BESOUGHT HIM BEFORE TAKING THE PRISONERS AWAY TO PERMIT HER TO SPEAK TO THE COMMANDING GENERAL PHILIPPUS HER FATHER'S GUEST WHO SHE WAS CERTAIN WAS IN THE PALACE", "subset": "test_other", "task_type": "understanding", "prediction": "lastly with earnest warmth she besought him before taking the prisoners away to permit her to speak to the commanding general philippus her father s guest who she was certain was in the palace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3920, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0033.flac", "answer": "HE WAS APPEARING BEFORE HIS COMPANIONS ONLY TO GIVE TRUTH ITS JUST DUE", "subset": "test_other", "task_type": "understanding", "prediction": "he was appearing before his companions only to give truth its just due", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3921, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0017.flac", "answer": "AS SOON AS THE CAPTIVE ARTIST WAS ALONE WITH THE WOMAN HE LOVED HE CLASPED HER HAND POURING FORTH INCOHERENT WORDS OF THE MOST ARDENT GRATITUDE AND WHEN HE FELT HER WARMLY RETURN THE PRESSURE HE COULD NOT RESTRAIN THE DESIRE TO CLASP HER TO HIS HEART", "subset": "test_other", "task_type": "understanding", "prediction": "as soon as the captive artist was alone with the woman he loved he clasped her hand pouring forth incoherent words of the most ardent gratitude and when he felt her warmly return the pressure he could not restrain the desire to clasp her to his heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3922, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0026.flac", "answer": "BRING THIS BEFORE YOUR MIND AND EVERYTHING ELSE THAT YOU MUST ACCEPT WITH IT IF YOU CONSENT WHEN THE TIME ARRIVES TO BECOME MINE CONCEAL AND PALLIATE NOTHING", "subset": "test_other", "task_type": "understanding", "prediction": "bring this before your mind and everything else that you must accept with it if you consent when the time arrives to become mine conceal and palliate nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3923, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0031.flac", "answer": "ON THE WAY HIS HEART THROBBED ALMOST TO BURSTING", "subset": "test_other", "task_type": "understanding", "prediction": "on the way his heart throbbed almost to bursting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3924, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0018.flac", "answer": "IN SPITE OF HIS DEEP MENTAL DISTRESS HE COULD HAVE SHOUTED ALOUD IN HIS DELIGHT AND GRATITUDE", "subset": "test_other", "task_type": "understanding", "prediction": "in spite of his deep mental distress he could have shouted aloud in his delight and gratitude", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3925, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0023.flac", "answer": "THEN DAPHNE RAISED HER FACE TO HIS ASKING SO THE DEMETER IS THE WORK OF MYRTILUS", "subset": "test_other", "task_type": "understanding", "prediction": "then daphne raised her face to his asking so the demeter is the work of myrtillus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3926, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0014.flac", "answer": "CRIED HERMON IN GRATEFUL AGITATION BUT SHE WOULD NOT LISTEN TO HIM AND FOLLOWED THE SOLDIER WHOM THE CAPTAIN DETAILED TO GUIDE HER INTO THE PALACE", "subset": "test_other", "task_type": "understanding", "prediction": "cried hermon in grateful agitation but she would not listen to him and followed the soldier whom the captain detailed to guide her into the palace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3927, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0022.flac", "answer": "BUT HERMON WITH DROOPING HEAD MURMURED TO MORROW I SHALL NO LONGER BE WHAT I AM NOW", "subset": "test_other", "task_type": "understanding", "prediction": "but hermann with drooping head murmured to morrow i shall no longer be what i am now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3928, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0027.flac", "answer": "SO ARCHIAS INTENDED TO LEAVE THE CITY ON ONE OF HIS OWN SHIPS THAT VERY DAY", "subset": "test_other", "task_type": "understanding", "prediction": "sorakais intended to leave the city on one of his own ships that very day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3929, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0015.flac", "answer": "TO MORROW YOU SHALL CONFESS TO ME WHO TREACHEROUSLY DIRECTED YOU TO THIS DANGEROUS PATH", "subset": "test_other", "task_type": "understanding", "prediction": "to morrow you shall confess to me who treacherously directed you to this dangerous path", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3930, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0000.flac", "answer": "NOT A SOUND IF YOU VALUE YOUR LIVES", "subset": "test_other", "task_type": "understanding", "prediction": "not a sound if you value your lives", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3931, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0012.flac", "answer": "SOMETIMES WITH TOUCHING ENTREATY SOMETIMES WITH IMPERIOUS COMMAND SHE PROTESTED AFTER GIVING HIM HER NAME THAT THIS MATTER COULD BE NOTHING BUT AN UNFORTUNATE MISTAKE", "subset": "test_other", "task_type": "understanding", "prediction": "sometimes with touching entreaty sometimes with imperious command she protested after giving him her name that this matter could be nothing but an unfortunate mistake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3932, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0035.flac", "answer": "SHOUTED HIS FRIEND SOTELES IN JOYFUL SURPRISE IN THE MIDST OF THIS PAINFUL WALK HERMON", "subset": "test_other", "task_type": "understanding", "prediction": "shouted his friend sotilus in joyful surprise in the midst of his painful walk hermann", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3933, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0036.flac", "answer": "EVEN WHILE HE BELIEVED HIMSELF TO BE THE CREATOR OF THE DEMETER HE HAD BEEN SERIOUSLY TROUBLED BY THE PRAISE OF SO MANY CRITICS BECAUSE IT HAD EXPOSED HIM TO THE SUSPICION OF HAVING BECOME FAITHLESS TO HIS ART AND HIS NATURE", "subset": "test_other", "task_type": "understanding", "prediction": "even while he believed himself to be the creator of the demeter he had been seriously troubled by the praise of so many critics because it had exposed him to the suspicion of having become faithless to his art and his nature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3934, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0032.flac", "answer": "EVEN DAPHNE'S IMAGE AND WHAT THREATENED HER FATHER AND HER WITH HIM RECEDED FAR INTO THE BACKGROUND", "subset": "test_other", "task_type": "understanding", "prediction": "even daphne s image and what threatened her father and her with him receded far into the background", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3935, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0016.flac", "answer": "DAPHNE AGAIN PLEADED FOR THE LIBERATION OF THE PRISONERS BUT PHILIPPUS SILENCED HER WITH THE GRAVE EXCLAMATION THE ORDER OF THE KING", "subset": "test_other", "task_type": "understanding", "prediction": "daphne again pleaded for the liberation of the prisoners but philippa silenced her with the grave exclamation the order of the king", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3936, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0009.flac", "answer": "THE POWER WHICH DELIVERED HIM OVER TO DEATH JUST AT THAT MOMENT WAS NOT NEMESIS NO IT WAS A KINDLY DEITY", "subset": "test_other", "task_type": "understanding", "prediction": "the power which delivered him over to death just at that moment was not nemesis no it was a kindly deity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3937, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0030.flac", "answer": "BESIDES HE KNEW THAT THE OBJECT OF HIS LOVE WOULD NOT PART FROM HIM WITHOUT GRANTING HIM ONE LAST WORD", "subset": "test_other", "task_type": "understanding", "prediction": "besides he knew that the object of his love would not part from him without granting him one last word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3938, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0025.flac", "answer": "AND I FOOL BLINDED ALSO IN MIND COULD BE VEXED WITH YOU FOR IT", "subset": "test_other", "task_type": "understanding", "prediction": "and i fool blinded also in mind could be vexed with you for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3939, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0004.flac", "answer": "OUGHT HE NOT TO GREET THIS SUDDEN END AS A BOON FROM THE IMMORTALS", "subset": "test_other", "task_type": "understanding", "prediction": "ought he not to greet his sudden end as a boon from the immortals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3940, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0019.flac", "answer": "HE MIGHT NOW HAVE BEEN PERMITTED TO BIND FOREVER TO HIS LIFE THE WOMAN WHO HAD JUST RESCUED HIM FROM THE GREATEST DANGER BUT THE CONFESSION HE MUST MAKE TO HIS FELLOW ARTISTS IN THE PALAESTRA THE FOLLOWING MORNING STILL SEALED HIS LIPS YET IN THIS HOUR HE FELT THAT HE WAS UNITED TO HER AND OUGHT NOT TO CONCEAL WHAT AWAITED HIM SO OBEYING A STRONG IMPULSE HE EXCLAIMED YOU KNOW THAT I LOVE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "he might now have been permitted to bind for ever to his life the woman who had just rescued him from the greatest danger but the confession he must make to his fellow artists in the palestra the following morning still sealed his lips yet in this hour he felt that he was united to her and ought not to conceal what awaited him so obeying a strong impulse he exclaimed you know that i love you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3941, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0007.flac", "answer": "IF HE HAD PASSED INTO ANNIHILATION HE HERMON WISHED TO FOLLOW HIM THITHER AND ANNIHILATION CERTAINLY MEANT REDEMPTION FROM PAIN AND MISERY", "subset": "test_other", "task_type": "understanding", "prediction": "if he had passed into annihilation he hermod wished to follow him thither and annihilation certainly meant redemption from pain and misery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3942, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0037.flac", "answer": "HONOUR TO MYRTILUS AND HIS ART BUT HE TRUSTED THIS NOBLE FESTAL ASSEMBLAGE WOULD PARDON THE UNINTENTIONAL DECEPTION AND AID HIS PRAYER FOR RECOVERY", "subset": "test_other", "task_type": "understanding", "prediction": "honor to myrtilus and his art but he trusted this noble festal assemblage would pardon the unintentional deception and aid his prayer for recovery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3943, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0010.flac", "answer": "YET IT WAS NO ILLUSION THAT DECEIVED HIM", "subset": "test_other", "task_type": "understanding", "prediction": "yet it was no illusion that deceived him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3944, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0020.flac", "answer": "I LOVE YOU AND HAVE LOVED YOU ALWAYS", "subset": "test_other", "task_type": "understanding", "prediction": "i love you and have loved you always", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3945, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0011.flac", "answer": "AGAIN HE HEARD THE BELOVED VOICE AND THIS TIME IT ADDRESSED NOT ONLY HIM BUT WITH THE UTMOST HASTE THE COMMANDER OF THE SOLDIERS", "subset": "test_other", "task_type": "understanding", "prediction": "again he heard the beloved voice and this time it addressed not only him but with the utmost haste the commander of the soldiers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3946, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0029.flac", "answer": "HIS HEART CONTRACTED PAINFULLY AND HIS SOLICITUDE ABOUT HIS UNCLE'S FATE INCREASED WHEN PHILIPPUS INFORMED HIM THAT THE CONSPIRATORS HAD BEEN ARRESTED AT THE BANQUET AND HEADED BY AMYNTAS THE RHODIAN CHRYSIPPUS AND PROCLUS HAD PERISHED BY THE EXECUTIONER'S SWORD AT SUNRISE", "subset": "test_other", "task_type": "understanding", "prediction": "his heart contracted painfully and his solicitude about his uncle's fate increased when philippus informed him that the conspirators had been arrested at the banquet and headed by amintas the rhodian chrysippus and proclus had perished by the executioner s sword at sunrise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3947, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0001.flac", "answer": "TO OFFER RESISTANCE WOULD HAVE BEEN MADNESS FOR EVEN HERMON PERCEIVED BY THE LOUD CLANKING OF WEAPONS AROUND THEM THE GREATLY SUPERIOR POWER OF THE ENEMY AND THEY WERE ACTING BY THE ORDERS OF THE KING TO THE PRISON NEAR THE PLACE OF EXECUTION", "subset": "test_other", "task_type": "understanding", "prediction": "to offer resistance would have been madness for even hermon perceived by the loud clanking of weapons around them the greatly superior power of the enemy and they were acting by the orders of the king to the prison near the place of execution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3948, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0021.flac", "answer": "DAPHNE EXCLAIMED TENDERLY WHAT MORE IS NEEDED", "subset": "test_other", "task_type": "understanding", "prediction": "daphne exclaimed tenderly what more is needed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3949, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0024.flac", "answer": "WHAT A TERRIBLE ORDEAL AGAIN AWAITS YOU", "subset": "test_other", "task_type": "understanding", "prediction": "what a terrible ordeal again awaits you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3950, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5484/24318/5484-24318-0005.flac", "answer": "DID IT NOT SPARE HIM A HUMILIATION AS GREAT AND PAINFUL AS COULD BE IMAGINED", "subset": "test_other", "task_type": "understanding", "prediction": "did it not spare him a humiliation as great and painful as could be imagined", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3951, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0008.flac", "answer": "I BELIEVE HE HATH DENOUNCED ME TO THE EUNUCH HENCE THESE PAGES ET ABOUT ME AND HE HATH MADE ME AN ACCOMPLICE IN HIS CRIME", "subset": "test_other", "task_type": "understanding", "prediction": "i believe he hath denounced me to the eunuch hence these pages at about me and he hath made me an accomplice in his crime", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3952, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0001.flac", "answer": "THEN SHE THREW HERSELF UPON HIM AND HE GATHERED HER TO HIS BOSOM AND THE TWAIN FELL DOWN IN A FAINTING FIT", "subset": "test_other", "task_type": "understanding", "prediction": "then she threw herself upon him and he gathered her to his bosom and the twain fell down in a fainting fit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3953, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0006.flac", "answer": "THE CHAMBERLAIN CALLED THE CASTRATO AND CHARGED HIM TO DO ACCORDINGLY SO HE REPLIED I HEAR AND I OBEY AND HE TOOK HIS PAGES WITH HIM AND WENT OUT IN SEARCH OF THE STOKER TILL HE FOUND HIM IN THE REAR OF THE CARAVAN GIRTHING HIS ASS AND PREPARING FOR FLIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "the chamberlet called the castrato and charged him to do accordingly so he replied i hear and i obey and he took his pages with him and went out in search of the stalker till he found him in the rear of the caravan girding his ass and preparing for flight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3954, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0007.flac", "answer": "SHE SAID IT HATH REACHED ME O AUSPICIOUS KING THAT WHEN THE STOKER GIRTHED HIS ASS FOR FLIGHT AND BESPAKE HIMSELF SAYING OH WOULD I KNEW WHAT IS BECOME OF HIM", "subset": "test_other", "task_type": "understanding", "prediction": "she said it hath reached me o auspicious king that when the stalker girded his ass for flight and bespake himself saying o would i knew what is become of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3955, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0010.flac", "answer": "BUT NOW I WILL NOT LEAVE THEE BETWEEN THIS PLACE AND BAGHDAD AND WHAT BETIDETH THY COMRADE SHALL BETIDE THEE", "subset": "test_other", "task_type": "understanding", "prediction": "but now i will not leave thee between this place and baghdad and what betideth thy comrade shall betide thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3956, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0000.flac", "answer": "AND ALSO THESE", "subset": "test_other", "task_type": "understanding", "prediction": "and also these", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3957, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0003.flac", "answer": "AFTER A WHILE THEY CAME TO THEMSELVES AND NUZHAT AL ZAMAN REJOICED WITH EXCEEDING JOY OPPRESSION AND DEPRESSION LEFT HER AND GLADNESS TOOK THE MASTERY OF HER AND SHE REPEATED THESE VERSES", "subset": "test_other", "task_type": "understanding", "prediction": "after a while they came to themselves and usat alzaman rejoiced with exceeding joy oppression and depression left her and gladness took the mastery of her and she repeated these verses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3958, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0005.flac", "answer": "BUT NOW GO TO THY MASTER AND BRING HIM QUICKLY TO ME", "subset": "test_other", "task_type": "understanding", "prediction": "but now go to thy master and bring him quickly to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3959, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0013.flac", "answer": "AND HE ANSWERED I AM THE CHAMBERLAIN OF THE EMIR OF DAMASCUS KING SHARRKAN SON OF OMAR BIN AL NU'UMAN LORD OF BAGHDAD AND OF THE LAND OF KHORASAN AND I BRING TRIBUTE AND PRESENTS FROM HIM TO HIS FATHER IN BAGHDAD", "subset": "test_other", "task_type": "understanding", "prediction": "and he answered i am the chamberlain of the emir of damascus king sharkan son of omar bin al nuuman lord of baghdad and of the land of khorasan and i bring tribute and presents from him to his father in baghdad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3960, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0002.flac", "answer": "WHEN THE EUNUCH SAW THIS CASE HE WONDERED AT THEM AND THROWING OVER THEM SOMEWHAT TO COVER THEM WAITED TILL THEY SHOULD RECOVER", "subset": "test_other", "task_type": "understanding", "prediction": "when the eunuch saw this case he wondered at them and throwing over them somewhat to cover them waited till they should recover", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3961, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0014.flac", "answer": "SO FARE YE FORWARDS NO HARM SHALL BEFAL YOU TILL YOU JOIN HIS GRAND WAZIR DANDAN", "subset": "test_other", "task_type": "understanding", "prediction": "so fare ye forwards no harm shall befall you till you join his grand wazir dandan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3962, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0017.flac", "answer": "AND AMONGST THEM WERE SOME WHO WOULD HAVE CHOSEN THE CADET ZAU AL MAKAN FOR QUOTH THEY HIS NAME BE LIGHT OF THE PLACE AND HE HATH A SISTER NUZHAT AL ZAMAN HIGHS THE DELIGHT OF THE TIME BUT THEY SET OUT FIVE YEARS AGO FOR AL HIJAZ AND NONE WOTTETH WHAT IS BECOME OF THEM", "subset": "test_other", "task_type": "understanding", "prediction": "and amongst them were some who would have chosen the cadet zawa al makan for quoth they his name belighteth the place and he hath a sister nuzhat al zaman hies the delight of the time but they set out five years ago for al hijaz and none wotteth what is become of them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3963, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0009.flac", "answer": "WHY DIDST THOU SAY I NEVER REPEATED THESE COUPLETS NOR DO I KNOW WHO REPEATED THEM WHEN IT WAS THY COMPANION", "subset": "test_other", "task_type": "understanding", "prediction": "why didst thou say i never repeated these couplets nor do i know who repeated them when it was thy companion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3964, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0011.flac", "answer": "TWAS AS I FEARED THE COMING ILLS DISCERNING BUT UNTO ALLAH WE ARE ALL RETURNING", "subset": "test_other", "task_type": "understanding", "prediction": "twas as i feared the khamineel s discerning but unto allah we are all returning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3965, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0016.flac", "answer": "SO IT WAS AGREED THAT WE GO TO DAMASCUS AND FETCH THENCE THE KING'S SON SHARRKAN AND MAKE HIM SULTAN OVER HIS FATHER'S REALM", "subset": "test_other", "task_type": "understanding", "prediction": "so it was agreed that we go to damascus and fetch thence the king s son sharkan and make him sultan over his father s realm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3966, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0004.flac", "answer": "ACCORDINGLY SHE TOLD HIM ALL THAT HAD COME TO HER SINCE THEIR SEPARATION AT THE KHAN AND WHAT HAD HAPPENED TO HER WITH THE BADAWI HOW THE MERCHANT HAD BOUGHT HER OF HIM AND HAD TAKEN HER TO HER BROTHER SHARRKAN AND HAD SOLD HER TO HIM HOW HE HAD FREED HER AT THE TIME OF BUYING HOW HE HAD MADE A MARRIAGE CONTRACT WITH HER AND HAD GONE IN TO HER AND HOW THE KING THEIR SIRE HAD SENT AND ASKED FOR HER FROM SHARRKAN", "subset": "test_other", "task_type": "understanding", "prediction": "accordingly she told him all that had come to her since their separation at the khan and what had happened to her with the badawi how the merchant had bought her of him and had taken her to her brother sharkan and had sold her to him how he had freed her at the time of buying how he had made a marriage contract with her and had gone in to her and how the king their sire had sent and asked for her from sharkan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3967, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0015.flac", "answer": "THEN HE BADE HIM BE SEATED AND QUESTIONED HIM AND HE REPLIED THAT HE WAS CHAMBERLAIN TO THE EMIR OF DAMASCUS AND WAS BOUND TO KING OMAR WITH PRESENTS AND THE TRIBUTE OF SYRIA", "subset": "test_other", "task_type": "understanding", "prediction": "then he bade him be seated and questioned him and he replied that he was chamberlain to the emir of damascus and was bound to king omar with presents and the tribute of syria", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3968, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164915/2033-164915-0012.flac", "answer": "THEN THE EUNUCH CRIED UPON THE PAGES SAYING TAKE HIM OFF THE ASS", "subset": "test_other", "task_type": "understanding", "prediction": "then the eunuch cried upon the pages saying take him off the ass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3969, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0021.flac", "answer": "WE WILL DO THEE NO UPRIGHT O MY SON NOR WRONG THEE IN AUGHT BUT OUR OBJECT IS THAT THOU BEND THY GRACIOUS STEPS WITH ME TO MY MISTRESS TO RECEIVE HER ANSWER AND RETURN IN WEAL AND SAFETY AND THOU SHALT HAVE A HANDSOME PRESENT AS ONE WHO BRINGETH GOOD NEWS", "subset": "test_other", "task_type": "understanding", "prediction": "we will do thee no upright o my son nor wrong thee in aught but our object is that thou bend thy gracious steps with me to my mistress to receive her answer and return in weal and safety and thou shalt have a handsome present as one who bringeth good news", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3970, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0022.flac", "answer": "THEN THE EUNUCH WENT OUT TO ZAU AL MAKAN AND SAID TO HIM RECITE WHAT VERSES THOU KNOWEST FOR MY LADY IS HERE HARD BY LISTENING TO THEE AND AFTER I WILL ASK THEE OF THY NAME AND THY NATIVE COUNTRY AND THY CONDITION", "subset": "test_other", "task_type": "understanding", "prediction": "then the eunuch went out to zau al makan and said to him recite what verses thou knowest for my lady is here hard by listening to thee and after i will ask thee of thy name and thy native country and thy condition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3971, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0001.flac", "answer": "BUT SHE SAID WHOMSOEVER THOU SEEST AWAKE HE IS THE RECITER", "subset": "test_other", "task_type": "understanding", "prediction": "but she said whomsoever thou seest awake he is the reciter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3972, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0003.flac", "answer": "REJOINED THE EUNUCH WHO THEN WAS THE RECITER POINT HIM OUT TO ME", "subset": "test_other", "task_type": "understanding", "prediction": "rejoined the eunuch who then was the reciter point him out to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3973, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0000.flac", "answer": "REPLIED HE OF A TRUTH I HEARD HIM NOT AND I WOT HIM NOT AND FOLKS ARE ALL SLEEPING", "subset": "test_other", "task_type": "understanding", "prediction": "replied he of a truth i heard him not and i wot him not and folks are all sleeping", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3974, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0004.flac", "answer": "BY ALLAH REPLIED THE FIREMAN I TELL THEE THE TRUTH", "subset": "test_other", "task_type": "understanding", "prediction": "by allah replied the fireman i tell thee the truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3975, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0011.flac", "answer": "BUT TAKE THESE HUNDRED DINERS AND GIVE THEM TO THE SINGER AND BRING HIM TO ME GENTLY AND DO HIM NO HURT", "subset": "test_other", "task_type": "understanding", "prediction": "but take these hundred diners and give them to the singer and bring him to me gently and do him no hurt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3976, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0018.flac", "answer": "I SAY WHAT MADE MY IGNOMY WHATE'ER THE BITTER CUP I DRAIN FAR BE FRO ME THAT LAND TO FLEE NOR WILL I BOW TO THOSE WHO BLAME AND FOR SUCH LOVE WOULD DEAL ME SHAME", "subset": "test_other", "task_type": "understanding", "prediction": "i say what made my ignomy whatever the bitter cup i drain far be from me thy land to flee nor will i bow to those who blame and for such love would deal me shame", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3977, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0007.flac", "answer": "AND HE ALSO IMPROVISED THE TWO FOLLOWING DISTICHS", "subset": "test_other", "task_type": "understanding", "prediction": "and he also improvised the two following distichs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3978, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0006.flac", "answer": "WHAT AILS THEE THEN THAT THOU MUST NEEDS RECITE VERSES SEEING THAT WE ARE TIRED OUT WITH WALKING AND WATCHING AND ALL THE FOLK ARE ASLEEP FOR THEY REQUIRE SLEEP TO REST THEM OF THEIR FATIGUE", "subset": "test_other", "task_type": "understanding", "prediction": "what ails thee then that thou must needs recite verses seeing that we are tired out with walking and watching and all the folk are asleep for they require sleep to rest them of their fatigue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3979, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0019.flac", "answer": "THEN SAID THE EUNUCH TO ZAU AL MAKAN PEACE BE WITH THEE O MY LORD", "subset": "test_other", "task_type": "understanding", "prediction": "then said the eunuch to zau al makan peace be with thee o my lord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3980, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0012.flac", "answer": "RETURN QUICKLY AND LINGER NOT", "subset": "test_other", "task_type": "understanding", "prediction": "return quickly and linger not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3981, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0009.flac", "answer": "HE WHO RECITED THE FIRST TIME HATH RECITED A SECOND TIME AND I HEARD HIM HARD BY", "subset": "test_other", "task_type": "understanding", "prediction": "he who recited the first time hath recited the second time and i heard him hard by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3982, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0005.flac", "answer": "TELL ME WHAT HAPPENED QUOTH ZAU AL MAKAN", "subset": "test_other", "task_type": "understanding", "prediction": "tell me what happened what zawa makaan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3983, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0020.flac", "answer": "O MY LORD CONTINUED THE EUNUCH AND SHAHRAZAD PERCEIVED THE DAWN OF DAY AND CEASED TO SAY HER PERMITTED SAY", "subset": "test_other", "task_type": "understanding", "prediction": "o my lord continued the eunuch and shahrazad perceived the dawn of day and ceased to say her permitted say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3984, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0017.flac", "answer": "THEN HE KISSED THE EUNUCH'S HEAD AND SPAKE HIM FAIR TILL HE WENT AWAY BUT THE CASTRATO FETCHED A ROUND AND RETURNING SECRETLY CAME AND STOOD BEHIND THE FIREMAN FEARING TO GO BACK TO HIS MISTRESS WITHOUT TIDINGS", "subset": "test_other", "task_type": "understanding", "prediction": "then he kissed the eunuchs head and spake him fair till he went away but the castrato fetched a round and returning secretly came and stood behind the fireman fearing to go back to his mistress without tidings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3985, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0015.flac", "answer": "NOW WHEN THE FIREMAN HEARD THESE WORDS HE FEARED FOR ZAU AL MAKAN AND WEPT WITH EXCEEDING WEEPING AND SAID TO THE EUNUCH BY ALLAH IT WAS NOT I AND I KNOW HIM NOT", "subset": "test_other", "task_type": "understanding", "prediction": "now when the fireman heard these words he feared for zau al makan and wept with exceeding weeping and said to the eunuch by allah it was not i and i know him not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3986, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0013.flac", "answer": "WHEN IT WAS THE SEVENTY THIRD NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "when it was the seventy third night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3987, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0002.flac", "answer": "THEN SAID THE EUNUCH ART THOU HE WHO REPEATED POETRY BUT NOW AND MY LADY HEARD HIM", "subset": "test_other", "task_type": "understanding", "prediction": "then said the eunuch art thou he who repeated poetry but now and my lady heard him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3988, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0008.flac", "answer": "WHEN NUZHAT AL ZAMAN HEARD THE FIRST IMPROVISATION SHE CALLED TO MIND HER FATHER AND HER MOTHER AND HER BROTHER AND THEIR WHILOME HOME THEN SHE WEPT AND CRIED AT THE EUNUCH AND SAID TO HIM WOE TO THEE", "subset": "test_other", "task_type": "understanding", "prediction": "when nusaybah al zaman heard the first improvisation she called to mind her father and her mother and her brother and their willom home then she wept and cried to the eunuch and said to him woe to thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3989, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0010.flac", "answer": "BY ALLAH AN THOU FETCH HIM NOT TO ME I WILL ASSUREDLY ROUSE THE CHAMBERLAIN ON THEE AND HE SHALL BEAT THEE AND CAST THEE OUT", "subset": "test_other", "task_type": "understanding", "prediction": "by allah an thou fetch him not to me i will assuredly rouse the chamberlain on thee and he shall beat thee and cast thee out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3990, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0016.flac", "answer": "SO GO THOU TO THY STATION AND IF THOU AGAIN MEET ANY ONE AFTER THIS HOUR RECITING AUGHT OF POETRY WHETHER HE BE NEAR OR FAR IT WILL BE I OR SOME ONE I KNOW AND THOU SHALT NOT LEARN OF HIM BUT BY ME", "subset": "test_other", "task_type": "understanding", "prediction": "so go thou to thy station and if thou again meet any one after this hour reciting aught of poetry whether he be near or far it will be i or some one i know and thou shalt not learn of him but by me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3991, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164914/2033-164914-0014.flac", "answer": "BUT THE EUNUCH SAID I WILL NOT LEAVE THEE TILL THOU SHOW ME WHO IT WAS THAT RECITED THE VERSES FOR I DREAD RETURNING TO MY LADY WITHOUT HIM", "subset": "test_other", "task_type": "understanding", "prediction": "but the eunuch said i will not leave thee till thou show me who it was that recited the verses for i dread returning to my lady without him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3992, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0009.flac", "answer": "MOREOVER THE SULTAN COMMANDED HIS WAZIR DANDAN CALL A TEN DAYS HALT OF THE ARMY THAT HE MIGHT BE PRIVATE WITH HIM AND LEARN FROM HIM HOW AND WHEREFORE HIS FATHER HAD BEEN SLAIN", "subset": "test_other", "task_type": "understanding", "prediction": "moreover the sultan commanded his wazir dandan call a ten days halt of the army that he might be private with him and learn from him how and wherefore his father had been slain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3993, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0002.flac", "answer": "WHEN THE MINISTER HEARD THESE WORDS HE REJOICED WITH GREAT JOY AND SAID O CHAMBERLAIN TELL ME THE TALE OF THE TWAIN AND WHAT BEFEL THEM AND THE CAUSE OF THEIR LONG ABSENCE", "subset": "test_other", "task_type": "understanding", "prediction": "when the minister heard these words he rejoiced with great joy and said o chamberlain tell me the tale of the twain and what befell them and the cause of their long absence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3994, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0003.flac", "answer": "ZAU AL MAKAN BOWED HIS HEAD AWHILE AND THEN SAID I ACCEPT THIS POSITION FOR INDEED THERE WAS NO REFUSING AND HE WAS CERTIFIED THAT THE CHAMBERLAIN HAD COUNSELLED HIM WELL AND WISELY AND SET HIM ON THE RIGHT WAY", "subset": "test_other", "task_type": "understanding", "prediction": "zawarmakan bowed his head awhile and then said i accept the position for indeed there was no refusing and he was certified that the chamberlain had counselled him well and wisely and set him on the right way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3995, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0008.flac", "answer": "LASTLY THE MINISTER WENT IN AND KISSED THE GROUND BEFORE ZAU AL MAKAN WHO ROSE TO MEET HIM SAYING WELCOME O WAZIR AND SIRE SANS PEER", "subset": "test_other", "task_type": "understanding", "prediction": "lastly the minister went in and kissed the ground before zau al makan who rose to meet him saying welcome o wazir and sire sans peer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3996, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0006.flac", "answer": "WHEN IT WAS THE SEVENTY EIGHTH NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "when it was the seventy eighth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3997, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0005.flac", "answer": "AFTER AWHILE THE DUST DISPERSED AND THERE APPEARED UNDER IT THE ARMY OF BAGHDAD AND KHORASAN A CONQUERING HOST LIKE THE FULL TIDE SEA AND SHAHRAZAD PERCEIVED THE DAWN OF DAY AND CEASED TO SAY HER PERMITTED SAY", "subset": "test_other", "task_type": "understanding", "prediction": "after a while the dust dispersed and there appeared under it the army of baghdad and khorasan a conquering host like the full tide sea and shahrazad perceived the dawn of day and ceased to say her permitted say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3998, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0010.flac", "answer": "HE THEN REPAIRED TO THE HEART OF THE ENCAMPMENT AND ORDERED THE HOST TO HALT TEN DAYS", "subset": "test_other", "task_type": "understanding", "prediction": "he then repaired to the heart of the encampment and ordered the host to halt ten days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3999, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0000.flac", "answer": "SO HE TURNED TO THE WAZIR DANDAN AND SAID TO HIM VERILY YOUR TALE IS A WONDER OF WONDERS", "subset": "test_other", "task_type": "understanding", "prediction": "so he turned to the wazir dundan and said to him verily your tale is a wonder of wonders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4000, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0007.flac", "answer": "AND IN IT ALL REJOICED AT THE ACCESSION OF THE LIGHT OF THE PLACE", "subset": "test_other", "task_type": "understanding", "prediction": "and in it all rejoiced at the accession of the light of the place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4001, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0001.flac", "answer": "KNOW O CHIEF WAZIR THAT HERE WHERE YOU HAVE ENCOUNTERED ME ALLAH HATH GIVEN YOU REST FROM FATIGUE AND BRINGETH YOU YOUR DESIRE AFTER THE EASIEST OF FASHIONS FOR THAT HIS ALMIGHTY WILL RESTORETH TO YOU ZAU AL MAKAN AND HIS SISTER NUZHAT AL ZAMAN WHEREBY WE WILL SETTLE THE MATTER AS WE EASILY CAN", "subset": "test_other", "task_type": "understanding", "prediction": "know o chief wazir that here where you have encountered me allah hath given you rest from fatigue and bringeth you your desire after the easiest of fashions for that his almighty will restoreth to you zau al makan and his sister nuzhat al zaman whereby we will settle the matter as we easily can", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4002, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2033/164916/2033-164916-0004.flac", "answer": "THEN HE ADDED O MY UNCLE HOW SHALL I DO WITH MY BROTHER SHARRKAN", "subset": "test_other", "task_type": "understanding", "prediction": "then he added o my uncle how shall i do with my brother sharkan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4003, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0014.flac", "answer": "POLLY FELT A VERY CORDIAL FRIENDSHIP FOR MISTER SYDNEY BUT NOT ONE PARTICLE OF THE LOVE WHICH IS THE ONLY COIN IN WHICH LOVE CAN BE TRULY PAID", "subset": "test_other", "task_type": "understanding", "prediction": "polly felt a very cordial friendship for mr sydney but not one particle of the love which is the only coin in which love can be truly paid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4004, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0037.flac", "answer": "NOW DON'T BE AFFECTED POLLY BUT JUST TELL ME LIKE A DEAR HAS N'T HE PROPOSED", "subset": "test_other", "task_type": "understanding", "prediction": "now dont be affected polly but just tell me like a dear has not he proposed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4005, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0001.flac", "answer": "THE MORE PROPOSALS THE MORE CREDIT", "subset": "test_other", "task_type": "understanding", "prediction": "the more proposals the more credit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4006, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0009.flac", "answer": "I DON'T THINK IT WAS HIS WEALTH ACCOMPLISHMENTS OR POSITION THAT MOST ATTRACTED POLLY THOUGH THESE DOUBTLESS POSSESSED A GREATER INFLUENCE THAN SHE SUSPECTED", "subset": "test_other", "task_type": "understanding", "prediction": "i do not think it was his wealth accomplishments or position that most attracted polly though these doubtless possessed a greater influence than she suspected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4007, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0020.flac", "answer": "HOW HE GOT THERE WAS NEVER VERY CLEAR TO POLLY BUT THERE HE WAS FLUSHED AND A LITTLE OUT OF BREATH BUT LOOKING SO GLAD TO SEE HER THAT SHE HAD N'T THE HEART TO BE STIFF AND COOL AS SHE HAD FULLY INTENDED TO BE WHEN THEY MET", "subset": "test_other", "task_type": "understanding", "prediction": "how he got there was never very clear to polly but there he was flushed and a little out of breath but looking so glad to see her that she had not the heart to be stiff and cool as she had fully intended to be when they met", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4008, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0041.flac", "answer": "WELL I ALWAYS MEANT TO TRY IT IF I GOT A CHANCE AND I HAVE", "subset": "test_other", "task_type": "understanding", "prediction": "well i always meant to try it if i got a chance and i have", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4009, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0002.flac", "answer": "I VE TRIED IT AND LIKED IT AND MAYBE THIS IS THE CONSEQUENCE OF THAT NIGHT'S FUN", "subset": "test_other", "task_type": "understanding", "prediction": "i have tried it and liked it and maybe this is the consequence of that night s fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4010, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0016.flac", "answer": "WHEN SATURDAY CAME POLLY STARTED AS USUAL FOR A VISIT TO BECKY AND BESS BUT COULD N'T RESIST STOPPING AT THE SHAWS TO LEAVE A LITTLE PARCEL FOR FAN THOUGH IT WAS CALLING TIME", "subset": "test_other", "task_type": "understanding", "prediction": "when saturday came polly started as usual for a visit to backy and bess but could not resist stopping at the shaws to leave a little parcel for fan though it was calling time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4011, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0012.flac", "answer": "LATELY THIS HAD CHANGED ESPECIALLY TOWARDS POLLY AND IT FLATTERED HER MORE THAN SHE WOULD CONFESS EVEN TO HERSELF", "subset": "test_other", "task_type": "understanding", "prediction": "lately this had changed especially towards polly and it flattered her more than she would confess even to herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4012, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0033.flac", "answer": "WAGGING TO AND FRO AS USUAL WHAT'S THE NEWS WITH YOU", "subset": "test_other", "task_type": "understanding", "prediction": "walking to and fro as usual what is the news with you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4013, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0023.flac", "answer": "SHE DID NOT MEAN TO TELL BUT HIS FRANKNESS WAS SO AGREEABLE SHE FORGOT HERSELF", "subset": "test_other", "task_type": "understanding", "prediction": "she did not mean to tell but his frankness was so agreeable she forgot herself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4014, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0034.flac", "answer": "PERHAPS SHE LL JILT HIM", "subset": "test_other", "task_type": "understanding", "prediction": "perhaps she chilled him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4015, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0045.flac", "answer": "BUT POLLY IT WOULD HAVE BEEN A GRAND THING FOR YOU", "subset": "test_other", "task_type": "understanding", "prediction": "but polly it would have been a grand thing for you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4016, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0027.flac", "answer": "ASKED THE ARTFUL YOUNG MAN LAYING A TRAP INTO WHICH POLLY IMMEDIATELY FELL", "subset": "test_other", "task_type": "understanding", "prediction": "asked the artful young man laying a trap into which polly immediately fell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4017, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0013.flac", "answer": "AT FIRST SHE TRIED TO THINK SHE COULD BUT UNFORTUNATELY HEARTS ARE SO CONTRARY THAT THEY WON'T BE OBEDIENT TO REASON WILL OR EVEN GRATITUDE", "subset": "test_other", "task_type": "understanding", "prediction": "at first she tried to think she could but unfortunately hearts are so contrary that they won t be obedient to reason will or even gratitude", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4018, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0018.flac", "answer": "TAKE HOLD OF MASTER CHARLEY'S HAND MISS MAMIE AND WALK PRETTY LIKE WILLY AND FLOSSY SAID THE MAID", "subset": "test_other", "task_type": "understanding", "prediction": "take hold of massa charley s hand miss mamie and walk pretty like willie and flossy said the maid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4019, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0024.flac", "answer": "BUT I KNOW HER BETTER AND I ASSURE YOU THAT SHE DOES IMPROVE SHE TRIES TO MEND HER FAULTS THOUGH SHE WON'T OWN IT AND WILL SURPRISE YOU SOME DAY BY THE AMOUNT OF HEART AND SENSE AND GOODNESS SHE HAS GOT", "subset": "test_other", "task_type": "understanding", "prediction": "but i know her better and i assure you that she does improve she tries to mend her faults though she won t own it and will surprise you some day by the amount of heart and sense and goodness she has got", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4020, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0039.flac", "answer": "TRULY TRULY FAN", "subset": "test_other", "task_type": "understanding", "prediction": "truly truly fan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4021, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0006.flac", "answer": "LET ME SEE HOW CAN I BEGIN", "subset": "test_other", "task_type": "understanding", "prediction": "let me see how can i begin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4022, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0010.flac", "answer": "IT WAS THAT INDESCRIBABLE SOMETHING WHICH WOMEN ARE QUICK TO SEE AND FEEL IN MEN WHO HAVE BEEN BLESSED WITH WISE AND GOOD MOTHERS", "subset": "test_other", "task_type": "understanding", "prediction": "it was that indescribable something which women are quick to see and feel in men who have been blessed with wise and good mothers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4023, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0017.flac", "answer": "A FOOLISH LITTLE SPEECH TO MAKE TO A DOG BUT YOU SEE POLLY WAS ONLY A TENDER HEARTED GIRL TRYING TO DO HER DUTY", "subset": "test_other", "task_type": "understanding", "prediction": "a foolish little speech to make to a dog but you see polly was only a tender hearted girl trying to do her duty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4024, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0011.flac", "answer": "THIS HAD AN ESPECIAL CHARM TO POLLY FOR SHE SOON FOUND THAT THIS SIDE OF HIS CHARACTER WAS NOT SHOWN TO EVERY ONE", "subset": "test_other", "task_type": "understanding", "prediction": "this had an especial charm to polly for she soon found that this side of his character was not shown to every one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4025, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0042.flac", "answer": "I JUST GAVE HIM A HINT AND HE TOOK IT", "subset": "test_other", "task_type": "understanding", "prediction": "i just gave him a hint and he took it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4026, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0038.flac", "answer": "DON'T YOU THINK HE MEANS TO", "subset": "test_other", "task_type": "understanding", "prediction": "dont you think he means to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4027, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0005.flac", "answer": "I COULD DO SO MUCH FOR ALL AT HOME HOW I SHOULD ENJOY THAT", "subset": "test_other", "task_type": "understanding", "prediction": "i could do so much for all at home how i should enjoy that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4028, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0031.flac", "answer": "HE WAS GONE BEFORE SHE COULD DO ANYTHING BUT LOOK UP AT HIM WITH A REMORSEFUL FACE AND SHE WALKED ON FEELING THAT THE FIRST AND PERHAPS THE ONLY LOVER SHE WOULD EVER HAVE HAD READ HIS ANSWER AND ACCEPTED IT IN SILENCE", "subset": "test_other", "task_type": "understanding", "prediction": "he was gone before she could do anything but look up at him with a remorseful face and she walked on feeling that the first and perhaps the only lover she would ever have had read his answer and accepted it in silence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4029, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0043.flac", "answer": "HE MEANT TO GO AWAY BEFORE THAT SO DON'T THINK HIS HEART IS BROKEN OR MIND WHAT SILLY TATTLERS SAY", "subset": "test_other", "task_type": "understanding", "prediction": "he meant to go away before that so don think his heart is broken or mind what silly tattlers say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4030, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0003.flac", "answer": "JUST SUPPOSE IT IS TRUE THAT HE DOES ASK ME AND I SAY YES", "subset": "test_other", "task_type": "understanding", "prediction": "just suppose it is true that he does ask me and i say yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4031, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0030.flac", "answer": "SHE THOUGHT SHE HAD A GOOD DEAL OF THE COQUETTE IN HER AND I VE NO DOUBT THAT WITH TIME AND TRAINING SHE WOULD HAVE BECOME A VERY DANGEROUS LITTLE PERSON BUT NOW SHE WAS FAR TOO TRANSPARENT AND STRAIGHTFORWARD BY NATURE EVEN TO TELL A WHITE LIE CLEVERLY", "subset": "test_other", "task_type": "understanding", "prediction": "she thought she had a good deal of the coquette in her and i have no doubt that with time and training she would have become a very dangerous little person but now she was far too transparent and straightforward by nature even to tell a white lie cleverly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4032, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0044.flac", "answer": "HE UNDERSTOOD AND BEING A GENTLEMAN MADE NO FUSS", "subset": "test_other", "task_type": "understanding", "prediction": "he understood and being a chandlerman made no fuss", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4033, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0035.flac", "answer": "UTTERLY DONE WITH AND LAID UPON THE SHELF", "subset": "test_other", "task_type": "understanding", "prediction": "utterly done with and laid upon the shelf", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4034, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0025.flac", "answer": "THANK YOU NO", "subset": "test_other", "task_type": "understanding", "prediction": "thank you no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4035, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0040.flac", "answer": "I DON'T MEAN TO BE PRYING BUT I REALLY THOUGHT HE DID", "subset": "test_other", "task_type": "understanding", "prediction": "i dont mean to be prying but i really thought he did", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4036, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0028.flac", "answer": "HE WAS QUICKER TO TAKE A HINT THAN SHE HAD EXPECTED AND BEING BOTH PROUD AND GENEROUS RESOLVED TO SETTLE THE MATTER AT ONCE FOR POLLY'S SAKE AS WELL AS HIS OWN", "subset": "test_other", "task_type": "understanding", "prediction": "he was quicker to take a hint than she had expected and being both proud and generous he sought to settle the matter at once for polly s sake as well as his own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4037, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0019.flac", "answer": "AT A STREET CORNER A BLACK EYED SCHOOL BOY WAS PARTING FROM A ROSY FACED SCHOOL GIRL WHOSE MUSIC ROLL HE WAS RELUCTANTLY SURRENDERING", "subset": "test_other", "task_type": "understanding", "prediction": "at a street corner a black eyed schoolboy was parting from a rosy faced schoolgirl whose music roll he was reluctantly surrendering", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4038, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0008.flac", "answer": "NOW AS POLLY WAS BY NO MEANS A PERFECT CREATURE I AM FREE TO CONFESS THAT THE OLD TEMPTATION ASSAILED HER MORE THAN ONCE THAT WEEK FOR WHEN THE FIRST EXCITEMENT OF THE DODGING REFORM HAD SUBSIDED SHE MISSED THE PLEASANT LITTLE INTERVIEWS THAT USED TO PUT A CERTAIN FLAVOR OF ROMANCE INTO HER DULL HARD WORKING DAYS", "subset": "test_other", "task_type": "understanding", "prediction": "now as polly was by no means a perfect creature i am free to confess that the old temptation assailed her more than once that week for when the first excitement of the duchess reform had subsided she missed the pleasant little interviews that used to put a certain flavor of romance into her dull hard working days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4039, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0029.flac", "answer": "SO WHEN SHE MADE HER LAST BRILLIANT REMARK HE SAID QUIETLY WATCHING HER FACE KEENLY ALL THE WHILE I THOUGHT SO WELL I M GOING OUT OF TOWN ON BUSINESS FOR SEVERAL WEEKS SO YOU CAN ENJOY YOUR LITTLE BIT OF COUNTRY WITHOUT BEING ANNOYED BY ME ANNOYED", "subset": "test_other", "task_type": "understanding", "prediction": "so when she made her last buoyant remark he said quietly watching her face keenly all the while i thought so well i am going out of town on business for several weeks so you can enjoy your little bit of country without being annoyed by me annoyed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4040, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0036.flac", "answer": "MINNIE SAID THE OTHER DAY SHE WISHED SHE WAS A PIGEON SO SHE COULD PADDLE IN THE PUDDLES AND NOT FUSS ABOUT RUBBERS", "subset": "test_other", "task_type": "understanding", "prediction": "minnie said the other day she wished she was a pigeon so she could paddle in the puddles and not fuss about rabbles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4041, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0021.flac", "answer": "SHE REALLY COULD N'T HELP IT IT WAS SO PLEASANT TO SEE HIM AGAIN JUST WHEN SHE WAS FEELING SO LONELY", "subset": "test_other", "task_type": "understanding", "prediction": "she really could not help it it was so pleasant to see him again just when she was feeling so lonely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4042, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0022.flac", "answer": "THAT IS THE WAY I GET TO THE ROTHS ANSWERED POLLY", "subset": "test_other", "task_type": "understanding", "prediction": "that is the way i get to the worse answered polly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4043, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0015.flac", "answer": "THIS FINISHED POLLY'S INDECISION AND AFTER THAT NIGHT SHE NEVER ALLOWED HERSELF TO DWELL UPON THE PLEASANT TEMPTATION WHICH CAME IN A GUISE PARTICULARLY ATTRACTIVE TO A YOUNG GIRL WITH A SPICE OF THE OLD EVE IN HER COMPOSITION", "subset": "test_other", "task_type": "understanding", "prediction": "this finished polly s indecision and after that night she never allowed herself to dwell upon the pleasant temptation which came in a guise particularly attractive to a young girl with the spice of the old eve in her composition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4044, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0004.flac", "answer": "WHAT A SPITEFUL THING I AM", "subset": "test_other", "task_type": "understanding", "prediction": "what a spiteful thing i am", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4045, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0032.flac", "answer": "POLLY DID NOT RETURN TO HER FAVORITE WALK TILL SHE LEARNED FROM MINNIE THAT UNCLE HAD REALLY LEFT TOWN AND THEN SHE FOUND THAT HIS FRIENDLY COMPANY AND CONVERSATION WAS WHAT HAD MADE THE WAY SO PLEASANT AFTER ALL", "subset": "test_other", "task_type": "understanding", "prediction": "parley did not return to her favorite walk till she learned from minnie that uncle had really left town and then she found that his friendly company and conversation was what had made the way so pleasant after all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4046, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0026.flac", "answer": "HOW LOVELY THE PARK LOOKS SHE SAID IN GREAT CONFUSION", "subset": "test_other", "task_type": "understanding", "prediction": "how lovely the park looks she said in great confusion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4047, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0046.flac", "answer": "I M ODD YOU KNOW AND PREFER TO BE AN INDEPENDENT SPINSTER AND TEACH MUSIC ALL MY DAYS", "subset": "test_other", "task_type": "understanding", "prediction": "i am aught you know and prefer to be an independent spinster and teach music all my days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4048, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0000.flac", "answer": "SHE PULLED HER HAIR DOWN TURNED HER SKIRT BACK PUT HER FEET ON THE FENDER AND TOOK PUTTEL INTO HER LAP ALL OF WHICH ARRANGEMENTS SIGNIFIED THAT SOMETHING VERY IMPORTANT HAD GOT TO BE THOUGHT OVER AND SETTLED", "subset": "test_other", "task_type": "understanding", "prediction": "she pulled her hair down turned her skirt back put her feet on the fender and took pottle into her lap all of which arrangements signified that something very important had got to be thought over and settled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4049, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159605/3331-159605-0007.flac", "answer": "HE HAS KNOWN HER ALL HER LIFE AND HAS A GOOD INFLUENCE OVER HER", "subset": "test_other", "task_type": "understanding", "prediction": "he has known her all her life and has a good influence over her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4050, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0000.flac", "answer": "NEVER MIND WHAT THE BUSINESS WAS IT SUFFICES TO SAY THAT IT WAS A GOOD BEGINNING FOR A YOUNG MAN LIKE TOM WHO HAVING BEEN BORN AND BRED IN THE MOST CONSERVATIVE CLASS OF THE MOST CONCEITED CITY IN NEW ENGLAND NEEDED JUST THE HEALTHY HEARTY SOCIAL INFLUENCES OF THE WEST TO WIDEN HIS VIEWS AND MAKE A MAN OF HIM", "subset": "test_other", "task_type": "understanding", "prediction": "never mind what the business was it suffices to say that it was a good beginning for a young man like tom who having been born and bred in the most conservative class of the most conceited city in new england needed just the healthy hearty social influences of the west to widen his views and make a man of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4051, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0020.flac", "answer": "IF FANNY WANTED TO SHOW HIM WHAT SHE COULD DO TOWARD MAKING A PLEASANT HOME SHE CERTAINLY SUCCEEDED BETTER THAN SHE SUSPECTED FOR IN SPITE OF MANY FAILURES AND DISCOURAGEMENTS BEHIND THE SCENES THE LITTLE HOUSE BECAME A MOST ATTRACTIVE PLACE TO MISTER SYDNEY AT LEAST FOR HE WAS MORE THE HOUSE FRIEND THAN EVER AND SEEMED DETERMINED TO PROVE THAT CHANGE OF FORTUNE MADE NO DIFFERENCE TO HIM", "subset": "test_other", "task_type": "understanding", "prediction": "if fanny wanted to show him what she could do toward making a pleasant home she certainly succeeded better than she suspected for in spite of many failures and discouragements behind the scenes the little house became a most attractive place to mr sydney at least for he was more the house friend than ever and seemed determined to prove that change of fortune made no difference to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4052, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0010.flac", "answer": "POOR POLLY WAS SO TAKEN BY SURPRISE THAT SHE HAD NOT A WORD TO SAY", "subset": "test_other", "task_type": "understanding", "prediction": "poor polly was so taken by surprise that she had not a word to say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4053, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0023.flac", "answer": "FOR NED WAS SO ABSORBED IN BUSINESS THAT HE IGNORED THE WHOLE BAILEY QUESTION AND LEFT THEM IN UTTER DARKNESS", "subset": "test_other", "task_type": "understanding", "prediction": "for ned was so absorbed in business that he ignored the whole bailey question and left them in utter darkness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4054, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0017.flac", "answer": "SUPPOSE I SAY A WORD TO TOM JUST INQUIRE AFTER HIS HEART IN A GENERAL WAY YOU KNOW AND GIVE HIM A CHANCE TO TELL ME IF THERE IS ANYTHING TO TELL", "subset": "test_other", "task_type": "understanding", "prediction": "suppose i say a word to tom just inquire after his heart in a general way you know and give him a chance to tell me if there is anything to tell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4055, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0024.flac", "answer": "FANNY CAME WALKING IN UPON HER ONE DAY LOOKING AS IF SHE BROUGHT TIDINGS OF SUCH GREAT JOY THAT SHE HARDLY KNEW HOW TO TELL THEM", "subset": "test_other", "task_type": "understanding", "prediction": "fanny came walking in upon her one day looking as if she bore tidings of such great joy that she hardly knew how to tell them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4056, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0003.flac", "answer": "IF IT HAD NOT BEEN FOR TWO THINGS I FEAR SHE NEVER WOULD HAVE STOOD A SUMMER IN TOWN BUT SYDNEY OFTEN CALLED TILL HIS VACATION CAME AND A VOLUMINOUS CORRESPONDENCE WITH POLLY BEGUILED THE LONG DAYS", "subset": "test_other", "task_type": "understanding", "prediction": "if it had not been for two things i fear she never would have stood a summer in town but sydney often called till his vacation came and a voluminous correspondence with polly beguiled the long days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4057, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0005.flac", "answer": "NO I M ONLY TIRED HAD A GOOD DEAL TO DO LATELY AND THE DULL WEATHER MAKES ME JUST A TRIFLE BLUE", "subset": "test_other", "task_type": "understanding", "prediction": "no i am only tired had a good deal to do lately and the dull weather makes me just a trifle blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4058, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0014.flac", "answer": "IT WAS SO TENDER EARNEST AND DEFIANT THAT FANNY FORGOT THE DEFENCE OF HER OWN LOVER IN ADMIRATION OF POLLY'S LOYALTY TO HERS FOR THIS FAITHFUL ALL ABSORBING LOVE WAS A NEW REVELATION TO FANNY WHO WAS USED TO HEARING HER FRIENDS BOAST OF TWO OR THREE LOVERS A YEAR AND CALCULATE THEIR RESPECTIVE VALUES WITH ALMOST AS MUCH COOLNESS AS THE YOUNG MEN DISCUSSED THE FORTUNES OF THE GIRLS THEY WISHED FOR BUT COULD NOT AFFORD TO MARRY", "subset": "test_other", "task_type": "understanding", "prediction": "it was so tender earnest and defiant that fanny forgot the defence of her own lover in admiration of polly s loyalty to hers for this faithful all absorbing love was a new revelation to fanny who was used to hearing her friends boast of two or three lovers a year and calculate their respective values with almost as much coolness as the young men discussed the fortunes of the girls they wished for but could not afford to marry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4059, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0016.flac", "answer": "SAID FANNY TURNING HOPEFUL ALL AT ONCE", "subset": "test_other", "task_type": "understanding", "prediction": "said fanny turning hopeful all at once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4060, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0001.flac", "answer": "FORTUNATELY EVERY ONE WAS SO BUSY WITH THE NECESSARY PREPARATIONS THAT THERE WAS NO TIME FOR ROMANCE OF ANY SORT AND THE FOUR YOUNG PEOPLE WORKED TOGETHER AS SOBERLY AND SENSIBLY AS IF ALL SORTS OF EMOTIONS WERE NOT BOTTLED UP IN THEIR RESPECTIVE HEARTS", "subset": "test_other", "task_type": "understanding", "prediction": "fortunately every one was so busy with the necessary preparations that there was no time for romance of any sort and the four young people worked together as soberly and sensibly as if all sorts of emotions were not bottled up in their respective hearts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4061, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0012.flac", "answer": "ONCE OR TWICE BUT SORT OF JOKINGLY AND I THOUGHT IT WAS ONLY SOME LITTLE FLIRTATION", "subset": "test_other", "task_type": "understanding", "prediction": "once or twice but sort of jokingly and i thought it was only some little flirtation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4062, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0015.flac", "answer": "I HOPE MARIA BAILEY IS ALL HE THINKS HER SHE ADDED SOFTLY FOR I COULD N'T BEAR TO HAVE HIM DISAPPOINTED AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "i hope maria bailey is all he thinks her she added softly for i could not bear to have him disappointed again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4063, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0025.flac", "answer": "BUT IF WORK BASKETS WERE GIFTED WITH POWERS OF SPEECH THEY COULD TELL STORIES MORE TRUE AND TENDER THAN ANY WE READ", "subset": "test_other", "task_type": "understanding", "prediction": "but if work baskets were gifted with powers of speech they could tell stories more true and tender than any we read", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4064, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0011.flac", "answer": "NONE WERE NEEDED HER TELLTALE FACE ANSWERED FOR HER AS WELL AS THE IMPULSE WHICH MADE HER HIDE HER HEAD IN THE SOFA CUSHION LIKE A FOOLISH OSTRICH WHEN THE HUNTERS ARE AFTER IT", "subset": "test_other", "task_type": "understanding", "prediction": "none were needed her taut red face answered for her as well as the impulse which made her hide her head in the sofa cushion like a foolish ostrich when the hunters are after it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4065, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0004.flac", "answer": "TOM WROTE ONCE A WEEK TO HIS MOTHER BUT THE LETTERS WERE SHORT AND NOT VERY SATISFACTORY FOR MEN NEVER DO TELL THE INTERESTING LITTLE THINGS THAT WOMEN BEST LIKE TO HEAR", "subset": "test_other", "task_type": "understanding", "prediction": "tom wrote once a week to his mother but their letters were short and not very satisfactory for men never do tell the interesting little things that women best like to hear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4066, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0009.flac", "answer": "CRIED POLLY WITH THE HEARTIEST SATISFACTION IN HER VOICE", "subset": "test_other", "task_type": "understanding", "prediction": "cried polly with the heartiest satisfaction in her voice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4067, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0019.flac", "answer": "IT WAS A VERY DIFFERENT WINTER FROM THE LAST FOR BOTH THE GIRLS", "subset": "test_other", "task_type": "understanding", "prediction": "it was a very different winter from the last for both the girls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4068, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0018.flac", "answer": "BEAR IT PEOPLE ALWAYS DO BEAR THINGS SOMEHOW ANSWERED POLLY LOOKING AS IF SENTENCE HAD BEEN PASSED UPON HER", "subset": "test_other", "task_type": "understanding", "prediction": "bear it people always do bear things somehow answered polly looking as if sentence had been passed upon her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4069, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0007.flac", "answer": "I TRY NOT TO DECEIVE MYSELF BUT IT DOES SEEM AS IF THERE WAS A CHANCE OF HAPPINESS FOR ME", "subset": "test_other", "task_type": "understanding", "prediction": "i try not to deceive myself but it does seem as if there was a chance of happiness for me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4070, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0021.flac", "answer": "SHE KEPT MUCH AT HOME WHEN THE DAY'S WORK WAS DONE FINDING IT PLEASANTER TO SIT DREAMING OVER BOOK OR SEWING ALONE THAN TO EXERT HERSELF EVEN TO GO TO THE SHAWS", "subset": "test_other", "task_type": "understanding", "prediction": "she kept much at home when the day s work was done finding it pleasanter to sit dreaming of a book or sewing alone than to exert herself even to go to the shops", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4071, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0022.flac", "answer": "POLLY WAS NOT AT ALL LIKE HERSELF THAT WINTER AND THOSE NEAREST TO HER SAW AND WONDERED AT IT MOST", "subset": "test_other", "task_type": "understanding", "prediction": "polly was not at all like herself that winter and those nearest to her saw and wondered at it most", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4072, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0008.flac", "answer": "THANK HEAVEN FOR THAT", "subset": "test_other", "task_type": "understanding", "prediction": "thank heaven for that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4073, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0013.flac", "answer": "IT WAS SO STUPID OF ME NOT TO GUESS BEFORE", "subset": "test_other", "task_type": "understanding", "prediction": "it was so stupid of me not to guess before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4074, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0006.flac", "answer": "FORGIVE ME POLLY BUT I CAN'T HELP SAYING IT FOR IT IS THERE AND I WANT TO BE AS TRUE TO YOU AS YOU WERE TO ME IF I CAN", "subset": "test_other", "task_type": "understanding", "prediction": "forgive me polly but i can not help saying it for it is there and i want to be as true to you as you were to me if i can", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4075, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3331/159609/3331-159609-0002.flac", "answer": "PITY THAT THE END SHOULD COME SO SOON BUT THE HOUR DID ITS WORK AND WENT ITS WAY LEAVING A CLEARER ATMOSPHERE BEHIND THOUGH THE YOUNG FOLKS DID NOT SEE IT THEN FOR THEIR EYES WERE DIM BECAUSE OF THE PARTINGS THAT MUST BE", "subset": "test_other", "task_type": "understanding", "prediction": "pity that the end should come so soon but the hour did its work and wended its way leaving a clearer atmosphere behind though the young folks did not see it then for their eyes were dim because of the partings that must be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4076, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0002.flac", "answer": "NO UNLESS YOU CAN TELL ME WHEN TO EXPECT HIM HOME", "subset": "test_other", "task_type": "understanding", "prediction": "no unless you can tell me when to expect him home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4077, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0027.flac", "answer": "AFTER THAT THEY WILL REPAIR TO THEIR COUNTRY HOME", "subset": "test_other", "task_type": "understanding", "prediction": "after that they will repair to their country home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4078, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0024.flac", "answer": "MILICENT FLEW TO THANK ME OVERFLOWING WITH GRATITUDE", "subset": "test_other", "task_type": "understanding", "prediction": "millicent flew to thank me overwhelming its gratitude", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4079, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0007.flac", "answer": "NEVER MIND MY PLAIN SPEAKING SAID I IT IS FROM THE BEST OF MOTIVES", "subset": "test_other", "task_type": "understanding", "prediction": "never mind my plain speaking said i it is from the best of motives", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4080, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0022.flac", "answer": "WHERE'S MILICENT", "subset": "test_other", "task_type": "understanding", "prediction": "where is millicent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4081, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0013.flac", "answer": "NOT YEARS FOR SHE'S ONLY FIVE AND TWENTY", "subset": "test_other", "task_type": "understanding", "prediction": "not ears for she is only five and twenty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4082, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0006.flac", "answer": "NO I'D RATHER BE LIKE MYSELF BAD AS I AM", "subset": "test_other", "task_type": "understanding", "prediction": "no i d rather be like myself that as i am", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4083, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0003.flac", "answer": "I CAN'T YOU DON'T WANT HIM DO YOU", "subset": "test_other", "task_type": "understanding", "prediction": "i can t you don t want him do you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4084, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0016.flac", "answer": "HE FOLLOWED ME INTO THE LIBRARY", "subset": "test_other", "task_type": "understanding", "prediction": "he followed me into the library", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4085, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0009.flac", "answer": "OH NO I COULDN'T STAND THAT", "subset": "test_other", "task_type": "understanding", "prediction": "oh no i could understand that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4086, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0023.flac", "answer": "NAY NOT I SAID HE TURNING HER ROUND AND PUSHING HER TOWARDS ME", "subset": "test_other", "task_type": "understanding", "prediction": "nay not i said he turning her round and pushing her towards me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4087, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0018.flac", "answer": "THE FORMER WAS FULL OF TROUBLE AND ANGUISH NOT ACCUSING HIM BUT DEEPLY REGRETTING HIS CONNECTION WITH HIS PROFLIGATE COMPANIONS ABUSING MISTER GRIMSBY AND OTHERS INSINUATING BITTER THINGS AGAINST MISTER HUNTINGDON AND MOST INGENIOUSLY THROWING THE BLAME OF HER HUSBAND'S MISCONDUCT ON TO OTHER MEN'S SHOULDERS", "subset": "test_other", "task_type": "understanding", "prediction": "the former was full of trouble and anguish not accusing him but deeply regretting his connection with his profligate companions abusing mr grimsby and others insinuating bitter things against mr hunt and then and most ingenuously throwing the blame of her husband s misconduct on the other man s shoulders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4088, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0004.flac", "answer": "IT IS A RESOLUTION YOU OUGHT TO HAVE FORMED LONG AGO", "subset": "test_other", "task_type": "understanding", "prediction": "it is a resolution you ought to have formed long ago", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4089, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0025.flac", "answer": "CRIED SHE I COULDN'T HAVE INFLUENCED HIM I'M SURE BY ANYTHING THAT I COULD HAVE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "cried she i could have influenced him i am sure by anything that i could have said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4090, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0020.flac", "answer": "IF YOU INTEND TO REFORM INVOKE GOD'S BLESSING HIS MERCY AND HIS AID NOT HIS CURSE", "subset": "test_other", "task_type": "understanding", "prediction": "if you intend to reform invoke god s blessing his mercy and his aid not his curse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4091, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0014.flac", "answer": "WHAT WOULD YOU MAKE OF ME AND THE CHILDREN TO BE SURE THAT WORRY HER TO DEATH BETWEEN THEM", "subset": "test_other", "task_type": "understanding", "prediction": "what should you make of me and the children to be sure that were hurt to death between them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4092, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0010.flac", "answer": "FIRE AND FURY", "subset": "test_other", "task_type": "understanding", "prediction": "fire and fury", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4093, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0021.flac", "answer": "GOD HELP ME THEN FOR I'M SURE I NEED IT", "subset": "test_other", "task_type": "understanding", "prediction": "god help me then for i am sure i need it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4094, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0008.flac", "answer": "BUT TELL ME SHOULD YOU WISH YOUR SONS TO BE LIKE MISTER HUNTINGDON OR EVEN LIKE YOURSELF", "subset": "test_other", "task_type": "understanding", "prediction": "but tell me should you wish your sons to be like mr huntingdon or even like yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4095, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0017.flac", "answer": "I SOUGHT OUT AND PUT INTO HIS HANDS TWO OF MILICENT'S LETTERS ONE DATED FROM LONDON AND WRITTEN DURING ONE OF HIS WILDEST SEASONS OF RECKLESS DISSIPATION THE OTHER IN THE COUNTRY DURING A LUCID INTERVAL", "subset": "test_other", "task_type": "understanding", "prediction": "i sought halton and put into his hands two of millicent s letters one dated from london and written during one of his wildest seasons of reckless dissipation the other in the country during a lucid interval", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4096, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0001.flac", "answer": "MISTER AND MISSUS HATTERSLEY HAVE BEEN STAYING AT THE GROVE A FORTNIGHT AND AS MISTER HARGRAVE IS STILL ABSENT AND THE WEATHER WAS REMARKABLY FINE I NEVER PASSED A DAY WITHOUT SEEING MY TWO FRIENDS MILICENT AND ESTHER EITHER THERE OR HERE", "subset": "test_other", "task_type": "understanding", "prediction": "mr and mrs hattersley have been staying at the grove a fortnight and as mrs hargrave is still absent and the weather was remarkably fine i never passed the day without seeing my two friends millicent and esther either there or here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4097, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0000.flac", "answer": "VAIN HOPE I FEAR", "subset": "test_other", "task_type": "understanding", "prediction": "vain hope i fear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4098, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0026.flac", "answer": "YOU NEVER TRIED ME MILLY SAID HE", "subset": "test_other", "task_type": "understanding", "prediction": "you never tried me merely said he", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4099, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0019.flac", "answer": "I'VE BEEN A CURSED RASCAL GOD KNOWS SAID HE AS HE GAVE IT A HEARTY SQUEEZE BUT YOU SEE IF I DON'T MAKE AMENDS FOR IT D N ME IF I DON'T", "subset": "test_other", "task_type": "understanding", "prediction": "ive been a cursed rascal god knows said he as he gave it a hearty squeeze but you see if i dont make amends for it damn me if i dont", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0015.flac", "answer": "I KNOW THEY ARE BLESS THEM", "subset": "test_other", "task_type": "understanding", "prediction": "i know they are bless them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0012.flac", "answer": "BUT HANG IT THAT'S NOT MY FAULT", "subset": "test_other", "task_type": "understanding", "prediction": "but hang it that is not my fault", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0005.flac", "answer": "WE ALL HAVE A BIT OF A LIKING FOR HIM AT THE BOTTOM OF OUR HEARTS THOUGH WE CAN'T RESPECT HIM", "subset": "test_other", "task_type": "understanding", "prediction": "we all have a bit of a liking for him at the bottom of our hearts though we cant respect him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131564/533-131564-0011.flac", "answer": "NOW DON'T BURST INTO A TEMPEST AT THAT", "subset": "test_other", "task_type": "understanding", "prediction": "now don t force him to a tempest of death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0014.flac", "answer": "I WATCHED HER A FEW MOMENTS WITH A FEELING OF MALEVOLENT GRATIFICATION THEN MOVING TOWARDS THE DOOR I CALMLY ASKED IF SHE HAD ANYTHING MORE TO SAY", "subset": "test_other", "task_type": "understanding", "prediction": "i watched her a few moments with a feeling of malevolent gratification then moving towards the door i calmly asked if she had anything more to say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0007.flac", "answer": "UPON PERUSING THIS SHE TURNED SCARLET AND BIT HER LIP", "subset": "test_other", "task_type": "understanding", "prediction": "upon perusing this she turned scarlet and bit her lip", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0009.flac", "answer": "WILL YOU OBLIGE ME HELEN CONTINUED SHE", "subset": "test_other", "task_type": "understanding", "prediction": "will you oblige me ellen continued she", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0006.flac", "answer": "I AM TOO WELL ACQUAINTED WITH YOUR CHARACTER AND CONDUCT TO FEEL ANY REAL FRIENDSHIP FOR YOU AND AS I AM WITHOUT YOUR TALENT FOR DISSIMULATION I CANNOT ASSUME THE APPEARANCE OF IT", "subset": "test_other", "task_type": "understanding", "prediction": "i am too well acquainted with their character and conduct to feel any real friendship for you and as i am without your talent for dissimulation i cannot assume the appearance of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0003.flac", "answer": "I SOMETIMES THINK I OUGHT TO GIVE HIM CREDIT FOR THE GOOD FEELING HE SIMULATES SO WELL AND THEN AGAIN I THINK IT IS MY DUTY TO SUSPECT HIM UNDER THE PECULIAR CIRCUMSTANCES IN WHICH I AM PLACED", "subset": "test_other", "task_type": "understanding", "prediction": "i sometimes think i ought to give him credit for the good feeling he simulated so well and then again i think it is my duty to suspect him under the peculiar circumstances in which i am placed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0018.flac", "answer": "I CANNOT RENOUNCE WHAT IS DEARER THAN LIFE SHE MUTTERED IN A LOW HURRIED TONE", "subset": "test_other", "task_type": "understanding", "prediction": "i cannot renounce what is dearer than life she muttered in a low hurried tone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0008.flac", "answer": "YOU MAY GO MILICENT AND SHE'LL FOLLOW IN A WHILE MILICENT WENT", "subset": "test_other", "task_type": "understanding", "prediction": "you may go millicent and shell follow in a while millicent went", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0011.flac", "answer": "IF I WERE SUSPICIOUS I REPLIED I SHOULD HAVE DISCOVERED YOUR INFAMY LONG BEFORE", "subset": "test_other", "task_type": "understanding", "prediction": "if i were suspicious i replied i should have discovered your infamy long before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0005.flac", "answer": "THEY HAD BETAKEN THEMSELVES TO THEIR WORK I LESS TO DIVERT MY MIND THAN TO DEPRECATE CONVERSATION HAD PROVIDED MYSELF WITH A BOOK", "subset": "test_other", "task_type": "understanding", "prediction": "they have taken themselves to their work i less to divert my mind than to deprecate conversation have provided myself with a book", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0015.flac", "answer": "YES YES", "subset": "test_other", "task_type": "understanding", "prediction": "yes yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0025.flac", "answer": "HOW DARE YOU MENTION HIS NAME TO ME", "subset": "test_other", "task_type": "understanding", "prediction": "how dare you mention his name to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0000.flac", "answer": "BUT HOW AM I TO GET OVER THE TEN OR TWELVE DAYS THAT MUST YET ELAPSE BEFORE THEY GO", "subset": "test_other", "task_type": "understanding", "prediction": "but how am i to get over the ten or twelve days that must yet elapse before they go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0010.flac", "answer": "AH YOU ARE SUSPICIOUS", "subset": "test_other", "task_type": "understanding", "prediction": "you are suspicious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0019.flac", "answer": "IF YOU ARE GENEROUS HERE IS A FITTING OPPORTUNITY FOR THE EXERCISE OF YOUR MAGNANIMITY IF YOU ARE PROUD HERE AM I YOUR RIVAL READY TO ACKNOWLEDGE MYSELF YOUR DEBTOR FOR AN ACT OF THE MOST NOBLE FORBEARANCE", "subset": "test_other", "task_type": "understanding", "prediction": "if you are generous here is a fitting opportunity for the exercise of your magnanimity if you are proud here am i your rival rather pronounce myself your debtor for an act of the most noble forbearance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0001.flac", "answer": "FOR NONE COULD INJURE ME AS HE HAS DONE OH", "subset": "test_other", "task_type": "understanding", "prediction": "for none could endure me as he has done oh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0023.flac", "answer": "I WOULD NOT FOR MUCH THAT SHE SHOULD KNOW THE INFAMY AND DISGRACE OF HER RELATION", "subset": "test_other", "task_type": "understanding", "prediction": "i would not for much satisfaction know the infamy and disgrace of a relation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0004.flac", "answer": "I HAVE DONE WELL TO RECORD THEM SO MINUTELY", "subset": "test_other", "task_type": "understanding", "prediction": "have done well to record them so minutely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0013.flac", "answer": "SHE COLOURED AGAIN EXCESSIVELY AND REMAINED SILENT PRESSING HER FINGER AGAINST HER TEETH AND GAZING INTO THE FIRE", "subset": "test_other", "task_type": "understanding", "prediction": "she coloured again excessively and remained silent pressing her finger against her teeth and gazing into the fire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0024.flac", "answer": "YOU USE HARD WORDS MISSUS HUNTINGDON BUT I CAN PARDON YOU", "subset": "test_other", "task_type": "understanding", "prediction": "you use hard words mrs huntingdon but i can pardon you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0016.flac", "answer": "SUPPOSE I DO", "subset": "test_other", "task_type": "understanding", "prediction": "suppose i do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0020.flac", "answer": "I SHALL NOT TELL HIM", "subset": "test_other", "task_type": "understanding", "prediction": "i shall not tell him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0017.flac", "answer": "SHE PAUSED IN EVIDENT DISCONCERTION AND PERPLEXITY MINGLED WITH ANGER SHE DARED NOT SHOW", "subset": "test_other", "task_type": "understanding", "prediction": "she paused in evident disconcertion and perplexity mingled with anger she dared not show", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0002.flac", "answer": "THE WORD STARES ME IN THE FACE LIKE A GUILTY CONFESSION BUT IT IS TRUE I HATE HIM I HATE HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the word stares me in the face like a guilty confession but it is true i hate him i hate him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0021.flac", "answer": "GIVE ME NO THANKS IT IS NOT FOR YOUR SAKE THAT I REFRAIN", "subset": "test_other", "task_type": "understanding", "prediction": "give me no thanks it is not for your sake that i refrain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0012.flac", "answer": "I ENJOY A MOONLIGHT RAMBLE AS WELL AS YOU I ANSWERED STEADILY FIXING MY EYES UPON HER AND THE SHRUBBERY HAPPENS TO BE ONE OF MY FAVOURITE RESORTS", "subset": "test_other", "task_type": "understanding", "prediction": "i enjoy a moonlight ramble as well as you i answered steadily fixing my eyes upon her and the fruaries happens to be one of my favorite resorts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131556/533-131556-0022.flac", "answer": "AND MILICENT WILL YOU TELL HER", "subset": "test_other", "task_type": "understanding", "prediction": "and millicent will you tell her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0024.flac", "answer": "I HELD ON TO HIM FRANTICALLY AND SOMEHOW I GOT THERE AND LOOKED DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "i held on to him frantically and somehow i got there and looked down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0010.flac", "answer": "PUT ON HEAVY SHOES AND SOME OLD DARK CLOTHES AND MAKE UP YOUR MIND NOT TO BE SURPRISED AT ANYTHING", "subset": "test_other", "task_type": "understanding", "prediction": "put on heavy shoes and some old dark clothes and make up your mind not to be surprised at anything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0011.flac", "answer": "LIDDY WAS SLEEPING THE SLEEP OF THE JUST WHEN I WENT UP STAIRS AND I HUNTED OUT MY THINGS CAUTIOUSLY", "subset": "test_other", "task_type": "understanding", "prediction": "lily was sleeping asleep with a just when i went upstairs and i hunted out my things cautiously", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0003.flac", "answer": "FORTUNATELY WARNER AND THE DETECTIVES WERE KEEPING BACHELOR HALL IN THE LODGE", "subset": "test_other", "task_type": "understanding", "prediction": "fortunately warren and the detective were keeping bachelor hall in lodge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0008.flac", "answer": "THE MOST UNUSUAL THING I CAN THINK OF WOULD BE A PEACEFUL NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "the most unusual thing i can think of would be a peaceful night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0015.flac", "answer": "ONCE ONLY SOMEBODY SPOKE AND THEN IT WAS AN EMPHATIC BIT OF PROFANITY FROM DOCTOR STEWART WHEN HE RAN INTO A WIRE FENCE", "subset": "test_other", "task_type": "understanding", "prediction": "once only somebody spoke and then it was an emphatic bit of profanity from dr stewart when he ran into a wire fence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0016.flac", "answer": "I HARDLY KNOW WHAT I EXPECTED", "subset": "test_other", "task_type": "understanding", "prediction": "i hardly know what i expected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0020.flac", "answer": "IT WAS ALEX ARMED WITH TWO LONG HANDLED SPADES", "subset": "test_other", "task_type": "understanding", "prediction": "it was alex armed with two long handled spades", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0023.flac", "answer": "A DOCTOR IS GENERALLY SUPPOSED TO BE HANDIER AT BURYING FOLKS THAN AT DIGGING THEM UP", "subset": "test_other", "task_type": "understanding", "prediction": "a doctor is generally supposed to be a handier at burying folks than at digging them up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0004.flac", "answer": "OUT OF DEFERENCE TO LIDDY THEY WASHED THEIR DISHES ONCE A DAY AND THEY CONCOCTED QUEER MESSES ACCORDING TO THEIR SEVERAL ABILITIES", "subset": "test_other", "task_type": "understanding", "prediction": "out of deference to leddy they washed her dishes once a day and they concocted queer messes according to their several abilities", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0007.flac", "answer": "I MEAN HE PERSISTED DO YOU FEEL AS THOUGH YOU COULD GO THROUGH WITH SOMETHING RATHER UNUSUAL", "subset": "test_other", "task_type": "understanding", "prediction": "i mean he persisted do you feel as though you could go through with something rather unusual", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0012.flac", "answer": "THEY WERE TALKING CONFIDENTIALLY TOGETHER BUT WHEN I CAME DOWN THEY CEASED", "subset": "test_other", "task_type": "understanding", "prediction": "they were talking confidentially together but when i came down they ceased", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0002.flac", "answer": "I AM SURE I KISSED LIDDY AND I HAVE HAD TERRIBLE MOMENTS SINCE WHEN I SEEM TO REMEMBER KISSING MISTER JAMIESON TOO IN THE EXCITEMENT", "subset": "test_other", "task_type": "understanding", "prediction": "i am sure i kissed leddy and i have had terrible moments since when i seemed to remember kissing mr jameson too with the excitement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0022.flac", "answer": "THERE'S ONE THING SURE I'LL NOT BE SUSPECTED OF COMPLICITY", "subset": "test_other", "task_type": "understanding", "prediction": "there is one thing sure i will not be suspected of complicity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0019.flac", "answer": "IN SPITE OF MYSELF I DREW MY BREATH IN SHARPLY", "subset": "test_other", "task_type": "understanding", "prediction": "in spite of myself i drew my breath in sharply", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0006.flac", "answer": "I HAVE NONE I SAID HAPPILY", "subset": "test_other", "task_type": "understanding", "prediction": "i have none i said happily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0005.flac", "answer": "MISS INNES HE SAID STOPPING ME AS I WAS ABOUT TO GO TO MY ROOM UP STAIRS HOW ARE YOUR NERVES TONIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "miss eames he said stopping me as i was about to go to my room upstairs how are your nerves to night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0021.flac", "answer": "THE DOCTOR KEPT A KEEN LOOKOUT BUT NO ONE APPEARED", "subset": "test_other", "task_type": "understanding", "prediction": "the doctor kept a keen lookout but no one appeared", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0018.flac", "answer": "I CONFESS THAT JUST AT THAT MINUTE EVEN SUNNYSIDE SEEMED A CHEERFUL SPOT", "subset": "test_other", "task_type": "understanding", "prediction": "i confess that just at that minute even sunnyside seemed a cheerful spot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0014.flac", "answer": "I ASKED NO QUESTIONS", "subset": "test_other", "task_type": "understanding", "prediction": "i asked no questions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0013.flac", "answer": "THERE WERE A FEW PREPARATIONS TO BE MADE THE LOCKS TO BE GONE OVER WINTERS TO BE INSTRUCTED AS TO RENEWED VIGILANCE AND THEN AFTER EXTINGUISHING THE HALL LIGHT WE CREPT IN THE DARKNESS THROUGH THE FRONT DOOR AND INTO THE NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "there were a few preparations to be made the logs to be gone over winters to be instructed as to renewed vigilance and then after extinguishing the hall light we crept in the darkness through the front door and into the night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0001.flac", "answer": "I KNEW WELL ENOUGH THAT HE MIGHT BE CARRIED THOUSANDS OF MILES IN THE BOX CAR LOCKED IN PERHAPS WITHOUT WATER OR FOOD", "subset": "test_other", "task_type": "understanding", "prediction": "i knew well enough that he might be carried thousands of miles in the box car locked in perhaps without water or food", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0000.flac", "answer": "WHEN CHURCHYARDS YAWN", "subset": "test_other", "task_type": "understanding", "prediction": "when churchyards yawn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0017.flac", "answer": "THE DOCTOR WAS PUFFING SOMEWHAT WHEN WE FINALLY CAME TO A HALT", "subset": "test_other", "task_type": "understanding", "prediction": "the doctor was puffing somewhat when we finally came to a halt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/1066/533-1066-0009.flac", "answer": "SOMETHING IS GOING TO OCCUR HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "something is going to occur he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0004.flac", "answer": "AND PUTTING THE KEYS INTO HIS POCKET HE WALKED INTO THE LIBRARY", "subset": "test_other", "task_type": "understanding", "prediction": "and putting the keys into his pocket he walked into the library", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0014.flac", "answer": "HERE BENSON ENTERED WITH THE CANDLES AND THERE FOLLOWED A BRIEF INTERVAL OF SILENCE I SITTING STILL IN MY CHAIR AND HE STANDING WITH HIS BACK TO THE FIRE SILENTLY TRIUMPHING IN MY DESPAIR", "subset": "test_other", "task_type": "understanding", "prediction": "here benson entered with candles and there followed the brief interval of silence i sitting still in my chair and he standing with his back to the fire silently triumphing in my despair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0011.flac", "answer": "WHAT GREAT DISCOVERY HAVE YOU MADE NOW MISTER HUNTINGDON", "subset": "test_other", "task_type": "understanding", "prediction": "what great discovery have you made now mister hantinen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0006.flac", "answer": "MISTER HUNTINGDON THEN WENT UP STAIRS", "subset": "test_other", "task_type": "understanding", "prediction": "mister huntington then went upstairs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0010.flac", "answer": "AND AS FOR THE HOUSEHOLD MATTERS MISSUS GREAVES MUST BE VERY PARTICULAR IN KEEPING HER ACCOUNTS WE MUST GO UPON AN ENTIRELY NEW PLAN", "subset": "test_other", "task_type": "understanding", "prediction": "and as for the household matters mrs gribbs must be very particular in keeping her accounts we must go upon an entirely new plan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0000.flac", "answer": "IT SEEMS VERY INTERESTING LOVE SAID HE LIFTING HIS HEAD AND TURNING TO WHERE I STOOD WRINGING MY HANDS IN SILENT RAGE AND ANGUISH BUT IT'S RATHER LONG I'LL LOOK AT IT SOME OTHER TIME AND MEANWHILE I'LL TROUBLE YOU FOR YOUR KEYS MY DEAR WHAT KEYS", "subset": "test_other", "task_type": "understanding", "prediction": "it seems very interesting love said he lifting his head and turning to where i stood wringing my hand in silent rage and anguish but it is rather long i will look at it some other time and meanwhile i will trouble you for your keys my dear what keys", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0002.flac", "answer": "THE KEY OF MY DESK IN FACT WAS AT THAT MOMENT IN THE LOCK AND THE OTHERS WERE ATTACHED TO IT", "subset": "test_other", "task_type": "understanding", "prediction": "the key of my desk in fact was at that moment in the lock and the others were attached to it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0016.flac", "answer": "I TRY TO LOOK TO HIM AND RAISE MY HEART TO HEAVEN BUT IT WILL CLEAVE TO THE DUST", "subset": "test_other", "task_type": "understanding", "prediction": "i tried to look to him and raise my heart to heaven but it will cleave to the dust", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0003.flac", "answer": "NOW THEN SNEERED HE WE MUST HAVE A CONFISCATION OF PROPERTY", "subset": "test_other", "task_type": "understanding", "prediction": "now then sneered he we must have a confiscation of property", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0007.flac", "answer": "MUTTERED HE STARTING BACK SHE'S THE VERY DEVIL FOR SPITE", "subset": "test_other", "task_type": "understanding", "prediction": "muttered he starting back she is a very devil for spite", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0009.flac", "answer": "I SHALL PUT YOU UPON A SMALL MONTHLY ALLOWANCE IN FUTURE FOR YOUR OWN PRIVATE EXPENSES AND YOU NEEDN'T TROUBLE YOURSELF ANY MORE ABOUT MY CONCERNS I SHALL LOOK OUT FOR A STEWARD MY DEAR I WON'T EXPOSE YOU TO THE TEMPTATION", "subset": "test_other", "task_type": "understanding", "prediction": "i shall put you upon a small monthly allowance in future for your own private expenses and you needn t trouble yourself any more about my concerns i shall look out for a steward my dear i won t expose you to temptation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0008.flac", "answer": "I DIDN'T SAY I'D BROKEN IT DID I RETURNED HE", "subset": "test_other", "task_type": "understanding", "prediction": "i didn say i had broken it did i returned he", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0015.flac", "answer": "I KNOW THAT DAY AFTER DAY SUCH FEELINGS WILL RETURN UPON ME", "subset": "test_other", "task_type": "understanding", "prediction": "i know that day after day such feelings will return upon me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0012.flac", "answer": "HAVE I ATTEMPTED TO DEFRAUD YOU", "subset": "test_other", "task_type": "understanding", "prediction": "have i attempted to defraud you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0005.flac", "answer": "THAT AND ALL REPLIED THE MASTER AND THE THINGS WERE CLEARED AWAY", "subset": "test_other", "task_type": "understanding", "prediction": "that and all replied messer and the things were cleared away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0001.flac", "answer": "THE KEYS OF YOUR CABINET DESK DRAWERS AND WHATEVER ELSE YOU POSSESS SAID HE RISING AND HOLDING OUT HIS HAND", "subset": "test_other", "task_type": "understanding", "prediction": "the keys of your cabinet desk drawer and whatever else you possess said he rising and holding out his hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/533/131562/533-131562-0013.flac", "answer": "NOT IN MONEY MATTERS EXACTLY IT SEEMS BUT IT'S BEST TO KEEP OUT OF THE WAY OF TEMPTATION", "subset": "test_other", "task_type": "understanding", "prediction": "not in money matters exactly it seems but he is best to keep out of the way of temptation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0003.flac", "answer": "AND THE SCHOOL GIRLS WOULD BEGIN TO LAUGH NOT IN THEIR SLEEVES BUT UNDER THEIR VEILS CHARMING LITTLE STIFLED LAUGHS WHICH MADE THE VOCAL MOTHERS FROWN", "subset": "test_other", "task_type": "understanding", "prediction": "and the schoolgirls would begin to laugh not in their sleeves but under their veils charming little stifled laughs which made the vocal mothers frown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0004.flac", "answer": "IT WAS A CENTURY WHICH SPOKE THROUGH HER BUT IT WAS THE EIGHTEENTH CENTURY", "subset": "test_other", "task_type": "understanding", "prediction": "it was a century which spoke through her but it was the eighteenth century", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0012.flac", "answer": "MORAL LOVE CONQUERED BY THE COLIC", "subset": "test_other", "task_type": "understanding", "prediction": "moral love conquered by the colic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0000.flac", "answer": "SHE HAD EVEN BEEN IN SOCIETY BEFORE THE REVOLUTION", "subset": "test_other", "task_type": "understanding", "prediction": "she had even been in society before the revolution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0002.flac", "answer": "EVERY YEAR SHE SOLEMNLY RENEWED HER VOWS AND AT THE MOMENT OF TAKING THE OATH SHE SAID TO THE PRIEST MONSEIGNEUR SAINT FRANCOIS GAVE IT TO MONSEIGNEUR SAINT JULIEN MONSEIGNEUR SAINT JULIEN GAVE IT TO MONSEIGNEUR SAINT EUSEBIUS MONSEIGNEUR SAINT EUSEBIUS GAVE IT TO MONSEIGNEUR SAINT PROCOPIUS ET CETERA ET CETERA", "subset": "test_other", "task_type": "understanding", "prediction": "every year she solemnly renewed her vows and at the moment of taking the oath she said to the priest monseigneur saint francois gave it to monseigneur saint julien monseigneur saint julien gave it to monseigneur saint eusebius monseigneur saint eusebius gave it to monseigneur saint procopius etc etc", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0007.flac", "answer": "THUS IT FURNISHED A SUBJECT OF COMMENT FOR ALL THOSE WHO WERE UNOCCUPIED OR BORED IN THE CONVENT", "subset": "test_other", "task_type": "understanding", "prediction": "thus it furnished a subject of comment for all those who were unoccupied or bored in the convent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0009.flac", "answer": "THEY LOST THEMSELVES IN CONJECTURES", "subset": "test_other", "task_type": "understanding", "prediction": "they lost themselves in conjectures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0011.flac", "answer": "HE IS RESISTING FLUTTERING HIS TINY WINGS AND STILL MAKING AN EFFORT TO FLY BUT THE DANCER IS LAUGHING WITH A SATANICAL AIR", "subset": "test_other", "task_type": "understanding", "prediction": "he is resisting fluttering his tiny wings and still making an effort to fly but the dancer is laughing with a satanical air", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0008.flac", "answer": "SOME UNIQUE CHAPLET SOME AUTHENTIC RELIC", "subset": "test_other", "task_type": "understanding", "prediction": "some unique chaplet some authentic relic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0001.flac", "answer": "IT WAS HER PLEASURE AND HER VANITY TO DRAG IN THESE NAMES ON EVERY PRETEXT", "subset": "test_other", "task_type": "understanding", "prediction": "it was her pleasure and her vanity to drag in these names on every pretext", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0005.flac", "answer": "THE RULE OF FONTEVRAULT DID NOT FORBID THIS", "subset": "test_other", "task_type": "understanding", "prediction": "the rule of fontevraud did not forbid this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0006.flac", "answer": "SHE WOULD NOT SHOW THIS OBJECT TO ANYONE", "subset": "test_other", "task_type": "understanding", "prediction": "she would not show this object to any one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168656/3528-168656-0010.flac", "answer": "WHEN THE POOR OLD WOMAN DIED THEY RUSHED TO HER CUPBOARD MORE HASTILY THAN WAS FITTING PERHAPS AND OPENED IT", "subset": "test_other", "task_type": "understanding", "prediction": "when the poor old woman died they rushed to her cupboard more hastily than was fitting perhaps and opened it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0077.flac", "answer": "THE WORLD IS NOTHING IN THE PRESENCE OF THE CROSS", "subset": "test_other", "task_type": "understanding", "prediction": "the world is nothing in the presence of the cross", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0100.flac", "answer": "THE OFFICE FOR THE DEAD WILL THEN BE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "the office for the dead will then be set", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0033.flac", "answer": "HEY MORE OFTEN", "subset": "test_other", "task_type": "understanding", "prediction": "hey more often", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0099.flac", "answer": "YOU WILL CLOSE THE COFFIN THE SISTERS WILL CARRY IT TO THE CHAPEL", "subset": "test_other", "task_type": "understanding", "prediction": "you will close the coffin the sisters will carry it to the chapel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0088.flac", "answer": "WE ARE IGNORANT AND IMPIOUS", "subset": "test_other", "task_type": "understanding", "prediction": "we are ignorant and impious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0001.flac", "answer": "WE WILL PRESENT A STENOGRAPHIC REPORT OF THE DIALOGUE WHICH THEN ENSUED TO THE BEST OF OUR ABILITY", "subset": "test_other", "task_type": "understanding", "prediction": "we will present a stenographic report of the dialogue which then ensued to the best of our ability", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0092.flac", "answer": "THEY SHUT THEIR EYES TO THE TRUTH DARKNESS IS THE RULE", "subset": "test_other", "task_type": "understanding", "prediction": "they shut their eyes to the truth darkness is the rule", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0083.flac", "answer": "ON ONE SIDE SAINT BERNARD ON THE OTHER THE AGENT OF THE SANITARY DEPARTMENT", "subset": "test_other", "task_type": "understanding", "prediction": "on one side saint bernard on the other the agent of the sanitary department", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0084.flac", "answer": "GOD SUBORDINATED TO THE COMMISSARY OF POLICE SUCH IS THE AGE SILENCE FAUVENT", "subset": "test_other", "task_type": "understanding", "prediction": "god subordinated to the commissary of police such is the age silence favart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0012.flac", "answer": "AND A WOMAN IS NOT A MAN BUT MY BROTHER IS THE STRONG ONE THOUGH", "subset": "test_other", "task_type": "understanding", "prediction": "and a woman is not a man but my brother is the strong one though", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0118.flac", "answer": "AT ELEVEN O'CLOCK EXACTLY I AM TO BE IN THE CHAPEL", "subset": "test_other", "task_type": "understanding", "prediction": "at eleven o clock exactly i am to be in the chapel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0025.flac", "answer": "YOU KNOW THAT A MOTHER DIED THIS MORNING", "subset": "test_other", "task_type": "understanding", "prediction": "you know that a mother died this morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0056.flac", "answer": "FOR THAT MATTER NO REVEREND MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "for that matter no reverend mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0070.flac", "answer": "BUT IT IS FORBIDDEN", "subset": "test_other", "task_type": "understanding", "prediction": "but it is forbidden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0017.flac", "answer": "WILL THAT BE ALL NO", "subset": "test_other", "task_type": "understanding", "prediction": "will that be all no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0105.flac", "answer": "HAS THE DOCTOR FOR THE DEAD PAID HIS VISIT", "subset": "test_other", "task_type": "understanding", "prediction": "has the doctor for the dead paid his visit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0072.flac", "answer": "THINK FATHER FAUVENT IF SHE WERE TO WORK MIRACLES HERE", "subset": "test_other", "task_type": "understanding", "prediction": "think father frobenn if she were to work miracles here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0114.flac", "answer": "YOU WILL DO IT AS SPEEDILY AS POSSIBLE", "subset": "test_other", "task_type": "understanding", "prediction": "you will do it as speedily as possible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0095.flac", "answer": "BY ORDER OF THE KING SIGNIFIES TO DAY BY ORDER OF THE REVOLUTION", "subset": "test_other", "task_type": "understanding", "prediction": "by order of the king signifies to day by order of the revolution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0113.flac", "answer": "IF YOU WERE EVER TO HAVE ANY OTHER JOBS OF THIS SORT MY BROTHER IS THE STRONG MAN FOR YOU A PERFECT TURK", "subset": "test_other", "task_type": "understanding", "prediction": "if you were ever to have any other jobs of this sort my brother is the strong man for you a perfect turk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0029.flac", "answer": "IT WAS MOTHER CRUCIFIXION", "subset": "test_other", "task_type": "understanding", "prediction": "it was mother crucifixion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0053.flac", "answer": "YES REVEREND MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "yes reverend mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0022.flac", "answer": "WHEN THE VAULT IS OPEN I WILL CLOSE IT AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "will the vaulters open i will close it again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0090.flac", "answer": "BECAUSE THERE HAVE BEEN BAD PRIESTS BECAUSE SAGITTAIRE BISHOP OF GAP WAS THE BROTHER OF SALONE BISHOP OF EMBRUN AND BECAUSE BOTH OF THEM FOLLOWED MOMMOL", "subset": "test_other", "task_type": "understanding", "prediction": "because there have been bad priests because sagittera bishop of gap was a brother of salone bishop of embrun and because both of them followed mamert", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0010.flac", "answer": "BECAUSE DOM MABILLON GIVES FOUR HUNDRED AND SEVENTEEN EPISTLES OF SAINT BERNARD WHILE MERLONUS HORSTIUS ONLY GIVES THREE HUNDRED AND SIXTY SEVEN I DO NOT DESPISE MERLONUS HORSTIUS NEITHER DO I", "subset": "test_other", "task_type": "understanding", "prediction": "because dom marbolon gives four hundred and seventeen epistles of st bernard while merlonus horstius only gives three hundred and sixty seven i do not despise merlonus horstius neither do i", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0031.flac", "answer": "THE MOTHERS HAVE TAKEN HER TO THE DEAD ROOM WHICH OPENS ON THE CHURCH I KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "the mothers have taken her through the dead room which opens on the church i know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0116.flac", "answer": "EVERYTHING MUST HAVE BEEN COMPLETED A GOOD QUARTER OF AN HOUR BEFORE THAT", "subset": "test_other", "task_type": "understanding", "prediction": "everything must have been completed a good quarter of an hour before that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0066.flac", "answer": "YOU WILL HAVE AN IRON BAR YES BUT", "subset": "test_other", "task_type": "understanding", "prediction": "you will have an iron bar yes but", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0111.flac", "answer": "I HAVE MY HEAP OF OLD IRON AT THE BOTTOM OF THE GARDEN", "subset": "test_other", "task_type": "understanding", "prediction": "i have my heap of old iron at the bottom of the garden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0097.flac", "answer": "GAUTHIER BISHOP OF CHALONS HELD HIS OWN IN THIS MATTER AGAINST OTHO DUKE OF BURGUNDY", "subset": "test_other", "task_type": "understanding", "prediction": "gauthier bishop of chalon held his own in this matter against otho duke of burgundy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0037.flac", "answer": "BUT I DID NOT SAY MORE OFTEN", "subset": "test_other", "task_type": "understanding", "prediction": "but i did not say more often", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0130.flac", "answer": "I WILL MAKE THAT MY SPECIAL BUSINESS", "subset": "test_other", "task_type": "understanding", "prediction": "i will make that my special business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0117.flac", "answer": "I WILL DO ANYTHING TO PROVE MY ZEAL TOWARDS THE COMMUNITY THESE ARE MY ORDERS I AM TO NAIL UP THE COFFIN", "subset": "test_other", "task_type": "understanding", "prediction": "i will do anything to prove my zeal towards the community these are my orders i am to nail up the coffin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0119.flac", "answer": "MOTHER ASCENSION WILL BE THERE TWO MEN WOULD BE BETTER", "subset": "test_other", "task_type": "understanding", "prediction": "mother ascension will be there two men would be better", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0035.flac", "answer": "I SAY MORE OFTEN MORE OFTEN THAN WHAT", "subset": "test_other", "task_type": "understanding", "prediction": "i say more often more often than what", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0127.flac", "answer": "THE VIL STUCK FAST IN HIS THROAT", "subset": "test_other", "task_type": "understanding", "prediction": "the veal stuck fast in his throat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0060.flac", "answer": "I AM AT THE ORDERS OF THE VERY REVEREND COMMUNITY", "subset": "test_other", "task_type": "understanding", "prediction": "i am at the orders of the very reverend community", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0016.flac", "answer": "THAT IS GOOD REVEREND MOTHER I WILL OPEN THE VAULT", "subset": "test_other", "task_type": "understanding", "prediction": "that is good reverend mother i will open the vault", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0023.flac", "answer": "BUT BEFORE THAT WHAT REVEREND MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "but before that what reverend mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0089.flac", "answer": "AND THEN RELIGION IS ATTACKED WHY", "subset": "test_other", "task_type": "understanding", "prediction": "and then religion is attacked why", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0110.flac", "answer": "WHERE WILL YOU OBTAIN IT", "subset": "test_other", "task_type": "understanding", "prediction": "where will you obtain it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0059.flac", "answer": "SO I SHALL HAVE TO NAIL UP THAT COFFIN YES", "subset": "test_other", "task_type": "understanding", "prediction": "so i shall have to nail up that coffin yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0091.flac", "answer": "THEY PERSECUTE THE SAINTS", "subset": "test_other", "task_type": "understanding", "prediction": "they persecute the saints", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0094.flac", "answer": "OH HOW WICKED PEOPLE ARE", "subset": "test_other", "task_type": "understanding", "prediction": "oh how wicked people are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0000.flac", "answer": "THE PRIORESS RETURNED AND SEATED HERSELF ONCE MORE ON HER CHAIR", "subset": "test_other", "task_type": "understanding", "prediction": "the prioress returned and seated herself once more on her chair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0125.flac", "answer": "IT WILL BE GIVEN TO THE EARTH EMPTY", "subset": "test_other", "task_type": "understanding", "prediction": "it will be given to the earth empty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0026.flac", "answer": "NO DID YOU NOT HEAR THE BELL", "subset": "test_other", "task_type": "understanding", "prediction": "no did you not hear the bell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0032.flac", "answer": "A FINE SIGHT IT WOULD BE TO SEE A MAN ENTER THE DEAD ROOM MORE OFTEN", "subset": "test_other", "task_type": "understanding", "prediction": "a fine sight it would be to see a man enter the dead room more often", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0052.flac", "answer": "SHE CONTINUED FATHER FAUVENT", "subset": "test_other", "task_type": "understanding", "prediction": "she continued father frovin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0081.flac", "answer": "THE FIRST ABBOT OF CLAIRVAUX", "subset": "test_other", "task_type": "understanding", "prediction": "the first abbot of clairvaux", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0073.flac", "answer": "WHAT A GLORY OF GOD FOR THE COMMUNITY AND MIRACLES ISSUE FROM TOMBS", "subset": "test_other", "task_type": "understanding", "prediction": "what a glory of god for the community and miracles issue from tombs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0101.flac", "answer": "BUT SHE WILL HEAR SHE WILL NOT LISTEN", "subset": "test_other", "task_type": "understanding", "prediction": "but she will hear she will not listen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0080.flac", "answer": "I HAVE ON MY RIGHT BENOIT AND ON MY LEFT BERNARD WHO WAS BERNARD", "subset": "test_other", "task_type": "understanding", "prediction": "i have on my right benoit and on my left bernard who was bernard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0104.flac", "answer": "YOU WILL REMOVE YOUR BELL", "subset": "test_other", "task_type": "understanding", "prediction": "you will remove your belt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0098.flac", "answer": "THE PRIORESS TOOK BREATH THEN TURNED TO FAUCHELEVENT", "subset": "test_other", "task_type": "understanding", "prediction": "the prioress took breath then turned to fauchelevent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0057.flac", "answer": "FATHER FAUVENT MOTHER CRUCIFIXION WILL BE INTERRED IN THE COFFIN IN WHICH SHE HAS SLEPT FOR THE LAST TWENTY YEARS THAT IS JUST", "subset": "test_other", "task_type": "understanding", "prediction": "father favent mother crucifixion will be interred in the coffin in which she has slept for the last twenty years that is just", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0013.flac", "answer": "AND CAN YOU GET A LEVER", "subset": "test_other", "task_type": "understanding", "prediction": "and can you get a lover", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0115.flac", "answer": "I CANNOT WORK VERY FAST I AM INFIRM THAT IS WHY I REQUIRE AN ASSISTANT I LIMP", "subset": "test_other", "task_type": "understanding", "prediction": "i cannot work very fast i am infirm that is why i require an assistant i limp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0011.flac", "answer": "MERIT CONSISTS IN WORKING ACCORDING TO ONE'S STRENGTH A CLOISTER IS NOT A DOCK YARD", "subset": "test_other", "task_type": "understanding", "prediction": "merit consists in working according to one s strength a cloister is not a dockyard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0112.flac", "answer": "REVEREND MOTHER WHAT", "subset": "test_other", "task_type": "understanding", "prediction": "reverend mother what", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0129.flac", "answer": "I WILL PUT EARTH IN THE COFFIN REVEREND MOTHER THAT WILL PRODUCE THE EFFECT OF A CORPSE", "subset": "test_other", "task_type": "understanding", "prediction": "i will put earth in the coffin reverend mother that will produce the effect of a corpse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0096.flac", "answer": "ONE NO LONGER KNOWS WHAT IS DUE TO THE LIVING OR TO THE DEAD A HOLY DEATH IS PROHIBITED", "subset": "test_other", "task_type": "understanding", "prediction": "one no longer knows what is due to the living or to the dead a holy death is prohibited", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0021.flac", "answer": "AND TO HOLD YOUR PEACE ABOUT EVERYTHING YES REVEREND MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "and to hold your peace about everything yes reverend mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0120.flac", "answer": "HOWEVER NEVER MIND I SHALL HAVE MY LEVER", "subset": "test_other", "task_type": "understanding", "prediction": "however never mind i shall have my lover", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0093.flac", "answer": "THE MOST FEROCIOUS BEASTS ARE BEASTS WHICH ARE BLIND", "subset": "test_other", "task_type": "understanding", "prediction": "the most ferocious beasts are beasts which are blind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0085.flac", "answer": "NO ONE DOUBTS THE RIGHT OF THE MONASTERY TO SEPULTURE", "subset": "test_other", "task_type": "understanding", "prediction": "no one doubts the right of the monastery to sepulture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0121.flac", "answer": "AFTER WHICH THERE WILL BE NO TRACE OF ANYTHING", "subset": "test_other", "task_type": "understanding", "prediction": "after which there will be no trace of anything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0047.flac", "answer": "THERE WAS SOMETHING OF PARADISE IN THAT DEATH", "subset": "test_other", "task_type": "understanding", "prediction": "there was something of paradise in that death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0064.flac", "answer": "FAUCHELEVENT STARTED THE VAULT UNDER THE ALTAR", "subset": "test_other", "task_type": "understanding", "prediction": "fauchelevent started the vault under the altar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0040.flac", "answer": "IT CUT MORE OFTEN SHORT", "subset": "test_other", "task_type": "understanding", "prediction": "it cut more often short", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0109.flac", "answer": "THAT IS WELL FATHER FAUVENT", "subset": "test_other", "task_type": "understanding", "prediction": "that is well father fervin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0126.flac", "answer": "AH THE DE EXCLAIMED FAUCHELEVENT", "subset": "test_other", "task_type": "understanding", "prediction": "ah lyda exclaimed fauchelevent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0107.flac", "answer": "THE PEAL WHICH ORDERS THE DOCTOR FOR THE DEAD TO BE SUMMONED HAS ALREADY BEEN RUNG", "subset": "test_other", "task_type": "understanding", "prediction": "the peal which orders the doctor for the dead to be summoned has already been rung", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0006.flac", "answer": "THE SLAB OF THE PAVEMENT WHICH IS AT THE SIDE OF THE ALTAR", "subset": "test_other", "task_type": "understanding", "prediction": "the slab of the pavement which is at the side of the altar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0061.flac", "answer": "THE FOUR MOTHER PRECENTORS WILL ASSIST YOU", "subset": "test_other", "task_type": "understanding", "prediction": "the four mother precentors will assist you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0086.flac", "answer": "ONLY FANATICS AND THOSE IN ERROR DENY IT", "subset": "test_other", "task_type": "understanding", "prediction": "only fanatics and those in error deny it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0075.flac", "answer": "BUT THE COMMISSARY OF POLICE", "subset": "test_other", "task_type": "understanding", "prediction": "but the commissary of police", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0055.flac", "answer": "THE DEAD MUST BE OBEYED SO BE IT", "subset": "test_other", "task_type": "understanding", "prediction": "the dead must be obeyed so be it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0034.flac", "answer": "WHAT DO YOU SAY", "subset": "test_other", "task_type": "understanding", "prediction": "what do you say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0015.flac", "answer": "I WILL PUT THE LEVER THROUGH IT", "subset": "test_other", "task_type": "understanding", "prediction": "i will put the lever through it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0071.flac", "answer": "OH I AM A STONE IN YOUR WALLS", "subset": "test_other", "task_type": "understanding", "prediction": "oh i am a stone in your walls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0079.flac", "answer": "THE PRIORESS WHO WAS USUALLY SUBJECTED TO THE BARRIER OF SILENCE AND WHOSE RESERVOIR WAS OVERFULL ROSE AND EXCLAIMED WITH THE LOQUACITY OF A DAM WHICH HAS BROKEN AWAY", "subset": "test_other", "task_type": "understanding", "prediction": "the prioress who was usually subjected to the barrier of silence and whose reservoir was over full rose and exclaimed with the eloquacity of a dam which has broken away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0128.flac", "answer": "HE MADE HASTE TO IMPROVISE AN EXPEDIENT TO MAKE HER FORGET THE OATH", "subset": "test_other", "task_type": "understanding", "prediction": "he made haste to improvise an expedient to make her forget the oath", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0124.flac", "answer": "WHAT IS TO BE DONE WITH THAT COFFIN FATHER FAUVENT", "subset": "test_other", "task_type": "understanding", "prediction": "what is to be done with that coffin father防范", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0049.flac", "answer": "FAUCHELEVENT HELD HIS PEACE SHE WENT ON", "subset": "test_other", "task_type": "understanding", "prediction": "fauchelevent held his peace she went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0008.flac", "answer": "IT WOULD BE A GOOD THING TO HAVE TWO MEN FOR IT", "subset": "test_other", "task_type": "understanding", "prediction": "it would be a good thing to have two men for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0027.flac", "answer": "NOTHING CAN BE HEARD AT THE BOTTOM OF THE GARDEN REALLY", "subset": "test_other", "task_type": "understanding", "prediction": "nothing can be heard at the bottom of the garden really", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0019.flac", "answer": "FAUVENT WE HAVE CONFIDENCE IN YOU", "subset": "test_other", "task_type": "understanding", "prediction": "faulvat we have confidence in you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0058.flac", "answer": "IT IS A CONTINUATION OF HER SLUMBER", "subset": "test_other", "task_type": "understanding", "prediction": "it is a continuation of her slumber", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0004.flac", "answer": "AND YOU HAVE BEEN IN THE CHOIR IN PURSUANCE OF YOUR DUTIES TWO OR THREE TIMES", "subset": "test_other", "task_type": "understanding", "prediction": "and you have been in the choir in pursuance of your duties two or three times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0068.flac", "answer": "THE DEAD MUST BE OBEYED TO BE BURIED IN THE VAULT UNDER THE ALTAR OF THE CHAPEL NOT TO GO TO PROFANE EARTH TO REMAIN THERE IN DEATH WHERE SHE PRAYED WHILE LIVING SUCH WAS THE LAST WISH OF MOTHER CRUCIFIXION", "subset": "test_other", "task_type": "understanding", "prediction": "the dead must be obeyed to be buried in the vault under the altar of the chapel not to go to profane earth to remain there in death where she prayed while living such was the last wish of mother crucifixion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0054.flac", "answer": "SAINT TERENTIUS BISHOP OF PORT WHERE THE MOUTH OF THE TIBER EMPTIES INTO THE SEA REQUESTED THAT ON HIS TOMB MIGHT BE ENGRAVED THE SIGN WHICH WAS PLACED ON THE GRAVES OF PARRICIDES IN THE HOPE THAT PASSERS BY WOULD SPIT ON HIS TOMB THIS WAS DONE", "subset": "test_other", "task_type": "understanding", "prediction": "saint terentius bishop of port where the mouth of the tiber empties into the sea requested that on his tomb might be engraved the sign which was placed on the graves of parricides in the hope that passers by would spit on his tomb this was done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0038.flac", "answer": "AT THAT MOMENT NINE O'CLOCK STRUCK", "subset": "test_other", "task_type": "understanding", "prediction": "at that moment nine o clock struck", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0123.flac", "answer": "THE EMPTY COFFIN REMAINS THIS PRODUCED A PAUSE", "subset": "test_other", "task_type": "understanding", "prediction": "the empty coffin remains this produced a pause", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0036.flac", "answer": "REVEREND MOTHER I DID NOT SAY MORE OFTEN THAN WHAT I SAID MORE OFTEN", "subset": "test_other", "task_type": "understanding", "prediction": "reverend mother i did not say more often than what i said more often", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0042.flac", "answer": "IN HER LIFETIME MOTHER CRUCIFIXION MADE CONVERTS AFTER HER DEATH SHE WILL PERFORM MIRACLES SHE WILL", "subset": "test_other", "task_type": "understanding", "prediction": "in her lifetime mother crucifixion made converts after her death she will perform miracles she will", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0063.flac", "answer": "WHERE INTO THE VAULT", "subset": "test_other", "task_type": "understanding", "prediction": "where into the vault", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0045.flac", "answer": "SHE GAVE US HER LAST COMMANDS", "subset": "test_other", "task_type": "understanding", "prediction": "she gave us her last commands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0102.flac", "answer": "BESIDES WHAT THE CLOISTER KNOWS THE WORLD LEARNS NOT", "subset": "test_other", "task_type": "understanding", "prediction": "besides what the cloister knows the world learns not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0003.flac", "answer": "REVEREND MOTHER DO YOU KNOW THE CHAPEL", "subset": "test_other", "task_type": "understanding", "prediction": "reverend mother do you know the chapel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0020.flac", "answer": "I AM HERE TO DO ANYTHING YOU WISH", "subset": "test_other", "task_type": "understanding", "prediction": "i am here to do anything you wish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0051.flac", "answer": "FORTUNATELY THE PRIORESS COMPLETELY ABSORBED IN HER OWN THOUGHTS DID NOT HEAR IT", "subset": "test_other", "task_type": "understanding", "prediction": "fortunately the prioress completely absorbed in her own thoughts did not hear it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0062.flac", "answer": "NO IN LOWERING THE COFFIN", "subset": "test_other", "task_type": "understanding", "prediction": "no in lowering the coffin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0030.flac", "answer": "THREE YEARS AGO MADAME DE BETHUNE A JANSENIST TURNED ORTHODOX MERELY FROM HAVING SEEN MOTHER CRUCIFIXION AT PRAYER AH", "subset": "test_other", "task_type": "understanding", "prediction": "three years ago madame de bethune a jansenist turned orthodox merely from having seen mother crucifixion at prayer ah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0067.flac", "answer": "YOU WILL RAISE THE STONE WITH THE BAR BY MEANS OF THE RING BUT", "subset": "test_other", "task_type": "understanding", "prediction": "you will raise the stone with the bar by means of the ring but", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0044.flac", "answer": "SHE RETAINED HER CONSCIOUSNESS TO THE VERY LAST MOMENT", "subset": "test_other", "task_type": "understanding", "prediction": "she retained her consciousness to the very last moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0106.flac", "answer": "HE WILL PAY IT AT FOUR O'CLOCK TO DAY", "subset": "test_other", "task_type": "understanding", "prediction": "he will pay it at four o clock to day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0108.flac", "answer": "BUT YOU DO NOT UNDERSTAND ANY OF THE PEALS", "subset": "test_other", "task_type": "understanding", "prediction": "but you do not understand any of the pills", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0046.flac", "answer": "IF YOU HAD A LITTLE MORE FAITH AND IF YOU COULD HAVE BEEN IN HER CELL SHE WOULD HAVE CURED YOUR LEG MERELY BY TOUCHING IT SHE SMILED", "subset": "test_other", "task_type": "understanding", "prediction": "if you had a little more faith and if you could have been in her cell she would have cured your leg merely by touching it she smiled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0078.flac", "answer": "MARTIN THE ELEVENTH GENERAL OF THE CARTHUSIANS GAVE TO HIS ORDER THIS DEVICE STAT CRUX DUM VOLVITUR ORBIS", "subset": "test_other", "task_type": "understanding", "prediction": "martin the eleventh general of the carthusians gave to his order this device stat crux dum volvitur orbis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0039.flac", "answer": "AT NINE O'CLOCK IN THE MORNING AND AT ALL HOURS PRAISED AND ADORED BE THE MOST HOLY SACRAMENT OF THE ALTAR SAID THE PRIORESS", "subset": "test_other", "task_type": "understanding", "prediction": "at nine o clock in the morning and at all hours praised and adored be the most holy sacrament of the altar said the prioress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0122.flac", "answer": "THE GOVERNMENT WILL HAVE NO SUSPICION", "subset": "test_other", "task_type": "understanding", "prediction": "the government will have no suspicion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0074.flac", "answer": "BUT REVEREND MOTHER IF THE AGENT OF THE SANITARY COMMISSION", "subset": "test_other", "task_type": "understanding", "prediction": "but reverend mother if the agent of the sanitary commission", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0069.flac", "answer": "SHE ASKED IT OF US THAT IS TO SAY COMMANDED US", "subset": "test_other", "task_type": "understanding", "prediction": "she asked it of us that is to say commanded us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0005.flac", "answer": "THERE IS A STONE TO BE RAISED HEAVY", "subset": "test_other", "task_type": "understanding", "prediction": "there is a stone to be raised heavy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0014.flac", "answer": "THERE IS A RING IN THE STONE", "subset": "test_other", "task_type": "understanding", "prediction": "there is a ring in the stone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0087.flac", "answer": "WE LIVE IN TIMES OF TERRIBLE CONFUSION", "subset": "test_other", "task_type": "understanding", "prediction": "we live in times of terrible confusion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0050.flac", "answer": "I HAVE CONSULTED UPON THIS POINT MANY ECCLESIASTICS LABORING IN OUR LORD WHO OCCUPY THEMSELVES IN THE EXERCISES OF THE CLERICAL LIFE AND WHO BEAR WONDERFUL FRUIT", "subset": "test_other", "task_type": "understanding", "prediction": "i have consulted upon this point many ecclesiastics laboring in our lord who occupy themselves in the exercises of the clerical life and who bear wonderful fruit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0043.flac", "answer": "FATHER FAUVENT THE COMMUNITY HAS BEEN BLESSED IN MOTHER CRUCIFIXION", "subset": "test_other", "task_type": "understanding", "prediction": "father fauvent the community has been blessed in mother crucifixion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0082.flac", "answer": "HIS ORDER HAS PRODUCED FORTY POPES TWO HUNDRED CARDINALS FIFTY PATRIARCHS SIXTEEN HUNDRED ARCHBISHOPS FOUR THOUSAND SIX HUNDRED BISHOPS FOUR EMPERORS TWELVE EMPRESSES FORTY SIX KINGS FORTY ONE QUEENS THREE THOUSAND SIX HUNDRED CANONIZED SAINTS AND HAS BEEN IN EXISTENCE FOR FOURTEEN HUNDRED YEARS", "subset": "test_other", "task_type": "understanding", "prediction": "his order has produced forty popes two hundred cardinals fifty patriarchs sixteen hundred archbishops four thousand six hundred bishops four emperors twelve empresses forty six kings forty one queens three thousand six hundred canonized saints and has been in existence for fourteen hundred years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0009.flac", "answer": "A WOMAN IS NEVER A MAN", "subset": "test_other", "task_type": "understanding", "prediction": "a woman is never a man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0024.flac", "answer": "FATHER FAUVENT REVEREND MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "father fauvent reverend mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0002.flac", "answer": "FATHER FAUVENT", "subset": "test_other", "task_type": "understanding", "prediction": "father fauvent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0048.flac", "answer": "FAUCHELEVENT THOUGHT THAT IT WAS AN ORISON WHICH SHE WAS FINISHING", "subset": "test_other", "task_type": "understanding", "prediction": "frochlevat thought that it was an orison which she was finishing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0076.flac", "answer": "CHONODEMAIRE ONE OF THE SEVEN GERMAN KINGS WHO ENTERED AMONG THE GAULS UNDER THE EMPIRE OF CONSTANTIUS EXPRESSLY RECOGNIZED THE RIGHT OF NUNS TO BE BURIED IN RELIGION THAT IS TO SAY BENEATH THE ALTAR", "subset": "test_other", "task_type": "understanding", "prediction": "schoeno de mer one of the seven german kings who entered among the gauls under the empire of constantius expressly recognized the right of nuns to be buried in religion that is to say beneath the altar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0041.flac", "answer": "FAUCHELEVENT MOPPED HIS FOREHEAD", "subset": "test_other", "task_type": "understanding", "prediction": "fauchelevent mopped his forehead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0007.flac", "answer": "THE SLAB WHICH CLOSES THE VAULT YES", "subset": "test_other", "task_type": "understanding", "prediction": "the slab which closes the vault yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0103.flac", "answer": "A PAUSE ENSUED", "subset": "test_other", "task_type": "understanding", "prediction": "a pause ensued", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0018.flac", "answer": "GIVE ME YOUR ORDERS VERY REVEREND MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "give me your orders very reverend mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0065.flac", "answer": "UNDER THE ALTAR BUT", "subset": "test_other", "task_type": "understanding", "prediction": "under the altar but", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3528/168669/3528-168669-0028.flac", "answer": "AND THEN THE WIND IS NOT BLOWING IN MY DIRECTION THIS MORNING", "subset": "test_other", "task_type": "understanding", "prediction": "and then the wind is not blowing in my direction this morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0025.flac", "answer": "ABOUT THE LAST OF DECEMBER EIGHTEEN SEVENTY THREE I ARRIVED IN CARROLL PARISH LOUISIANA", "subset": "test_other", "task_type": "understanding", "prediction": "about the last of december eighteen seventy three i arrived in carroll parish louisiana", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0024.flac", "answer": "HELVIN FICKLE AND WIFE OF GREENTON VALLEY WERE ATTENDING THE SPRINGS AT THAT TIME AND EITHER OF THEM WILL TESTIFY TO THE ABOVE FOR JOHN AND I SAT IN FRONT OF MISTER SMITH WHILE HE WAS PREACHING AND WAS IN HIS COMPANY FOR A FEW MOMENTS TOGETHER WITH HIS WIFE AND MISTER AND MISSUS FICKLE AFTER SERVICE", "subset": "test_other", "task_type": "understanding", "prediction": "helvin fickle and wife of greenton valley were attending the springs at that time and either of them will testify to the above for john and i sat in front of mr smith while he was preaching and was in his company for a few moments together with his wife and mr and miss fickle after the service", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0013.flac", "answer": "I WENT TO KANSAS WHERE OUR CATTLE WERE IN WOODSON COUNTY AT COLONEL RIDGE'S", "subset": "test_other", "task_type": "understanding", "prediction": "and went to kansas where our cattle were in woodson county at colonel ridge s", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0023.flac", "answer": "THERE WERE FIFTY OR A HUNDRED PERSONS THERE WHO WILL TESTIFY IN ANY COURT THAT JOHN AND I WERE THERE", "subset": "test_other", "task_type": "understanding", "prediction": "there were fifty or a hundred persons there who will testify in any court that john and i were there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0002.flac", "answer": "THIS RAID WAS ACCOMPANIED BY BLOODSHED JUDGE MC LAIN THE BANKER BEING SHOT THOUGH NOT FATALLY", "subset": "test_other", "task_type": "understanding", "prediction": "this raid was accompanied by bloodshed judge mclean the banker being shot though not fatally", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0021.flac", "answer": "POOR JOHN HE HAS BEEN HUNTED DOWN AND SHOT LIKE A WILD BEAST AND NEVER WAS A BOY MORE INNOCENT", "subset": "test_other", "task_type": "understanding", "prediction": "poor john he has been hunted down and shot like a wild beast and never was a boy more innocent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0001.flac", "answer": "IT WAS CLAIMED BY PEOPLE OF LIBERTY THAT THEY POSITIVELY RECOGNIZED AMONG THE ROBBERS OLL SHEPHERD RED MONKERS AND BUD PENCE WHO HAD SEEN SERVICE WITH QUANTRELL", "subset": "test_other", "task_type": "understanding", "prediction": "it was claimed by people of liberty that they positively recognized among the robbers all shepherd red mockers and bud pence who had seen service with quantrell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0014.flac", "answer": "DURING THE SUMMER I WAS EITHER IN SAINT CLAIR JACKSON OR KANSAS BUT AS THERE WAS NO ROBBERY COMMITTED THAT SUMMER IT MAKES NO DIFFERENCE WHERE I WAS", "subset": "test_other", "task_type": "understanding", "prediction": "during the summer i was either in st clair jackson or kansas but as there was no robbery committed that summer it makes no difference where i was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0005.flac", "answer": "IT WAS CHARGED THAT ARTHUR MC COY OR A C MC COY AND MYSELF HAD BEEN PARTICIPANTS IN THE GAD'S HILL AFFAIR AND THE TWO STAGE ROBBERIES", "subset": "test_other", "task_type": "understanding", "prediction": "it was charged that arthur mccoy or a c mccoy and myself had been participants in the gadshill affair and the two stage robberies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0020.flac", "answer": "WE WERE NOT ON GOOD TERMS AT THE TIME NOR HAVE WE BEEN FOR SEVERAL YEARS", "subset": "test_other", "task_type": "understanding", "prediction": "we were not on good terms at the time nor have we been for several years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0006.flac", "answer": "THE PARTS OF THIS LETTER NOW RELEVANT ARE AS FOLLOWS", "subset": "test_other", "task_type": "understanding", "prediction": "the parts of this letter now relevant are as follows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0010.flac", "answer": "THIS CAN BE PROVED BY BOTH OF THEM ALSO BY SHERIFF BARKLEY AND FIFTY OTHER RESPECTABLE MEN OF THAT COUNTY", "subset": "test_other", "task_type": "understanding", "prediction": "this can be proved by both of them also by sheriff barkley and fifty other respectable men of that county", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0022.flac", "answer": "DOCTOR L LEWIS WAS HIS PHYSICIAN", "subset": "test_other", "task_type": "understanding", "prediction": "doctor l lewis was his physician", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0015.flac", "answer": "I WENT THROUGH INDEPENDENCE AND FROM THERE TO ACE WEBB'S", "subset": "test_other", "task_type": "understanding", "prediction": "i went through independence and from there to ace webs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0026.flac", "answer": "I STAYED THERE UNTIL THE EIGHTH OF FEBRUARY EIGHTEEN SEVENTY FOUR", "subset": "test_other", "task_type": "understanding", "prediction": "i stayed there until the eighth of february eighteen seventy four", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0027.flac", "answer": "I HAD NOT HEARD OF THAT WHEN I WROTE THE LETTER OF EIGHTEEN SEVENTY FOUR AND TO CORRECT ANY MISAPPREHENSION THAT MIGHT BE CREATED BY OMITTING IT I WILL SAY THAT AT THAT TIME I WAS AT NEOSHO KANSAS WITH A DROVE OF CATTLE WHICH I SOLD TO MAJOR RAY", "subset": "test_other", "task_type": "understanding", "prediction": "i had not heard of that when i wrote the letter of eighteen seventy four and to correct any misapprehension that might be created by omitting it i will say that at the time i was at neosho kansas with a drove of cattle which i sold to major ray", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0019.flac", "answer": "I MET SEVERAL OF MY FRIENDS AMONG THEM WAS BOB HUDSPETH", "subset": "test_other", "task_type": "understanding", "prediction": "i met several of my friends among them was bob huthbeth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0012.flac", "answer": "I THEN WENT TO ARKANSAS AND RETURNED TO SAINT CLAIR COUNTY ABOUT THE FIRST OF MAY", "subset": "test_other", "task_type": "understanding", "prediction": "i then went to arkansas and returned to st clair county about the first of may", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0011.flac", "answer": "I BROUGHT THE CATTLE TO KANSAS THAT FALL AND REMAINED IN SAINT CLAIR COUNTY UNTIL FEBRUARY", "subset": "test_other", "task_type": "understanding", "prediction": "i brought the cattle to kansas that fall and remained in st clair county until february", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0016.flac", "answer": "THERE I TOOK DINNER AND THEN WENT TO DOCTOR L W TWYMAN'S", "subset": "test_other", "task_type": "understanding", "prediction": "there i took dinner and then went to dr l w twyman s", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0018.flac", "answer": "WE CROSSED ON THE BRIDGE STAYED IN THE CITY ALL NIGHT AND THE NEXT MORNING WE RODE UP THROUGH THE CITY", "subset": "test_other", "task_type": "understanding", "prediction": "we crossed on the bridge stayed in the city all night and the next morning we rode up through the city", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0017.flac", "answer": "OUR BUSINESS THERE WAS TO SEE E P WEST HE WAS NOT AT HOME BUT THE FAMILY WILL REMEMBER THAT WE WERE THERE", "subset": "test_other", "task_type": "understanding", "prediction": "our business there was to see e p west he was not at home but the family will remember that we were there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0004.flac", "answer": "JUNE THIRD EIGHTEEN SEVENTY ONE OBOCOCK BROTHERS BANK AT CORYDON IOWA WAS ROBBED OF FORTY THOUSAND DOLLARS BY SEVEN MEN IN BROAD DAYLIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "june third eighteen seventy one obakock brothers bank at croydon iowa was robbed of forty thousand dollars by seven men in broad daylight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0003.flac", "answer": "NO WARRANT WAS ISSUED FOR THE YOUNGERS BUT SUBSEQUENT HISTORIANS HAVE INFERENTIALLY AT LEAST ACCUSED US OF TAKING PART BUT AS I SAID BEFORE THERE IS NO TRUTH IN THE ACCUSATION", "subset": "test_other", "task_type": "understanding", "prediction": "no warrant was issued for the younger but subsequent historians have inferentially at least accused us of taking part but as i said before there is no truth in the accusation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0007.flac", "answer": "YOU MAY USE THIS LETTER IN YOUR OWN WAY", "subset": "test_other", "task_type": "understanding", "prediction": "you may use this letter in your own way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0000.flac", "answer": "ALTHOUGH EVERY BOOK PURPORTING TO NARRATE THE LIVES OF THE YOUNGER BROTHERS HAS TOLD OF THE LIBERTY ROBBERY AND IMPLIED THAT WE HAD A PART IN IT THE YOUNGERS WERE NOT SUSPECTED AT THAT TIME NOR FOR A LONG TIME AFTERWARD", "subset": "test_other", "task_type": "understanding", "prediction": "although every book purporting to narrate the lives of the younger brothers has told of the liberty robbery and implied that we had a part in it the youngers were not suspected at that time nor for a long time afterward", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0008.flac", "answer": "I WILL GIVE YOU THIS OUTLINE AND SKETCH OF MY WHEREABOUTS AND ACTIONS AT THE TIME OF CERTAIN ROBBERIES WITH WHICH I AM CHARGED", "subset": "test_other", "task_type": "understanding", "prediction": "i will give you this outline and sketch of my whereabouts and actions at the time of certain robberies with which i am charged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0028.flac", "answer": "IT WAS IMMEDIATELY FOLLOWING THE ROCK ISLAND ROBBERY AT ADAIR IOWA THAT THERE FIRST APPEARED A DELIBERATE ENLISTMENT OF SOME LOCAL PAPERS IN MISSOURI TO CONNECT US WITH THIS ROBBERY", "subset": "test_other", "task_type": "understanding", "prediction": "it was immediately following the rock island robbery at adair iowa that there first appeared a deliberate enlistment of some local papers in missouri to connect us with this robbery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280076/7975-280076-0009.flac", "answer": "AT THE TIME OF THE GALLATIN BANK ROBBERY I WAS GATHERING CATTLE IN ELLIS COUNTY TEXAS CATTLE THAT I BOUGHT FROM PLEAS TAYLOR AND RECTOR", "subset": "test_other", "task_type": "understanding", "prediction": "at the time of the gallatin bank robbery i was gathering cattle in ellis county texas cattle that i bought from plaze taylor and rector", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0008.flac", "answer": "THEY DID MARK MY CLOTHES IN ONE OR TWO PLACES HOWEVER", "subset": "test_other", "task_type": "understanding", "prediction": "they did mark my clothes in one or two places however", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0012.flac", "answer": "THE WOUNDED OF BOTH FORCES WERE GATHERED UP AND WERE PLACED IN HOUSES", "subset": "test_other", "task_type": "understanding", "prediction": "the wounded of both forces were gathered up and were placed in houses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0010.flac", "answer": "I WAS TOLD BY SOME OF OUR MEN FROM THE WESTERN BORDER OF THE STATE THAT THEY RECOGNIZED THE DARING YOUNG RIDER AS COLE YOUNGER", "subset": "test_other", "task_type": "understanding", "prediction": "i was told by some of our men from the western border of the state that they recognized the daring young rider as cole younger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0000.flac", "answer": "WE TOOK THE OATH PERHAPS THREE HUNDRED OF US DOWN ON LUTHER MASON'S FARM A FEW MILES FROM WHERE I NOW WRITE WHERE COLONEL HAYS HAD ENCAMPED AFTER INDEPENDENCE", "subset": "test_other", "task_type": "understanding", "prediction": "we took the oath perhaps three hundred of us down on luther mason s farm a few miles from where i now write where colonel hays had encamped after independence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0005.flac", "answer": "I THINK HE'LL BE RATHER TOUGH MEAT FOR BREAKFAST I REPLIED HE MIGHT BE ALL RIGHT FOR DINNER", "subset": "test_other", "task_type": "understanding", "prediction": "i think he will be rather tough meat for breakfast i replied he might be all right for dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0001.flac", "answer": "BOONE MUIR AND MYSELF MET COFFEE AND THE REST BELOW ROSE HILL ON GRAND RIVER", "subset": "test_other", "task_type": "understanding", "prediction": "boone ewer and myself made coffee and the rest below rose hill on grand river", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0004.flac", "answer": "COME IN COLONEL HAYS EXCLAIMED COLONEL COCKRELL", "subset": "test_other", "task_type": "understanding", "prediction": "come in colonel hays exclaimed colonel cockrell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0009.flac", "answer": "MAJOR FOSTER IN A LETTER TO JUDGE GEORGE M BENNETT OF MINNEAPOLIS SAID", "subset": "test_other", "task_type": "understanding", "prediction": "major foster in a letter to judge georgian bennett of minneapolis said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0006.flac", "answer": "JACKMAN WITH A PARTY OF THIRTY SEASONED MEN CHARGED THE INDIANA GUNS AND CAPTURED THEM BUT MAJOR FOSTER LED A GALLANT CHARGE AGAINST THE INVADERS AND RECAPTURED THE PIECES", "subset": "test_other", "task_type": "understanding", "prediction": "jackman with a party of thirty seasoned men charged the indian guns and captured them but major faustor led a gallant charge against the invaders and recaptured the pieces", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0007.flac", "answer": "WE WERE OUT OF AMMUNITION AND WERE HELPLESS HAD THE FIGHT BEEN PRESSED", "subset": "test_other", "task_type": "understanding", "prediction": "we were out of ammunition and were helpless had the fight been pressed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0002.flac", "answer": "ACCORDINGLY I WAS SHORTLY AWAKENED TO ACCOMPANY HIM TO LONE JACK WHERE HE WOULD PERSONALLY MAKE KNOWN THE SITUATION TO THE OTHER COLONELS", "subset": "test_other", "task_type": "understanding", "prediction": "accordingly i was shortly awakened to accompany him to lone jack where he would personally make known the situation to the other colonels", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0011.flac", "answer": "ABOUT NINE THIRTY A M I WAS SHOT DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "about nine thirty a m i was shot down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280063/7975-280063-0003.flac", "answer": "FOSTER HAD NEARLY ONE THOUSAND CAVALRYMEN AND TWO PIECES OF RABB'S INDIANA BATTERY THAT HAD ALREADY MADE FOR ITSELF A NAME FOR HARD FIGHTING", "subset": "test_other", "task_type": "understanding", "prediction": "foster had nearly one thousand cavalrymen and two pieces of rabb s indiana battery that had already made for itself a name for hard fighting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0002.flac", "answer": "BOB'S SHATTERED ELBOW WAS REQUIRING FREQUENT ATTENTION AND THAT NIGHT WE MADE ONLY NINE MILES AND MONDAY MONDAY NIGHT AND TUESDAY WE SPENT IN A DESERTED FARM HOUSE CLOSE TO MANKATO", "subset": "test_other", "task_type": "understanding", "prediction": "bob shattered elbows requiring frequent attention and that night we made only nine miles and monday monday night and tuesday we spent in a deserted farm house close to mankato", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0001.flac", "answer": "FRIDAY WE MOVED TOWARD WATERVILLE AND FRIDAY NIGHT WE CAMPED BETWEEN ELYSIAN AND GERMAN LAKE", "subset": "test_other", "task_type": "understanding", "prediction": "friday we moved toward waterville and friday night we camped between alician and german lake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0008.flac", "answer": "BUT THEY SOON AFTER GOT CLOSE ENOUGH SO THAT ONE OF THEM BROKE MY WALKING STICK WITH A SHOT", "subset": "test_other", "task_type": "understanding", "prediction": "but they soon after got close enough so that one of them broke my walking stick with a shot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0016.flac", "answer": "SHERIFF GLISPIN OF WATONWAN COUNTY WHO WAS TAKING BOB'S PISTOL FROM HIM WAS ALSO SHOUTING TO THE FELLOW", "subset": "test_other", "task_type": "understanding", "prediction": "sheriff glispin of watowahn county who was taking bob s pistol from him was also shouting to the fellow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0004.flac", "answer": "FINALLY WE ADMINISTERED TO HIM AN OATH NOT TO BETRAY OUR WHEREABOUTS UNTIL WE HAD TIME TO MAKE OUR ESCAPE AND HE AGREED NOT TO", "subset": "test_other", "task_type": "understanding", "prediction": "finally we administered to him an oath not to betray our whereabouts until we had time to make our escape and he agreed not to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0015.flac", "answer": "ONE OF THE FELLOWS IN THE OUTER LINE NOT BRAVE ENOUGH HIMSELF TO JOIN THE VOLUNTEERS WHO HAD COME IN TO BEAT US OUT WAS NOT DISPOSED TO BELIEVE IN THE SURRENDER AND HAD HIS GUN LEVELLED ON BOB IN SPITE OF THE HANDKERCHIEF WHICH WAS WAVING AS A FLAG OF TRUCE", "subset": "test_other", "task_type": "understanding", "prediction": "one of the fellows in the outer line not brave enough himself to join the volunteers who had come in to beat us out was not disposed to believe in the surrender and had his gun leveled on bob in spite of the handkerchief which was waving as a flag of truce", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0011.flac", "answer": "FORMING IN LINE FOUR PACES APART HE ORDERED THEM TO ADVANCE RAPIDLY AND CONCENTRATE THE FIRE OF THE WHOLE LINE THE INSTANT THE ROBBERS WERE DISCOVERED", "subset": "test_other", "task_type": "understanding", "prediction": "forming in line four paces apart he ordered them to advance rapidly and concentrate the fire of the whole line the instant the robbers were discovered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0010.flac", "answer": "SIX STEPPED TO THE FRONT SHERIFF GLISPIN COLONEL T L VOUGHT B M RICE G A BRADFORD C A POMEROY AND S J SEVERSON", "subset": "test_other", "task_type": "understanding", "prediction": "six stepped to the front sheriff glispin col t l vaught b m rice g a bradford c a pomeroy and s j severson", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0017.flac", "answer": "INCLUDING THOSE RECEIVED IN AND ON THE WAY FROM NORTHFIELD I HAD ELEVEN WOUNDS", "subset": "test_other", "task_type": "understanding", "prediction": "including those received in and on the way from northfield i had eleven wounds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0005.flac", "answer": "NO SOONER HOWEVER WAS HE RELEASED THAN HE MADE POSTHASTE INTO MANKATO TO ANNOUNCE OUR PRESENCE AND IN A FEW MINUTES ANOTHER POSSE WAS LOOKING FOR US", "subset": "test_other", "task_type": "understanding", "prediction": "no sooner however was he released than he made post haste into mankato to announce our presence and in a few minutes another posse was looking for us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0006.flac", "answer": "THE WHISTLE ON THE OIL MILL BLEW AND WE FEARED THAT IT WAS A SIGNAL THAT HAD BEEN AGREED UPON TO ALARM THE TOWN IN CASE WE WERE OBSERVED BUT WE WERE NOT MOLESTED", "subset": "test_other", "task_type": "understanding", "prediction": "the whistle on the ore mill blew and we feared that it was a signal that had been agreed upon to alarm the town in case we were observed but we were not molested", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0013.flac", "answer": "THERE IS NO USE STOPPING TO PICK UP A COMRADE HERE FOR WE CAN'T GET HIM THROUGH THE LINE JUST CHARGE THEM AND MAKE IT IF WE CAN", "subset": "test_other", "task_type": "understanding", "prediction": "there is no use stopping to pick up a comrade here for we can not get him through the line just charge them and make it if we can", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0007.flac", "answer": "HE HAD TO SLEEP WITH IT PILLOWED ON MY BREAST JIM BEING ALSO CRIPPLED WITH A WOUND IN HIS SHOULDER AND WE COULD NOT GET MUCH SLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "he had to sleep with it pillowed on my breast jim being also crippled with a wound in his shoulder and we could not get much sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0012.flac", "answer": "MAKE FOR THE HORSES I SAID EVERY MAN FOR HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "make for the horses i said every man for himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0018.flac", "answer": "AND SHERIFF GLISPIN'S ORDER NOT TO SHOOT WAS THE BEGINNING OF THE PROTECTORATE THAT MINNESOTA PEOPLE ESTABLISHED OVER US", "subset": "test_other", "task_type": "understanding", "prediction": "and sheriff g Lisbon s order not to shoot was the beginning of the protectorate that Minnesota people established over us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0014.flac", "answer": "I GOT UP AS THE SIGNAL FOR THE CHARGE AND WE FIRED ONE VOLLEY", "subset": "test_other", "task_type": "understanding", "prediction": "i got up as a signal for the charge and we fired one volley", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0003.flac", "answer": "THAT DAY A MAN NAMED DUNNING DISCOVERED US AND WE TOOK HIM PRISONER", "subset": "test_other", "task_type": "understanding", "prediction": "that day a man named dunning discovered us and we took him prisoner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0000.flac", "answer": "THAT NIGHT IT STARTED TO RAIN AND WE WORE OUT OUR HORSES", "subset": "test_other", "task_type": "understanding", "prediction": "that night it started to rain and we wore out our horses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280085/7975-280085-0009.flac", "answer": "WE WERE IN SIGHT OF OUR LONG SOUGHT HORSES WHEN THEY CUT US OFF FROM THE ANIMALS AND OUR LAST HOPE WAS GONE", "subset": "test_other", "task_type": "understanding", "prediction": "we were in sight of our long sawed horses when they cut us off from the animals and our last hope was gone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0009.flac", "answer": "MISSUS WELLS STAYED TO GUARD THE REMAINS WHILE HER SON CARRIED THE NEWS OF THE MURDER TO COLONEL PEABODY OF THE FEDERAL COMMAND WHO WAS THEN IN CAMP AT KANSAS CITY", "subset": "test_other", "task_type": "understanding", "prediction": "miss wells stayed to guard the remains while her son carried the news of the murder to colonel peabody of the federal command who was then in camp at kansas city", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0001.flac", "answer": "HENRY WASHINGTON YOUNGER MY FATHER REPRESENTED JACKSON COUNTY THREE TIMES IN THE LEGISLATURE AND WAS ALSO JUDGE OF THE COUNTY COURT", "subset": "test_other", "task_type": "understanding", "prediction": "henry washington younger my father represented jackson county three times in the legislature and was also a judge of the county court", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0005.flac", "answer": "MY ELDEST BROTHER RICHARD DIED IN EIGHTEEN SIXTY", "subset": "test_other", "task_type": "understanding", "prediction": "my eldest brother richard died in eighteen sixty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0000.flac", "answer": "THESE HATREDS WERE SOON TO MAKE TROUBLE FOR ME OF WHICH I HAD NEVER DREAMED", "subset": "test_other", "task_type": "understanding", "prediction": "these hatreds were soon to make trouble for me of which i had never dreamed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0006.flac", "answer": "MY FATHER WAS IN THE EMPLOY OF THE UNITED STATES GOVERNMENT AND HAD THE MAIL CONTRACT FOR FIVE HUNDRED MILES", "subset": "test_other", "task_type": "understanding", "prediction": "my father was in the employ of the united states government and had the mail contract for five hundred miles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0002.flac", "answer": "MY MOTHER WHO WAS BURSHEBA FRISTOE OF INDEPENDENCE WAS THE DAUGHTER OF RICHARD FRISTOE WHO FOUGHT UNDER GENERAL ANDREW JACKSON AT NEW ORLEANS JACKSON COUNTY HAVING BEEN SO NAMED AT MY GRANDFATHER FRISTOE'S INSISTENCE", "subset": "test_other", "task_type": "understanding", "prediction": "my mother who was beresbia frustow of independence was a daughter of richard frustow who fought under general andrew jackson at new orleans jackson county having been so named at my grandfather frustow s insistence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0018.flac", "answer": "ONE OF THE CONDITIONS UPON WHICH HER LIFE WAS SPARED WAS THAT SHE WOULD REPORT AT LEXINGTON WEEKLY", "subset": "test_other", "task_type": "understanding", "prediction": "one of the conditions upon which her life was spared was that she would report at lexington weekly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0004.flac", "answer": "MY BROTHER JAMES WAS BORN JANUARY FIFTEENTH EIGHTEEN FORTY EIGHT JOHN IN EIGHTEEN FIFTY ONE AND ROBERT IN DECEMBER EIGHTEEN FIFTY THREE", "subset": "test_other", "task_type": "understanding", "prediction": "my brother james was born january fifteenth eighteen forty eight john in eighteen fifty one and robert in december eighteen fifty three", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0016.flac", "answer": "I HAVE ALWAYS FELT THAT THE EXPOSURE TO WHICH SHE WAS SUBJECTED ON THIS CRUEL JOURNEY TOO HARD EVEN FOR A MAN TO TAKE WAS THE DIRECT CAUSE OF HER DEATH", "subset": "test_other", "task_type": "understanding", "prediction": "i have always felt that the exposure to which she was subjected on this cruel journey too hard even for a man to take was a direct cause of her death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0019.flac", "answer": "ONE OF MY OLD SCHOOL TEACHERS WHOM I HAVE NEVER SEEN SINCE THE SPRING OR SUMMER OF EIGHTEEN SIXTY TWO IS STEPHEN B ELKINS SENATOR FROM WEST VIRGINIA", "subset": "test_other", "task_type": "understanding", "prediction": "one of my old school teachers whom i have never seen since the spring or summer of eighteen sixty two is stephen b elkins senator from west virginia", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0014.flac", "answer": "BUT SHE FAILED TO FIND THE COMFORT SHE SOUGHT FOR ANNOYANCES CONTINUED IN A MORE AGGRAVATED FORM", "subset": "test_other", "task_type": "understanding", "prediction": "but she failed to find the comfort she sought for annoyances continued in a more aggravated form", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0010.flac", "answer": "MISSUS MC CORKLE JUMPED FROM THE WINDOW OF THE HOUSE AND ESCAPED", "subset": "test_other", "task_type": "understanding", "prediction": "miss mccorkle jumped from the window of the house and escaped", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0015.flac", "answer": "TWO MONTHS AFTER THIS INCIDENT THE SAME PERSECUTORS AGAIN ENTERED OUR HOME IN THE DEAD OF THE NIGHT AND AT THE POINT OF A PISTOL TRIED TO FORCE MY MOTHER TO SET FIRE TO HER OWN HOME", "subset": "test_other", "task_type": "understanding", "prediction": "two months after this incident the same persecutors again entered our home in the dead of the night and at the point of a pistol tried to force my mother to set fire to her own home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0007.flac", "answer": "HE HAD STARTED BACK TO HARRISONVILLE IN A BUGGY BUT WAS WAYLAID ONE MILE SOUTH OF WESTPORT A SUBURB OF KANSAS CITY AND BRUTALLY MURDERED FALLING OUT OF HIS BUGGY INTO THE ROAD WITH THREE MORTAL BULLET WOUNDS", "subset": "test_other", "task_type": "understanding", "prediction": "he had started back to harrisonville in a buggy but was waylaid one mile south of westport a suburb of kansas city and brutally murdered falling out of his buggy into the road with three mortal bullet wounds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0013.flac", "answer": "EVERY KNOT REPRESENTED A HUMAN LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "every knot represented a human life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0003.flac", "answer": "I CANNOT REMEMBER WHEN I DID NOT KNOW HOW TO SHOOT", "subset": "test_other", "task_type": "understanding", "prediction": "i cannot remember when i did not know how to shoot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0017.flac", "answer": "FROM HARRISONVILLE SHE WENT TO WAVERLY WHERE SHE WAS HOUNDED CONTINUALLY", "subset": "test_other", "task_type": "understanding", "prediction": "from harrisonville she went to waverly where she was hounded continually", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0012.flac", "answer": "NOW OLD LADY CALL ON YOUR PROTECTORS WHY DON'T YOU CALL ON COLE YOUNGER NOW", "subset": "test_other", "task_type": "understanding", "prediction": "now old lady call on your protectors why dont you call on cole younger now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0011.flac", "answer": "AS THE RAIDERS LEFT ONE OF THEM SHOUTED", "subset": "test_other", "task_type": "understanding", "prediction": "as the raiders left one of them shouted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0020.flac", "answer": "WHEN I WAS TAKEN PRISONER I EXPECTED TO BE SHOT WITHOUT CEREMONY", "subset": "test_other", "task_type": "understanding", "prediction": "when i was taken prisoner i expected to be shot without ceremony", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280057/7975-280057-0008.flac", "answer": "MISSUS WASHINGTON WELLS AND HER SON SAMUEL ON THE ROAD HOME FROM KANSAS CITY TO LEE'S SUMMIT RECOGNIZED THE BODY AS THAT OF MY FATHER", "subset": "test_other", "task_type": "understanding", "prediction": "miss washington wales and her son samuel on the road home from kansas city to lee summit recognized the body as that of my father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0002.flac", "answer": "WHEN WE CAME UP I TOLD MILLER TO SHUT THE BANK DOOR WHICH THEY HAD LEFT OPEN IN THEIR HURRY", "subset": "test_other", "task_type": "understanding", "prediction": "when we came up i told miller to shut the bank door which they had left open in their hurry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0005.flac", "answer": "AND I CALLED TO HIM TO GET INSIDE AT THE SAME TIME FIRING A PISTOL SHOT IN THE AIR AS A SIGNAL TO THE THREE BOYS AT THE BRIDGE THAT WE HAD BEEN DISCOVERED", "subset": "test_other", "task_type": "understanding", "prediction": "and i called to him to get inside at the same time firing a pistol shot in the air as a signal to the three boys at the bridge that we had been discovered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0012.flac", "answer": "CHANGING HIS PISTOL TO HIS LEFT HAND BOB RAN OUT AND MOUNTED MILLER'S MARE", "subset": "test_other", "task_type": "understanding", "prediction": "changing his pistol to his left hand bob ran out and mounted miller s mare", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0004.flac", "answer": "GET YOUR GUNS BOYS THEY'RE ROBBING THE BANK", "subset": "test_other", "task_type": "understanding", "prediction": "get your guns boys they are robbing the bank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0001.flac", "answer": "WHEN MILLER AND I CROSSED THE BRIDGE THE THREE WERE ON SOME DRY GOODS BOXES AT THE CORNER NEAR THE BANK AND AS SOON AS THEY SAW US WENT RIGHT INTO THE BANK INSTEAD OF WAITING FOR US TO GET THERE", "subset": "test_other", "task_type": "understanding", "prediction": "when miller and i crossed the bridge the three were on some dry goods boxes at the corner near the bank and as soon as they saw us went right into the bank instead of waiting for us to get there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0010.flac", "answer": "EVERY TIME I SAW ANY ONE WITH A BEAD ON ME I WOULD DROP OFF MY HORSE AND TRY TO DRIVE THE SHOOTER INSIDE BUT I COULD NOT SEE IN EVERY DIRECTION", "subset": "test_other", "task_type": "understanding", "prediction": "every time i saw any one with a bead on me i would drop off my horse and try to drive the shooter inside but i could not see in every direction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0013.flac", "answer": "WHAT KEPT YOU SO LONG I ASKED PITTS", "subset": "test_other", "task_type": "understanding", "prediction": "what kept you so long i asked pitts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0003.flac", "answer": "J S ALLEN WHOSE HARDWARE STORE WAS NEAR TRIED TO GO INTO THE BANK BUT MILLER ORDERED HIM AWAY AND HE RAN AROUND THE CORNER SHOUTING", "subset": "test_other", "task_type": "understanding", "prediction": "j s allen whose hardware store was near tried to go into the bank but miller ordered him away and he ran around the corner shouting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0007.flac", "answer": "CHADWELL WOODS AND JIM RODE UP AND JOINED US SHOUTING TO PEOPLE IN THE STREET TO GET INSIDE AND FIRING THEIR PISTOLS TO EMPHASIZE THEIR COMMANDS", "subset": "test_other", "task_type": "understanding", "prediction": "chadwell woods and jim rode up and joined us shouting to the people in the street to get inside and firing their pistols to emphasize their commands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0016.flac", "answer": "THE SHUTTERS WERE CLOSED AND THIS CAUSED BUNKER AN INSTANT'S DELAY THAT WAS ALMOST FATAL PITTS CHASED HIM WITH A BULLET", "subset": "test_other", "task_type": "understanding", "prediction": "the shutters were closed and this caused bunker an instant delay that was almost fatal fitzhugh chased him with a bullet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0000.flac", "answer": "I URGED ON THE BOYS THAT WHATEVER HAPPENED WE SHOULD NOT SHOOT ANY ONE", "subset": "test_other", "task_type": "understanding", "prediction": "i urged on the boys that whatever happened we should not shoot any one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0017.flac", "answer": "THE FIRST ONE MISSED HIM BUT THE SECOND WENT THROUGH HIS RIGHT SHOULDER", "subset": "test_other", "task_type": "understanding", "prediction": "the first one missed him but the second went through his right shoulder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0009.flac", "answer": "MEANTIME THE STREET WAS GETTING UNCOMFORTABLY HOT", "subset": "test_other", "task_type": "understanding", "prediction": "meantime the street was getting uncomfortably hot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0008.flac", "answer": "IF ANY OF OUR PARTY SHOT HIM IT MUST HAVE BEEN WOODS", "subset": "test_other", "task_type": "understanding", "prediction": "if any of our party shot him it must have been woods", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0011.flac", "answer": "DOCTOR WHEELER WHO HAD GONE UPSTAIRS IN THE HOTEL SHOT MILLER AND HE LAY DYING IN THE STREET", "subset": "test_other", "task_type": "understanding", "prediction": "doctor wheeler who had gone upstairs in the hotel shot miller and he laid dying in the street", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0015.flac", "answer": "WHERE'S THE MONEY OUTSIDE THE SAFE BOB ASKED", "subset": "test_other", "task_type": "understanding", "prediction": "where is the money outside the safe bob asked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0006.flac", "answer": "ALMOST AT THIS INSTANT I HEARD A PISTOL SHOT IN THE BANK", "subset": "test_other", "task_type": "understanding", "prediction": "almost at this instant i heard a pistol shot in the bank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7975/280084/7975-280084-0014.flac", "answer": "AS TO THE REST OF THE AFFAIR INSIDE THE BANK I TAKE THE ACCOUNT OF A NORTHFIELD NARRATOR", "subset": "test_other", "task_type": "understanding", "prediction": "as to the rest of the affair inside the bank i take the account of a northfield narrator", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0006.flac", "answer": "I DONE SO AND THEN WE ALL THREE STARTED ON AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "i done so and then we all three started on again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0021.flac", "answer": "WHEN WE STRUCK THE BOAT SHE WAS ABOUT DONE LOADING AND PRETTY SOON SHE GOT OFF", "subset": "test_other", "task_type": "understanding", "prediction": "when we struck the boat she was about done loading and pretty soon she got off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0005.flac", "answer": "GIT ABOARD SAYS THE KING", "subset": "test_other", "task_type": "understanding", "prediction": "get aboard says the king", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0001.flac", "answer": "THE KING'S DUDS WAS ALL BLACK AND HE DID LOOK REAL SWELL AND STARCHY", "subset": "test_other", "task_type": "understanding", "prediction": "the king s duds was all black and he did look real swell and starchy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0002.flac", "answer": "WHY BEFORE HE LOOKED LIKE THE ORNERIEST OLD RIP THAT EVER WAS BUT NOW WHEN HE'D TAKE OFF HIS NEW WHITE BEAVER AND MAKE A BOW AND DO A SMILE HE LOOKED THAT GRAND AND GOOD AND PIOUS THAT YOU'D SAY HE HAD WALKED RIGHT OUT OF THE ARK AND MAYBE WAS OLD LEVITICUS HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "why before he looked like the horniest old rip that ever was but now when he d take off his new white beaver and make a bow and do a smile he looked that grand and good and pious that you d say he had walked right out of the ark and maybe was old leviticus himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0008.flac", "answer": "HE ASKED THE KING WHERE HE WAS GOING AND THE KING TOLD HIM HE'D COME DOWN THE RIVER AND LANDED AT THE OTHER VILLAGE THIS MORNING AND NOW HE WAS GOING UP A FEW MILE TO SEE AN OLD FRIEND ON A FARM UP THERE THE YOUNG FELLOW SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "he asked the king where he was going and the king told him he had come down the river and landed at the other village this morning and now he was going up a few mile to see an old friend on a farm up there the young fellow says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0009.flac", "answer": "BUT THEN I SAYS AGAIN NO I RECKON IT AIN'T HIM OR ELSE HE WOULDN'T BE PADDLING UP THE RIVER YOU AIN'T HIM ARE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "but then i says again no i reckon it ain t him or else he wouldn t be paddling up the river you ain t him are you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0003.flac", "answer": "JIM CLEANED UP THE CANOE AND I GOT MY PADDLE READY", "subset": "test_other", "task_type": "understanding", "prediction": "jim cleaned up the canoe and i got my paddle ready", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0014.flac", "answer": "BUT IT'LL BE LOVELY WISHT I WAS A GOING", "subset": "test_other", "task_type": "understanding", "prediction": "but it ll be lovely wished i was a going", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0017.flac", "answer": "OLD PETER HAD FRIENDS AND THEY AIN'T GOING TO LET THEM COME TO NO HARM", "subset": "test_other", "task_type": "understanding", "prediction": "old peter had friends and they ain t going to let them come to no harm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0010.flac", "answer": "NO MY NAME'S BLODGETT ELEXANDER BLODGETT REVEREND ELEXANDER BLODGETT I S'POSE I MUST SAY AS I'M ONE O THE LORD'S POOR SERVANTS", "subset": "test_other", "task_type": "understanding", "prediction": "no my name is blodgett alexander blodgett reverend alexander blodgett i s'pose i must say as i am one of the lard s poor servants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0024.flac", "answer": "BUT THE KING WAS CA'M HE SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "but the king was calm he says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0023.flac", "answer": "SO THEN THEY WAITED FOR A STEAMBOAT", "subset": "test_other", "task_type": "understanding", "prediction": "so then they waited for a steamboat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0022.flac", "answer": "NOW HUSTLE BACK RIGHT OFF AND FETCH THE DUKE UP HERE AND THE NEW CARPET BAGS", "subset": "test_other", "task_type": "understanding", "prediction": "now hustle back right off and fetch the duke up here and the new carpet bags", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0004.flac", "answer": "WHER YOU BOUND FOR YOUNG MAN", "subset": "test_other", "task_type": "understanding", "prediction": "where are you bound for young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0020.flac", "answer": "WAS PETER WILKS WELL OFF", "subset": "test_other", "task_type": "understanding", "prediction": "was peter wilks well off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0013.flac", "answer": "I'M GOING IN A SHIP NEXT WEDNESDAY FOR RYO JANEERO WHERE MY UNCLE LIVES", "subset": "test_other", "task_type": "understanding", "prediction": "i am going in a ship next wednesday for rio janeiro where my uncle is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0025.flac", "answer": "THEY GIVE A GLANCE AT ONE ANOTHER AND NODDED THEIR HEADS AS MUCH AS TO SAY WHAT D I TELL YOU", "subset": "test_other", "task_type": "understanding", "prediction": "they give a glance at one another and nodded their heads as much as to say would to tell you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0019.flac", "answer": "WHEN THEY'RE DEEP THEY WON'T STOP FOR A HAIL", "subset": "test_other", "task_type": "understanding", "prediction": "when they are deep they wont stop for a hail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0015.flac", "answer": "MARY JANE'S NINETEEN SUSAN'S FIFTEEN AND JOANNA'S ABOUT FOURTEENTHAT'S THE ONE THAT GIVES HERSELF TO GOOD WORKS AND HAS A HARE LIP POOR THINGS", "subset": "test_other", "task_type": "understanding", "prediction": "mary jane is nineteen susan is fifteen and joanna is about fourteen that is the one that gives herself to good works and has a hare lip poor things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0000.flac", "answer": "WHICH WAS SOUND ENOUGH JUDGMENT BUT YOU TAKE THE AVERAGE MAN AND HE WOULDN'T WAIT FOR HIM TO HOWL", "subset": "test_other", "task_type": "understanding", "prediction": "which was sound enough judgment but you take the average man and he wouldnt wait for him to howl", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0011.flac", "answer": "YOU SEE HE WAS PRETTY OLD AND GEORGE'S G'YIRLS WAS TOO YOUNG TO BE MUCH COMPANY FOR HIM EXCEPT MARY JANE THE RED HEADED ONE AND SO HE WAS KINDER LONESOME AFTER GEORGE AND HIS WIFE DIED AND DIDN'T SEEM TO CARE MUCH TO LIVE", "subset": "test_other", "task_type": "understanding", "prediction": "you see he was pretty old and george s girls was too young to be much company for him except mary jane the red headed one and so he was kinder lonesome after george and his wife died and didn t seem to care much to live", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0026.flac", "answer": "THEN ONE OF THEM SAYS KIND OF SOFT AND GENTLE", "subset": "test_other", "task_type": "understanding", "prediction": "then one of them says kind of soft and gentle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0016.flac", "answer": "WELL THEY COULD BE WORSE OFF", "subset": "test_other", "task_type": "understanding", "prediction": "well they could be worse off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0012.flac", "answer": "TOO BAD TOO BAD HE COULDN'T A LIVED TO SEE HIS BROTHERS POOR SOUL", "subset": "test_other", "task_type": "understanding", "prediction": "too bad too bad he couldnt a lived to see his brothers poor soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0018.flac", "answer": "BLAMED IF HE DIDN'T INQUIRE ABOUT EVERYBODY AND EVERYTHING IN THAT BLESSED TOWN AND ALL ABOUT THE WILKSES AND ABOUT PETER'S BUSINESSWHICH WAS A TANNER AND ABOUT GEORGE'SWHICH WAS A CARPENTER AND ABOUT HARVEY'SWHICH WAS A DISSENTERING MINISTER AND SO ON AND SO ON THEN HE SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "blamed if he didn t acquire about everybody and everything in that blessed town and all about the wilkeses and about peter s business which was a tanner and about george s which was a carpenter and about harvey s which was a dissenting minister and so on and so on then he says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163391/3005-163391-0007.flac", "answer": "THE YOUNG CHAP WAS MIGHTY THANKFUL SAID IT WAS TOUGH WORK TOTING HIS BAGGAGE SUCH WEATHER", "subset": "test_other", "task_type": "understanding", "prediction": "the young chap was mighty thankful said it was tough work toting his baggage such weather", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0002.flac", "answer": "THE STILLNESS WAS AWFUL CREEPY AND UNCOMFORTABLE", "subset": "test_other", "task_type": "understanding", "prediction": "the stillness was awful creepy and uncomfortable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0003.flac", "answer": "SHERBURN RUN HIS EYE SLOW ALONG THE CROWD AND WHEREVER IT STRUCK THE PEOPLE TRIED A LITTLE TO OUT GAZE HIM BUT THEY COULDN'T THEY DROPPED THEIR EYES AND LOOKED SNEAKY", "subset": "test_other", "task_type": "understanding", "prediction": "sherburn run his eye slow along the crowd and wherever it struck the people tried a little to outgaze him but they couldnt they dropped their eyes and looked sneaky", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0007.flac", "answer": "YOU DIDN'T WANT TO COME", "subset": "test_other", "task_type": "understanding", "prediction": "you didn t want to come", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0004.flac", "answer": "THE AVERAGE MAN'S A COWARD", "subset": "test_other", "task_type": "understanding", "prediction": "the average man is a coward", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0008.flac", "answer": "BUT A MOB WITHOUT ANY MAN AT THE HEAD OF IT IS BENEATH PITIFULNESS", "subset": "test_other", "task_type": "understanding", "prediction": "but a mob without any man at the head of it is beneath pitifulness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0014.flac", "answer": "SO THEN THE RINGMASTER HE MADE A LITTLE SPEECH AND SAID HE HOPED THERE WOULDN'T BE NO DISTURBANCE AND IF THE MAN WOULD PROMISE HE WOULDN'T MAKE NO MORE TROUBLE HE WOULD LET HIM RIDE IF HE THOUGHT HE COULD STAY ON THE HORSE", "subset": "test_other", "task_type": "understanding", "prediction": "so then the ring master he made a little speech and said he hoped there would n t be no disturbance and if the man would promise he would n t make no more trouble he would let him ride if he thought he could stay on the horse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0009.flac", "answer": "NOW LEAVE AND TAKE YOUR HALF A MAN WITH YOU TOSSING HIS GUN UP ACROSS HIS LEFT ARM AND COCKING IT WHEN HE SAYS THIS", "subset": "test_other", "task_type": "understanding", "prediction": "now leave and take your half a man with ye tossing his gun up across his left arm and cocking it when he says this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0018.flac", "answer": "WHY IT WAS ONE OF HIS OWN MEN", "subset": "test_other", "task_type": "understanding", "prediction": "why it was one of his own men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0016.flac", "answer": "AND THE HORSE A GOING LIKE A HOUSE AFIRE TOO", "subset": "test_other", "task_type": "understanding", "prediction": "and a horse a going like a house afire too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0010.flac", "answer": "THE CROWD WASHED BACK SUDDEN AND THEN BROKE ALL APART AND WENT TEARING OFF EVERY WHICH WAY AND BUCK HARKNESS HE HEELED IT AFTER THEM LOOKING TOLERABLE CHEAP", "subset": "test_other", "task_type": "understanding", "prediction": "the crowd washed back sudden and then broke all apart and went tearing off every which way and buck harkness he heeled it after them looking tolerable cheap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0005.flac", "answer": "BECAUSE THEY'RE AFRAID THE MAN'S FRIENDS WILL SHOOT THEM IN THE BACK IN THE DARKAND IT'S JUST WHAT THEY WOULD DO", "subset": "test_other", "task_type": "understanding", "prediction": "because they are afraid the man s friends will shoot them in the back in the dark and it s just what they would do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0015.flac", "answer": "IT WARN'T FUNNY TO ME THOUGH I WAS ALL OF A TREMBLE TO SEE HIS DANGER", "subset": "test_other", "task_type": "understanding", "prediction": "it warn t funny to me though i was all of a tremble to see his danger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0013.flac", "answer": "AND ONE OR TWO WOMEN BEGUN TO SCREAM", "subset": "test_other", "task_type": "understanding", "prediction": "and one or two women began to scream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0000.flac", "answer": "THEY SWARMED UP IN FRONT OF SHERBURN'S PALINGS AS THICK AS THEY COULD JAM TOGETHER AND YOU COULDN'T HEAR YOURSELF THINK FOR THE NOISE", "subset": "test_other", "task_type": "understanding", "prediction": "they swarmed up in front of sherburne s palings as thick as they could jam together and you couldn t hear yourself think for the noise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0006.flac", "answer": "SO THEY ALWAYS ACQUIT AND THEN A MAN GOES IN THE NIGHT WITH A HUNDRED MASKED COWARDS AT HIS BACK AND LYNCHES THE RASCAL", "subset": "test_other", "task_type": "understanding", "prediction": "so they always acquit and then a man goes in the night with a hundred masked cowards at his back and lynches the rascal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0017.flac", "answer": "HE SHED THEM SO THICK THEY KIND OF CLOGGED UP THE AIR AND ALTOGETHER HE SHED SEVENTEEN SUITS", "subset": "test_other", "task_type": "understanding", "prediction": "he shed them so thick they kind of clogged up the air and altogether he shed seventeen suits", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0012.flac", "answer": "THEY ARGUED AND TRIED TO KEEP HIM OUT BUT HE WOULDN'T LISTEN AND THE WHOLE SHOW COME TO A STANDSTILL", "subset": "test_other", "task_type": "understanding", "prediction": "they argued and tried to keep him out but he wouldn t listen and the whole show come to a his fans do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0001.flac", "answer": "SOME SUNG OUT TEAR DOWN THE FENCE TEAR DOWN THE FENCE", "subset": "test_other", "task_type": "understanding", "prediction": "some sung out tear down the fence tear down the fence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163389/3005-163389-0011.flac", "answer": "YOU CAN'T BE TOO CAREFUL", "subset": "test_other", "task_type": "understanding", "prediction": "you can t be too careful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0020.flac", "answer": "HAS HE COME NO SAYS HER HUSBAND", "subset": "test_other", "task_type": "understanding", "prediction": "has he come no says her husband", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0030.flac", "answer": "THEN I SAYS TO MYSELF S'POSE TOM SAWYER COMES DOWN ON THAT BOAT", "subset": "test_other", "task_type": "understanding", "prediction": "then i says to myself spose tom sawyer comes down on that boat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0003.flac", "answer": "SO THEN SHE STARTED FOR THE HOUSE LEADING ME BY THE HAND AND THE CHILDREN TAGGING AFTER", "subset": "test_other", "task_type": "understanding", "prediction": "so then she started for the house leading me by the hand and the children tagging after", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0000.flac", "answer": "PHELPS WAS ONE OF THESE LITTLE ONE HORSE COTTON PLANTATIONS AND THEY ALL LOOK ALIKE", "subset": "test_other", "task_type": "understanding", "prediction": "phelps was one of these little one horse cotton plantations and they all look alike", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0017.flac", "answer": "CHILDREN DON'T YOU SAY A WORD", "subset": "test_other", "task_type": "understanding", "prediction": "children dont you say a word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0021.flac", "answer": "I CAN'T IMAGINE SAYS THE OLD GENTLEMAN AND I MUST SAY IT MAKES ME DREADFUL UNEASY", "subset": "test_other", "task_type": "understanding", "prediction": "i can imagine says the old gentleman and i must say it makes me dreadful uneasy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0015.flac", "answer": "SO I SAYS TO MYSELF HERE'S ANOTHER PLACE WHERE I GOT TO RESK THE TRUTH", "subset": "test_other", "task_type": "understanding", "prediction": "so i says to myself here is another place where i got to rest the truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0002.flac", "answer": "I OUT WITH A YES'M BEFORE I THOUGHT", "subset": "test_other", "task_type": "understanding", "prediction": "ah out with a yes em fore i thought", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0006.flac", "answer": "AND I THINK HE DIED AFTERWARDS HE WAS A BAPTIST", "subset": "test_other", "task_type": "understanding", "prediction": "and i think he died afterwards he was a baptist", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0011.flac", "answer": "IT WAS KINDER THIN ICE BUT I SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "it was kinder thin ice but i says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0018.flac", "answer": "I SEE I WAS IN A FIX NOW", "subset": "test_other", "task_type": "understanding", "prediction": "i see i was in a fix now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0010.flac", "answer": "WHY CHILD IT LL BE STOLE", "subset": "test_other", "task_type": "understanding", "prediction": "why child it ll be stole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0007.flac", "answer": "YES IT WAS MORTIFICATIONTHAT WAS IT", "subset": "test_other", "task_type": "understanding", "prediction": "yes it was mortification that was it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0019.flac", "answer": "MISSUS PHELPS SHE JUMPS FOR HIM AND SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "mrs phelps she jumps for him and says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0014.flac", "answer": "I SEE IT WARN'T A BIT OF USE TO TRY TO GO AHEAD I'D GOT TO THROW UP MY HAND", "subset": "test_other", "task_type": "understanding", "prediction": "i see it warn t a bit of use to try to go ahead i d got to throw up my hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0008.flac", "answer": "YOUR UNCLE'S BEEN UP TO THE TOWN EVERY DAY TO FETCH YOU", "subset": "test_other", "task_type": "understanding", "prediction": "your uncle has been up to the town every day to fetch you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0001.flac", "answer": "I WENT AROUND AND CLUMB OVER THE BACK STILE BY THE ASH HOPPER AND STARTED FOR THE KITCHEN", "subset": "test_other", "task_type": "understanding", "prediction": "i went around and climbed over the back stile by the ash hopper and started for the kitchen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0027.flac", "answer": "I HAIN'T NO IDEA WHO IS IT", "subset": "test_other", "task_type": "understanding", "prediction": "i hain t no idee who is it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0029.flac", "answer": "BEING TOM SAWYER WAS EASY AND COMFORTABLE AND IT STAYED EASY AND COMFORTABLE TILL BY AND BY I HEAR A STEAMBOAT COUGHING ALONG DOWN THE RIVER", "subset": "test_other", "task_type": "understanding", "prediction": "being tom sawyer was easy and comfortable and it stayed easy and comfortable till by and by i hear a steamboat coughing along down the river", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0025.flac", "answer": "WHY SILAS LOOK YONDER UP THE ROAD AIN'T THAT SOMEBODY COMING", "subset": "test_other", "task_type": "understanding", "prediction": "why silas look yonder up the road ain t that somebody coming", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0009.flac", "answer": "YOU MUST A MET HIM ON THE ROAD DIDN'T YOU OLDISH MAN WITH A", "subset": "test_other", "task_type": "understanding", "prediction": "you must a met him on the road didn t you oldish man with a", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0022.flac", "answer": "UNEASY SHE SAYS I'M READY TO GO DISTRACTED", "subset": "test_other", "task_type": "understanding", "prediction": "uneasy she says i am ready to go distracted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0023.flac", "answer": "HE MUST A COME AND YOU'VE MISSED HIM ALONG THE ROAD", "subset": "test_other", "task_type": "understanding", "prediction": "he must a come and youve missed him along the road", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0026.flac", "answer": "THE OLD GENTLEMAN STARED AND SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "the old gentleman stared and says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0012.flac", "answer": "I HAD MY MIND ON THE CHILDREN ALL THE TIME I WANTED TO GET THEM OUT TO ONE SIDE AND PUMP THEM A LITTLE AND FIND OUT WHO I WAS", "subset": "test_other", "task_type": "understanding", "prediction": "i had my mind on the children all the time i wanted to get them out to one side and pump them a little and find out who i was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0004.flac", "answer": "WHEN WE GOT THERE SHE SET ME DOWN IN A SPLIT BOTTOMED CHAIR AND SET HERSELF DOWN ON A LITTLE LOW STOOL IN FRONT OF ME HOLDING BOTH OF MY HANDS AND SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "when we got there she set me down in a split bottom chair and set herself down on a little low stool in front of me holding both of my hands and says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0013.flac", "answer": "PRETTY SOON SHE MADE THE COLD CHILLS STREAK ALL DOWN MY BACK BECAUSE SHE SAYS", "subset": "test_other", "task_type": "understanding", "prediction": "pretty soon she made the cold chill streak all down my back because she says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0016.flac", "answer": "I OPENED MY MOUTH TO BEGIN BUT SHE GRABBED ME AND HUSTLED ME IN BEHIND THE BED AND SAYS HERE HE COMES", "subset": "test_other", "task_type": "understanding", "prediction": "i opened my mouth to begin but she grabbed me and hustled me in behind the bed and says here he comes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0005.flac", "answer": "WELL IT'S LUCKY BECAUSE SOMETIMES PEOPLE DO GET HURT", "subset": "test_other", "task_type": "understanding", "prediction": "well it is lucky because sometimes people do get hurt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0028.flac", "answer": "IT'S TOM SAWYER", "subset": "test_other", "task_type": "understanding", "prediction": "is tom sawyer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163399/3005-163399-0024.flac", "answer": "OH DON'T DISTRESS ME ANY MORE'N I'M ALREADY DISTRESSED", "subset": "test_other", "task_type": "understanding", "prediction": "oh dont distress me any more than i am already distressed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0001.flac", "answer": "THE PEOPLE MOST KILLED THEMSELVES LAUGHING AND WHEN THE KING GOT DONE CAPERING AND CAPERED OFF BEHIND THE SCENES THEY ROARED AND CLAPPED AND STORMED AND HAW HAWED TILL HE COME BACK AND DONE IT OVER AGAIN AND AFTER THAT THEY MADE HIM DO IT ANOTHER TIME", "subset": "test_other", "task_type": "understanding", "prediction": "the people most killed themselves laughing and when the king got done capering and capered off behind the scenes they roared and clapped and stormed and haw hawed till he come back and done it over again and after that they made him do it another time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0004.flac", "answer": "EVERYBODY SINGS OUT SOLD", "subset": "test_other", "task_type": "understanding", "prediction": "everybody sings out sold", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0029.flac", "answer": "I LAY I MAKE YOU MINE", "subset": "test_other", "task_type": "understanding", "prediction": "i lay i make you mine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0023.flac", "answer": "NOW DE DUKE HE'S A TOLERBLE LIKELY MAN IN SOME WAYS", "subset": "test_other", "task_type": "understanding", "prediction": "now de duke he is a tolerable like the man in some ways", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0000.flac", "answer": "ANDBUT NEVER MIND THE REST OF HIS OUTFIT IT WAS JUST WILD BUT IT WAS AWFUL FUNNY", "subset": "test_other", "task_type": "understanding", "prediction": "and but never mind the rest of his outfit it was jist wild but it was awful funny", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0028.flac", "answer": "DOAN YOU HEAR ME SHET DE DO", "subset": "test_other", "task_type": "understanding", "prediction": "doan you hear me shut de do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0015.flac", "answer": "AND LOOK AT CHARLES SECOND AND LOUIS FOURTEEN AND LOUIS FIFTEEN AND JAMES SECOND AND EDWARD SECOND AND RICHARD THIRD AND FORTY MORE BESIDES ALL THEM SAXON HEPTARCHIES THAT USED TO RIP AROUND SO IN OLD TIMES AND RAISE CAIN", "subset": "test_other", "task_type": "understanding", "prediction": "and look at charles second and lewis fourteen and lewis fifteen and james second and edward second and richard third and forty more besides all them saxon heptarchies that used to rip around so in old times and raise cain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0005.flac", "answer": "BUT A BIG FINE LOOKING MAN JUMPS UP ON A BENCH AND SHOUTS HOLD ON", "subset": "test_other", "task_type": "understanding", "prediction": "but a big fine looking man jumps up on a bench and shouts hold on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0010.flac", "answer": "WE NEVER SHOWED A LIGHT TILL WE WAS ABOUT TEN MILE BELOW THE VILLAGE", "subset": "test_other", "task_type": "understanding", "prediction": "we never showed a light till we was about ten mile below the village", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0027.flac", "answer": "HE WAS OFTEN MOANING AND MOURNING THAT WAY NIGHTS WHEN HE JUDGED I WAS ASLEEP AND SAYING PO LITTLE LIZABETH", "subset": "test_other", "task_type": "understanding", "prediction": "he was often moaning and mourning that way nights when he judged i was asleep and saying po little lizbeth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0008.flac", "answer": "YOU BET IT IS THE JEDGE IS RIGHT EVERYBODY SINGS OUT", "subset": "test_other", "task_type": "understanding", "prediction": "you bet it is the judge is right everybody sings out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0003.flac", "answer": "THE DUKE SAYS YES", "subset": "test_other", "task_type": "understanding", "prediction": "the duke says yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0007.flac", "answer": "WHAT WE WANT IS TO GO OUT OF HERE QUIET AND TALK THIS SHOW UP AND SELL THE REST OF THE TOWN", "subset": "test_other", "task_type": "understanding", "prediction": "what we want is to go out of here quiet and talk this show up and sell the rest of the town", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0030.flac", "answer": "JIS AS LOUD AS I COULD YELL", "subset": "test_other", "task_type": "understanding", "prediction": "just as loud as i could yell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0006.flac", "answer": "JUST A WORD GENTLEMEN THEY STOPPED TO LISTEN", "subset": "test_other", "task_type": "understanding", "prediction": "just a word gentlemen they stopped to listen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0026.flac", "answer": "IT DON'T SEEM NATURAL BUT I RECKON IT'S SO", "subset": "test_other", "task_type": "understanding", "prediction": "it don t seem natural but i reckon it so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0022.flac", "answer": "WELL THEY ALL DO JIM", "subset": "test_other", "task_type": "understanding", "prediction": "well they all do jim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0002.flac", "answer": "TWENTY PEOPLE SINGS OUT", "subset": "test_other", "task_type": "understanding", "prediction": "twenty people sings out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0021.flac", "answer": "TAKE THEM ALL AROUND THEY'RE A MIGHTY ORNERY LOT IT'S THE WAY THEY'RE RAISED", "subset": "test_other", "task_type": "understanding", "prediction": "take them all around they are a mighty ornery lot it is the way they are raised", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0009.flac", "answer": "WE STRUCK THE RAFT AT THE SAME TIME AND IN LESS THAN TWO SECONDS WE WAS GLIDING DOWN STREAM ALL DARK AND STILL AND EDGING TOWARDS THE MIDDLE OF THE RIVER NOBODY SAYING A WORD", "subset": "test_other", "task_type": "understanding", "prediction": "we struck the raft at the same time and in less than two seconds we was gliding down stream all dark and still and edging towards the middle of the river nobody saying a word", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0020.flac", "answer": "ALL I SAY IS KINGS IS KINGS AND YOU GOT TO MAKE ALLOWANCES", "subset": "test_other", "task_type": "understanding", "prediction": "all i say is kings is kings and you got to make allowances", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0011.flac", "answer": "GREENHORNS FLATHEADS", "subset": "test_other", "task_type": "understanding", "prediction": "greenhorns flatheads", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0019.flac", "answer": "S'POSE HE OPENED HIS MOUTHWHAT THEN", "subset": "test_other", "task_type": "understanding", "prediction": "spose he opened his mouth what then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0024.flac", "answer": "THIS ONE'S A MIDDLING HARD LOT FOR A DUKE", "subset": "test_other", "task_type": "understanding", "prediction": "this one is a middling hard lot for a duke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0016.flac", "answer": "MY YOU OUGHT TO SEEN OLD HENRY THE EIGHT WHEN HE WAS IN BLOOM HE WAS A BLOSSOM", "subset": "test_other", "task_type": "understanding", "prediction": "my you ought to seen old henry the eighth when he was in bloom he was a blossom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0012.flac", "answer": "NO I SAYS IT DON'T", "subset": "test_other", "task_type": "understanding", "prediction": "no i says it dont", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0018.flac", "answer": "WELL HENRY HE TAKES A NOTION HE WANTS TO GET UP SOME TROUBLE WITH THIS COUNTRY", "subset": "test_other", "task_type": "understanding", "prediction": "well henry he takes a notion he wants to get up some trouble with this country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0017.flac", "answer": "RING UP FAIR ROSAMUN", "subset": "test_other", "task_type": "understanding", "prediction": "ring up fair rosamond", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0014.flac", "answer": "WELL THAT'S WHAT I'M A SAYING ALL KINGS IS MOSTLY RAPSCALLIONS AS FUR AS I CAN MAKE OUT IS DAT SO", "subset": "test_other", "task_type": "understanding", "prediction": "well that s what i m a sayin all kings is mostly rapscallions as fur as i can make out is dat so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0025.flac", "answer": "WHEN I WAKED UP JUST AT DAYBREAK HE WAS SITTING THERE WITH HIS HEAD DOWN BETWIXT HIS KNEES MOANING AND MOURNING TO HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "when i waked up jist at daybreak he was sitting there with his head down betwixt his knees moaning and mourning to himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3005/163390/3005-163390-0013.flac", "answer": "WELL IT DON'T BECAUSE IT'S IN THE BREED I RECKON THEY'RE ALL ALIKE", "subset": "test_other", "task_type": "understanding", "prediction": "well it dont because its in the breed i reckon they are all alive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0000.flac", "answer": "LEVIN DID NOT CARE TO EAT AND HE WAS NOT SMOKING HE DID NOT WANT TO JOIN HIS OWN FRIENDS THAT IS SERGEY IVANOVITCH STEPAN ARKADYEVITCH SVIAZHSKY AND THE REST BECAUSE VRONSKY IN HIS EQUERRY'S UNIFORM WAS STANDING WITH THEM IN EAGER CONVERSATION", "subset": "test_other", "task_type": "understanding", "prediction": "levin did not care to eat and he was not smoking he did not want to join his own friends that is sergey ivanovitch stepan arkadyevitch sviazhsky and the rest because vronsky in his equerry s uniform was standing with them in eager conversation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0015.flac", "answer": "IF WE'RE LAYING OUT A GARDEN PLANNING ONE BEFORE THE HOUSE YOU KNOW AND THERE YOU'VE A TREE THAT'S STOOD FOR CENTURIES IN THE VERY SPOT OLD AND GNARLED IT MAY BE AND YET YOU DON'T CUT DOWN THE OLD FELLOW TO MAKE ROOM FOR THE FLOWERBEDS BUT LAY OUT YOUR BEDS SO AS TO TAKE ADVANTAGE OF THE TREE", "subset": "test_other", "task_type": "understanding", "prediction": "if we are laying out a garden planning one before the house you know and there you have a tree that stood a century in the very spot old and gnarled it may be and yet you do not cut down the old fellow to make room for the flower beds but lay out your beds so as to take advantage of the tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0003.flac", "answer": "I HAVE TOLD HIM SO BUT IT MAKES NO DIFFERENCE ONLY THINK OF IT", "subset": "test_other", "task_type": "understanding", "prediction": "i have told him so but it makes no difference only think of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0004.flac", "answer": "THESE PERSONS WERE UNMISTAKABLY SEEKING A PLACE WHERE THEY COULD TALK WITHOUT BEING OVERHEARD", "subset": "test_other", "task_type": "understanding", "prediction": "these persons were unmistakably seeking a place where they could talk without being overheard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0014.flac", "answer": "THAT IT MAY BE BUT STILL IT OUGHT TO BE TREATED A LITTLE MORE RESPECTFULLY", "subset": "test_other", "task_type": "understanding", "prediction": "that it may be but still it ought to be treated a little more respectfully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0023.flac", "answer": "HERE YOU'VE THOUSANDS OF LIMES AND EACH WOULD MAKE TWO GOOD BUNDLES OF BARK", "subset": "test_other", "task_type": "understanding", "prediction": "here you have thousands of limes and each would make two good bundles of bark", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0010.flac", "answer": "THEN TOO ONE MUST KEEP UP CONNECTIONS", "subset": "test_other", "task_type": "understanding", "prediction": "then too one must keep up connections", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0008.flac", "answer": "WHY WHAT IS THERE TO UNDERSTAND", "subset": "test_other", "task_type": "understanding", "prediction": "why what is there to understand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0022.flac", "answer": "TO MY THINKING I'D CUT DOWN THAT LIME TREE", "subset": "test_other", "task_type": "understanding", "prediction": "to my thinking id cut down that lime tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0021.flac", "answer": "WE WALKED ABOUT THE FIELDS AND THE GARDEN NO SAID HE STEPAN VASSILIEVITCH EVERYTHING'S WELL LOOKED AFTER BUT YOUR GARDEN'S NEGLECTED", "subset": "test_other", "task_type": "understanding", "prediction": "we walked about the fields and the garden no said he stepan mihalitch everything is well looked after but your garden is neglected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0001.flac", "answer": "HE WENT TO THE WINDOW AND SAT DOWN SCANNING THE GROUPS AND LISTENING TO WHAT WAS BEING SAID AROUND HIM", "subset": "test_other", "task_type": "understanding", "prediction": "he went to the window and sat down scanning the groups and listening to what was being said around him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0002.flac", "answer": "HE'S SUCH A BLACKGUARD", "subset": "test_other", "task_type": "understanding", "prediction": "he is such a blackguard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0005.flac", "answer": "SHALL WE GO ON YOUR EXCELLENCY FINE CHAMPAGNE", "subset": "test_other", "task_type": "understanding", "prediction": "shall we go on your excellency find champagne", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0028.flac", "answer": "SAID LEVIN RETURNING TO A THOUGHT THAT HAD STRUCK HIM", "subset": "test_other", "task_type": "understanding", "prediction": "said levin returning to a thought that had struck him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0013.flac", "answer": "THEY'RE PROPRIETORS OF A SORT BUT WE'RE THE LANDOWNERS", "subset": "test_other", "task_type": "understanding", "prediction": "they are proprietors of a sort but we are the landowners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0027.flac", "answer": "WHY DON'T WE CUT DOWN OUR PARKS FOR TIMBER", "subset": "test_other", "task_type": "understanding", "prediction": "why dont we cut down our parks for timber", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0012.flac", "answer": "AND THEN TO TELL THE TRUTH THERE'S ONE'S OWN INTERESTS", "subset": "test_other", "task_type": "understanding", "prediction": "and then to tell the truth there is one s own interests", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0026.flac", "answer": "THE LANDOWNER CHUCKLED UNDER HIS WHITE MUSTACHES", "subset": "test_other", "task_type": "understanding", "prediction": "the landowner chuckled under his white moustaches", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0030.flac", "answer": "THERE'S THE PEASANTS TOO I WONDER AT THEM SOMETIMES ANY GOOD PEASANT TRIES TO TAKE ALL THE LAND HE CAN", "subset": "test_other", "task_type": "understanding", "prediction": "there is the peasants too i wonder at them sometimes any good peasant tries to take all the land he can", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0020.flac", "answer": "SO THERE'LL BE NO ONE TO KEEP IT UP AND YET ONE DOES IT", "subset": "test_other", "task_type": "understanding", "prediction": "so there will be no one to keep it up and yet one does it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0031.flac", "answer": "WITHOUT A RETURN TOO AT A SIMPLE LOSS", "subset": "test_other", "task_type": "understanding", "prediction": "without a return too at a simple loss", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0006.flac", "answer": "LAST YEAR AT OUR DISTRICT MARSHAL NIKOLAY IVANOVITCH'S", "subset": "test_other", "task_type": "understanding", "prediction": "last year at our district marshal nikolai ivanovichs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0011.flac", "answer": "IT'S A MORAL OBLIGATION OF A SORT", "subset": "test_other", "task_type": "understanding", "prediction": "its a moral obligation of a sort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0025.flac", "answer": "YES IT'S RATHER STRANGE HE WENT ON", "subset": "test_other", "task_type": "understanding", "prediction": "yes it is rather strange he went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0019.flac", "answer": "AND WHAT'S MORE THE LANDOWNER WENT ON LEANING HIS ELBOWS ON THE WINDOW AND CHATTING ON MY SON I MUST TELL YOU HAS NO TASTE FOR IT", "subset": "test_other", "task_type": "understanding", "prediction": "and once more the landowner went on leaning his elbows on the window and chatting on my son i must tell you has no taste for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0029.flac", "answer": "THERE'S A CLASS INSTINCT TOO OF WHAT ONE OUGHT AND OUGHTN'T TO DO", "subset": "test_other", "task_type": "understanding", "prediction": "there is a class instinct too of what one ought and ought not to do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0018.flac", "answer": "OH WELL ONE DOES IT WHAT WOULD YOU HAVE", "subset": "test_other", "task_type": "understanding", "prediction": "oh well one does it what would you have", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0017.flac", "answer": "BUT ONE'S WORK IS THROWN IN FOR NOTHING", "subset": "test_other", "task_type": "understanding", "prediction": "but one s work is thrown in for nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0007.flac", "answer": "OH STILL JUST THE SAME ALWAYS AT A LOSS THE LANDOWNER ANSWERED WITH A RESIGNED SMILE BUT WITH AN EXPRESSION OF SERENITY AND CONVICTION THAT SO IT MUST BE", "subset": "test_other", "task_type": "understanding", "prediction": "oh still just the same always at a loss the landowner answered with a resigned smile but with an expression of serenity and conviction that so it must be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0016.flac", "answer": "WELL AND HOW IS YOUR LAND DOING", "subset": "test_other", "task_type": "understanding", "prediction": "well and how is your land doing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0024.flac", "answer": "YOU'RE MARRIED I'VE HEARD SAID THE LANDOWNER", "subset": "test_other", "task_type": "understanding", "prediction": "you are married i heard said the landowner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41169/5442-41169-0009.flac", "answer": "THERE'S NO MEANING IN IT AT ALL", "subset": "test_other", "task_type": "understanding", "prediction": "there is no meaning in it at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0006.flac", "answer": "BRIGHT AND NATTY WERE THE CHINTZ CURTAINS AND THE LITTLE TOILET SET OUT NOT INELEGANTLY AND HER PET PIPING GOLDFINCH ASLEEP ON HIS PERCH WITH HIS BIT OF SUGAR BETWEEN THE WIRES OF HIS CAGE HER PILLOW SO WHITE AND UNPRESSED WITH ITS LITTLE EDGING OF LACE", "subset": "test_other", "task_type": "understanding", "prediction": "bright and natty were the chintz curtains and the little toilet set out not inelegantly and her pet piping goldfinch asleep on his perch with his bit of sugar between the wires of his cage her pillow so white and unpressed with its little edging of lace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0004.flac", "answer": "OH FRIGHTFUL FRIGHTFUL", "subset": "test_other", "task_type": "understanding", "prediction": "oh frightful frightful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0016.flac", "answer": "HERE WERE THE FLOW OF SOUL AND OF STOUT LONG PIPES LONG YARNS AND TOLERABLY LONG CREDITS AND THE HUMBLE SCAPEGRACES OF THE TOWN RESORTED THITHER FOR THE PLEASURES OF A CLUB LIFE AND OFTEN REVELLED DEEP INTO THE SMALL HOURS OF THE MORNING", "subset": "test_other", "task_type": "understanding", "prediction": "here were the flow of soul and of stout long pipes long yarns and tolerably long credits and the humblest cape graces of the town resorted thither for the pleasures of a club life and often revelled deep into the small hours of the morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0017.flac", "answer": "LOSE NO TIME AND I'LL GIVE YOU HALF A CROWN", "subset": "test_other", "task_type": "understanding", "prediction": "lose no time and i will give you half a crown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0007.flac", "answer": "WHEN HE CAME BACK TO THE DRAWING ROOM A TOILET BOTTLE OF EAU DE COLOGNE IN HIS HAND WITH HER LACE HANDKERCHIEF HE BATHED HER TEMPLES AND FOREHEAD", "subset": "test_other", "task_type": "understanding", "prediction": "when he came back to the drawing room a toilet bottle of eau de cologne in his hand with her lace handkerchief he bathed her temples and forehead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0005.flac", "answer": "STANLEY STANLEY IT WOULD BE MERCY TO KILL ME SHE BROKE OUT AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "stanley stanley it would be mercy to kill me she broke her again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0001.flac", "answer": "THERE WAS A VERY NATURAL SAVAGERY AND DEJECTION THERE AND A WILD LEER IN HIS YELLOW EYES RACHEL SAT DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "there was a very natural savagery and dejection there and a wild lure in his yellow eyes rachel sat down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0008.flac", "answer": "THERE WAS NOTHING VERY BROTHERLY IN HIS LOOK AS HE PEERED INTO HER PALE SHARP FEATURES DURING THE PROCESS", "subset": "test_other", "task_type": "understanding", "prediction": "there was nothing very brotherly in his look as he peered into her pale sharp features during the process", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0000.flac", "answer": "CAPTAIN LAKE DID NOT LOOK AT ALL LIKE A LONDON DANDY NOW", "subset": "test_other", "task_type": "understanding", "prediction": "captain lake did not look at all like a london dandy now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0009.flac", "answer": "THERE DON'T MIND ME SHE SAID SHARPLY AND GETTING UP SHE LOOKED DOWN AT HER DRESS AND THIN SHOES AND SEEMING TO RECOLLECT HERSELF SHE TOOK THE CANDLE HE HAD JUST SET DOWN AND WENT SWIFTLY TO HER ROOM", "subset": "test_other", "task_type": "understanding", "prediction": "there don not mind me she said sharply and getting up she looked down at her dress and thin shoes and seeming to recollect herself she took the candle he had just set down and went swiftly to her room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0012.flac", "answer": "I'LL STAY HERE THAT IS IN THE DRAWING ROOM SHE ANSWERED AND THE FACE WAS WITHDRAWN", "subset": "test_other", "task_type": "understanding", "prediction": "i will stay here that is in the drawing room she answered and the face was withdrawn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0019.flac", "answer": "IF I THOUGHT YOU'D FAIL ME NOW TAMAR I SHOULD NEVER COME BACK GOOD NIGHT TAMAR", "subset": "test_other", "task_type": "understanding", "prediction": "if i thought you would fail me now tamar i should never come back good night tamar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0011.flac", "answer": "RACHEL LAKE RACHEL LAKE WHAT ARE YOU NOW", "subset": "test_other", "task_type": "understanding", "prediction": "rachel leek rachel leek what are you now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0015.flac", "answer": "BUT LUKE WAS NOT THERE AND CAPTAIN LAKE RECOLLECTING HIS HABITS AND HIS HAUNT HURRIED ON TO THE SILVER LION WHICH HAS ITS GABLE TOWARDS THE COMMON ONLY ABOUT A HUNDRED STEPS AWAY FOR DISTANCES ARE NOT GREAT IN GYLINGDEN", "subset": "test_other", "task_type": "understanding", "prediction": "but luke was none there and captain lake recollecting his habits and his haunt hurried on to the silver lion which has its gable towards the common only about a hundred steps away for distances are not great in gillingden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0002.flac", "answer": "A SLAVE ONLY THINK A SLAVE", "subset": "test_other", "task_type": "understanding", "prediction": "a slave only think a slave", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0013.flac", "answer": "HE SLACKENED HIS PACE AND TAPPED SHARPLY AT THE LITTLE WINDOW OF THAT MODEST POST OFFICE AT WHICH THE YOUNG LADIES IN THE PONY CARRIAGE HAD PULLED UP THE DAY BEFORE AND WITHIN WHICH LUKE WAGGOT WAS WONT TO SLEEP IN A SORT OF WOODEN BOX THAT FOLDED UP AND APPEARED TO BE A CHEST OF DRAWERS ALL DAY", "subset": "test_other", "task_type": "understanding", "prediction": "he slackened his pace and tapped sharply at the little window of that modest post office at which the young ladies in the pony carriage had pulled up the day before and within which luke waggett was wont to sleep in a sort of wooden box that folded up and appeared to be a chest of drawers all day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0018.flac", "answer": "LUKE STUCK ON HIS GREASY WIDEAWAKE AND IN A FEW MINUTES MORE THE DOG CART WAS TRUNDLED OUT INTO THE LANE AND THE HORSE HARNESSED WENT BETWEEN THE SHAFTS WITH THAT WONDERFUL CHEERFULNESS WITH WHICH THEY BEAR TO BE CALLED UP UNDER STARTLING CIRCUMSTANCES AT UNSEASONABLE HOURS", "subset": "test_other", "task_type": "understanding", "prediction": "luke stuck on his greasy wideawake and in a few minutes more the dogcart was trundled out into the lane and the horse harnessed went between the shafts with that wonderful cheerfulness with which they bear to be called up under startling circumstances and unseasonable hours", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0003.flac", "answer": "OH FRIGHTFUL FRIGHTFUL IS IT A DREAM", "subset": "test_other", "task_type": "understanding", "prediction": "oh frightful frightful is it a dream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0014.flac", "answer": "LUKE TOOK CARE OF MISTER LARKIN'S DOGS AND GROOMED MISTER WYLDER'S HORSE AND CLEANED UP HIS DOG CART FOR MARK BEING CLOSE ABOUT MONEY AND FINDING THAT THE THING WAS TO BE DONE MORE CHEAPLY THAT WAY PUT UP HIS HORSE AND DOG CART IN THE POST OFFICE PREMISES AND SO EVADED THE LIVERY CHARGES OF THE BRANDON ARMS", "subset": "test_other", "task_type": "understanding", "prediction": "luke took care of mr larkins dogs and groomed mr wilder s horse and cleaned up his dogcart for mark being close about money and finding that the thing was to be done more cheaply that way put up his horse and dogcart in the post office premises and so evaded the livery charges of the brandon arms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/32873/5442-32873-0010.flac", "answer": "AND SHE THREW BACK HER VEIL AND GOING HURRIEDLY TO THE TOILET MECHANICALLY SURVEYED HERSELF IN THE GLASS", "subset": "test_other", "task_type": "understanding", "prediction": "and she threw back her veil and going hurriedly to the toilet mechanically surveyed herself in the glass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0016.flac", "answer": "HAVING PUT IT IN HE RECOLLECTED THAT HE OUGHT TO HAVE THRUST HIS LEFT HAND TOO AND SO HE THRUST IT IN THOUGH TOO LATE AND STILL MORE OVERCOME WITH CONFUSION HE BEAT A HASTY RETREAT INTO THE BACKGROUND", "subset": "test_other", "task_type": "understanding", "prediction": "having put it in he recollected that he ought to have thrust his left hand too and so he thrust it in though too late and still more overcome with confusion he beat a hasty retreat into the background", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0009.flac", "answer": "HE FORGOT AS SERGEY IVANOVITCH EXPLAINED TO HIM AFTERWARDS THIS SYLLOGISM THAT IT WAS NECESSARY FOR THE PUBLIC GOOD TO GET RID OF THE MARSHAL OF THE PROVINCE THAT TO GET RID OF THE MARSHAL IT WAS NECESSARY TO HAVE A MAJORITY OF VOTES THAT TO GET A MAJORITY OF VOTES IT WAS NECESSARY TO SECURE FLEROV'S RIGHT TO VOTE THAT TO SECURE THE RECOGNITION OF FLEROV'S RIGHT TO VOTE THEY MUST DECIDE ON THE INTERPRETATION TO BE PUT ON THE ACT", "subset": "test_other", "task_type": "understanding", "prediction": "he forgot as sergey ivanovitch explained to him afterwards this syllogism that it was necessary for the public good to get rid of the marshal of the province that to get rid of the marshal it was necessary to have a majority of votes that to get a majority of votes it was necessary to secure flerov's right to vote that to secure the recognition of flerov's right to vote they must decide on the interpretation to be put on the act", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0003.flac", "answer": "SHOUTS WERE RAISED AND FOR A MOMENT ALL WAS CONFUSION SO THAT THE MARSHAL OF THE PROVINCE HAD TO CALL FOR ORDER A BALLOT", "subset": "test_other", "task_type": "understanding", "prediction": "shouts were raised and for a moment all was confusion so that the marshal of the province had to call for order a ballad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0004.flac", "answer": "WE SHED OUR BLOOD FOR OUR COUNTRY", "subset": "test_other", "task_type": "understanding", "prediction": "we shed our blood for our country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0026.flac", "answer": "TWO NOBLE GENTLEMEN WHO HAD A WEAKNESS FOR STRONG DRINK HAD BEEN MADE DRUNK BY THE PARTISANS OF SNETKOV AND A THIRD HAD BEEN ROBBED OF HIS UNIFORM", "subset": "test_other", "task_type": "understanding", "prediction": "two noble gentlemen who had a weakness for strong drink had been made drunk by the partisans of snetkov and a third had been robbed of his uniform", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0007.flac", "answer": "THEY EXPRESSED THE MOST IMPLACABLE HATRED", "subset": "test_other", "task_type": "understanding", "prediction": "they expressed the most implacable hatred", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0015.flac", "answer": "THAT IS A MATTER FOR EACH MAN'S OWN DECISION HE SAID SEVERELY", "subset": "test_other", "task_type": "understanding", "prediction": "that is a matter for each man s own decision he said severely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0024.flac", "answer": "AND THE MARSHAL DISAPPEARED THROUGH A SIDE DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "and the marshal disappeared through a side door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0021.flac", "answer": "IN REPLY SNETKOV SPOKE OF THE TRUST THE NOBLEMEN OF THE PROVINCE HAD PLACED IN HIM THE AFFECTION THEY HAD SHOWN HIM WHICH HE DID NOT DESERVE AS HIS ONLY MERIT HAD BEEN HIS ATTACHMENT TO THE NOBILITY TO WHOM HE HAD DEVOTED TWELVE YEARS OF SERVICE", "subset": "test_other", "task_type": "understanding", "prediction": "in reply snetkov spoke of the trust the noblemen of the province had placed in him the affection they had shown him which he did not deserve as his only merit had been his attachment to the nobility to whom he had devoted twelve years of service", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0017.flac", "answer": "A HUNDRED AND TWENTY SIX FOR ADMISSION NINETY EIGHT AGAINST", "subset": "test_other", "task_type": "understanding", "prediction": "a hundred and twenty six for admission ninety eight against", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0012.flac", "answer": "HE PARTICULARLY LIKED THE WAY ONE GRAY WHISKERED WAITER WHO SHOWED HIS SCORN FOR THE OTHER YOUNGER ONES AND WAS JEERED AT BY THEM WAS TEACHING THEM HOW TO FOLD UP NAPKINS PROPERLY", "subset": "test_other", "task_type": "understanding", "prediction": "he particularly liked the way one grey whiskered waiter who showed a scorn for the other younger ones and was jeered at by them was teaching them how to fold up napkins properly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0025.flac", "answer": "THEY WERE TO PROCEED IMMEDIATELY TO THE ELECTION", "subset": "test_other", "task_type": "understanding", "prediction": "they were to proceed immediately to the election", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0023.flac", "answer": "IF THERE ARE MEN YOUNGER AND MORE DESERVING THAN I LET THEM SERVE", "subset": "test_other", "task_type": "understanding", "prediction": "if there are men younger and more deserving than i let them serve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0027.flac", "answer": "ON LEARNING THIS THE NEW PARTY HAD MADE HASTE DURING THE DISPUTE ABOUT FLEROV TO SEND SOME OF THEIR MEN IN A SLEDGE TO CLOTHE THE STRIPPED GENTLEMAN AND TO BRING ALONG ONE OF THE INTOXICATED TO THE MEETING", "subset": "test_other", "task_type": "understanding", "prediction": "on learning this the new party had made haste during the dispute about fleurov to send some of their men in a sledge to clothe the stripped gentleman and to bring along one of the intoxicated to the meeting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0000.flac", "answer": "THE ACT SAID THAT IN CASE OF DIFFERENCE OF OPINION THERE MUST BE A BALLOT", "subset": "test_other", "task_type": "understanding", "prediction": "the act said that in case of difference of opinion there must be a ballot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0001.flac", "answer": "HE WENT UP TO THE TABLE AND STRIKING IT WITH HIS FINGER RING HE SHOUTED LOUDLY A BALLOT", "subset": "test_other", "task_type": "understanding", "prediction": "he went up to the table and striking it with his finger ring he shouted loudly a ballad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0011.flac", "answer": "TO ESCAPE FROM THIS PAINFUL FEELING HE WENT AWAY INTO THE OTHER ROOM WHERE THERE WAS NOBODY EXCEPT THE WAITERS AT THE REFRESHMENT BAR", "subset": "test_other", "task_type": "understanding", "prediction": "to escape from this painful feeling he went away into the other room where there was nobody except the waiters at the refreshment bar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0010.flac", "answer": "BUT LEVIN FORGOT ALL THAT AND IT WAS PAINFUL TO HIM TO SEE ALL THESE EXCELLENT PERSONS FOR WHOM HE HAD A RESPECT IN SUCH AN UNPLEASANT AND VICIOUS STATE OF EXCITEMENT", "subset": "test_other", "task_type": "understanding", "prediction": "but levin forgot all that and it was painful to him to see all these excellent persons for whom he had a respect in such an unpleasant and vicious state of excitement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0018.flac", "answer": "SANG OUT THE VOICE OF THE SECRETARY WHO COULD NOT PRONOUNCE THE LETTER R", "subset": "test_other", "task_type": "understanding", "prediction": "sang out the voice of the secretary who could not pronounce the letter r", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0019.flac", "answer": "THEN THERE WAS A LAUGH A BUTTON AND TWO NUTS WERE FOUND IN THE BOX", "subset": "test_other", "task_type": "understanding", "prediction": "then there was a laugh a button and two knots were found in the box", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0006.flac", "answer": "VOTES PLEASE BEASTLY", "subset": "test_other", "task_type": "understanding", "prediction": "votes please please", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0013.flac", "answer": "LEVIN ADVANCED BUT UTTERLY FORGETTING WHAT HE WAS TO DO AND MUCH EMBARRASSED HE TURNED TO SERGEY IVANOVITCH WITH THE QUESTION WHERE AM I TO PUT IT", "subset": "test_other", "task_type": "understanding", "prediction": "levin advanced but utterly forgetting what he was to do and much embarrassed he turned to sergey ivanovitch with the question where am i to put it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0014.flac", "answer": "SERGEY IVANOVITCH FROWNED", "subset": "test_other", "task_type": "understanding", "prediction": "sergey ivanovitch frowned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0002.flac", "answer": "HE WAS SHOUTING FOR THE VERY COURSE SERGEY IVANOVITCH HAD PROPOSED BUT IT WAS EVIDENT THAT HE HATED HIM AND ALL HIS PARTY AND THIS FEELING OF HATRED SPREAD THROUGH THE WHOLE PARTY AND ROUSED IN OPPOSITION TO IT THE SAME VINDICTIVENESS THOUGH IN A MORE SEEMLY FORM ON THE OTHER SIDE", "subset": "test_other", "task_type": "understanding", "prediction": "he was shouting for the very course sergey ivanovitch had proposed but it was evident that he hated him and all his party and this feeling of hatred spread through the whole party and roused in opposition to it the same vindictiveness though in a more seemly form on the other side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0020.flac", "answer": "BUT THE OLD PARTY DID NOT CONSIDER THEMSELVES CONQUERED", "subset": "test_other", "task_type": "understanding", "prediction": "but the old party did not consider themselves conquered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0005.flac", "answer": "THE CONFIDENCE OF THE MONARCH NO CHECKING THE ACCOUNTS OF THE MARSHAL HE'S NOT A CASHIER BUT THAT'S NOT THE POINT", "subset": "test_other", "task_type": "understanding", "prediction": "the confidence of the monarch no checking the accounts of the marshal he is not a cashier but that is not the point", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0022.flac", "answer": "THIS EXPRESSION IN THE MARSHAL'S FACE WAS PARTICULARLY TOUCHING TO LEVIN BECAUSE ONLY THE DAY BEFORE HE HAD BEEN AT HIS HOUSE ABOUT HIS TRUSTEE BUSINESS AND HAD SEEN HIM IN ALL HIS GRANDEUR A KIND HEARTED FATHERLY MAN", "subset": "test_other", "task_type": "understanding", "prediction": "this expression in the marshal s face was particularly touching to levin because only the day before he had been at his house about his trusty business and had seen him in all his grandeur a kind hearted fatherly man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/5442/41168/5442-41168-0008.flac", "answer": "LEVIN DID NOT IN THE LEAST UNDERSTAND WHAT WAS THE MATTER AND HE MARVELED AT THE PASSION WITH WHICH IT WAS DISPUTED WHETHER OR NOT THE DECISION ABOUT FLEROV SHOULD BE PUT TO THE VOTE", "subset": "test_other", "task_type": "understanding", "prediction": "levin did not in the least understand what was the matter and he marvelled at the passion with which it was disputed whether or not the decision about flerov should be put to the vote", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0004.flac", "answer": "UNLUCKY ME AND THE MOTHER THAT BORE ME", "subset": "test_other", "task_type": "understanding", "prediction": "unlucky me and the mother that bore me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0017.flac", "answer": "AND A VERY RESPECTABLE ONE SAID THE INNKEEPER", "subset": "test_other", "task_type": "understanding", "prediction": "and a very respectable one said the innkeeper", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0019.flac", "answer": "HE SAW HIM RISING AND FALLING IN THE AIR WITH SUCH GRACE AND NIMBLENESS THAT HAD HIS RAGE ALLOWED HIM IT IS MY BELIEF HE WOULD HAVE LAUGHED", "subset": "test_other", "task_type": "understanding", "prediction": "he saw him rising and falling in the air with such grace and nimbleness that had his rage allowed him it is my belief he would have laughed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0008.flac", "answer": "MINE COULD SPEAK TOO SAID DON QUIXOTE BUT THAT IS NOT A SUFFICIENT REASON FOR BELIEVING THAT WHAT WE SEE IS THE ENCHANTED MOOR", "subset": "test_other", "task_type": "understanding", "prediction": "might could speak too said don quixote but that is not a sufficient reason for believing that what we see is the enchanted moor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0013.flac", "answer": "DON QUIXOTE CONSENTED AND HE TAKING IT WITH BOTH HANDS IN GOOD FAITH AND WITH A BETTER WILL GULPED DOWN AND DRAINED OFF VERY LITTLE LESS THAN HIS MASTER", "subset": "test_other", "task_type": "understanding", "prediction": "don quixote consented and he taking it with both hands in good faith and with a better will gulped it down and drained it off very little less than his master", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0005.flac", "answer": "DIDN'T I SAY SO WORSE LUCK TO MY LINE SAID SANCHO", "subset": "test_other", "task_type": "understanding", "prediction": "didnt i say so worse luck to my lines said sancho", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0016.flac", "answer": "THEN THIS IS AN INN SAID DON QUIXOTE", "subset": "test_other", "task_type": "understanding", "prediction": "then this is an inn said don quixote", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0011.flac", "answer": "TO BE BRIEF HE TOOK THE MATERIALS OF WHICH HE MADE A COMPOUND MIXING THEM ALL AND BOILING THEM A GOOD WHILE UNTIL IT SEEMED TO HIM THEY HAD COME TO PERFECTION", "subset": "test_other", "task_type": "understanding", "prediction": "to be brief he took the materials of which he made a compound mixing them all and boiling them a good while until it seemed to him they had come to perfection", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0015.flac", "answer": "SEARCH YOUR MEMORY AND IF YOU FIND ANYTHING OF THIS KIND YOU NEED ONLY TELL ME OF IT AND I PROMISE YOU BY THE ORDER OF KNIGHTHOOD WHICH I HAVE RECEIVED TO PROCURE YOU SATISFACTION AND REPARATION TO THE UTMOST OF YOUR DESIRE", "subset": "test_other", "task_type": "understanding", "prediction": "search your memory and if you find anything of this kind you need only tell me of it and i promise you by the order of knighthood which i have received to procure you satisfaction and reparation to the utmost of your desire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0014.flac", "answer": "IF YOUR WORSHIP KNEW THAT RETURNED SANCHO WOE BETIDE ME AND ALL MY KINDRED WHY DID YOU LET ME TASTE IT", "subset": "test_other", "task_type": "understanding", "prediction": "if your worship knew that returned sancho woe betide me and all my kindred why did you let me taste it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0010.flac", "answer": "SANCHO GOT UP WITH PAIN ENOUGH IN HIS BONES AND WENT AFTER THE INNKEEPER IN THE DARK AND MEETING THE OFFICER WHO WAS LOOKING TO SEE WHAT HAD BECOME OF HIS ENEMY HE SAID TO HIM SENOR WHOEVER YOU ARE DO US THE FAVOUR AND KINDNESS TO GIVE US A LITTLE ROSEMARY OIL SALT AND WINE FOR IT IS WANTED TO CURE ONE OF THE BEST KNIGHTS ERRANT ON EARTH WHO LIES ON YONDER BED WOUNDED BY THE HANDS OF THE ENCHANTED MOOR THAT IS IN THIS INN", "subset": "test_other", "task_type": "understanding", "prediction": "sancho got up with pain enough in his bones and went after the innkeeper in the dark and meeting the officer who was looking to see what had become of his enemy he said to him senor whoever you are do us the favour and kindness to give us a little of rosemary oil salt and wine for it is wanted to cure one of our best knights errant on earth who lies on yonder bed wounded by the hands of the enchanted moor that is in this inn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0009.flac", "answer": "THE OFFICER TURNED TO HIM AND SAID WELL HOW GOES IT GOOD MAN", "subset": "test_other", "task_type": "understanding", "prediction": "the officers turned to him and said well how goes it good man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0018.flac", "answer": "THE CRIES OF THE POOR BLANKETED WRETCH WERE SO LOUD THAT THEY REACHED THE EARS OF HIS MASTER WHO HALTING TO LISTEN ATTENTIVELY WAS PERSUADED THAT SOME NEW ADVENTURE WAS COMING UNTIL HE CLEARLY PERCEIVED THAT IT WAS HIS SQUIRE WHO UTTERED THEM", "subset": "test_other", "task_type": "understanding", "prediction": "the cries of the poor blanketet wretch were so loud that they reached the ears of his master who halting to listen attentively was persuaded that some new adventure was coming until he clearly perceived that it was his squire who uttered them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0020.flac", "answer": "SANCHO TOOK IT AND AS HE WAS RAISING IT TO HIS MOUTH HE WAS STOPPED BY THE CRIES OF HIS MASTER EXCLAIMING SANCHO MY SON DRINK NOT WATER DRINK IT NOT MY SON FOR IT WILL KILL THEE SEE HERE I HAVE THE BLESSED BALSAM AND HE HELD UP THE FLASK OF LIQUOR AND WITH DRINKING TWO DROPS OF IT THOU WILT CERTAINLY BE RESTORED", "subset": "test_other", "task_type": "understanding", "prediction": "sancho took it and as he was raising it to his mouth he was stopped by the cries of his master exclaiming sancho my son drink not water drink it not my son for it will kill thee see here i have the blessed balsam and he held up the flask of liquor and with drinking two drops with thou wilt certainly be restored", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0000.flac", "answer": "I SWEAR IT ANSWERED SANCHO", "subset": "test_other", "task_type": "understanding", "prediction": "i swear answered sancho", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0012.flac", "answer": "SANCHO PANZA WHO ALSO REGARDED THE AMENDMENT OF HIS MASTER AS MIRACULOUS BEGGED HIM TO GIVE HIM WHAT WAS LEFT IN THE PIGSKIN WHICH WAS NO SMALL QUANTITY", "subset": "test_other", "task_type": "understanding", "prediction": "sancho panza who also regarded the amendment of his master as miraculous begged him to give him what was left in the pigskin which was no small quantity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0003.flac", "answer": "THOUGH YOUR WORSHIP WAS NOT SO BADLY OFF HAVING IN YOUR ARMS THAT INCOMPARABLE BEAUTY YOU SPOKE OF BUT I WHAT DID I HAVE EXCEPT THE HEAVIEST WHACKS I THINK I HAD IN ALL MY LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "though your worship was not so badly off having in your arms the incomparable beauty you spoke of but i what did i have except the heaviest whacks that i think i had in all my life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0002.flac", "answer": "I SAY REPLIED SANCHO THAT I SWEAR TO HOLD MY TONGUE ABOUT IT TILL THE END OF YOUR WORSHIP'S DAYS AND GOD GRANT I MAY BE ABLE TO LET IT OUT TOMORROW", "subset": "test_other", "task_type": "understanding", "prediction": "i say replied sancho that i swear to hold my tongue about it till the end of your worship stays and gone gret i may be able to let it out to morrow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0001.flac", "answer": "I SAY SO CONTINUED DON QUIXOTE BECAUSE I HATE TAKING AWAY ANYONE'S GOOD NAME", "subset": "test_other", "task_type": "understanding", "prediction": "i say so continued don quixote because i hate taking away any one s good name", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0007.flac", "answer": "IF THEY DON'T LET THEMSELVES BE SEEN THEY LET THEMSELVES BE FELT SAID SANCHO IF NOT LET MY SHOULDERS SPEAK TO THE POINT", "subset": "test_other", "task_type": "understanding", "prediction": "if they do not let themselves be seen they let themselves be felt said sancho if not let my shoulder speak to the point", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/293981/367-293981-0006.flac", "answer": "IT CANNOT BE THE MOOR ANSWERED DON QUIXOTE FOR THOSE UNDER ENCHANTMENT DO NOT LET THEMSELVES BE SEEN BY ANYONE", "subset": "test_other", "task_type": "understanding", "prediction": "it cannot be the more answered don quixote for those under enchantment do not let themselves be seen by any one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0002.flac", "answer": "THIS QUESTION AND ANSWER MIGHT WELL GO INTO THE PRIMER OF INFORMATION FOR THOSE WHO COME TO SAN FRANCISCO FROM THE EAST FOR WHAT IS CALLED A LOBSTER IN SAN FRANCISCO IS NOT A LOBSTER AT ALL BUT A CRAYFISH", "subset": "test_other", "task_type": "understanding", "prediction": "this question and answer might well go into the primer of information for those who come to san francisco from the east for what is called a lobster in san francisco is not a lobster at all but a crayfish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0007.flac", "answer": "ONE POUND OF LOBSTER MEAT ONE TEASPOONFUL OF BUTTER ONE HALF PINT OF CREAM YOLKS OF FOUR EGGS ONE WINE GLASS OF SHERRY LOBSTER FAT", "subset": "test_other", "task_type": "understanding", "prediction": "one pound of lobster meat one teaspoonful of butter one half pint of cream yolks of four eggs one wine glass of sherry lobster fat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0023.flac", "answer": "ALL OF THE BETTER CLASS RESTAURANTS HOWEVER WILL SERVE THEM IF YOU ORDER THEM", "subset": "test_other", "task_type": "understanding", "prediction": "all the better class restaurants however will serve them if you order them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0016.flac", "answer": "TAKE THE MEAT OF ONE LARGE CRAB SCRAPING OUT ALL OF THE FAT FROM THE SHELL", "subset": "test_other", "task_type": "understanding", "prediction": "take the meat of one large crab scraping out all the fat from the shell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0025.flac", "answer": "BISQUE OF CRAWFISH", "subset": "test_other", "task_type": "understanding", "prediction": "bisque of crawfish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0013.flac", "answer": "GOBEY'S PASSED WITH THE FIRE AND THE LITTLE RESTAURANT BEARING HIS NAME AND IN CHARGE OF HIS WIDOW IN UNION SQUARE AVENUE HAS NOT ATTAINED THE FAME OF THE OLD PLACE", "subset": "test_other", "task_type": "understanding", "prediction": "goby has passed with the fire and the little restaurant bearing his name and in charge of his widow in union square avenue has not attained the fame of the old place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0006.flac", "answer": "LOBSTER A LA NEWBERG", "subset": "test_other", "task_type": "understanding", "prediction": "lobster a la newburg", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0022.flac", "answer": "SO FAR IT HAS BEEN USED MOSTLY FOR GARNISHMENT OF OTHER DISHES AND IT IS ONLY RECENTLY THAT THE HOF BRAU HAS BEEN MAKING A SPECIALTY OF THEM", "subset": "test_other", "task_type": "understanding", "prediction": "so far it has been used mostly for garnishment of other dishes and it is only recently that the hofbrau has been making a specialty of them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0017.flac", "answer": "SOAK THE CRAB MEAT IN THE SHERRY TWO HOURS BEFORE COOKING", "subset": "test_other", "task_type": "understanding", "prediction": "soak the crabmeat in the sherry two hours before cooking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0027.flac", "answer": "MINCE OR CUT INTO SMALL DICE A CARROT AN ONION ONE HEAD OF CELERY AND A FEW PARSLEY ROOTS AND TO THESE ADD A BAY LEAF A SPRIG OF THYME A LITTLE MINIONETTE PEPPER AND TWO OUNCES OF BUTTER", "subset": "test_other", "task_type": "understanding", "prediction": "mince or cut into small dice a carrot an onion one head of celery and a few parsley roots and to these add a bay leaf a sprig of thyme a little mignonette pepper and two ounces of butter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0026.flac", "answer": "TAKE THIRTY CRAWFISH FROM WHICH REMOVE THE GUT CONTAINING THE GALL IN THE FOLLOWING MANNER TAKE FIRM HOLD OF THE CRAWFISH WITH THE LEFT HAND SO AS TO AVOID BEING PINCHED BY ITS CLAWS WITH THE THUMB AND FOREFINGER OF THE RIGHT HAND PINCH THE EXTREME END OF THE CENTRAL FIN OF THE TAIL AND WITH A SUDDEN JERK THE GUT WILL BE WITHDRAWN", "subset": "test_other", "task_type": "understanding", "prediction": "take thirty crawfish from which remove the gut containing the gall in the following manner take firm hold of the crawfish with the left hand so as to avoid being pinched by its claws with the thumb and forefinger of the right hand pinch the extreme end of the central fin of the tail and with a sudden jerk the gut will be withdrawn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0031.flac", "answer": "PICK THE SHELLS OFF TWENTY FIVE OF THE CRAWFISH TAILS TRIM THEM NEATLY AND SET THEM ASIDE UNTIL WANTED", "subset": "test_other", "task_type": "understanding", "prediction": "pick the shells off twenty five of the crawfish tails trim them neatly and set them aside until wanted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0012.flac", "answer": "I SAY COME TO SAN FRANCISCO ADVISEDLY FOR WHILE THE CRAB IS FOUND ALL ALONG THE COAST IT IS PREPARED NOWHERE SO DELICIOUSLY AS IN SAN FRANCISCO", "subset": "test_other", "task_type": "understanding", "prediction": "i say come to san francisco advisedly for while the crab is found all along the coast it is prepared nowhere so deliciously as in san francisco", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0029.flac", "answer": "ALLOW THIS TO BOIL AND THEN ADD A QUART OF STRONG CONSOMME AND LET ALL CONTINUE BOILING FOR HALF AN HOUR", "subset": "test_other", "task_type": "understanding", "prediction": "allow this to boil and then add a quart of strong consomme and let all continue boiling for half an hour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0009.flac", "answer": "SERVE IN A CHAFING DISH WITH THIN SLICES OF DRY TOAST", "subset": "test_other", "task_type": "understanding", "prediction": "serve in a chafing dish with thin slices of dry toast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0033.flac", "answer": "THIS BUTTER IS MADE AS FOLLOWS PLACE THE SHELLS ON A BAKING SHEET IN THE OVEN TO DRY LET THE SHELLS COOL AND THEN POUND THEM IN A MORTAR WITH A LITTLE LOBSTER CORAL AND FOUR OUNCES OF FRESH BUTTER THOROUGHLY BRUISING THE WHOLE TOGETHER SO AS TO MAKE A FINE PASTE", "subset": "test_other", "task_type": "understanding", "prediction": "this butter is made as follows place the shells on a baking sheet in the oven to dry let the shells cool and then pound them in a mortar with a little lobster coral and four ounces of fresh butter thoroughly bruising the whole together so as to make a fine paste", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0021.flac", "answer": "LOBSTER IN MINIATURE", "subset": "test_other", "task_type": "understanding", "prediction": "lobster in miniature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0005.flac", "answer": "IT WAS HERE THAT MOST MAGNIFICENT DINNERS WERE ARRANGED IT WAS HERE THAT EXTRAORDINARY DISHES WERE CONCOCTED BY CHEFS OF WORLD WIDE FAME IT WAS HERE THAT LOBSTER A LA NEWBERG REACHED ITS HIGHEST PERFECTION AND THIS IS THE RECIPE THAT WAS FOLLOWED WHEN IT WAS PREPARED IN THE DELMONICO", "subset": "test_other", "task_type": "understanding", "prediction": "it was here that most magnificent dinners were arranged it was here that extraordinary dishes were concocted by chefs of world wide fame it was here that lobster a la newburg reached its highest perfection and this is the recipe that was followed when it was prepared in the delmonico", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0008.flac", "answer": "PUT THIS IN A DOUBLE BOILER AND LET COOK UNTIL THICK STIRRING CONSTANTLY", "subset": "test_other", "task_type": "understanding", "prediction": "put this in a double boiler and let cook until thick stirring constantly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0032.flac", "answer": "RESERVE SOME OF THE SPAWN ALSO HALF OF THE BODY SHELLS WITH WHICH TO MAKE THE CRAWFISH BUTTER TO FINISH THE SOUP", "subset": "test_other", "task_type": "understanding", "prediction": "reserve some of the spawn also half of the body shells with which to make the crawfish butter to finish the soup", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0018.flac", "answer": "CHOP FINE THE ONION SWEET PEPPER AND TOMATO WITH THE ROSEMARY", "subset": "test_other", "task_type": "understanding", "prediction": "chop fine the onion sweet pepper and tomato with the rosemary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0010.flac", "answer": "KING OF SHELL FISH", "subset": "test_other", "task_type": "understanding", "prediction": "king of shellfish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0024.flac", "answer": "THIS IS THE RECIPE FOR EIGHT PEOPLE AND IT IS WELL WORTH TRYING IF YOU ARE GIVING A DINNER OF IMPORTANCE", "subset": "test_other", "task_type": "understanding", "prediction": "this is the recipe for eight people and it is well worth trying if you are giving a dinner of importance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0030.flac", "answer": "PICK OUT THE CRAWFISH AND STRAIN THE BROTH THROUGH A NAPKIN BY PRESSURE INTO A BASIN IN ORDER TO EXTRACT ALL THE ESSENCE FROM THE VEGETABLES", "subset": "test_other", "task_type": "understanding", "prediction": "Pick out the crawfish and strain the broth through a napkin by pressure into a basin in order to extract all the essence from the vegetables.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0015.flac", "answer": "GOBEY'S CRAB STEW", "subset": "test_other", "task_type": "understanding", "prediction": "goby s crab stew", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0004.flac", "answer": "A BOOK COULD BE WRITTEN ABOUT THIS RESTAURANT AND THEN ALL WOULD NOT BE TOLD FOR ALL ITS SECRETS CAN NEVER BE KNOWN", "subset": "test_other", "task_type": "understanding", "prediction": "a book could be written about this restaurant and then all would not be told for all its secrets can never be known", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0003.flac", "answer": "THE PACIFIC CRAYFISH HOWEVER SERVES EVERY PURPOSE AND WHILE MANY CONTEND THAT ITS MEAT IS NOT SO DELICATE IN FLAVOR AS THAT OF ITS EASTERN COUSIN THE CALIFORNIAN WILL AS STRENUOUSLY INSIST THAT IT IS BETTER BUT OF COURSE SOMETHING MUST ALWAYS BE ALLOWED FOR THE PATRIOTISM OF THE CALIFORNIAN", "subset": "test_other", "task_type": "understanding", "prediction": "the pacific crayfish however serves every purpose and while many contend that its meat is not so delicate in flavor as that of its eastern cousin the californian will as strenuously insist that it is better but of course something must always be allowed for the patriotism of the californians", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0019.flac", "answer": "HEAT THIS IN A STEWPAN AND WHEN SIMMERING ADD THE SHERRY AND CRAB MEAT AND LET ALL COOK TOGETHER WITH A SLOW FIRE FOR EIGHT MINUTES", "subset": "test_other", "task_type": "understanding", "prediction": "heat this in a stewpan and when simmering add the sherry and crab meat and let all cook together with a slow fire for eight minutes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0014.flac", "answer": "IT IS POSSIBLE THAT SHE KNOWS THE SECRET OF PREPARING CRAB AS IT WAS PREPARED IN THE GOBEY'S OF BEFORE THE FIRE BUT HIS PRESTIGE DID NOT DESCEND TO HER", "subset": "test_other", "task_type": "understanding", "prediction": "it is possible that she knows the secret of preparing crab as it was prepared in the goby of before the fire but his prestige did not descend to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0020.flac", "answer": "SERVE IN A CHAFING DISH WITH TOASTED CRACKERS OR THIN SLICES OF TOASTED BREAD", "subset": "test_other", "task_type": "understanding", "prediction": "serve in a chafing dish with toasted crackers or thin slices of toasted bread", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0000.flac", "answer": "LOBSTERS AND LOBSTERS", "subset": "test_other", "task_type": "understanding", "prediction": "lobsters and lobsters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0028.flac", "answer": "PUT THESE INGREDIENTS INTO A STEWPAN AND FRY THEM TEN MINUTES THEN THROW IN THE CRAWFISH AND POUR ON THEM HALF A BOTTLE OF FRENCH WHITE WINE", "subset": "test_other", "task_type": "understanding", "prediction": "put these ingredients into a stew pan and fry them ten minutes then throw in the crawfish and pour on them half a bottle of french white wine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0001.flac", "answer": "WHEN IS A LOBSTER NOT A LOBSTER WHEN IT IS A CRAYFISH", "subset": "test_other", "task_type": "understanding", "prediction": "when is a lobster not a lobster when it is a crayfish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/367/130732/367-130732-0011.flac", "answer": "ONE HAS TO COME TO SAN FRANCISCO TO PARTAKE OF THE KING OF SHELL FISH THE MAMMOTH PACIFIC CRAB", "subset": "test_other", "task_type": "understanding", "prediction": "one has to come to san francisco to partake of the king of shellfish the mammoth pacific crab", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0010.flac", "answer": "SHE BEGGED VERY PRETTILY AND GOT IT AND THEN SHE BRUSHED HER HAIR AND THE GOLD DROPPED FROM IT", "subset": "test_other", "task_type": "understanding", "prediction": "she begged very prettily and got it and then she brushed her hair and the gold dropped from it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0008.flac", "answer": "WHAT IS MY BROTHER SAYING ASKED HIS SISTER AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "what is my brother saying asked his sister again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0009.flac", "answer": "ON THE FIRST THURSDAY NIGHT AFTER THIS A BEAUTIFUL MAIDEN CAME INTO THE KITCHEN OF THE PALACE AND BEGGED THE KITCHEN MAID WHO SLEPT THERE TO LEND HER A BRUSH", "subset": "test_other", "task_type": "understanding", "prediction": "on the first thursday night after this a beautiful maiden came into the kitchen of the palace and begged the kitchen maid who slept there to lend her a brush", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0011.flac", "answer": "OUT ON THEE UGLY BUSHY BRIDE SLEEPING SO SOFT BY THE YOUNG KING'S SIDE ON SAND AND STONES MY BED I MAKE AND MY BROTHER SLEEPS WITH THE COLD SNAKE UNPITIED AND UNWEPT", "subset": "test_other", "task_type": "understanding", "prediction": "out on thee ugly bushy browed sleeping so soft by the young king s side on sand and stones my bed i make and my brother sleeps with the cold snake unpitied and unwept", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0004.flac", "answer": "WHEN THE KING ENTERED AND SAW IT HE STOOD STILL AS IF HE WERE IN FETTERS AND COULD NOT STIR FROM THE SPOT FOR THE PICTURE SEEMED TO HIM SO BEAUTIFUL", "subset": "test_other", "task_type": "understanding", "prediction": "when the king entered and saw it he stood still as if he were in fetters and could not stir from the spot for the picture seemed to him so beautiful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0013.flac", "answer": "THIS TIME ALSO AS BEFORE SHE BORROWED A BRUSH AND BRUSHED HER HAIR WITH IT AND THE GOLD DROPPED DOWN AS SHE DID IT AND AGAIN SHE SENT THE DOG OUT THREE TIMES AND WHEN DAY DAWNED SHE DEPARTED BUT AS SHE WAS GOING SHE SAID AS SHE HAD SAID BEFORE I SHALL COME ONCE MORE AND THEN NEVER AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "this time also as before she borrowed a brush and brushed her hair with it and the gold dropped down as she did it and again she sent the dog out three times and when day dawned she departed but as she was going she said as she had said before i shall come once more and then never again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0012.flac", "answer": "I SHALL COME TWICE MORE AND THEN NEVER AGAIN SAID SHE", "subset": "test_other", "task_type": "understanding", "prediction": "i shall come twice more and then never again said she", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0007.flac", "answer": "WELL IF MY BROTHER SAYS SO I MUST DO IT SAID THE MAN'S DAUGHTER AND SHE FLUNG HER CASKET INTO THE SEA", "subset": "test_other", "task_type": "understanding", "prediction": "well if my brother says so i must do it said the man s daughter and she flung her casket into the sea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0005.flac", "answer": "THE YOUTH PROMISED TO MAKE ALL THE HASTE HE COULD AND SET FORTH FROM THE KING'S PALACE", "subset": "test_other", "task_type": "understanding", "prediction": "the youth promised to make all the haste he could and set forth from the king s palace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0001.flac", "answer": "FROM THE VERY DAY THAT THE NEW WIFE CAME INTO THE HOUSE THERE WAS NO PEACE FOR THE MAN'S CHILDREN AND NOT A CORNER TO BE FOUND WHERE THEY COULD GET ANY REST SO THE BOY THOUGHT THAT THE BEST THING HE COULD DO WAS TO GO OUT INTO THE WORLD AND TRY TO EARN HIS OWN BREAD", "subset": "test_other", "task_type": "understanding", "prediction": "from the very day that the new wife came into the house there was no peace for the man s children and not a corner to be found where they could get any rest so the boy thought that the best thing he could do was to go out into the world and try to earn his own bread", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0002.flac", "answer": "BUT HIS SISTER WHO WAS STILL AT HOME FARED WORSE AND WORSE", "subset": "test_other", "task_type": "understanding", "prediction": "but his sister who was still at home fared worse and worse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0003.flac", "answer": "KISS ME GIRL SAID THE HEAD", "subset": "test_other", "task_type": "understanding", "prediction": "kiss me girl said the head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0006.flac", "answer": "AT LAST THEY CAME IN SIGHT OF LAND", "subset": "test_other", "task_type": "understanding", "prediction": "at last they came in sight of land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0000.flac", "answer": "THERE WAS ONCE ON A TIME A WIDOWER WHO HAD A SON AND A DAUGHTER BY HIS FIRST WIFE", "subset": "test_other", "task_type": "understanding", "prediction": "there was once on a time a widower who had a son and a daughter by his first wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163619/3538-163619-0014.flac", "answer": "NO ONE CAN TELL HOW DELIGHTED THE KING WAS TO GET RID OF THAT HIDEOUS BUSHY BRIDE AND GET A QUEEN WHO WAS BRIGHT AND BEAUTIFUL AS DAY ITSELF", "subset": "test_other", "task_type": "understanding", "prediction": "no one can tell how delighted the king was to get rid of that hideous bushy bride and get a queen who was bright and beautiful as day itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0014.flac", "answer": "AND THUS THEY JOURNEYED ONWARDS A LONG LONG WAY", "subset": "test_other", "task_type": "understanding", "prediction": "and thus they journeyed onwards a long long way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0000.flac", "answer": "WILT THOU SERVE ME AND WATCH MY SEVEN FOALS ASKED THE KING", "subset": "test_other", "task_type": "understanding", "prediction": "wilt thou serve me and watch my seven foals asked the king", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0022.flac", "answer": "NOW THEN SAID THE FOAL DOST THOU NOT SEE ANYTHING NOW", "subset": "test_other", "task_type": "understanding", "prediction": "now then said the foal dost thou not see anything now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0018.flac", "answer": "CINDERLAD TRIED BUT COULD NOT DO IT SO HE HAD TO TAKE A DRAUGHT FROM THE PITCHER AND THEN ONE MORE AND AFTER THAT STILL ANOTHER AND THEN HE WAS ABLE TO WIELD THE SWORD WITH PERFECT EASE", "subset": "test_other", "task_type": "understanding", "prediction": "cinderlad tried but could not do it so he had to take a draught from the pitcher and then one more and after that still another and then he was able to wield the sword with perfect ease", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0024.flac", "answer": "I HAVE DONE MY BEST REPLIED CINDERLAD", "subset": "test_other", "task_type": "understanding", "prediction": "i have done my best replied cinder lad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0023.flac", "answer": "THAT IS A RIVER SAID THE FOAL AND WE HAVE TO CROSS IT", "subset": "test_other", "task_type": "understanding", "prediction": "that is a river said the foal and we have to cross it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0001.flac", "answer": "THE YOUTH THOUGHT THAT IT WAS VERY EASY WORK TO WATCH THE FOALS AND THAT HE COULD DO IT WELL ENOUGH", "subset": "test_other", "task_type": "understanding", "prediction": "the youth thought that it was very easy work to wash the foals and that he could do it well enough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0013.flac", "answer": "I WOULD MUCH RATHER HAVE THE PRINCESS SAID CINDERLAD", "subset": "test_other", "task_type": "understanding", "prediction": "i would much rather have the princess said cinderlad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0020.flac", "answer": "WHEN THEY HAD TRAVELLED A LONG LONG WAY THE FOAL SAID DOST THOU SEE ANYTHING", "subset": "test_other", "task_type": "understanding", "prediction": "when they had travelled a long long way the foal said dost thou see anything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0017.flac", "answer": "IT LOOKS LIKE THE TRUNK OF A GREAT THICK BIRCH TREE", "subset": "test_other", "task_type": "understanding", "prediction": "it looks like the trunk of a great thick birch tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0004.flac", "answer": "HE HAD GONE OUT ONCE TO SEEK A PLACE HE SAID BUT NEVER WOULD HE DO SUCH A THING AGAIN", "subset": "test_other", "task_type": "understanding", "prediction": "he had gone out once to seek a place he said but never would he do such a thing again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0011.flac", "answer": "THE TWO BROTHERS LAUGHED AT HIM AND HIS FATHER AND MOTHER BEGGED HIM NOT TO GO BUT ALL TO NO PURPOSE AND CINDERLAD SET OUT ON HIS WAY", "subset": "test_other", "task_type": "understanding", "prediction": "the two brothers laughed at him and his father and mother begged him not to go but all to no purpose and cinderlad set out on his way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0021.flac", "answer": "AND NOW INQUIRED THE FOAL SEEST THOU NOTHING NOW", "subset": "test_other", "task_type": "understanding", "prediction": "and now inquired the fool seest thou nothing now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0007.flac", "answer": "COME HITHER COME HITHER MY HANDSOME SON AND LET ME COMB YOUR HAIR", "subset": "test_other", "task_type": "understanding", "prediction": "come hither come hither my handsome son and let me comb your hair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0008.flac", "answer": "THE YOUTH LIKED THE THOUGHT OF THIS LET THE FOALS RUN WHERE THEY CHOSE AND SEATED HIMSELF IN THE CLEFT OF THE ROCK BY THE SIDE OF THE OLD HAG", "subset": "test_other", "task_type": "understanding", "prediction": "the youth liked the thought of this let the foals run where they chose and seated himself in the cleft of the rock by the side of the old hag", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0003.flac", "answer": "YES THAT I HAVE SAID THE YOUTH", "subset": "test_other", "task_type": "understanding", "prediction": "yes that i have said the youth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0012.flac", "answer": "I AM WALKING ABOUT IN SEARCH OF A PLACE SAID CINDERLAD", "subset": "test_other", "task_type": "understanding", "prediction": "i am walking about in search of a place said cinderlad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0009.flac", "answer": "SO THERE HE SAT WITH HIS HEAD ON HER LAP TAKING HIS EASE THE LIVELONG DAY", "subset": "test_other", "task_type": "understanding", "prediction": "so there he sat with his head on her lap taking his ease the livelong day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0019.flac", "answer": "FOR WE ARE BROTHERS OF THE PRINCESS WHOM THOU ART TO HAVE WHEN THOU CANST TELL THE KING WHAT WE EAT AND DRINK BUT THERE IS A MIGHTY TROLL WHO HAS CAST A SPELL OVER US", "subset": "test_other", "task_type": "understanding", "prediction": "for we are brothers of the princess whom thou art to have when thou canst tell the king what we eat and drink but there is a mighty troll who has cast a spell over us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0002.flac", "answer": "HAST THOU WATCHED FAITHFULLY AND WELL THE WHOLE DAY LONG SAID THE KING WHEN THE LAD CAME INTO HIS PRESENCE IN THE EVENING", "subset": "test_other", "task_type": "understanding", "prediction": "hast thou watched faithfully and well the whole day long said the king when the lad came into his presence in the evening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0010.flac", "answer": "ON THE THIRD DAY CINDERLAD WANTED TO SET OUT", "subset": "test_other", "task_type": "understanding", "prediction": "on the third day sid and ladd wanted to set out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0006.flac", "answer": "WHEN HE HAD RUN AFTER THE FOALS FOR A LONG LONG TIME AND WAS HOT AND TIRED HE PASSED BY A CLEFT IN THE ROCK WHERE AN OLD WOMAN WAS SITTING SPINNING WITH A DISTAFF AND SHE CALLED TO HIM", "subset": "test_other", "task_type": "understanding", "prediction": "when he had run after the fowls for a long long time and was hot and tired he passed by a cleft in the rock where an old woman was sitting spinning with a distaff and she called to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0015.flac", "answer": "WHEN THEY HAD GONE THUS FOR A LONG LONG WAY THE FOAL AGAIN ASKED DOST THOU SEE ANYTHING NOW", "subset": "test_other", "task_type": "understanding", "prediction": "when they had gone thus for a long long way the foal again asked dost thou see anything now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0005.flac", "answer": "THEN THE KING PROMISED HIM THE SAME PUNISHMENT AND THE SAME REWARD THAT HE HAD PROMISED HIS BROTHER", "subset": "test_other", "task_type": "understanding", "prediction": "then the king promised him the same punishment and the same reward that he had promised his brother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163622/3538-163622-0016.flac", "answer": "YES NOW I SEE SOMETHING THAT IS WHITE SAID CINDERLAD", "subset": "test_other", "task_type": "understanding", "prediction": "yes now i see something that is white said cinderlad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0014.flac", "answer": "BUT ALL MEN DIE AND NO BRAVE MAN LETS DEATH FRIGHTEN HIM FROM HIS DESIRE", "subset": "test_other", "task_type": "understanding", "prediction": "but all men die and no brave man lets death frighten him from his desire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0001.flac", "answer": "THE OLD KING WENT OUT AND FOUGHT BRAVELY BUT AT LAST HIS SWORD BROKE AND HE WAS WOUNDED AND HIS MEN FLED", "subset": "test_other", "task_type": "understanding", "prediction": "the old king went out and fought bravely but at last his sword broke and he was wounded and his men fled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0000.flac", "answer": "ONCE UPON A TIME THERE WAS A KING IN THE NORTH WHO HAD WON MANY WARS BUT NOW HE WAS OLD", "subset": "test_other", "task_type": "understanding", "prediction": "once upon a time there was a king in the north who had won many wars but now he was old", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0007.flac", "answer": "ONLY ONE RING WAS LEFT WHICH THE DWARF WORE AND EVEN THAT WAS TAKEN FROM HIM", "subset": "test_other", "task_type": "understanding", "prediction": "only one ring was left which the dwarf wore and even that was taken from him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0026.flac", "answer": "NOT LONG TO WAIT HE SAID TILL THE BITTER SWORD STANDS FAST IN MY HEART AND THOU WILL NOT LIVE LONG WHEN I AM DEAD", "subset": "test_other", "task_type": "understanding", "prediction": "not long to wait he said till the bitter sword stands fast in my heart and thou wilt not live long when i am dead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0025.flac", "answer": "FOR HER HUSBAND SHE SAID HAD RIDDEN THROUGH THE FLAME WHEN NO OTHER MAN DARED FACE IT", "subset": "test_other", "task_type": "understanding", "prediction": "for her husband she said had ridden through the flame when no other man dared face it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0003.flac", "answer": "SO HE ASKED THE QUEEN HOW DO YOU KNOW IN THE DARK OF NIGHT WHETHER THE HOURS ARE WEARING TO THE MORNING AND SHE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "so he asked the queen how do you know in the dark of night whether the hours are wearing to the morning and she said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0008.flac", "answer": "SO REGIN MADE A SWORD AND SIGURD TRIED IT WITH A BLOW ON A LUMP OF IRON AND THE SWORD BROKE", "subset": "test_other", "task_type": "understanding", "prediction": "so regin made a sword and sigurd tried it with a blow on a lump of iron and the sword broke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0002.flac", "answer": "BUT IN THE NIGHT WHEN THE BATTLE WAS OVER HIS YOUNG WIFE CAME OUT AND SEARCHED FOR HIM AMONG THE SLAIN AND AT LAST SHE FOUND HIM AND ASKED WHETHER HE MIGHT BE HEALED", "subset": "test_other", "task_type": "understanding", "prediction": "but in the night when the battle was over his young wife came out and searched for him among the slain and at last she found him and asked whether he might be healed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0015.flac", "answer": "DIE THOU FAFNIR AND THEN FAFNIR DIED", "subset": "test_other", "task_type": "understanding", "prediction": "die thou fafnir and then fafnir died", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0022.flac", "answer": "THEN SIGURD RODE AWAY AND HE CAME TO THE HOUSE OF A KING WHO HAD A FAIR DAUGHTER", "subset": "test_other", "task_type": "understanding", "prediction": "then sigurd rode away and he came to the house of a king who had a fair daughter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0006.flac", "answer": "THEN THE PERSON WHO HAD KILLED OTTER WENT DOWN AND CAUGHT THE DWARF WHO OWNED ALL THE TREASURE AND TOOK IT FROM HIM", "subset": "test_other", "task_type": "understanding", "prediction": "then the person who had killed otter went down and caught the dwarf who owned all the treasure and took it from him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0024.flac", "answer": "FOR ONE DAY WHEN BRYNHILD AND GUDRUN WERE BATHING BRYNHILD WADED FARTHEST OUT INTO THE RIVER AND SAID SHE DID THAT TO SHOW SHE WAS GUIRUN'S SUPERIOR", "subset": "test_other", "task_type": "understanding", "prediction": "for one day when brynhild and gudrun were bathing brynhild waded farthest out into the river and said she did that to show she was gudrun s superior", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0016.flac", "answer": "THEN SIGURD RODE BACK AND MET REGIN AND REGIN ASKED HIM TO ROAST FAFNIR'S HEART AND LET HIM TASTE OF IT", "subset": "test_other", "task_type": "understanding", "prediction": "then sigurd rode back and met regin and regin asked him to roast fafnir s heart and let him taste of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0011.flac", "answer": "THEN HE SAW THE TRACK WHICH THE DRAGON MADE WHEN HE WENT TO A CLIFF TO DRINK AND THE TRACK WAS AS IF A GREAT RIVER HAD ROLLED ALONG AND LEFT A DEEP VALLEY", "subset": "test_other", "task_type": "understanding", "prediction": "then he saw the track which the dragon had made when he went to a cliff to drink and the track was as if a great river had rolled along and left a deep valley", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0004.flac", "answer": "THEN THE OLD MAN SAID DRIVE ALL THE HORSES INTO THE RIVER AND CHOOSE THE ONE THAT SWIMS ACROSS", "subset": "test_other", "task_type": "understanding", "prediction": "then the old man said drive all the horses into the river and choose the one that swims across", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0019.flac", "answer": "THAT LET HIM DO AND THEN RIDE OVER HINDFELL TO THE PLACE WHERE BRYNHILD SLEEPS", "subset": "test_other", "task_type": "understanding", "prediction": "that let him do then ride over hinfeld to the place where brunhild sleeps", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0009.flac", "answer": "THEN SIGURD WENT TO HIS MOTHER AND ASKED FOR THE BROKEN PIECES OF HIS FATHER'S BLADE AND GAVE THEM TO REGIN", "subset": "test_other", "task_type": "understanding", "prediction": "then sigurd went to his mother and asked for the broken pieces of his father s blade and gave them to regin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0023.flac", "answer": "THEN BRYNHILD'S FATHER TOLD GUNNAR THAT SHE WOULD MARRY NONE BUT HIM WHO COULD RIDE THE FLAME IN FRONT OF HER ENCHANTED TOWER AND THITHER THEY RODE AND GUNNAR SET HIS HORSE AT THE FLAME BUT HE WOULD NOT FACE IT", "subset": "test_other", "task_type": "understanding", "prediction": "lindbernilds father told gunnar that she would marry none but him who could ride the flame in front of her enchanted tower and thither they rode and gunnar set his horse at the flame but he would not face it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0005.flac", "answer": "HE IS NO BIGGER THAN OTHER DRAGONS SAID THE TUTOR AND IF YOU WERE AS BRAVE AS YOUR FATHER YOU WOULD NOT FEAR HIM", "subset": "test_other", "task_type": "understanding", "prediction": "he is no bigger than other dragons said the tutor and if you were as brave as your father you would not fear him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0018.flac", "answer": "THERE IS SIGURD ROASTING FAFNIR'S HEART FOR ANOTHER WHEN HE SHOULD TASTE OF IT HIMSELF AND LEARN ALL WISDOM", "subset": "test_other", "task_type": "understanding", "prediction": "there is sigurd roasting fafnir s heart for another when he should taste of it himself and learn all wisdom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0020.flac", "answer": "THERE MUST SHE SLEEP TILL THOU COMEST FOR HER WAKING RISE UP AND RIDE FOR NOW SURE SHE WILL SWEAR THE VOW FEARLESS OF BREAKING", "subset": "test_other", "task_type": "understanding", "prediction": "there must she sleep till thou comes for her waking rise up and ride for now sure she will swear the vow fearless of breaking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0021.flac", "answer": "THEN HE TOOK THE HELMET OFF THE HEAD OF THE SLEEPER AND BEHOLD SHE WAS A MOST BEAUTIFUL LADY", "subset": "test_other", "task_type": "understanding", "prediction": "then he took the helmet off the head of the sleeper and behold she was a most beautiful lady", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0012.flac", "answer": "BUT SIGURD WAITED TILL HALF OF HIM HAD CRAWLED OVER THE PIT AND THEN HE THRUST THE SWORD GRAM RIGHT INTO HIS VERY HEART", "subset": "test_other", "task_type": "understanding", "prediction": "but sigurd waited till half of him had crawled over the pit and then he thrust the sword gram right into his very heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0017.flac", "answer": "SO SIGURD PUT THE HEART OF FAFNIR ON A STAKE AND ROASTED IT", "subset": "test_other", "task_type": "understanding", "prediction": "so sigurd put the heart of fafnir on a stake and roasted it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0010.flac", "answer": "SO SIGURD SAID THAT SWORD WOULD DO", "subset": "test_other", "task_type": "understanding", "prediction": "so sigurd said that sword would do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/163624/3538-163624-0013.flac", "answer": "SIGURD SAID I WOULD TOUCH NONE OF IT IF BY LOSING IT I SHOULD NEVER DIE", "subset": "test_other", "task_type": "understanding", "prediction": "sigurd said i would touch none of it if by losing it i should never die", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0020.flac", "answer": "THE THOUSAND AND ONE ORNAMENTAL DISHES THAT ADORN THE TABLES OF THE WEALTHY SHOULD BE PURCHASED FROM THE CONFECTIONER THEY CANNOT PROFITABLY BE MADE AT HOME", "subset": "test_other", "task_type": "understanding", "prediction": "the thousand and one ornamental dishes that adorn the tables of the wealthy should be purchased from the confectioner they can not profitably be made at home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0011.flac", "answer": "FROM THIS EXAMPLE THE PROCESS OF PRESERVING FRUITS BY SYRUP WILL BE EASILY COMPREHENDED", "subset": "test_other", "task_type": "understanding", "prediction": "from this example the process of preserving fruits by syrup would be easily comprehended", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0000.flac", "answer": "GENERAL OBSERVATIONS ON PRESERVES CONFECTIONARY ICES AND DESSERT DISHES", "subset": "test_other", "task_type": "understanding", "prediction": "general observations on preserves confectionery ices and dessert dishes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0016.flac", "answer": "THAT THEY MAY KEEP IT IS NECESSARY NOT TO BE SPARING OF SUGAR FIFTEEN O THREE", "subset": "test_other", "task_type": "understanding", "prediction": "that they may keep it is necessary not to be sparing of sugar fifteen o three", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0003.flac", "answer": "BUT TO DISTINGUISH THESE PROPERLY REQUIRES VERY GREAT ATTENTION AND CONSIDERABLE EXPERIENCE", "subset": "test_other", "task_type": "understanding", "prediction": "but to distinguish these properly requires very great attention and considerable experience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0025.flac", "answer": "THE SPADDLE IS GENERALLY MADE OF COPPER KEPT BRIGHT AND CLEAN", "subset": "test_other", "task_type": "understanding", "prediction": "the spaddle is generally made of copper kept bright and clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0009.flac", "answer": "BOIL THEM UP THREE DAYS SUCCESSIVELY SKIMMING EACH TIME AND THEY WILL THEN BE FINISHED AND IN A STATE FIT TO BE PUT INTO POTS FOR USE", "subset": "test_other", "task_type": "understanding", "prediction": "boil them up three days successively skimming each time and they will then be finished and in a state fit to be put into pots for use", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0022.flac", "answer": "THE SHAPE OF THE DISHES VARIES AT DIFFERENT PERIODS THE PREVAILING FASHION AT PRESENT BEING OVAL AND CIRCULAR DISHES ON STEMS", "subset": "test_other", "task_type": "understanding", "prediction": "the shape of the dishes varies at different periods the prevailing fashion at present being oval and circular dishes on stems", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0006.flac", "answer": "IT IS CONSIDERED TO BE SUFFICIENTLY BOILED WHEN SOME TAKEN UP IN A SPOON POURS OUT LIKE OIL", "subset": "test_other", "task_type": "understanding", "prediction": "it is considered to be sufficiently boiled when some taken up in a spoon pours out like oil", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0001.flac", "answer": "THE EXPENSE OF PRESERVING THEM WITH SUGAR IS A SERIOUS OBJECTION FOR EXCEPT THE SUGAR IS USED IN CONSIDERABLE QUANTITIES THE SUCCESS IS VERY UNCERTAIN", "subset": "test_other", "task_type": "understanding", "prediction": "the expense of preserving them with sugar is a serious objection for except the sugar is used in considerable quantities the success is very uncertain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0002.flac", "answer": "FRUIT GATHERED IN WET OR FOGGY WEATHER WILL SOON BE MILDEWED AND BE OF NO SERVICE FOR PRESERVES", "subset": "test_other", "task_type": "understanding", "prediction": "fruit gathered in wet or foggy weather will soon be mildewed and be of no service for preserves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0024.flac", "answer": "AT DESSERTS OR AT SOME EVENING PARTIES ICES ARE SCARCELY TO BE DISPENSED WITH", "subset": "test_other", "task_type": "understanding", "prediction": "at desserts or at some evening parties ices are scarcely to be dispensed with", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0026.flac", "answer": "THEY SHOULD BE TAKEN IMMEDIATELY AFTER THE REPAST OR SOME HOURS AFTER BECAUSE THE TAKING THESE SUBSTANCES DURING THE PROCESS OF DIGESTION IS APT TO PROVOKE INDISPOSITION", "subset": "test_other", "task_type": "understanding", "prediction": "they should be taken immediately after the repast or some hours after because the taking of these substances during the process of digestion is apt to provoke indisposition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0019.flac", "answer": "IN SPEAKING OF CONFECTIONARY IT SHOULD BE REMARKED THAT ALL THE VARIOUS PREPARATIONS ABOVE NAMED COME STRICTLY SPEAKING UNDER THAT HEAD FOR THE VARIOUS FRUITS FLOWERS HERBS ROOTS AND JUICES WHICH WHEN BOILED WITH SUGAR WERE FORMERLY EMPLOYED IN PHARMACY AS WELL AS FOR SWEETMEATS WERE CALLED CONFECTIONS FROM THE LATIN WORD CONFICERE TO MAKE UP BUT THE TERM CONFECTIONARY EMBRACES A VERY LARGE CLASS INDEED OF SWEET FOOD MANY KINDS OF WHICH SHOULD NOT BE ATTEMPTED IN THE ORDINARY CUISINE", "subset": "test_other", "task_type": "understanding", "prediction": "in speaking of confectionery it should be remarked that all the various preparations above named come strictly speaking under that head for the various fruits flowers herbs roots and juices which when boiled with sugar were formerly employed in pharmacy as well as for sweetmeats were called confections from the latin word conficere to make up but the term confectionery embraces a very large class indeed of sweet food many kinds of which should not be attempted in the ordinary cuisine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0023.flac", "answer": "ICES", "subset": "test_other", "task_type": "understanding", "prediction": "isis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0007.flac", "answer": "BEFORE SUGAR WAS IN USE HONEY WAS EMPLOYED TO PRESERVE MANY VEGETABLE PRODUCTIONS THOUGH THIS SUBSTANCE HAS NOW GIVEN WAY TO THE JUICE OF THE SUGAR CANE", "subset": "test_other", "task_type": "understanding", "prediction": "before sugar was in use honey was employed to preserve many vegetable productions though this substance has now given way to the juice of the sugar cane", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0012.flac", "answer": "THEY SHOULD BE DRIED IN THE STOVE OR OVEN ON A SIEVE AND TURNED EVERY SIX OR EIGHT HOURS FRESH POWDERED SUGAR BEING SIFTED OVER THEM EVERY TIME THEY ARE TURNED", "subset": "test_other", "task_type": "understanding", "prediction": "they should be dried in the stove or oven on a sieve and turned every six or eight hours fresh powdered sugar being sifted over them every time they are turned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0005.flac", "answer": "LET IT BOIL UP AGAIN THEN TAKE IT OFF AND REMOVE CAREFULLY THE SCUM THAT HAS RISEN", "subset": "test_other", "task_type": "understanding", "prediction": "let it boil up again then take it off and remove carefully the scum that has risen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0015.flac", "answer": "MARMALADES AND JAMS DIFFER LITTLE FROM EACH OTHER THEY ARE PRESERVES OF A HALF LIQUID CONSISTENCY MADE BY BOILING THE PULP OF FRUITS AND SOMETIMES PART OF THE RINDS WITH SUGAR", "subset": "test_other", "task_type": "understanding", "prediction": "marmalades and jams differ little from each other they are preserves of half liquid consistency made by boiling the pulp of fruits and sometimes part of the rinds with sugar", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0008.flac", "answer": "FOURTEEN NINETY NINE", "subset": "test_other", "task_type": "understanding", "prediction": "fourteen ninety nine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0018.flac", "answer": "CONFECTIONARY FIFTEEN O EIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "confectionery fifteen o eight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0017.flac", "answer": "IN ALL THE OPERATIONS FOR PRESERVE MAKING WHEN THE PRESERVING PAN IS USED IT SHOULD NOT BE PLACED ON THE FIRE BUT ON A TRIVET UNLESS THE JAM IS MADE ON A HOT PLATE WHEN THIS IS NOT NECESSARY", "subset": "test_other", "task_type": "understanding", "prediction": "in all the operations for preserve making when the preserving pan is used it should not be placed on the fire but on a trivet unless the jam is made on a hot plate when this is not necessary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0004.flac", "answer": "IF YOU DIP THE FINGER INTO THE SYRUP AND APPLY IT TO THE THUMB THE TENACITY OF THE SYRUP WILL ON SEPARATING THE FINGER AND THUMB AFFORD A THREAD WHICH SHORTLY BREAKS THIS IS THE LITTLE THREAD", "subset": "test_other", "task_type": "understanding", "prediction": "if you dip the finger into the syrup and apply it to the thumb the tenacity of the syrup will on separating the finger and thumb afford a thread which shortly breaks this is the little thread", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0021.flac", "answer": "HOWEVER AS LATE AS THE REIGNS OF OUR TWO LAST GEORGES FABULOUS SUMS WERE OFTEN EXPENDED UPON FANCIFUL DESSERTS", "subset": "test_other", "task_type": "understanding", "prediction": "however as late as the reign of our two last georges fabulous sums were often expended upon fanciful desserts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0014.flac", "answer": "MARMALADES JAMS AND FRUIT PASTES ARE OF THE SAME NATURE AND ARE NOW IN VERY GENERAL REQUEST", "subset": "test_other", "task_type": "understanding", "prediction": "marmalades jams and fruit paste are of the same nature and are now in very general request", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0010.flac", "answer": "THE REASON WHY THE FRUIT IS EMPTIED OUT OF THE PRESERVING PAN INTO AN EARTHEN PAN IS THAT THE ACID OF THE FRUIT ACTS UPON THE COPPER OF WHICH THE PRESERVING PANS ARE USUALLY MADE", "subset": "test_other", "task_type": "understanding", "prediction": "the reason why the fruit is emptied out of the preserving pan into an earthen pan is that the acid of the fruit acts upon the copper of which the preserving pans are usually made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/3538/142836/3538-142836-0013.flac", "answer": "IN THIS WAY IT IS ALSO THAT ORANGE AND LEMON CHIPS ARE PRESERVED", "subset": "test_other", "task_type": "understanding", "prediction": "in this way it is also that orange and lemon chips are preserved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0005.flac", "answer": "AND SHE THREW DOWN THE JEW'S HEAD BEFORE HIM", "subset": "test_other", "task_type": "understanding", "prediction": "and she threw down the jews head before him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0009.flac", "answer": "PRESENTLY HASAN SHUMAN CAME OUT OF A CLOSET AND SAID TO HIM HAST THOU GOTTEN THE GEAR O ALI", "subset": "test_other", "task_type": "understanding", "prediction": "presently hasan shuman came out of a closet and said to him hast thou gotten the gear o ali", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0008.flac", "answer": "SO HE ATE AND FELL DOWN SENSELESS FOR THE SWEETMEATS WERE DRUGGED WITH BHANG WHEREUPON THE KAZI BUNDLED HIM INTO THE SACK AND MADE OFF WITH HIM CHARGER AND CHEST AND ALL TO THE BARRACK OF THE FORTY", "subset": "test_other", "task_type": "understanding", "prediction": "so he ate and fell down senseless for the sweetmeats were drugged with bang whereupon the kazi bundled him into the sack and made off with him charger and chasstenon to the barrack of the forty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0014.flac", "answer": "QUOTH AL RASHID WHOSE HEAD IS THIS", "subset": "test_other", "task_type": "understanding", "prediction": "quoth arashid whose head is this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0012.flac", "answer": "ANSWERED HASAN I KNOW WHERE HE IS AND OPENING THE DOOR OF THE CLOSET SHOWED HIM THE SWEETMEAT SELLER WITHIN DRUGGED AND SENSELESS", "subset": "test_other", "task_type": "understanding", "prediction": "answered hassan i know where he is and opening the door of the closet showed him the sweetmeat seller within drugged and senseless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0016.flac", "answer": "HE REPLIED I HAVE FORTY LADS BUT THEY ARE IN CAIRO", "subset": "test_other", "task_type": "understanding", "prediction": "he replied i have forty lads but they are in cairo", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0007.flac", "answer": "THEN HE SET OUT REJOICING TO RETURN TO THE BARRACK OF THE FORTY", "subset": "test_other", "task_type": "understanding", "prediction": "then he set out rejoicing to return to the barrack of the forty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0004.flac", "answer": "AND HAVING THUS ISLAMISED SHE ASKED HIM DO MEN IN THE FAITH OF AL ISLAM GIVE MARRIAGE PORTIONS TO WOMEN OR DO WOMEN DOWER MEN", "subset": "test_other", "task_type": "understanding", "prediction": "and having thus islamized she asked him do men in the faith of al islam give marriage portions to women or do women dower men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0015.flac", "answer": "SO ALI RELATED TO HIM ALL THAT HAD PASSED FROM FIRST TO LAST AND THE CALIPH SAID I HAD NOT THOUGHT THOU WOULDST KILL HIM FOR THAT HE WAS A SORCERER", "subset": "test_other", "task_type": "understanding", "prediction": "so ali related to him all that passed from first to last and the caliph said i had not thought that thou wouldst kill him for that he was a sorcerer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0002.flac", "answer": "THE KNOCKER REPLIED KAMAR DAUGHTER OF AZARIAH THE JEW SAY ME IS ALI OF CAIRO WITH YOU", "subset": "test_other", "task_type": "understanding", "prediction": "the knocker replied come out daughter of azariah the jew say me is ali of cairo with you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0013.flac", "answer": "SO I WENT ROUND ABOUT THE HIGHWAYS OF THE CITY TILL I MET A SWEETMEAT SELLER AND BUYING HIS CLOTHES AND STOCK IN TRADE AND GEAR FOR TEN DINARS DID WHAT WAS DONE", "subset": "test_other", "task_type": "understanding", "prediction": "so i went round about the highways of the city till i met a sweetmeat seller and buying his clothes and stock in trade and gear for ten dinars did what was done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0010.flac", "answer": "SO HE TOLD HIM WHAT HAD BEFALLEN HIM AND ADDED IF I KNOW WHITHER THE RASCAL IS GONE AND WHERE TO FIND THE KNAVE I WOULD PAY HIM OUT", "subset": "test_other", "task_type": "understanding", "prediction": "so he told them what had befallen him and added if i know whither the rascal is gone and where to find the knave i will pay him out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0006.flac", "answer": "NOW THE CAUSE OF HER SLAYING HER SIRE WAS AS FOLLOWS", "subset": "test_other", "task_type": "understanding", "prediction": "now the cause of her slaying her sire was as follows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0003.flac", "answer": "REPLIED THE BROKER'S DAUGHTER O THOU DAUGHTER OF A DOG", "subset": "test_other", "task_type": "understanding", "prediction": "replied the broker s daughter o thou daughter of a dog", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0011.flac", "answer": "KNOWEST THOU WHITHER HE WENT", "subset": "test_other", "task_type": "understanding", "prediction": "knowest thou whither he went", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0000.flac", "answer": "WHEN IT WAS THE SEVEN HUNDRED AND EIGHTEENTH NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "when it was the seven hundred and eighteenth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/258277/8461-258277-0001.flac", "answer": "BUT HE ANSWERED NEEDS MUST I HAVE ZAYNAB ALSO NOW SUDDENLY THERE CAME A RAP AT THE DOOR AND THE MAID SAID WHO IS AT THE DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "but he answered needs must i have zaynab osay now suddenly there came a rap at the door and the maid said who is at the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0007.flac", "answer": "THEY ARE FAST RISING AT LEAST SAID ULRICA AND A SIGNAL SHALL SOON WAVE TO WARN THE BESIEGERS TO PRESS HARD UPON THOSE WHO WOULD EXTINGUISH THEM", "subset": "test_other", "task_type": "understanding", "prediction": "they are fast rising at least said eureka and a signal shall soon wave to warn the besiegers to press hard upon those who would extinguish them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0013.flac", "answer": "AT LENGTH DE BRACY FELL", "subset": "test_other", "task_type": "understanding", "prediction": "at length de bracy fell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0010.flac", "answer": "THE BLACK KNIGHT WITH PORTENTOUS STRENGTH FORCED HIS WAY INWARD IN DESPITE OF DE BRACY AND HIS FOLLOWERS", "subset": "test_other", "task_type": "understanding", "prediction": "the black knight with portentous strength forces way inward in despite of de bracy and his followers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0026.flac", "answer": "HERE IS A BUGLE WHICH AN ENGLISH YEOMAN HAS ONCE WORN I PRAY YOU TO KEEP IT AS A MEMORIAL OF YOUR GALLANT BEARING", "subset": "test_other", "task_type": "understanding", "prediction": "here is a bugle which an english yeoman has once worn i pray you to keep it as a memorial of your gallant bearing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0012.flac", "answer": "THE BLACK KNIGHT WAS SOON ENGAGED IN DESPERATE COMBAT WITH THE NORMAN CHIEF AND THE VAULTED ROOF OF THE HALL RUNG WITH THEIR FURIOUS BLOWS", "subset": "test_other", "task_type": "understanding", "prediction": "the black knight was soon engaged in desperate combat with the norman chief and the vaulted roof of the hall rung with the furious blows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0021.flac", "answer": "BEFORE LONG THE TOWERING FLAMES HAD SURMOUNTED EVERY OBSTRUCTION AND ROSE TO THE EVENING SKIES ONE HUGE AND BURNING BEACON SEEN FAR AND WIDE THROUGH THE ADJACENT COUNTRY TOWER AFTER TOWER CRASHED DOWN WITH BLAZING ROOF AND RAFTER", "subset": "test_other", "task_type": "understanding", "prediction": "before long the towering flames had surmounted every obstruction and rose through the evening skies one huge and burning beacon seen far and wide through the adjacent country tower after tower crashed down with blazing roof and rafter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0017.flac", "answer": "THE LIFE OF EVERY MAN IN THE CASTLE SHALL ANSWER IT IF A HAIR OF HIS HEAD BE SINGED SHOW ME HIS CHAMBER", "subset": "test_other", "task_type": "understanding", "prediction": "the life of every man in the castle shall answer it if a hair of his head be singed show me his chamber", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0022.flac", "answer": "AT LENGTH WITH A TERRIFIC CRASH THE WHOLE TURRET GAVE WAY AND SHE PERISHED IN THE FLAMES WHICH HAD CONSUMED HER TYRANT", "subset": "test_other", "task_type": "understanding", "prediction": "at length with a terrific crash the whole tower gave way and she perished in the flames which had consumed her tyrant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0037.flac", "answer": "AT HIS FEET WAS PLACED A TABLE OCCUPIED BY TWO SCRIBES WHOSE DUTY IT WAS TO RECORD THE PROCEEDINGS OF THE DAY", "subset": "test_other", "task_type": "understanding", "prediction": "at his feet was placed a table occupied by two scribes whose duty it was to record the proceedings of the day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0027.flac", "answer": "SO SAYING HE MOUNTED HIS STRONG WAR HORSE AND RODE OFF THROUGH THE FOREST", "subset": "test_other", "task_type": "understanding", "prediction": "so saying he mounted his strong war horse and rode off through the forest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0009.flac", "answer": "THE DEFENDERS FINDING THE CASTLE TO BE ON FIRE NOW DETERMINED TO SELL THEIR LIVES AS DEARLY AS THEY COULD AND HEADED BY DE BRACY THEY THREW OPEN THE GATE AND WERE AT ONCE INVOLVED IN A TERRIFIC CONFLICT WITH THOSE OUTSIDE", "subset": "test_other", "task_type": "understanding", "prediction": "the defenders finding the castle to be on fire now determined to sell their lives as dearly as they could and headed by the bracy they threw open the gate and were at once involved in a terrific conflict with those outside", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0025.flac", "answer": "DE BRACY BOWED LOW AND IN SILENCE THREW HIMSELF UPON A HORSE AND GALLOPED OFF THROUGH THE WOOD", "subset": "test_other", "task_type": "understanding", "prediction": "de bracy bowed low and in silence threw himself upon a horse and galloped off through the woods", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0006.flac", "answer": "REMEMBEREST THOU THE MAGAZINE OF FUEL THAT IS STORED BENEATH THESE APARTMENTS WOMAN", "subset": "test_other", "task_type": "understanding", "prediction": "rememberest thou the magazine of fuel that is stored beneath these apartments woman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0034.flac", "answer": "POOR ISAAC WAS HURRIED OFF ACCORDINGLY AND EXPELLED FROM THE PRECEPTORY ALL HIS ENTREATIES AND EVEN HIS OFFERS UNHEARD AND DISREGARDED", "subset": "test_other", "task_type": "understanding", "prediction": "poor isaac was hurried off accordingly and expelled from the preceptory all his entreaties and even his offers unheard and disregarded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0005.flac", "answer": "EXCLAIMED THE NORMAN HO", "subset": "test_other", "task_type": "understanding", "prediction": "exclaimed the norman ho", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0029.flac", "answer": "AND WITH THIS EPISTLE THE UNHAPPY OLD MAN SET OUT TO PROCURE HIS DAUGHTER'S LIBERATION", "subset": "test_other", "task_type": "understanding", "prediction": "and with this epistle the unhappy old man set out to procure his daughter s liberation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0030.flac", "answer": "THE TEMPLAR IS FLED SAID DE BRACY IN ANSWER TO THE PRINCE'S EAGER QUESTIONS FRONT DE BOEUF YOU WILL NEVER SEE MORE AND HE ADDED IN A LOW AND EMPHATIC TONE RICHARD IS IN ENGLAND I HAVE SEEN HIM AND SPOKEN WITH HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the templar is fled said de bracy in answer to the prince s eager questions front de boeuf you will never see more and he added in a low and emphatic tone richard is in england i have seen him and spoken with him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0011.flac", "answer": "TWO OF THE FOREMOST INSTANTLY FELL AND THE REST GAVE WAY NOTWITHSTANDING ALL THEIR LEADERS EFFORTS TO STOP THEM", "subset": "test_other", "task_type": "understanding", "prediction": "two of the foremost instantly fell and the rest gave way notwithstanding all the leaders efforts to stop them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0020.flac", "answer": "AS THE FIRE COMMENCED TO SPREAD RAPIDLY THROUGH ALL PARTS OF THE CASTLE ULRICA APPEARED ON ONE OF THE TURRETS", "subset": "test_other", "task_type": "understanding", "prediction": "as the fire commenced to spread rapidly through all parts of the castle eureka appeared on one of the turrets", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0031.flac", "answer": "HE APPEALED TO DE BRACY TO ASSIST HIM IN THIS PROJECT AND BECAME AT ONCE DEEPLY SUSPICIOUS OF THE KNIGHT'S LOYALTY TOWARDS HIM WHEN HE DECLINED TO LIFT HAND AGAINST THE MAN WHO HAD SPARED HIS OWN LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "he appealed to de bracy to assist him in this project and became at once deeply suspicious of the knight s loyalty towards him when he declined to lift hand against the man who had spared his own life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0028.flac", "answer": "DURING ALL THIS TIME ISAAC OF YORK SAT MOURNFULLY APART GRIEVING FOR THE LOSS OF HIS DEARLY LOVED DAUGHTER REBECCA", "subset": "test_other", "task_type": "understanding", "prediction": "during all this time isaac of york sat mournfully apart grieving for the loss of his dearly loved daughter rebecca", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0036.flac", "answer": "SHE GAZED ACCORDINGLY UPON A SCENE WHICH MIGHT WELL HAVE STRUCK TERROR INTO A BOLDER HEART THAN HERS", "subset": "test_other", "task_type": "understanding", "prediction": "she gazed accordingly upon a scene which might well have struck terror into a bolder heart than hers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0015.flac", "answer": "YET FIRST LET ME SAY SAID DE BRACY WHAT IT IMPORTS THEE TO KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "yet first let me say said de bracy what it imports thee to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0003.flac", "answer": "WHAT ART THOU HE EXCLAIMED IN TERROR", "subset": "test_other", "task_type": "understanding", "prediction": "what art thou he exclaimed in terror", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0019.flac", "answer": "BUT IN OTHER PARTS THE BESIEGERS PURSUED THE DEFENDERS OF THE CASTLE FROM CHAMBER TO CHAMBER AND SATIATED IN THEIR BLOOD THE VENGEANCE WHICH HAD LONG ANIMATED THEM AGAINST THE SOLDIERS OF THE TYRANT FRONT DE BOEUF", "subset": "test_other", "task_type": "understanding", "prediction": "but in other parts the besiegers pursued the defenders of the castle from chamber to chamber and satiated in the blood the vengeance which had long animated them against the soldiers of the tyrant front de boeuf", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0008.flac", "answer": "MEANWHILE THE BLACK KNIGHT HAD LED HIS FORCES AGAIN TO THE ATTACK AND SO VIGOROUS WAS THEIR ASSAULT THAT BEFORE LONG THE GATE OF THE CASTLE ALONE SEPARATED THEM FROM THOSE WITHIN", "subset": "test_other", "task_type": "understanding", "prediction": "meanwhile the black knight had led his forces again to the attack and so vigorous was their assault that before long the gate of the castle alone separated them from those within", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0035.flac", "answer": "THE ASSURANCE THAT SHE POSSESSED SOME FRIEND IN THIS AWFUL ASSEMBLY GAVE HER COURAGE TO LOOK AROUND AND TO MARK INTO WHOSE PRESENCE SHE HAD BEEN CONDUCTED", "subset": "test_other", "task_type": "understanding", "prediction": "the assurance that she possessed some friend in this awful assembly gave a courage to look around and to mark into whose presence she had been conducted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0033.flac", "answer": "HE HAD NOT UNTIL THEN BEEN INFORMED OF THE PRESENCE OF THE JEWISH MAIDEN IN THE ABODE OF THE TEMPLARS AND GREAT WAS HIS FURY AND INDIGNATION ON LEARNING THAT SHE WAS AMONGST THEM", "subset": "test_other", "task_type": "understanding", "prediction": "he had not until then been informed of the presence of the jewish maiden in the abode of the templars and great was his fury and indignation on learning that she was amongst them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0023.flac", "answer": "WHEN THE OUTLAWS HAD DIVIDED THE SPOILS WHICH THEY HAD TAKEN FROM THE CASTLE OF TORQUILSTONE CEDRIC PREPARED TO TAKE HIS DEPARTURE", "subset": "test_other", "task_type": "understanding", "prediction": "when the outlaws had divided the spoils which they had taken from the castle of torquilstone cedric prepared to take his departure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0002.flac", "answer": "AS HE LAY UPON HIS BED RACKED WITH PAIN AND MENTAL AGONY AND FILLED WITH THE FEAR OF RAPIDLY APPROACHING DEATH HE HEARD A VOICE ADDRESS HIM", "subset": "test_other", "task_type": "understanding", "prediction": "as he lay upon his bed racked with pain and mental agony and filled with a fear of rapidly approaching death he heard a voice address him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0038.flac", "answer": "THE PRECEPTORS OF WHOM THERE WERE FOUR PRESENT OCCUPIED SEATS BEHIND THEIR SUPERIORS AND BEHIND THEM STOOD THE ESQUIRES OF THE ORDER ROBED IN WHITE", "subset": "test_other", "task_type": "understanding", "prediction": "the preceptors of whom there were four present occupied seats behind the superiors and behind them stood the esquires of the order robed in white", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0001.flac", "answer": "IT WAS ON THEIR JOURNEY TO THAT TOWN THAT THEY WERE OVERTAKEN ON THE ROAD BY CEDRIC AND HIS PARTY IN WHOSE COMPANY THEY WERE AFTERWARDS CARRIED CAPTIVE TO THE CASTLE OF TORQUILSTONE", "subset": "test_other", "task_type": "understanding", "prediction": "it was on their journey to that town that they were overtaken on the road by cedric and his party in whose company they were afterwards carried captive to the castle of torquilstone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0018.flac", "answer": "RAISING THE WOUNDED MAN WITH EASE THE BLACK KNIGHT RUSHED WITH HIM TO THE POSTERN GATE AND HAVING THERE DELIVERED HIS BURDEN TO THE CARE OF TWO YEOMEN HE AGAIN ENTERED THE CASTLE TO ASSIST IN THE RESCUE OF THE OTHER PRISONERS", "subset": "test_other", "task_type": "understanding", "prediction": "raising the wounded man with ease the black knight rushed with them to the postern gate and having there delivered his burden to the care of two yeomen he again entered the castle to assist in the rescue of the other prisoners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0004.flac", "answer": "LEAVE ME AND SEEK THE SAXON WITCH ULRICA WHO WAS MY TEMPTRESS LET HER AS WELL AS I TASTE THE TORTURES WHICH ANTICIPATE HELL", "subset": "test_other", "task_type": "understanding", "prediction": "leave me and seek the saxon witch eureka who was my temptress let her as well as i taste the tortures which anticipate hell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0032.flac", "answer": "BEFORE REACHING HIS DESTINATION HE WAS TOLD THAT LUCAS DE BEAUMANOIR THE GRAND MASTER OF THE ORDER OF THE TEMPLARS WAS THEN ON VISIT TO THE PRECEPTORY", "subset": "test_other", "task_type": "understanding", "prediction": "before reaching his destination he was told that lucas de bormannoir the grand master of the order of the templars was then on a visit to the preceptory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0024.flac", "answer": "HE LEFT THE GALLANT BAND OF FORESTERS SORROWING DEEPLY FOR HIS LOST FRIEND THE LORD OF CONINGSBURGH AND HE AND HIS FOLLOWERS HAD SCARCE DEPARTED WHEN A PROCESSION MOVED SLOWLY FROM UNDER THE GREENWOOD BRANCHES IN THE DIRECTION WHICH HE HAD TAKEN IN THE CENTRE OF WHICH WAS THE CAR IN WHICH THE BODY OF ATHELSTANE WAS LAID", "subset": "test_other", "task_type": "understanding", "prediction": "he left the gallant band of foresters sorrowing deeply for his lost friend the lord of coningsburgh and he and his followers had scarce departed when a procession moved slowly from under the greenwood branches in the direction which he had taken in the centre of which was the car in which the body of adelstane was laid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0016.flac", "answer": "EXCLAIMED THE BLACK KNIGHT PRISONER AND PERISH", "subset": "test_other", "task_type": "understanding", "prediction": "exclaimed the black knight prisoner and perish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0000.flac", "answer": "HIS FOLLOWERS RUSHED FORWARD TO WHERE HE LAY AND THEIR UNITED FORCE COMPELLING THE BLACK KNIGHT TO PAUSE THEY DRAGGED THEIR WOUNDED LEADER WITHIN THE WALLS", "subset": "test_other", "task_type": "understanding", "prediction": "his followers rush forward to where he lay and their united force compelling the black knight to pause they drag the wounded leader within the walls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/281231/8461-281231-0014.flac", "answer": "TELL ME THY NAME OR WORK THY PLEASURE ON ME", "subset": "test_other", "task_type": "understanding", "prediction": "tell me thy name or work thy pleasure on me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0003.flac", "answer": "I WANT TO SEE ALL THE PICTURES THE MODERN PICTURES ESPECIALLY", "subset": "test_other", "task_type": "understanding", "prediction": "i want to see all the pictures the modern pictures especially", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0001.flac", "answer": "SHE MEANT TO BE SCRUPULOUSLY CONSCIENTIOUS IN THE ADMINISTRATION OF HER TALENTS AND SOMETIMES AT CHURCH ON A SUNDAY WHEN THE SERMON WAS PARTICULARLY AWAKENING SHE MENTALLY DEBATED THE SERIOUS QUESTION AS TO WHETHER NEW BONNETS AND A PAIR OF JOUVIN'S GLOVES DAILY WERE NOT SINFUL BUT I THINK SHE DECIDED THAT THE NEW BONNETS AND GLOVES WERE ON THE WHOLE A PARDONABLE WEAKNESS AS BEING GOOD FOR TRADE", "subset": "test_other", "task_type": "understanding", "prediction": "she meant to be scrupulously conscientious in the administration of her talents and sometimes at church on a sunday when the sermon was particularly awakening she mentally debated a serious question as to whether new bonnets and a pair of juvans gloves daily were not sinful but i think she decided that the new bonnets and gloves were on the whole a pardonable weakness as being good for trade", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0006.flac", "answer": "IT WAS DRAWING TOWARDS THE CLOSE OF THIS DELIGHTFUL HONEYMOON TOUR AND IT WAS A BRIGHT SUNSHINY MORNING EARLY IN FEBRUARY BUT FEBRUARY IN PARIS IS SOMETIMES BETTER THAN APRIL IN LONDON", "subset": "test_other", "task_type": "understanding", "prediction": "he was drawing towards the close of this delightful honeymoon tour and it was a bright sunshiny morning early in february but february in paris is sometimes better than april in london", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0002.flac", "answer": "ONE MORNING LAURA TOLD HER HUSBAND WITH A GAY LAUGH THAT SHE WAS GOING TO VICTIMIZE HIM BUT HE WAS TO PROMISE TO BE PATIENT AND BEAR WITH HER FOR ONCE IN A WAY", "subset": "test_other", "task_type": "understanding", "prediction": "one morning laurent told her husband with a gay laugh that she was going to victimize him but he was to promise to be patient and bear with her for once in a way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0014.flac", "answer": "I DON'T THINK YOU WILL HAVE ANY DIFFICULTY IN FINDING THE HOUSE", "subset": "test_other", "task_type": "understanding", "prediction": "i do not think you will have any difficulty in finding the house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0007.flac", "answer": "BUT SHE FIXED UPON A PICTURE WHICH SHE SAID SHE PREFERRED TO ANYTHING SHE HAD SEEN IN THE GALLERY", "subset": "test_other", "task_type": "understanding", "prediction": "but she fixed upon a picture which she said she preferred to anything she had seen in the gallery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0005.flac", "answer": "SHE RETURNED IN A LITTLE MORE THAN TEN MINUTES IN THE FRESHEST TOILETTE ALL PALE SHIMMERING BLUE LIKE THE SPRING SKY WITH PEARL GREY GLOVES AND BOOTS AND PARASOL AND A BONNET THAT SEEMED MADE OF AZURE BUTTERFLIES", "subset": "test_other", "task_type": "understanding", "prediction": "she returned in a little more than ten minutes in the freshest toilette all pale shimmering blue like the spring sky with pearl gray gloves and boots and parasol and a bonnet that seemed made of azure butterflies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0000.flac", "answer": "AND LAURA HAD HER OWN PET PLANS", "subset": "test_other", "task_type": "understanding", "prediction": "and laura had her own pet plans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0004.flac", "answer": "I REMEMBER ALL THE RUBENSES AT THE LOUVRE FOR I SAW THEM THREE YEARS AGO WHEN I WAS STAYING IN PARIS WITH GRANDPAPA", "subset": "test_other", "task_type": "understanding", "prediction": "i remember all the rubens says at the louvre for i saw them three years ago when i was staying in paris with grandpapa", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0013.flac", "answer": "BUT THERE ARE SOME OTHERS WHO SAY THAT HIS MEMORY HAS NOT ALTOGETHER FAILED AND THAT HE IS STILL ENOUGH HARSHLY CRITICAL TOWARDS THE WORKS OF OTHERS", "subset": "test_other", "task_type": "understanding", "prediction": "but there are some others who say that his memory has not altogether failed and that he is still enough harshly critical towards the works of others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0010.flac", "answer": "I SHOULD SO LIKE ONE TO HANG IN MY MORNING ROOM AT JOCELYN'S ROCK", "subset": "test_other", "task_type": "understanding", "prediction": "i should so like one to hang in my morning room at jocelyn s rock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0015.flac", "answer": "YOU WILL BE DOING ME SUCH A FAVOUR PHILIP IF YOU'LL SAY YES", "subset": "test_other", "task_type": "understanding", "prediction": "you will be doing me such a favor philip if you will say yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0011.flac", "answer": "SHE TURNED TO THE FRENCH ARTIST PRESENTLY AND ASKED HIM WHERE THE ELDER MISTER KERSTALL LIVED AND IF THERE WAS ANY POSSIBILITY OF SEEING HIM", "subset": "test_other", "task_type": "understanding", "prediction": "she turned to the french artist presently and asked him where the elder mr cairnster lived and if there was any possibility of seeing him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0012.flac", "answer": "THEY HAVE SAID THAT HE IS EVEN A LITTLE IMBECILE THAT HE DOES NOT REMEMBER HIMSELF OF THE MOST COMMON EVENTS OF HIS LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "they have said that he is even a little imbecile that he does not remember himself of the most common events of his life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0009.flac", "answer": "HOW I WISH YOU COULD GET ME A COPY OF THAT PICTURE PHILIP LAURA SAID ENTREATINGLY", "subset": "test_other", "task_type": "understanding", "prediction": "how i wish you could get me a copy of that picture of philip laura said entreatingly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/8461/278226/8461-278226-0008.flac", "answer": "PHILIP JOCELYN WAS EXAMINING SOME PICTURES ON THE OTHER SIDE OF THE ROOM WHEN HIS WIFE MADE THIS DISCOVERY", "subset": "test_other", "task_type": "understanding", "prediction": "philip jocelyn was examining some pictures on the other side of the room when his wife made this discovery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0015.flac", "answer": "AFTER SEVERAL MONTHS WERE WASTED AND PIERO WOULD NEITHER WORK NOR PUT MEN TO WORK UPON THE PIECE I MADE HIM GIVE IT BACK", "subset": "test_other", "task_type": "understanding", "prediction": "after several months were wasted and piero would neither work nor put men to work upon the piece i made him give it back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0001.flac", "answer": "WHEN I SAW THAT THIS BUST CAME OUT SHARP AND CLEAN I SET AT ONCE TO CONSTRUCT A LITTLE FURNACE IN THE WORKSHOP ERECTED FOR ME BY THE DUKE AFTER MY OWN PLANS AND DESIGN IN THE HOUSE WHICH THE DUKE HAD GIVEN ME", "subset": "test_other", "task_type": "understanding", "prediction": "when i saw that this bust came out sharp and clean i set at once to construct a little furnace in the workshop erected for me by the duke after my own plans and design in the house which the duke had given me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0009.flac", "answer": "I SAID MY LORD I THANK YOU AND BEG YOU TO CONDESCEND SO FAR AS TO LISTEN TO FOUR WORDS IT IS TRUE THAT HE LENT ME A PAIR OF OLD SCALES TWO ANVILS AND THREE LITTLE HAMMERS WHICH ARTICLES I BEGGED HIS WORKMAN GIORGIO DA CORTONA FIFTEEN DAYS AGO TO FETCH BACK", "subset": "test_other", "task_type": "understanding", "prediction": "i said my lord i thank you and beg you to condescend so far as to listen to four words it is true that he lent me a pair of old scales two anvils and three little hammers which articles i begged his workman giorgio da cortona fifteen days ago to fetch back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0007.flac", "answer": "I HAD BETTER LOOK TO MY CONDUCT FOR IT HAD COME TO HIS EARS THAT I RELIED UPON HIS FAVOUR TO TAKE IN FIRST ONE MAN AND THEN ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "i had better look to my conduct for it had come to his ears that i relied upon his favour to take in first one man and then another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0014.flac", "answer": "I AM WILLING TO ENTER INTO COMPETITION WITH THE ANCIENTS AND FEEL ABLE TO SURPASS THEM FOR SINCE THOSE EARLY DAYS IN WHICH I MADE THE MEDALS OF POPE CLEMENT I HAVE LEARNED SO MUCH THAT I CAN NOW PRODUCE FAR BETTER PIECES OF THE KIND I THINK I CAN ALSO OUTDO THE COINS I STRUCK FOR DUKE ALESSANDRO WHICH ARE STILL HELD IN HIGH ESTEEM IN LIKE MANNER I COULD MAKE FOR YOU LARGE PIECES OF GOLD AND SILVER PLATE AS I DID SO OFTEN FOR THAT NOBLE MONARCH KING FRANCIS OF FRANCE THANKS TO THE GREAT CONVENIENCES HE ALLOWED ME WITHOUT EVER LOSING TIME FOR THE EXECUTION OF COLOSSAL STATUES OR OTHER WORKS OF THE SCULPTORS CRAFT", "subset": "test_other", "task_type": "understanding", "prediction": "i am willing to enter into competition with the ancients and feel able to surpass them for since those early days in which i made the medals of pope clement i have learned so much that i can now produce far better pieces of the kind i think i can also outdo the coins i struck for duke alessandro which are still held in high esteem in like manner i could make for you large pieces of gold and silver plate as i did so often for that noble monarch king francis of france thanks to the great conveniences he allowed me without ever losing time for the execution of colossal statues or other works of the sculptor s craft", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0008.flac", "answer": "I BEGGED HIS MOST ILLUSTRIOUS EXCELLENCY TO NAME A SINGLE PERSON WHOM I HAD EVER TAKEN IN", "subset": "test_other", "task_type": "understanding", "prediction": "i begged his most illustrious excellency to name a single person whom i had ever taken in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0000.flac", "answer": "AS I THOUGHT THAT THIS WAS DUE TO SOME FAULT IN THE EARTH I WANTED TO MAKE THESE FIRST EXPERIMENTS BEFORE I UNDERTOOK MY PERSEUS", "subset": "test_other", "task_type": "understanding", "prediction": "as i thought that this was due to some fault in the earth i wanted to make these first experiments before i undertook my perseus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0018.flac", "answer": "HAVING THIS EXCELLENT RESOLVE IN HEART I REACHED MY HOME", "subset": "test_other", "task_type": "understanding", "prediction": "having this excellent resolve in heart i reached my home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0003.flac", "answer": "I IN MY TURN FEEL THE SAME DESIRE AND HOPE TO PLAY MY PART LIKE THEM THEREFORE MY LORD GIVE ME THE LEAVE TO GO", "subset": "test_other", "task_type": "understanding", "prediction": "i in my turn feel the same desire and hope to play my part like them therefore my lord give me the leave to go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0006.flac", "answer": "THEN I THANKED HIM AND SAID I HAD NO GREATER DESIRE THAN TO SHOW THOSE ENVIOUS FOLK THAT I HAD IT IN ME TO EXECUTE THE PROMISED WORK", "subset": "test_other", "task_type": "understanding", "prediction": "then i thanked him and said i had no greater desire than to show those envious folk that i had it in me to execute the promised work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0012.flac", "answer": "WHEN HE HAD HEARD THIS SPEECH THE DUKE ROSE UP IN ANGER AND SENT FOR BERNARDONE WHO WAS FORCED TO TAKE FLIGHT AS FAR AS VENICE HE AND ANTONIO LANDI WITH HIM", "subset": "test_other", "task_type": "understanding", "prediction": "when he had heard this speech the duke rose up in anger and sent for barnardone who was forced to take flight as far as venice he and antonio landi with him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0013.flac", "answer": "YOU HAD BETTER PUT THIS TO THE PROOF AND I WILL GO AT ONCE TO THE BARGELLO", "subset": "test_other", "task_type": "understanding", "prediction": "you had better put this to the proof and i will go at once to the bargello", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0016.flac", "answer": "AMONG ARTISTS CERTAIN ENRAGED SCULPTORS LAUGHED AT ME AND CALLED ME THE NEW SCULPTOR", "subset": "test_other", "task_type": "understanding", "prediction": "among artists certain enraged sculptors laughed at me and called me the new sculptor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0017.flac", "answer": "NOW I HOPE TO SHOW THEM THAT I AM AN OLD SCULPTOR IF GOD SHALL GRANT ME THE BOON OF FINISHING MY PERSEUS FOR THAT NOBLE PIAZZA OF HIS MOST ILLUSTRIOUS EXCELLENCY", "subset": "test_other", "task_type": "understanding", "prediction": "now i hope to show them that i am an old sculptor if god shall grant me the boon of finishing my perseus for that noble piazza of his most illustrious excellency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0011.flac", "answer": "I HOPE TO PROVE ON WHAT ACCOUNT THAT SCOUNDREL TRIES TO BRING ME INTO DISGRACE", "subset": "test_other", "task_type": "understanding", "prediction": "i hope to prove on what account that scoundrel tries to bring me into disgrace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4840, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0010.flac", "answer": "GIORGIO CAME FOR THEM HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "giorgio came for them his health", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4841, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0005.flac", "answer": "I ASK NO FURTHER REWARD FOR MY LABOURS UP TO THIS TIME THAN THE GRACIOUS FAVOUR OF YOUR MOST ILLUSTRIOUS EXCELLENCY", "subset": "test_other", "task_type": "understanding", "prediction": "i ask no further reward for my labors up to this time than the gracious favor of your most illustrious excellency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4842, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0002.flac", "answer": "IT WAS AN EXTREMELY DIFFICULT TASK AND I WAS ANXIOUS TO OBSERVE ALL THE NICETIES OF ART WHICH I HAD LEARNED SO AS NOT TO LAPSE INTO SOME ERROR", "subset": "test_other", "task_type": "understanding", "prediction": "it was an extremely difficult task and i was anxious to observe all the niceties of art which i had learned so as not to lapse into some error", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4843, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/14317/4294-14317-0004.flac", "answer": "BUT BEWARE OF LETTING BANDINELLO QUIT YOU RATHER BESTOW UPON HIM ALWAYS MORE THAN HE DEMANDS FOR IF HE GOES INTO FOREIGN PARTS HIS IGNORANCE IS SO PRESUMPTUOUS THAT HE IS JUST THE MAN TO DISGRACE OUR MOST ILLUSTRIOUS SCHOOL", "subset": "test_other", "task_type": "understanding", "prediction": "but beware of letting bandinello quit you rather bestow upon him always more than he demands for if he goes into foreign parts his ignorance is so presumptuous that he is just the man to disgrace our most illustrious school", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4844, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0008.flac", "answer": "HIS DISCOMFORT WAS AUGMENTED BY ALL THE REFLECTIONS WHICH OCCURRED TO HIM", "subset": "test_other", "task_type": "understanding", "prediction": "his discomfort was augmented by all the reflections which occurred to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4845, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0014.flac", "answer": "SILVER GOLD HERE IT IS", "subset": "test_other", "task_type": "understanding", "prediction": "silver gold here it is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4846, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0006.flac", "answer": "WHATEVER MAY HAVE BEEN HIS DESIRE TO REMAIN WHERE HE WAS HE COULD NOT HALT THERE HE WAS IRRESISTIBLY CONSTRAINED TO CONTINUE TO ADVANCE TO EXAMINE TO THINK TO MARCH FURTHER", "subset": "test_other", "task_type": "understanding", "prediction": "whatever may have been his desire to remain where he was he could not halt there he was irresistibly constrained to continue to advance to examine to think to march further", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4847, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0009.flac", "answer": "IN THE TROUBLED STATE OF HIS CONSCIENCE HE NO LONGER THOUGHT OF CERTAIN SERIOUS SIDES OF EXISTENCE", "subset": "test_other", "task_type": "understanding", "prediction": "in the troubled state of his conscience he no longer thought of certain serious sides of existence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4848, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0027.flac", "answer": "ONE MORNING ON HIS RETURN FROM THE LAW SCHOOL MARIUS FOUND A LETTER FROM HIS AUNT AND THE SIXTY PISTOLES THAT IS TO SAY SIX HUNDRED FRANCS IN GOLD IN A SEALED BOX", "subset": "test_other", "task_type": "understanding", "prediction": "one morning on his return from the law school marius found a letter from his aunt and the sixty pistoles that is to say six hundred francs in gold in a sealed box", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4849, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0028.flac", "answer": "MARIUS SENT BACK THE THIRTY LOUIS TO HIS AUNT WITH A RESPECTFUL LETTER IN WHICH HE STATED THAT HE HAD SUFFICIENT MEANS OF SUBSISTENCE AND THAT HE SHOULD BE ABLE THENCEFORTH TO SUPPLY ALL HIS NEEDS", "subset": "test_other", "task_type": "understanding", "prediction": "marius sent back the thirty louis to his aunt with a respectful letter in which he stated that he had sufficient means of subsistence and that he should be able thenceforth to supply all his needs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4850, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0001.flac", "answer": "HE HAD BUT JUST ACQUIRED A FAITH MUST HE THEN REJECT IT ALREADY", "subset": "test_other", "task_type": "understanding", "prediction": "he had but just acquired a faith must he then reject it already", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4851, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0000.flac", "answer": "HE FELT WHAT THE EARTH MAY POSSIBLY FEEL AT THE MOMENT WHEN IT IS TORN OPEN WITH THE IRON IN ORDER THAT GRAIN MAY BE DEPOSITED WITHIN IT IT FEELS ONLY THE WOUND THE QUIVER OF THE GERM AND THE JOY OF THE FRUIT ONLY ARRIVE LATER", "subset": "test_other", "task_type": "understanding", "prediction": "he felt what the earth may possibly feel at the moment when it is torn open with the iron in order that grain may be deposited within it it feels only the wound the quiver of the germ the joy of the fruit only arrive later", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4852, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0011.flac", "answer": "REQUEST COURFEYRAC TO COME AND TALK WITH ME SAID MARIUS", "subset": "test_other", "task_type": "understanding", "prediction": "request courfeyrac to come and talk with me said marius", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4853, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0025.flac", "answer": "I HAVE TEN FRANCS LEFT SAID MARIUS", "subset": "test_other", "task_type": "understanding", "prediction": "i have ten francs left said marius", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4854, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0004.flac", "answer": "MARIUS WAS CLEAR EYED AND HE REQUIRED THE TRUE LIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "marius was clear eyed and he required the true light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4855, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0010.flac", "answer": "THEY SOON ELBOWED HIM ABRUPTLY", "subset": "test_other", "task_type": "understanding", "prediction": "they soon elbowed him abruptly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4856, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0015.flac", "answer": "YOU WILL THEN HAVE ONLY A PAIR OF TROUSERS A WAISTCOAT A HAT AND A COAT AND MY BOOTS", "subset": "test_other", "task_type": "understanding", "prediction": "you will then have only a pair of trousers a waistcoat a hat and a coat and my boots", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4857, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0005.flac", "answer": "THE HALF LIGHTS OF DOUBT PAINED HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the half lights of doubt pained him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4858, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0018.flac", "answer": "DO YOU KNOW GERMAN NO", "subset": "test_other", "task_type": "understanding", "prediction": "do you know german no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4859, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0002.flac", "answer": "HE AFFIRMED TO HIMSELF THAT HE WOULD NOT HE DECLARED TO HIMSELF THAT HE WOULD NOT DOUBT AND HE BEGAN TO DOUBT IN SPITE OF HIMSELF", "subset": "test_other", "task_type": "understanding", "prediction": "he affirmed to himself that he would not he declared to himself that he would not doubt and he began to doubt in spite of himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4860, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0021.flac", "answer": "HE PAID TWENTY FRANCS FOR THE CAST OFF GARMENTS THEY WENT TO THE WATCHMAKER'S", "subset": "test_other", "task_type": "understanding", "prediction": "he paid twenty francs for the cast off garments they went to the watchmaker s", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4861, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0020.flac", "answer": "THE CLOTHES DEALER WAS SENT FOR", "subset": "test_other", "task_type": "understanding", "prediction": "the clothes dealer was sent for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4862, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0007.flac", "answer": "HE FEARED AFTER HAVING TAKEN SO MANY STEPS WHICH HAD BROUGHT HIM NEARER TO HIS FATHER TO NOW TAKE A STEP WHICH SHOULD ESTRANGE HIM FROM THAT FATHER", "subset": "test_other", "task_type": "understanding", "prediction": "he feared after having taken so many steps which had brought him nearer to his father to now take a step which should estrange him from that father", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4863, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0013.flac", "answer": "WHAT ARE YOU GOING TO DO I DO NOT KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "what are you going to do i do not know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4864, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0012.flac", "answer": "WHAT IS TO BECOME OF YOU SAID COURFEYRAC", "subset": "test_other", "task_type": "understanding", "prediction": "what is to become of you said courfeyrac", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4865, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0019.flac", "answer": "IT IS BADLY PAID WORK BUT ONE CAN LIVE BY IT", "subset": "test_other", "task_type": "understanding", "prediction": "it is badly paid work but one can live by it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4866, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0016.flac", "answer": "THAT WILL BE ENOUGH", "subset": "test_other", "task_type": "understanding", "prediction": "that will be enough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4867, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0024.flac", "answer": "THE LANDLORD PRESENTED HIS BILL WHICH HAD TO BE PAID ON THE SPOT", "subset": "test_other", "task_type": "understanding", "prediction": "the landlord presented his bill which had to be paid on the spot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4868, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0022.flac", "answer": "HE BOUGHT THE WATCH FOR FORTY FIVE FRANCS", "subset": "test_other", "task_type": "understanding", "prediction": "he bought the watch for forty five francs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4869, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0026.flac", "answer": "THAT WILL BE SWALLOWING A TONGUE VERY FAST OR A HUNDRED SOUS VERY SLOWLY", "subset": "test_other", "task_type": "understanding", "prediction": "that will be swallowing a tongue very fast or a hundred sous very slowly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4870, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0029.flac", "answer": "AT THAT MOMENT HE HAD THREE FRANCS LEFT", "subset": "test_other", "task_type": "understanding", "prediction": "at that moment he had three francs left", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4871, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0003.flac", "answer": "TO STAND BETWEEN TWO RELIGIONS FROM ONE OF WHICH YOU HAVE NOT AS YET EMERGED AND ANOTHER INTO WHICH YOU HAVE NOT YET ENTERED IS INTOLERABLE AND TWILIGHT IS PLEASING ONLY TO BAT LIKE SOULS", "subset": "test_other", "task_type": "understanding", "prediction": "to stand between two religions from one of which you have not as yet emerged and another into which you have not yet entered is intolerable and twilight is pleasing only to bat like souls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4872, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0017.flac", "answer": "NO IT IS NOT GOOD WHAT WILL YOU DO AFTER THAT", "subset": "test_other", "task_type": "understanding", "prediction": "no it is not good what will you do after that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4873, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/9934/4294-9934-0023.flac", "answer": "HELLO I HAD FORGOTTEN THAT SAID MARIUS", "subset": "test_other", "task_type": "understanding", "prediction": "hello i had forgotten that said marius", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4874, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0019.flac", "answer": "WHILE HE STOOD LOOKING AROUND HIM IN BEWILDERMENT A FIREFLY ALIGHTED ON HIS ARM FLASHING ITS LITTLE LANTERN IN THE PRINCE'S FACE IT CRIED THIS WAY MY FRIEND THE FLY SENT ME TO GUIDE YOU TO A PLACE OF SAFETY", "subset": "test_other", "task_type": "understanding", "prediction": "while he stood looking around him in bewilderment a firefly alighted on his arm flashing its little lantern in the prince s face it cried this way my friend the fly sent me to guide you to a place of safety", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4875, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0015.flac", "answer": "A FAINT GLIMMER OF LIGHT ON THE OPPOSITE WALL SHOWS ME THE KEYHOLE", "subset": "test_other", "task_type": "understanding", "prediction": "a faint glimmer of light on the opposite wall shows me the keyhole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4876, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0020.flac", "answer": "WHAT IS TO BECOME OF ME CRIED THE POOR PEASANT", "subset": "test_other", "task_type": "understanding", "prediction": "what is to become of me cried the poor peasant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4877, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0009.flac", "answer": "AT THIS MOMENT THERE WAS A DISTANT RUMBLING AS OF THUNDER TIS THE OGRE CRIED THE FAIRY WE MUST HASTEN", "subset": "test_other", "task_type": "understanding", "prediction": "at this moment there was a distant rumbling as of thunder tis the ogre cried the fairy we must hasten", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4878, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0002.flac", "answer": "BUT THE KING LAUGHED HIM TO SCORN THOU A SWORD HE QUOTH", "subset": "test_other", "task_type": "understanding", "prediction": "but the king laughed him to scorn thou a sword he quoth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4879, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0024.flac", "answer": "AMONG THOSE WHO DREW BACK WERE ETHELRIED'S BROTHERS THE THREE THAT WERE DARK AND THE THREE THAT WERE FAIR", "subset": "test_other", "task_type": "understanding", "prediction": "among those who drew back were ethelredes brothers the three that were dark and the three that were fair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4880, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0011.flac", "answer": "HE COULD SEE THE OGRE STANDING POWERLESS TO HURT HIM ON THE OTHER SIDE OF THE CHASM AND GNASHING HIS TEETH EACH ONE OF WHICH WAS AS BIG AS A MILLSTON", "subset": "test_other", "task_type": "understanding", "prediction": "he could see the ogre standing powerless to hurt him on the other side of the chasm and gnashing his teeth each one of which was as big as a millstone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4881, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0005.flac", "answer": "I DID BUT LAUGH TO THINK THE SWORD OF ETHELRIED HAD BEEN SO QUICKLY FOUND RESPONDED THE JESTER AND HE POINTED TO THE SCISSORS HANGING FROM THE TAILOR'S GIRDLE", "subset": "test_other", "task_type": "understanding", "prediction": "i did but laugh to think the sword of ethelred had been so quickly found responded the jester and he pointed to the scissors hanging from the tailor s girdle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4882, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0003.flac", "answer": "IN SOOTH THOU SHALT HAVE ONE BUT IT SHALL BE ONE BEFITTING THY MAIDEN SIZE AND COURAGE IF SO SMALL A WEAPON CAN BE FOUND IN ALL MY KINGDOM", "subset": "test_other", "task_type": "understanding", "prediction": "in sooth thou shalt have one but it shall be one befitting thine made in size and courage if so small a weapon can be found in all my kingdom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4883, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0022.flac", "answer": "THE GRANDAME WHOM HE SUPPLIED WITH FAGOTS THE MERCHANT WHOM HE RESCUED FROM ROBBERS THE KING'S COUNCILLOR TO WHOM HE GAVE AID ALL BECAME HIS FRIENDS UP AND DOWN THE LAND TO BEGGAR OR LORD HOMELESS WANDERER OR HIGH BORN DAME HE GLADLY GAVE UNSELFISH SERVICE ALL UNSOUGHT AND SUCH AS HE HELPED STRAIGHTWAY BECAME HIS FRIENDS", "subset": "test_other", "task_type": "understanding", "prediction": "the grand dame whom he supplied with faggots the merchant whom he rescued from robbers the king s counsellor to whom he gave aid all became his friends up and down the land beggar or lord homeless wanderer or high born dame he gladly gave unselfish service all unsought and such as he helped straightway became his friends", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4884, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0025.flac", "answer": "BUT ETHELRIED HEEDED NOT THEIR TAUNTS", "subset": "test_other", "task_type": "understanding", "prediction": "but ethelred heeded not their taunts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4885, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0010.flac", "answer": "SCISSORS GROW A GIANT'S HEIGHT AND SAVE US FROM THE OGRE'S MIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "scissors grow a giant s height and save us from yogurts might", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4886, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0000.flac", "answer": "BUT THE MIDDLE SON WAS LITTLE AND LORN HE WAS NEITHER DARK NOR FAIR HE WAS NEITHER HANDSOME NOR STRONG", "subset": "test_other", "task_type": "understanding", "prediction": "but the middle son was little and lorn he was neither dark nor fair he was neither handsome nor strong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4887, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0014.flac", "answer": "HE LIFTED THE SCISSORS AND WITH ONE STROKE DESTROYED THE WEB AND GAVE THE FLY ITS FREEDOM", "subset": "test_other", "task_type": "understanding", "prediction": "he lifted the scissors and with one stroke destroyed the web and gave the fly its freedom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4888, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0023.flac", "answer": "TO HIM WHO COULD BRING HER BACK TO HER FATHER'S CASTLE SHOULD BE GIVEN THE THRONE AND KINGDOM AS WELL AS THE PRINCESS HERSELF SO FROM FAR AND NEAR INDEED FROM ALMOST EVERY COUNTRY UNDER THE SUN CAME KNIGHTS AND PRINCES TO FIGHT THE OGRE", "subset": "test_other", "task_type": "understanding", "prediction": "to him who could bring her back to her father s castle should be given the throne and kingdom as well as the princess herself so from far and near indeed from almost every country under the sun came knights and princes to fight the ogre", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4889, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0013.flac", "answer": "THOU SHALT NOT BE LEFT A PRISONER IN THIS DISMAL SPOT WHILE I HAVE THE POWER TO HELP THEE", "subset": "test_other", "task_type": "understanding", "prediction": "thou shalt not be left a prisoner in this dismal spot while i have the power to help thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4890, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0007.flac", "answer": "THOU SHALT HAVE THY LIBERTY HE CRIED EVEN THOUGH THOU SHOULDST REND ME IN PIECES THE MOMENT THOU ART FREE", "subset": "test_other", "task_type": "understanding", "prediction": "thou shalt have thy liberty he cried even though thou shouldst rend me in pieces the moment thou art free", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4891, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0021.flac", "answer": "MY GRAIN MUST FALL AND ROT IN THE FIELD FROM OVERRIPENESS BECAUSE I HAVE NOT THE STRENGTH TO RISE AND HARVEST IT THEN INDEED MUST WE ALL STARVE", "subset": "test_other", "task_type": "understanding", "prediction": "my grain must fall and rot in the field from over ripeness because i have not the strength to rise and harvest it then indeed must we all starve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4892, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0026.flac", "answer": "SO THEY ALL CRIED OUT LONG AND LOUD LONG LIVE THE PRINCE PRINCE CISEAUX", "subset": "test_other", "task_type": "understanding", "prediction": "so they all cried out long and loud long live the prince prince sizzol", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4893, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0001.flac", "answer": "THROWING HIMSELF ON HIS KNEES BEFORE THE KING HE CRIED OH ROYAL SIRE BESTOW UPON ME ALSO A SWORD AND A STEED THAT I MAY UP AND AWAY TO FOLLOW MY BRETHREN", "subset": "test_other", "task_type": "understanding", "prediction": "throwing himself on his knees before the king he cried o royal sire bestow upon me also a sword and a steed that i may up and away follow my brethren", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4894, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0017.flac", "answer": "AS HE UTTERED THE WORDS THE SCISSORS LEAPED OUT OF HIS HAND AND BEGAN TO CUT THROUGH THE WOODEN SHUTTERS AS EASILY AS THROUGH A CHEESE", "subset": "test_other", "task_type": "understanding", "prediction": "as he uttered the words the scissors leaped out of his hand and began to cut through the wooden shutters as easily as through a cheese", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4895, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0006.flac", "answer": "ONE NIGHT AS HE LAY IN A DEEP FOREST TOO UNHAPPY TO SLEEP HE HEARD A NOISE NEAR AT HAND IN THE BUSHES", "subset": "test_other", "task_type": "understanding", "prediction": "one night as he lay in a deep forest too unhappy to sleep he heard a noise near at hand in the bushes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4896, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0008.flac", "answer": "IT HAD SUDDENLY DISAPPEARED AND IN ITS PLACE STOOD A BEAUTIFUL FAIRY WITH FILMY WINGS WHICH SHONE LIKE RAINBOWS IN THE MOONLIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "yet it had suddenly disappeared and in its place stood a beautiful fairy with filmy wings which shone like rainbows in the moonlight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4897, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0012.flac", "answer": "THE SIGHT WAS SO TERRIBLE THAT HE TURNED ON HIS HEEL AND FLED AWAY AS FAST AS HIS FEET COULD CARRY HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the sight was so terrible that he turned on his heel and fled away as fast as his feet could carry him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4898, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0004.flac", "answer": "FORTHWITH THE GRINNING JESTER BEGAN SHRIEKING WITH LAUGHTER SO THAT THE BELLS UPON HIS MOTLEY CAP WERE ALL SET A JANGLING", "subset": "test_other", "task_type": "understanding", "prediction": "forthwith the grinning jester began shrieking with laughter so that the bells upon his motley cap were all set a jangling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4899, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0018.flac", "answer": "IN A VERY SHORT TIME THE PRINCE HAD CRAWLED THROUGH THE OPENING", "subset": "test_other", "task_type": "understanding", "prediction": "in a very short time the prince had crawled through the opening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4900, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/35475/4294-35475-0016.flac", "answer": "THE PRINCE SPENT ALL THE FOLLOWING TIME UNTIL MIDNIGHT TRYING TO THINK OF A SUITABLE VERSE TO SAY TO THE SCISSORS", "subset": "test_other", "task_type": "understanding", "prediction": "the prince spent all the following time until midnight trying to think of a suitable verse to say to the scissors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4901, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/32859/4294-32859-0003.flac", "answer": "SIT DOWN BESIDE ME AND I'LL TELL YOU THE STORY", "subset": "test_other", "task_type": "understanding", "prediction": "sit down beside me and i will tell you the story", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4902, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/32859/4294-32859-0002.flac", "answer": "THE STORY OF FRIDOLIN AND RETZCH'S PRETTY OUTLINES", "subset": "test_other", "task_type": "understanding", "prediction": "the story of fridolin and wretchs pretty outlines", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4903, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/32859/4294-32859-0001.flac", "answer": "IT WAS HIS FANCY I SUPPOSE TO REVIVE CERTAIN SENTIMENTAL RELATIONS WHICH HAD IT MAY BE ONCE EXISTED BETWEEN HIM AND MISS LAKE AND HE WAS A PERSON OF THAT COMBATIVE TEMPERAMENT THAT MAGNIFIES AN OBJECT IN PROPORTION AS ITS PURSUIT IS THWARTED", "subset": "test_other", "task_type": "understanding", "prediction": "it was his fancy i suppose to revive certain sentimental relations which had it may be once existed between him and miss lake and he was a person of that combative temperament that magnifies an object in proportion as its pursuit is thwarted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4904, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/32859/4294-32859-0005.flac", "answer": "BUT HONEST MARK FORGOT THAT YOUNG LADIES DO NOT ALWAYS COME OUT QUITE ALONE AND JUMP UNASSISTED INTO THEIR VEHICLES", "subset": "test_other", "task_type": "understanding", "prediction": "but honest mark forgot that young ladies do not always come out quite alone and jump unassisted into their vehicles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4905, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/32859/4294-32859-0000.flac", "answer": "WYLDER WAS RATHER SURLY AFTER THE LADIES HAD FLOATED AWAY FROM THE SCENE AND HE DRANK HIS LIQUOR DOGGEDLY", "subset": "test_other", "task_type": "understanding", "prediction": "wylder was rather surly after the ladies had floated away from the scene and he drank his liquor doggedly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4906, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4294/32859/4294-32859-0004.flac", "answer": "HE ASSISTED AT IT BUT TOOK NO PART AND IN FACT WAS LISTENING TO THAT OTHER CONVERSATION WHICH SOUNDED WITH ITS PLEASANT GABBLE AND LAUGHTER LIKE A LITTLE MUSICAL TINKLE OF BELLS IN THE DISTANCE", "subset": "test_other", "task_type": "understanding", "prediction": "he assisted at it but took no part and in fact was listening to that other conversation which sounded with its pleasant gabble and laughter like a little musical tinkle of bells in the distance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4907, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0016.flac", "answer": "YES SIR I THINK I CAN DO IT SAFELY OR I SHOULD NOT TRY SIR", "subset": "test_other", "task_type": "understanding", "prediction": "yes sir i think i can do it safely or i should not try sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4908, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0013.flac", "answer": "HE PAUSED FINGERING HIS LOWER LIP AND LOOKING SIDEWAYS IN A REFLECTIVE FASHION AT CHRIS STANDING BEFORE HIM", "subset": "test_other", "task_type": "understanding", "prediction": "and paused fingering his lower lip and looking sideways in a reflective fashion at chris standing before him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4909, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0009.flac", "answer": "HIS FACE FROZE WITH NERVOUSNESS THAT THIS MIGHT NOT DO AS AN ANSWER AND HE STOOD STIFF AND STILL BEFORE CAPTAIN BLIZZARD", "subset": "test_other", "task_type": "understanding", "prediction": "his face rose with nervousness that this might not do as an answer and he stood stiff and still before captain blizzard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4910, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0010.flac", "answer": "THE CAPTAIN SAT FORWARD IN HIS CHAIR LOOKING AT HIM FOR A LONG MOMENT CONSIDERING", "subset": "test_other", "task_type": "understanding", "prediction": "the captain sat forward in his chair looking at him for a long moment considering", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4911, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0023.flac", "answer": "NOT SINCE HE HAD LEFT MISTER WICKER HAD CHRIS FELT SUCH CONFIDENCE AS HE DID IN THE WORDS AND ACTIONS OF CAPTAIN BLIZZARD", "subset": "test_other", "task_type": "understanding", "prediction": "not since he had left mr wicker had chris felt such confidence as he did in the words and actions of captain blizzard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4912, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0017.flac", "answer": "CAPTAIN BLIZZARD'S ROUND PINK FACE CREASED IN HIS WINNING SMILE", "subset": "test_other", "task_type": "understanding", "prediction": "captain blizzard s round pink face creased in its winning smile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4913, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0000.flac", "answer": "THEY WENT DOWN TO THEIR QUARTERS FIRST", "subset": "test_other", "task_type": "understanding", "prediction": "they went down to their quarters first", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4914, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0005.flac", "answer": "WE'VE WATER AND FRESH STORES TO TAKE ON THERE", "subset": "test_other", "task_type": "understanding", "prediction": "we ve water and fresh stalls to take on there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4915, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0011.flac", "answer": "THEN HE SAID WELL I DO NOT CARE FOR IT I CANNOT SAY I DO", "subset": "test_other", "task_type": "understanding", "prediction": "then he said well i do not care for it i cannot say that i do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4916, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0018.flac", "answer": "HE THEN WENT ON TO DESCRIBE WHAT ELSE WAS TO FOLLOW THE COVERING OF THE SHIP WITH LEAVES TO MAKE IT BLEND WITH ITS SURROUNDINGS", "subset": "test_other", "task_type": "understanding", "prediction": "he then went on to describe what else was to follow the covering of the ship with leaves to make it blend with its surroundings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4917, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0019.flac", "answer": "CAMOUFLAGE WAS NOT A WORD THE CAPTAIN OR ANYONE ELSE OF HIS TIME YET UNDERSTOOD", "subset": "test_other", "task_type": "understanding", "prediction": "camouflage was not a word the captain or anyone else of his time yet understood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4918, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0007.flac", "answer": "CERTAINLY MY BOY BOOMED OUT THE CAPTAIN HIS BLUE EYES ABRUPTLY KEEN AND PENETRATING", "subset": "test_other", "task_type": "understanding", "prediction": "certainly my boy boomed out the captain his blue eyes abruptly keen and penetrating", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4919, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0012.flac", "answer": "THIS SHIP IS MORE TO ME THAN WIFE OR MOTHER OR FAMILY", "subset": "test_other", "task_type": "understanding", "prediction": "this ship is more to me than wife or mother or family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4920, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0015.flac", "answer": "THIS SHIP ITS CARGO AND ITS MEN WILL BE IN YOUR HANDS", "subset": "test_other", "task_type": "understanding", "prediction": "this ship its cargo and its men will be in your hands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4921, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0008.flac", "answer": "MISTER FINNEY WILL BE SOME TIME ON DECK WE CANNOT BE OVERHEARD IN HERE", "subset": "test_other", "task_type": "understanding", "prediction": "mr finney will be some time on deck we cannot be overheard in here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4922, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0006.flac", "answer": "CHRIS LOST NO TIME AS SOON AS HE COULD DO IT WITHOUT BEING NOTICED IN HURRYING DOWN TO HIS CABIN", "subset": "test_other", "task_type": "understanding", "prediction": "chris lost no time as soon as he could do it without being noticed in hurrying down to his cabin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4923, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0003.flac", "answer": "IT LOOKS TO ME AS IF IT COULD HAVE BEEN ONE OF SEVERAL PEOPLE AND I'LL BE SWITCHED IF I KNOW WHO I'LL KEEP MY EYES OPEN", "subset": "test_other", "task_type": "understanding", "prediction": "it looks to me as if it could have been one of several people and i ll be switched if i know who i ll keep my eyes open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4924, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0020.flac", "answer": "WHAT CAN BE SAID DURING THAT TIME SIR CHRIS THOUGHT TO ASK", "subset": "test_other", "task_type": "understanding", "prediction": "what can be said during that time sir chris thought to ask", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4925, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0021.flac", "answer": "I AM SOMEWHAT SKILLED IN MEDICAMENTS I HAVE TO BE AS CAPTAIN OF A SHIP AND THE CREW KNOW IT", "subset": "test_other", "task_type": "understanding", "prediction": "i am somewhat skilled in medicaments i have to be as a captain of a ship and the crew know it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4926, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0022.flac", "answer": "I SHALL SAY THAT YOU ARE IN MY OWN CABIN SO THAT I CAN CARE FOR YOU", "subset": "test_other", "task_type": "understanding", "prediction": "i shall say that you are in my own cabin so that i can care for you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4927, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0004.flac", "answer": "THE MIRABELLE WAS NEARING TAHITI", "subset": "test_other", "task_type": "understanding", "prediction": "the mirabelle was nearing tahiti", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4928, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0025.flac", "answer": "THEIR CONVERSATION HAD TAKEN SOME LITTLE WHILE", "subset": "test_other", "task_type": "understanding", "prediction": "their conversation had taken some little while", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4929, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0024.flac", "answer": "HE KNEW NOW THAT HIS ABSENCE FOR AS LONG AS HE HAD TO BE AWAY WOULD BE COVERED UP AND SATISFACTORILY ACCOUNTED FOR", "subset": "test_other", "task_type": "understanding", "prediction": "he knew now that his absence for as long as he had had to be away would be covered up and satisfactorily accounted for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4930, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0001.flac", "answer": "GUESS MISTER FINNEY WENT TO HIS QUARTERS I DON'T REMEMBER SEEING HIM CROSS THE DECK OR COME OVER THAT WAY AT ALL", "subset": "test_other", "task_type": "understanding", "prediction": "guess mr finney went to his quarters i don t remember seeing him cross the deck or come over that way at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4931, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0014.flac", "answer": "WE SHALL SAY NO MORE BUT I TRUST YOU UNDERSTAND THE RESPONSIBILITY YOU HAVE", "subset": "test_other", "task_type": "understanding", "prediction": "we shall say no more but i trust you understand the responsibility you have", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4932, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28330/4852-28330-0002.flac", "answer": "NEXT NED CILLEY WAS RELIEVED AT THE HELM BY ELBERT JONES WHO TOOK OVER NED WENT ON DOWN", "subset": "test_other", "task_type": "understanding", "prediction": "next ned silly was relieved of the helm by albert jones who took over ned went on down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4933, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0015.flac", "answer": "IF HE WAS TO BE A MAGICIAN COULD HE MAKE THIS BOY COME TO LIFE", "subset": "test_other", "task_type": "understanding", "prediction": "if he was to be a magician could he make this boy come to life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4934, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0007.flac", "answer": "MISTER WICKER WAITED PATIENTLY BESIDE HIM FOR A FEW MOMENTS FOR CHRIS TO GET UP HIS COURAGE", "subset": "test_other", "task_type": "understanding", "prediction": "mr wicker waited patiently beside him for a few moments for chris to get up his courage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4935, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0005.flac", "answer": "HOW YOU HAVE IMPROVED MY BOY HE EXCLAIMED IT IS NOW TIME FOR YOU TO TRY AND THIS IS AS GOOD A CHANGE AS ANY", "subset": "test_other", "task_type": "understanding", "prediction": "how you have improved my boy he exclaimed it is now time for you to try and this is as good a change as any", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4936, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0027.flac", "answer": "THE WOODEN GRIN LOOSENED THE LARGE EYES TURNED THE HAND HOLDING THE HARD BOUQUET OF CARVED FLOWERS MOVED AND LET THE BOUQUET FALL", "subset": "test_other", "task_type": "understanding", "prediction": "the wooden grin loosened the large eyes turned the hand holding the hard bouquet of carved flowers moved let it let the bouquet fall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4937, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0011.flac", "answer": "HE THOUGHT NOT WITHOUT A FEELING OF PRIDE AND COMMENCED EXPERIMENTING WITH HIS TAIL AND FINS WITH SUCH ENTHUSIASM AND DELIGHT THAT SOME LITTLE TIME ELAPSED BEFORE MISTER WICKER'S VOICE BOOMED CLOSE BY", "subset": "test_other", "task_type": "understanding", "prediction": "he thought not without a feeling of pride and commenced experimenting with his tail and fins with such enthusiasm and delight that some little time elapsed before mr wicker's voice boomed butlers by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4938, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0000.flac", "answer": "THE LEARNING OF MAGIC WAS BY NO MEANS EASY", "subset": "test_other", "task_type": "understanding", "prediction": "the learning of magic was by no means easy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4939, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0010.flac", "answer": "HIS HEAD SWAM AND HE FELT FAINT AND A LITTLE SICK BUT HE PERSISTED THROUGH THE FINAL WORDS", "subset": "test_other", "task_type": "understanding", "prediction": "his head swam and he felt faint and a little sick but he persisted through the final words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4940, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0002.flac", "answer": "CHRIS THEREFORE THREW HIMSELF INTO ALL THE PRELIMINARIES OF HIS TASK", "subset": "test_other", "task_type": "understanding", "prediction": "chris therefore threw himself into all the preliminaries of his task", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4941, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0025.flac", "answer": "IT WAS AS IF THE STIFFNESS MELTED", "subset": "test_other", "task_type": "understanding", "prediction": "it was as if the stiffness melted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4942, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0012.flac", "answer": "SEVENTY FOUR BOOK ONE THE RETURN", "subset": "test_other", "task_type": "understanding", "prediction": "seventy four book one the return", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4943, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0006.flac", "answer": "SUPPOSE I CHANGE AND CAN'T CHANGE BACK", "subset": "test_other", "task_type": "understanding", "prediction": "suppose i change and cant change back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4944, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0020.flac", "answer": "THE AFTERNOON RAINY BEFORE INCREASED IN STORM", "subset": "test_other", "task_type": "understanding", "prediction": "the afternoon rainy before increased in storm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4945, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0004.flac", "answer": "WHAT SHALL I DO FIRST", "subset": "test_other", "task_type": "understanding", "prediction": "what should i all i do first", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4946, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0018.flac", "answer": "CHRIS GOT UP AND STOLE BACK TO MISTER WICKER'S DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "chris got up and stole back to mr worker s door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4947, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0019.flac", "answer": "HE HEARD THE MAGICIAN GOING UP THE SPIRAL STAIRCASE TO HIS ROOM ABOVE AND AFTER CHANGING HIMSELF TO A MOUSE TO SLIP UNDER THE DOOR AND SEE THAT THE ROOM WAS REALLY EMPTY CHRIS RESUMED HIS PROPER SHAPE AND OPENED THE DOORS OF THE CUPBOARD AT THE FAR END OF THE ROOM", "subset": "test_other", "task_type": "understanding", "prediction": "you heard that magician going up the spiral staircase to his room above and after changing himself to a mouse to slip under the door and see that the room was really empty mr jones proper shape and opened the doors of the cupboard at the far end of the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4948, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0008.flac", "answer": "THEN AS NOTHING HAPPENED WITH A VOICE LIKE A WHIP MISTER WICKER SAID START AT ONCE", "subset": "test_other", "task_type": "understanding", "prediction": "then has nothing happened with a voice like a whip mr wicker said start at once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4949, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0024.flac", "answer": "WITH INFINITE CAUTION CHRIS CLOSED THE DOOR SILENTLY BEHIND HIM AND RUNNING LIGHTLY FORWARD REACHED THE FIGURE OF THE NEGRO BOY", "subset": "test_other", "task_type": "understanding", "prediction": "with infinite caution chris closed the door silently behind him and running lightly forward reached the figure of the negro boy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4950, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0023.flac", "answer": "MISTER WICKER BEGAN MOVING ABOUT UPSTAIRS THE FLOORBOARDS CREAKED AND STILL CHRIS COULD NOT LEAVE UNTIL THE POTION FUMED AND GLOWED", "subset": "test_other", "task_type": "understanding", "prediction": "mr worker began moving about upstairs the floorboards creaked creak creak and still chris could not leave until the potion fumed and glowed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4951, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0003.flac", "answer": "ONE AFTERNOON WHEN HE RETURNED AFTER A REST TO MISTER WICKER'S STUDY HE SAW THAT THERE WAS SOMETHING NEW IN THE ROOM A BOWL WITH A GOLDFISH IN IT STOOD ON THE TABLE BUT MISTER WICKER WAS NOT TO BE SEEN", "subset": "test_other", "task_type": "understanding", "prediction": "one afternoon when he had returned after a rest to mr wicker s study he saw that there was something new in the room a bowl with a goldfish in it stood on the table but mr wicker was not to be seen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4952, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0009.flac", "answer": "THE SENSATION SPREAD FASTER AND FASTER", "subset": "test_other", "task_type": "understanding", "prediction": "the sensation spread faster and faster", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4953, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0016.flac", "answer": "HE SQUATTED ON HIS HAUNCHES EXAMINING THE CARVED WOODEN FIGURE ATTENTIVELY AND FELT CONVINCED THAT ONCE ALIVE THE BOY WOULD BE AN IDEAL AND HAPPY COMPANION", "subset": "test_other", "task_type": "understanding", "prediction": "he squatted on his haunches examined the carved wooden figure attentively and felt convinced that once alive the boy would be an ideal and happy companion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4954, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0017.flac", "answer": "BUT HOW DID ONE CHANGE INANIMATE TO ANIMATE", "subset": "test_other", "task_type": "understanding", "prediction": "but how did one a change inanimate to animate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4955, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0022.flac", "answer": "CERTAIN ELEMENTS WERE TO BE MIXED AND POURED AT THE PROPER TIME", "subset": "test_other", "task_type": "understanding", "prediction": "certain elements were to be mixed and poured at the proper time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4956, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0001.flac", "answer": "HE HAD TOLD HIS MASTER AT ONCE ABOUT SIMON GOSLER HIS HORDE OF MONEY AND HIS HIDING PLACES FOR IT", "subset": "test_other", "task_type": "understanding", "prediction": "he had told his master at once about simon gosler his hoard of money and his hiding places for it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4957, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0021.flac", "answer": "DUSK CAME TWO HOURS BEFORE ITS TIME THUNDER SNARLED IN THE SKY", "subset": "test_other", "task_type": "understanding", "prediction": "thus came two hours before its time thunder snarls in the sky", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4958, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0014.flac", "answer": "THEN ALL AT ONCE THE IDEA CAME TO CHRIS", "subset": "test_other", "task_type": "understanding", "prediction": "then all at once the idea came to chris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4959, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0013.flac", "answer": "THE FIGURE'S SHOES CARVED IN SOME EASTERN STYLE HAD CURVED UP POINTING TOES", "subset": "test_other", "task_type": "understanding", "prediction": "the figure shoes carved in some eastern style at curvetted pointing toes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4960, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28319/4852-28319-0026.flac", "answer": "UNDER HIS EYES THE WOODEN FOLDS OF CLOTH BECAME RICH SILK EMBROIDERY GLEAMED IN ITS REALITY UPON THE COAT AND OH THE FACE", "subset": "test_other", "task_type": "understanding", "prediction": "under his eyes wensoldes of cloth became rich silk embroidery gleamed in its reality upon the coat and oh the face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4961, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0000.flac", "answer": "SAY YOU KNOW SUMTHIN", "subset": "test_other", "task_type": "understanding", "prediction": "say you know something", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4962, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0013.flac", "answer": "AW SHUCKS", "subset": "test_other", "task_type": "understanding", "prediction": "aw shucks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4963, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0022.flac", "answer": "ON THE LEFT THE COIL OF ROPE IN THE CENTER THE MODEL OF A SAILING SHIP IN A GREEN GLASS BOTTLE AND ON THE RIGHT THE WOODEN STATUE OF A NEGRO BOY IN BAGGY TROUSERS TURKISH JACKET AND WHITE TURBAN", "subset": "test_other", "task_type": "understanding", "prediction": "on the left the coil of rope in the center the model of a sailing ship in a green glass bottle and on the right the wooden statue of a negro boy in baggy trousers turkish jacket and white turban", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4964, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0024.flac", "answer": "HE HAD NEVER SEEN ANYONE GO INTO MISTER WICKER'S SHOP NOW HE THOUGHT OF IT", "subset": "test_other", "task_type": "understanding", "prediction": "he had never seen any one go into mr worker s shop now he thought of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4965, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0011.flac", "answer": "BETCHA AREN'T GOIN AFTER ALL CHRIS TURNED ON HIM", "subset": "test_other", "task_type": "understanding", "prediction": "bet yer arent goin after all this turned on him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4966, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0026.flac", "answer": "A SUDDEN CAR HORN WOKE HIM FROM HIS DREAM", "subset": "test_other", "task_type": "understanding", "prediction": "a sudden car horn woke him from his dream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4967, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0018.flac", "answer": "THE AIR WAS GROWING CHILL AND CHRIS DECIDED TO FINISH HIS JOB", "subset": "test_other", "task_type": "understanding", "prediction": "the air was growing chill and chris decided to finish the job", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4968, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0006.flac", "answer": "WELL HE ADMITTED I DID", "subset": "test_other", "task_type": "understanding", "prediction": "well he admitted i did", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4969, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0025.flac", "answer": "HOW THEN DID HE LIVE AND WHAT DID HE EVER SELL", "subset": "test_other", "task_type": "understanding", "prediction": "how then did he live and what did he ever sell", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4970, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0005.flac", "answer": "MIKE BECAME UNEASY AND FISHED AN ELASTIC BAND OUT OF HIS POCKET MADE A FLICK OF PAPER AND SENT IT SOARING OUT INTO M STREET", "subset": "test_other", "task_type": "understanding", "prediction": "mike became uneasy and fished an elastic band out of his pocket made a flick of paper and sent it soaring out in m street", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4971, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0003.flac", "answer": "O K HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "okay he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4972, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0001.flac", "answer": "CHRIS LOOKED FROM A NICKEL PLATED FLASHLIGHT TO A CAR JACK AND SPARK PLUG", "subset": "test_other", "task_type": "understanding", "prediction": "chris looked from a nickel plated flashlight to a car jack and spark plug", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4973, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0007.flac", "answer": "CHRIS ASKED AND FOR THE FIRST TIME THAT DAY THE HEAVY WEIGHT HE CARRIED WITHIN HIM LIFTED AND LIGHTENED A LITTLE", "subset": "test_other", "task_type": "understanding", "prediction": "chris asked and for the first time that day the heavy weight he carried within him lifted and lightened a little", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4974, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0004.flac", "answer": "ONLY WHY DIDN'T YOU ASK HIM YOURSELF", "subset": "test_other", "task_type": "understanding", "prediction": "only why did n t you ask him yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4975, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0019.flac", "answer": "ALL AT ONCE HE WONDERED HOW HIS MOTHER WAS AND EVERYTHING IN HIM PINCHED AND TIGHTENED ITSELF", "subset": "test_other", "task_type": "understanding", "prediction": "all at once he wondered how his mother was and everything in him impinged and tightened itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4976, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0023.flac", "answer": "BUT THE NAME STILL SHOWED AT THE PROW AND MANY A TIME CHRIS SAFE AT HOME IN BED HAD SAILED IMAGINARY VOYAGES IN THE MIRABELLE", "subset": "test_other", "task_type": "understanding", "prediction": "but the name still showed at the prow and many a time chris safe at home in bed had sailed imaginary voyages in the mirabelle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4977, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0014.flac", "answer": "CHRIS STARTED OFF ONCE MORE PASSING THE BLEAK LITTLE VICTORIAN CHURCH PERCHED ON THE HILL ABOVE MISTER WICKER'S HOUSE", "subset": "test_other", "task_type": "understanding", "prediction": "chris started off once more passing a bleak little victorian church perched on the hill above mr wicker s house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4978, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0020.flac", "answer": "AT THE FOOT OF THE HILL HE REACHED THE HOUSE", "subset": "test_other", "task_type": "understanding", "prediction": "at the foot of the hill he reached the house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4979, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0016.flac", "answer": "THE LONGER WING TOWARD THE BACK HAD A BACK DOOR THAT OPENED ONTO WATER STREET THE SPACE BETWEEN THE HOUSE AND WISCONSIN AVENUE HAD BEEN MADE INTO A NEAT OBLONG FLOWER GARDEN FENCED OFF FROM THE SIDEWALK BY BOX SHRUBS AND A WHITE PICKET FENCE", "subset": "test_other", "task_type": "understanding", "prediction": "the longer wing toward the back got a back door that opened on a water street the space between the house and wisconsin avenue had been made into a neat oblong flower garden fenced off from the sidewalk by box shrubs and a white picket fence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4980, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0015.flac", "answer": "AN EMPTY LOT CUT INTO BY CHURCH LANE GAVE A LOOK OF ISOLATION TO THE L SHAPED BRICK BUILDING THAT SERVED MISTER WICKER AS BOTH HOUSE AND PLACE OF BUSINESS", "subset": "test_other", "task_type": "understanding", "prediction": "an empty lot cut in into by church lane gave a look of isolation to the l shaped brick building that served mr wicker as both house and place of business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4981, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0010.flac", "answer": "MIKE'S EXPRESSION CHANGED AT ONCE TO ONE OF TRIUMPH BUT CHRIS WAS ONLY PARTLY ENCOURAGED", "subset": "test_other", "task_type": "understanding", "prediction": "mikes expression changed at once to one of triumph but chris was only partially encouraged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4982, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0008.flac", "answer": "THINK HE REALLY NEEDS IT HE PURSUED", "subset": "test_other", "task_type": "understanding", "prediction": "think he really needs it he pursued", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4983, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0009.flac", "answer": "HE WOULD HAVE LIKED TO GET THE JOB FOR JAKEY WHO NEEDED IT BUT SOMEHOW THE TASK OF FACING MISTER WICKER ESPECIALLY NOW THAT THE LIGHT WAS GOING AND DUSK EDGING INTO THE STREETS WAS NOT WHAT CHRIS HAD INTENDED FOR ENDING THE AFTERNOON", "subset": "test_other", "task_type": "understanding", "prediction": "he would have liked to get the job for jakie who needed it but somehow the task of facing mr wicker especially now that the light was going and dusk edged into the streets was not what chrysanthemintended for ending the afternoon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4984, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0012.flac", "answer": "MIKE WAS STANDING ON THE CORNER", "subset": "test_other", "task_type": "understanding", "prediction": "mike was standing on the corner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4985, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0002.flac", "answer": "KNOW WHO NEEDS A JOB BAD THAT'S JAKEY HARRIS", "subset": "test_other", "task_type": "understanding", "prediction": "know who needs a job bad thats jakie harris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4986, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0021.flac", "answer": "THERE WERE THREE THINGS THAT ALWAYS CAUGHT HIS EYE AMID THE LITTER OF DUSTY PIECES", "subset": "test_other", "task_type": "understanding", "prediction": "there were three things that always caught his eye amid the litter of dusty pieces", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4987, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28311/4852-28311-0017.flac", "answer": "A LIVID YELLOW STAINED THE HORIZON BEYOND THE FACTORIES AND GRAY CLOUDS LOWERED AND TUMBLED ABOVE", "subset": "test_other", "task_type": "understanding", "prediction": "a livid yellow stained the horizon beyond the factories and gray clouds lowered and tumbled above", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4988, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0027.flac", "answer": "A COURTYARD WAS SPARSELY LIT BY A FLARING TORCH OR TWO SHOWING A SWINGING SIGN HUNG ON A POST", "subset": "test_other", "task_type": "understanding", "prediction": "a courtyard was fiercely lit by a flaring torch or two showing a swinging sign hung on a post", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4989, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0008.flac", "answer": "CHRIS SWALLOWED AND HIS VOICE CAME BACK TO HIM", "subset": "test_other", "task_type": "understanding", "prediction": "chris swallowed and his voice came back to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4990, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0005.flac", "answer": "THE DOUBLE FANS OF MINUTE WRINKLES BREAKING FROM EYE CORNER TO TEMPLE AND JOINING WITH THOSE OVER THE CHEEKBONES WERE DRAWN INTO THE HORIZONTAL LINES ACROSS THE DOMED FOREHEAD", "subset": "test_other", "task_type": "understanding", "prediction": "the double fans minute wrinkles breaking from eye corners and temple and joining with those over the cheek bones were drawn into the horizontal lines across the domed forehead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4991, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0025.flac", "answer": "NO ELECTRIC SIGNS NO LAMPLIT STREETS", "subset": "test_other", "task_type": "understanding", "prediction": "no electric signs no lamp lit streets", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4992, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0031.flac", "answer": "MY WINDOW HAS A POWER FOR THOSE FEW WHO ARE TO SEE", "subset": "test_other", "task_type": "understanding", "prediction": "my window has a power for those few who are to see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4993, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0021.flac", "answer": "ACROSS THE WATER WHERE WAS THE FREEWAY", "subset": "test_other", "task_type": "understanding", "prediction": "across the water where was the freeway", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4994, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0028.flac", "answer": "THE POST WAS PLANTED AT THE EDGE OF WHAT WAS NOW A BROAD AND MUDDY ROAD", "subset": "test_other", "task_type": "understanding", "prediction": "the post was planted at the edge of what was now a broad and money road", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4995, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0013.flac", "answer": "I I JUST WONDERED IF THE PLACE WAS STILL OPEN", "subset": "test_other", "task_type": "understanding", "prediction": "i i just wondered if the place was still open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4996, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0004.flac", "answer": "MISTER WICKER'S BACK BEING TOWARD THE SOURCE OF LIGHT CHRIS COULD NOT SEE HIS FACE", "subset": "test_other", "task_type": "understanding", "prediction": "mr wicker s back being toward the source of light chris could not see his face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4997, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0007.flac", "answer": "CHRIS BLINKED AND LOOKED AGAIN YES THEY WERE STILL THERE", "subset": "test_other", "task_type": "understanding", "prediction": "chris blinked and looked again yes they were still there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4998, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0029.flac", "answer": "A COACH WITH ITS TOP PILED HIGH WITH LUGGAGE STAMPED TO A HALT BESIDE THE FLAGGED COURTYARD", "subset": "test_other", "task_type": "understanding", "prediction": "the coach with its stock piled high with luggage stamped to a halt beside the flagged courtyard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4999, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0006.flac", "answer": "LITTLE TUFTS OF WHITE FUZZ ABOVE THE EARS WERE ALL THAT REMAINED OF THE ANTIQUARIAN'S HAIR BUT WHAT DREW AND HELD CHRIS'S GAZE WERE THE OLD MAN'S EYES", "subset": "test_other", "task_type": "understanding", "prediction": "little tufts of white fuzz above the ears were all that remained of the antiquarian s hair but what drew and held chris s gaze were the old man s eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5000, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0023.flac", "answer": "THE WAREHOUSES WERE STILL THERE", "subset": "test_other", "task_type": "understanding", "prediction": "the warehouses were still there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5001, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0018.flac", "answer": "THE ROOM SEEMED OVERLY STILL", "subset": "test_other", "task_type": "understanding", "prediction": "the room seemed overly still", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5002, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0012.flac", "answer": "JAKEY HARRIS HIS NAME IS AND HE REALLY NEEDS THE JOB", "subset": "test_other", "task_type": "understanding", "prediction": "jackie harris name isn t he really needs the job", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5003, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0017.flac", "answer": "BUT EVEN AS HE SLOWLY TURNED THE THOUGHT PIERCED HIS MIND WHY HAD HE NOT SEEN THE REFLECTION OF THE HEADLIGHTS OF THE CARS MOVING UP AROUND THE CORNER OF WATER STREET AND UP THE HILL TOWARD THE TRAFFIC SIGNALS", "subset": "test_other", "task_type": "understanding", "prediction": "but even as he slowly turned the thought pierced his mind why had he not seen the reflection of the headlights of the car as moving about around the corner of wall utter street not the hill toward the traffic signals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5004, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0019.flac", "answer": "THEN IN THAT SECOND HE TURNED AND FACED ABOUT", "subset": "test_other", "task_type": "understanding", "prediction": "then in that second he turned and faced about", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5005, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0009.flac", "answer": "YES SIR HE SAID", "subset": "test_other", "task_type": "understanding", "prediction": "yes sir he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5006, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0014.flac", "answer": "WHAT HE SAW WAS A FRESH CHEEKED LAD TALL FOR THIRTEEN STURDY WITH SINCERITY AND GOOD HUMOR IN HIS FACE AND SOMETHING SENSITIVE AND APPEALING ABOUT HIS EYES", "subset": "test_other", "task_type": "understanding", "prediction": "what he saw was a fresh cheeked lad tall for thirteen sturdy with sincerity and good humor in his face and something sensitive and appealing about his eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5007, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0020.flac", "answer": "THE WIDE BOW WINDOW WAS THERE BEFORE HIM THE THREE OBJECTS HE LIKED BEST SHOWING FROSTY IN THE MOONLIGHT THAT POURED IN FROM ACROSS THE WATER", "subset": "test_other", "task_type": "understanding", "prediction": "the wide bow window was there before him and three objects he liked best showing frosty in the moonlight that poured in from across the water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5008, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0010.flac", "answer": "I SAW YOUR SIGN AND I KNOW A BOY WHO NEEDS THE JOB", "subset": "test_other", "task_type": "understanding", "prediction": "i saw your sign and i know a boy who needs the job", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5009, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0030.flac", "answer": "THEY MOVED INTO THE INN THE COACH RATTLED OFF TO THE STABLE", "subset": "test_other", "task_type": "understanding", "prediction": "they moved into the inn the coach rattled off to the stable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5010, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0022.flac", "answer": "IT WAS NO LONGER THERE NOR WERE THE HIGH WALLS AND SMOKESTACKS OF FACTORIES TO BE SEEN", "subset": "test_other", "task_type": "understanding", "prediction": "it was no longer there nor were the high walls and smoke stacks of factories to be seen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5011, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0003.flac", "answer": "HEAVY HAND HEWN BEAMS CROSSED IT FROM ONE SIDE TO THE OTHER", "subset": "test_other", "task_type": "understanding", "prediction": "heavy hand hewn beams crossed it from one side to the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5012, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0026.flac", "answer": "WHERE THE PEOPLE'S DRUGSTORE HAD STOOD BUT A HALF HOUR BEFORE ROSE THE ROOFS OF WHAT WAS EVIDENTLY AN INN", "subset": "test_other", "task_type": "understanding", "prediction": "where the people s drug store had stood but half an hour before rose the roofs of what was evidently an inn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5013, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0011.flac", "answer": "HE'S A SCHOOLMATE OF MINE", "subset": "test_other", "task_type": "understanding", "prediction": "he is a schoolmate of mine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5014, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0002.flac", "answer": "WHAT WITH THE ONE WINDOW AND THE LOWERING DAY OUTSIDE THE LONG NARROW SHOP WAS SOMBER", "subset": "test_other", "task_type": "understanding", "prediction": "what with the one window and the lowering day outside the long narrow shop was somber", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5015, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0015.flac", "answer": "HE GUESSED THERE MUST BE A LIVELY FIRE IN THAT ROOM BEYOND", "subset": "test_other", "task_type": "understanding", "prediction": "he guessed there must be a lively fire in that room beyond", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5016, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0001.flac", "answer": "SO NOW ALONE UNTIL SOMEONE SHOULD ANSWER THE BELL HE LOOKED EAGERLY IF UNEASILY AROUND HIM", "subset": "test_other", "task_type": "understanding", "prediction": "so now alone until some one should answer the bell they looked eagerly if uneasily around him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5017, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0000.flac", "answer": "OF THE MANY TIMES HE HAD EXAMINED MISTER WICKER'S WINDOW AND PORED OVER THE ROPE THE SHIP AND THE NUBIAN BOY HE HAD NEVER GONE INTO MISTER WICKER'S SHOP", "subset": "test_other", "task_type": "understanding", "prediction": "though many times he had examined mr wicker s window and pored over the rope the ship and the nubian boy he had never gone into mr wicker s shop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5018, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0016.flac", "answer": "WOULD THAT INTERFERE WITH JAKEY'S GETTING THE JOB SIR", "subset": "test_other", "task_type": "understanding", "prediction": "would that interfere with jakie giggles getting the job sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5019, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4852/28312/4852-28312-0024.flac", "answer": "FLABBERGASTED AND BREATHLESS CHRIS WAS UNAWARE THAT HE HAD MOVED CLOSER TO PEER OUT THE WINDOW IN EVERY DIRECTION", "subset": "test_other", "task_type": "understanding", "prediction": "flabbergasted and breathless chris was unaware that he had moved closer to peer out the window in every direction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5020, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0014.flac", "answer": "SUCH NICE USEFUL GIFTS A FEW DUPLICATES OF COURSE", "subset": "test_other", "task_type": "understanding", "prediction": "such nice useful gifts a few duplicates of course", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5021, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0021.flac", "answer": "HOW ON EARTH ARE WE TO KNOW SAID PETER THE MEAN PIG HASN'T BROUGHT US A PRESENT AND I'M HANGED IF HE SHALL CARRY ONE OFF", "subset": "test_other", "task_type": "understanding", "prediction": "how on earth are we to know said peter the mean pig hasn't brought us a present and i am hanged if he shall carry one off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5022, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0001.flac", "answer": "WELL THE FAILING STILL EXISTS DOESN'T IT SAID HER HUSBAND OR DO YOU SUPPOSE A REFORM OF CHARACTER IS ENTAILED ALONG WITH THE ESTATE", "subset": "test_other", "task_type": "understanding", "prediction": "well the failing still exists does n t it said the husband or eh do you suppose a reform of character is entailed along with the estate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5023, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0033.flac", "answer": "PETER DASHED OUT OF THE ROOM WITH GLAD RELIEF HE HAD LIVED SO LONG DURING THE LAST FEW MINUTES THAT A GOLDEN WEDDING SEEMED WITHIN MEASURABLE DISTANCE", "subset": "test_other", "task_type": "understanding", "prediction": "peter dashed out of the room with glad relief he had lived so long during the last few minutes that a golden wedding seemed within measurable distance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5024, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0016.flac", "answer": "WE FEEL THAT WE MUST LIVE ON CREAM FOR THE REST OF OUR LIVES", "subset": "test_other", "task_type": "understanding", "prediction": "we feel that we must live on cream for the rest of our lives", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5025, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0032.flac", "answer": "THE PIGEONCOTES HAD TURNED PALER THAN EVER MISSUS PETER HAD A FINAL INSPIRATION", "subset": "test_other", "task_type": "understanding", "prediction": "the pigeon coats had turned paler than ever mrs spitter had a final inspiration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5026, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0009.flac", "answer": "SIGNED WILFRID PIGEONCOTE", "subset": "test_other", "task_type": "understanding", "prediction": "signed wilfred pigeoncoat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5027, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0015.flac", "answer": "SEVEN CREAM JUGS PUT IN PETER", "subset": "test_other", "task_type": "understanding", "prediction": "seven cream jugs put in peter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5028, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0031.flac", "answer": "SHE ROSE AND WENT OUT HURRIEDLY AS THOUGH TO ASSURE HERSELF THAT THE DRAWING ROOM WAS NOT BEING STRIPPED OF ITS SILVERWARE AND RETURNED A MOMENT LATER BEARING A CREAM JUG IN HER HANDS", "subset": "test_other", "task_type": "understanding", "prediction": "she rose and went out hurriedly as though to assure herself that the drawing room was not being stripped of its silverware and returned a moment later bearing a cream jug in her hands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5029, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0012.flac", "answer": "IN THE DRAWING ROOM AFTER DINNER THEIR NERVOUSNESS AND AWKWARDNESS INCREASED", "subset": "test_other", "task_type": "understanding", "prediction": "in the drawing room after dinner their nervousness and awkwardness increased", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5030, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0007.flac", "answer": "FROM HIS LATE SCHOOLDAYS ONWARD HE HAD BEEN POSSESSED BY AN ACUTE AND OBSTINATE FORM OF KLEPTOMANIA HE HAD THE ACQUISITIVE INSTINCT OF THE COLLECTOR WITHOUT ANY OF THE COLLECTOR'S DISCRIMINATION", "subset": "test_other", "task_type": "understanding", "prediction": "from his late school days onward he had been possessed by an acute and obstinate form of kleptomania he had the acquisitive instinct of the collector without any of the collectors discrimination", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5031, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0011.flac", "answer": "THE TALK FLITTED NERVOUSLY AND HURRIEDLY FROM ONE IMPERSONAL TOPIC TO ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "the talk flitted nervously and hurriedly from one impersonal topic to another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5032, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0013.flac", "answer": "OH WE HAVEN'T SHOWN YOU THE SILVER WEDDING PRESENTS SAID MISSUS PETER SUDDENLY AS THOUGH STRUCK BY A BRILLIANT IDEA FOR ENTERTAINING THE GUEST HERE THEY ALL ARE", "subset": "test_other", "task_type": "understanding", "prediction": "oh we haven t shown you the silver wedding presents said mrs pitter suddenly as though struck by a brilliant idea for entertaining the guests here they all are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5033, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0017.flac", "answer": "OF COURSE SOME OF THEM CAN BE CHANGED", "subset": "test_other", "task_type": "understanding", "prediction": "of course some of them can be changed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5034, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0019.flac", "answer": "VIGILANCE WAS NOT COMPLETELY CROWNED WITH A SENSE OF VICTORY", "subset": "test_other", "task_type": "understanding", "prediction": "vigilance was not completely crowned with a sense of victory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5035, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0026.flac", "answer": "I SHOULD HAVE GIVEN IT TO YOU LAST NIGHT AFTER DINNER ONLY IT HAPPENED TO BE A CREAM JUG AND YOU SEEMED ANNOYED AT HAVING SO MANY DUPLICATES SO I FELT RATHER AWKWARD ABOUT GIVING YOU ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "i should have given it to you last night after dinner only it happened to be a cream jug and you seemed annoyed at having so many duplicates so i felt rather awkward about giving you another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5036, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0006.flac", "answer": "AND THE REPUTATION WAS AN UNPLEASANT ONE", "subset": "test_other", "task_type": "understanding", "prediction": "and the reputation was an unpleasant one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5037, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0029.flac", "answer": "HUSBAND AND WIFE LOOKED BLANKLY AND DESPERATELY AT ONE ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "husband and wife looked blankly and desperately at one another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5038, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0020.flac", "answer": "AFTER THEY HAD SAID GOOD NIGHT TO THEIR VISITOR MISSUS PETER EXPRESSED HER CONVICTION THAT HE HAD TAKEN SOMETHING", "subset": "test_other", "task_type": "understanding", "prediction": "after they had said good night to their visitor mrs peter expressed her conviction that he had taken something", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5039, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0000.flac", "answer": "WITH THAT NOTORIOUS FAILING OF HIS HE WAS NOT THE SORT OF PERSON ONE WANTED IN ONE'S HOUSE", "subset": "test_other", "task_type": "understanding", "prediction": "with that notorious failing of his he was not the sort of person one wanted in ones house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5040, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0022.flac", "answer": "IT'S THE ONLY THING TO DO", "subset": "test_other", "task_type": "understanding", "prediction": "is the only thing to do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5041, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0018.flac", "answer": "I PUT IT DOWN BY THE CLARET JUG SAID WILFRID BUSY WITH ANOTHER OBJECT", "subset": "test_other", "task_type": "understanding", "prediction": "i put it down by the claret jug said wilfred busy with another object", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5042, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0024.flac", "answer": "IT'S AN UNPLEASANT THING TO HAVE TO SAY HE BLURTED OUT PRESENTLY BUT I'M AFRAID YOU MUST HAVE A THIEF AMONG YOUR SERVANTS SOMETHING'S BEEN TAKEN OUT OF MY PORTMANTEAU", "subset": "test_other", "task_type": "understanding", "prediction": "it is an unpleasant thing to have to say he blurted out presently but i am afraid you must have a thief among your servants something has been taken out of my portmanteau", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5043, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0027.flac", "answer": "THE SNATCHER HAD BEEN AN ORPHAN THESE MANY YEARS", "subset": "test_other", "task_type": "understanding", "prediction": "this natheere had been an orphan this many years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5044, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0028.flac", "answer": "LADY ERNESTINE PIGEONCOTE HIS MOTHER MOVED IN CIRCLES WHICH WERE ENTIRELY BEYOND THEIR COMPASS OR AMBITIONS AND THE SON WOULD PROBABLY ONE DAY BE AN AMBASSADOR", "subset": "test_other", "task_type": "understanding", "prediction": "lady ernestine pigeoncoat his mother moved in circles which were entirely beyond their compass or ambitions and the son would probably one day be an ambassador", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5045, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0030.flac", "answer": "IT WAS MISSUS PETER WHO ARRIVED FIRST AT AN INSPIRATION HOW DREADFUL TO THINK THERE ARE THIEVES IN THE HOUSE WE KEEP THE DRAWING ROOM LOCKED UP AT NIGHT OF COURSE BUT ANYTHING MIGHT BE CARRIED OFF WHILE WE ARE AT BREAKFAST", "subset": "test_other", "task_type": "understanding", "prediction": "it was mrs peter who arrived first at an inspiration how dreadful to think there are thieves in the house we keep the drawing room locked up at night of course but anything might be carried off while we are at breakfast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5046, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0036.flac", "answer": "DO YOU MEAN TO SAY HE'S A KLEPTOMANIAC LIKE COUSIN SNATCHER", "subset": "test_other", "task_type": "understanding", "prediction": "do you mean to say he is a kleptomaniac like cousin snatcher", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5047, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0025.flac", "answer": "IT WAS A LITTLE PRESENT FROM MY MOTHER AND MYSELF FOR YOUR SILVER WEDDING", "subset": "test_other", "task_type": "understanding", "prediction": "it was a little present from my mother and myself for your silver wedding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5048, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0037.flac", "answer": "BRAVE LITTLE WOMAN SAID PETER WITH A GASP OF RELIEF I COULD NEVER HAVE DONE IT", "subset": "test_other", "task_type": "understanding", "prediction": "brave little woman said peter with a gasp of relief i could never have done it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5049, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0010.flac", "answer": "I SUPPOSE HE'S BRINGING US A PRESENT FOR THE SILVER WEDDING GOOD GRACIOUS", "subset": "test_other", "task_type": "understanding", "prediction": "i suppose he is bringing us a present for the silver wedding good gracious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5050, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0003.flac", "answer": "WHEN A MAN IS ABSOLUTELY WEALTHY NOT MERELY WELL TO DO ALL SUSPICION OF SORDID MOTIVE NATURALLY DISAPPEARS THE THING BECOMES MERELY A TIRESOME MALADY", "subset": "test_other", "task_type": "understanding", "prediction": "when a man is absolutely wealthy not merely well to do all suspicion of sordid motive naturally disappears the thing becomes merely a tiresome malady", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5051, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0005.flac", "answer": "A WILFRID PIGEONCOTE HAD COVERED HIMSELF WITH HONOURS IN THE COURSE OF MARLBOROUGH'S CAMPAIGNS AND THE NAME WILFRID HAD BEEN A BAPTISMAL WEAKNESS IN THE FAMILY EVER SINCE THE NEW HEIR TO THE FAMILY DIGNITY AND ESTATES WAS A YOUNG MAN OF ABOUT FIVE AND TWENTY WHO WAS KNOWN MORE BY REPUTATION THAN BY PERSON TO A WIDE CIRCLE OF COUSINS AND KINSFOLK", "subset": "test_other", "task_type": "understanding", "prediction": "a wilfred pigeoncocke had covered himself with honours in the course of marlboroughs campaigns and the name wilfred had been a bethesmal weakness in the family ever since the new heir to the family dignity and estates was a young man of about five and twenty who was known more by reputation than by person to a wide circle of cousins and kinsfolk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5052, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0035.flac", "answer": "PETER'S LITTLE WEAKNESS IT RUNS IN THE FAMILY GOOD LORD", "subset": "test_other", "task_type": "understanding", "prediction": "peter is little weakness it runs in the family good lord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5053, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0008.flac", "answer": "THE SEARCH USUALLY PRODUCED A LARGE AND VARIED YIELD THIS IS FUNNY SAID PETER PIGEONCOTE TO HIS WIFE SOME HALF HOUR AFTER THEIR CONVERSATION HERE'S A TELEGRAM FROM WILFRID SAYING HE'S PASSING THROUGH HERE IN HIS MOTOR AND WOULD LIKE TO STOP AND PAY US HIS RESPECTS", "subset": "test_other", "task_type": "understanding", "prediction": "the search usually produced a large and varied yield this is funny said peter pigeonpotatoes wife some half hour after their conversation here is a telegram from wilfred saying he is passing through here in his motor and would like to stop and pay us his respects", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5054, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0023.flac", "answer": "WILFRID WAS LATE IN COMING DOWN TO BREAKFAST AND HIS MANNER SHOWED PLAINLY THAT SOMETHING WAS AMISS", "subset": "test_other", "task_type": "understanding", "prediction": "wilfrid was late in coming down to breakfast and his manner showed plainly that something was amiss", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5055, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0004.flac", "answer": "WILFRID PIGEONCOTE HAD SUDDENLY BECOME HEIR TO HIS UNCLE SIR WILFRID PIGEONCOTE ON THE DEATH OF HIS COUSIN MAJOR WILFRID PIGEONCOTE WHO HAD SUCCUMBED TO THE AFTER EFFECTS OF A POLO ACCIDENT", "subset": "test_other", "task_type": "understanding", "prediction": "wilfred pigeoncoat had suddenly become heir to his uncle sir wilfred pigeoncoat on the death of his cousin major wilfred pigeoncoat who had succumbed to the after effects of a polo accident", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5056, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0034.flac", "answer": "MISSUS PETER TURNED TO HER GUEST WITH CONFIDENTIAL COYNESS", "subset": "test_other", "task_type": "understanding", "prediction": "mrs peter turned to her guest with confidential coyness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5057, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2340/7105-2340-0002.flac", "answer": "BESIDES CYNICISM APART HIS BEING RICH WILL MAKE A DIFFERENCE IN THE WAY PEOPLE WILL LOOK AT HIS FAILING", "subset": "test_other", "task_type": "understanding", "prediction": "besides cynicism apart his being rich will make a difference in the way people will look at his failing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5058, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0029.flac", "answer": "A TELEGRAM WAS BROUGHT IN", "subset": "test_other", "task_type": "understanding", "prediction": "a telegram was brought in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5059, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0035.flac", "answer": "THE WARDERS HAVE A PRIVATE BAND OF THEIR OWN SAID THE GOVERNOR BUT OF COURSE I COULDN'T ALLOW THE MEN THEMSELVES", "subset": "test_other", "task_type": "understanding", "prediction": "the warders have a private band of their own said the governor but of course i couldnt allow the men themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5060, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0039.flac", "answer": "THE WORD OF THE SONG HAD REFERENCE IT WAS UNDERSTOOD TO THE INCARCERATING GOVERNMENT AND NOT TO THE DESTROYER OF THE ALBERT HALL", "subset": "test_other", "task_type": "understanding", "prediction": "the word of the song had reference it was understood to the incarcerating government and not to the destroyer of the albert hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5061, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0014.flac", "answer": "NOT LATER THAN SEVEN THIRTY THEN SAID THE CHIEF ORGANISER I HAVE PROMISED THE AGENT DOWN THERE THAT HE SHALL BE ABLE TO DISPLAY POSTERS ANNOUNCING PLATTERBAFF IS OUT BEFORE THE POLL OPENS", "subset": "test_other", "task_type": "understanding", "prediction": "not later than seven thirty then said the chief organizer i have promised the agent down there that he shall be able to display posters announcing platterbath is out before the poll opens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5062, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0018.flac", "answer": "HE SAYS HE NEVER HAS LEFT PRISON WITHOUT A BRASS BAND TO PLAY HIM OUT AND HE'S NOT GOING TO GO WITHOUT ONE NOW", "subset": "test_other", "task_type": "understanding", "prediction": "he says he never has left prison without a breast band to play him out and he is not going to go without one now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5063, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0038.flac", "answer": "IT WAS A TUNE THEY HAD ALL HEARD HUNDREDS OF TIMES SO THERE WAS NO DIFFICULTY IN TURNING OUT A PASSABLE IMITATION OF IT TO THE IMPROVISED STRAINS OF I DIDN'T WANT TO DO IT THE PRISONER STRODE FORTH TO FREEDOM", "subset": "test_other", "task_type": "understanding", "prediction": "it was a tune they had all heard hundreds of times so there was no difficulty in turning out a passable imitation of it to the improvised strains of i didn t want to do it the prisoners strode forth to freedom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5064, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0025.flac", "answer": "THIS IS NOT A MOMENT FOR STANDING ON DIGNITY HE OBSERVED BLUNTLY MUSICIANS MUST BE SUPPLIED AT ONCE", "subset": "test_other", "task_type": "understanding", "prediction": "this is not a moment for standing and dignity he observed bluntly mere sessions must be supplied at once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5065, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0001.flac", "answer": "HE HAD NOT ONLY PLEADED GUILTY BUT HAD EXPRESSED HIS INTENTION OF REPEATING HIS ESCAPADE IN OTHER DIRECTIONS AS SOON AS CIRCUMSTANCES PERMITTED THROUGHOUT THE TRIAL HE WAS BUSY EXAMINING A SMALL MODEL OF THE FREE TRADE HALL IN MANCHESTER", "subset": "test_other", "task_type": "understanding", "prediction": "he had not only pleaded guilty but had expressed his intention of repeating his escapade in other directions as soon as circumstances permitted throughout the trial he was busy examining a small model of the free trade hall in manchester", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5066, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0005.flac", "answer": "HENCE THE ANXIETY IN THE CROWDED COURT AND IN THE LITTLE GROUPS GATHERED ROUND THE TAPE MACHINES IN WHITEHALL AND DOWNING STREET AND OTHER AFFECTED CENTRES", "subset": "test_other", "task_type": "understanding", "prediction": "hence their anxiety in the crowded court and in the little groups gathered round the tape machines in whitehall and downing street and other affected centres", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5067, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0041.flac", "answer": "THE LOCAL TRADE UNIONISTS TOOK OFFENCE AT THE FACT OF CABINET MINISTERS HAVING PERSONALLY ACTED AS STRIKE BREAKERS AND EVEN THE RELEASE OF PLATTERBAFF FAILED TO PACIFY THEM", "subset": "test_other", "task_type": "understanding", "prediction": "the local trade unionists took offence at the fact of cabinet ministers having personally acted as strike breakers and even the release of plater bath failed to pacify them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5068, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0012.flac", "answer": "OUR MAJORITY LAST TIME WAS ONLY A THOUSAND AND SEVEN", "subset": "test_other", "task_type": "understanding", "prediction": "our majority last time was only a thousand and seven", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5069, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0004.flac", "answer": "A HEADLONG PARDON ON THE EVE OF A BYE ELECTION WITH THREATS OF A HEAVY VOTING DEFECTION IF IT WERE WITHHELD OR EVEN DELAYED WOULD NOT NECESSARILY BE A SURRENDER BUT IT WOULD LOOK LIKE ONE", "subset": "test_other", "task_type": "understanding", "prediction": "a headlong pardon on the eve of a by election with threats of a heavy voting defection if it were withheld or even delayed would not necessarily be a surrender but it would look like one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5070, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0016.flac", "answer": "DESPITE THE EARLINESS OF THE HOUR A SMALL CROWD HAD GATHERED IN THE STREET OUTSIDE AND THE HORRIBLE MENACING TRELAWNEY REFRAIN OF THE FIFTEEN HUNDRED VOTING MEN CAME IN A STEADY MONOTONOUS CHANT", "subset": "test_other", "task_type": "understanding", "prediction": "despite the earliness of the hour a small crowd had gathered in the street outside and the horrible menacing trill on a refrain of the fifteen hundred voting men came in a steady monotonous chant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5071, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0000.flac", "answer": "UNFORTUNATELY THERE COULD BE NO DOUBT OR MISCONCEPTION AS TO PLATTERBAFF'S GUILT", "subset": "test_other", "task_type": "understanding", "prediction": "unfortunately there could be no doubt our misconception as to plater baths guilt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5072, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0037.flac", "answer": "THE POPULAR SONG OF THE MOMENT REPLIED THE AGITATOR AFTER A MOMENT'S REFLECTION", "subset": "test_other", "task_type": "understanding", "prediction": "the popular song of the moment replied the agitator after a moment s reflection", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5073, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0026.flac", "answer": "CAN'T YOU GET A STRIKE PERMIT ASKED THE ORGANISER", "subset": "test_other", "task_type": "understanding", "prediction": "cant you get a strike permit asked the organizer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5074, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0034.flac", "answer": "DEMANDED THE CHIEF ORGANISER OF THE PRISON GOVERNOR DRUMS CYMBALS THOSE SORT OF THINGS", "subset": "test_other", "task_type": "understanding", "prediction": "demanded the chief organizer of the prison governor drums cymbals those sort of things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5075, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0011.flac", "answer": "FIFTEEN HUNDRED SAID THE PRIME MINISTER WITH A SHUDDER IT'S TOO HORRIBLE TO THINK OF", "subset": "test_other", "task_type": "understanding", "prediction": "fifteen hundred said the prime minister with a shudder it is too horrible to think of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5076, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0031.flac", "answer": "WITHOUT A BAND HE WOULD NOT GO AND THEY HAD NO BAND", "subset": "test_other", "task_type": "understanding", "prediction": "without a band he would not go and they had no band", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5077, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0009.flac", "answer": "THE JURY WISH TO ADD A RIDER DRAWING ATTENTION TO THE FACT THAT A BY ELECTION IS PENDING IN THE PARLIAMENTARY DIVISION OF NEMESIS ON HAND", "subset": "test_other", "task_type": "understanding", "prediction": "the jury wished to add a rider drawing attention to the fact that a by election is pending in the parliamentary division of nemesis on hand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5078, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0023.flac", "answer": "IN HEAVEN'S NAME WHY", "subset": "test_other", "task_type": "understanding", "prediction": "in heaven s name why", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5079, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0028.flac", "answer": "EIGHT O'CLOCK STRUCK THE CROWD OUTSIDE CHANTED WITH AN INCREASING VOLUME OF SOUND WILL VOTE THE OTHER WAY", "subset": "test_other", "task_type": "understanding", "prediction": "eight o clock struck the crowd outside chanted with an increasing volume of sound we ll vote the other way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5080, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0003.flac", "answer": "OF COURSE ANY SENTENCE WHICH THE LAW MIGHT FEEL COMPELLED TO INFLICT WOULD BE FOLLOWED BY AN IMMEDIATE PARDON BUT IT WAS HIGHLY DESIRABLE FROM THE GOVERNMENT'S POINT OF VIEW THAT THE NECESSITY FOR SUCH AN EXERCISE OF CLEMENCY SHOULD NOT ARISE", "subset": "test_other", "task_type": "understanding", "prediction": "of course any sentence which the law might feel compelled to inflict would be followed by an immediate pardon but it was highly desirable from the government's point of view that the necessity for such an exercise of clemency should not arise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5081, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0032.flac", "answer": "A QUARTER PAST TEN HALF PAST", "subset": "test_other", "task_type": "understanding", "prediction": "a quarter past ten half past", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5082, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0021.flac", "answer": "POLL OPENS IN FIVE MINUTES", "subset": "test_other", "task_type": "understanding", "prediction": "paul opens in five minutes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5083, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0033.flac", "answer": "HAVE YOU ANY BAND INSTRUMENTS OF AN EASY NATURE TO PLAY", "subset": "test_other", "task_type": "understanding", "prediction": "have you any band instruments of an easy nature to play", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5084, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0006.flac", "answer": "THE JURY RETURNED FROM CONSIDERING THEIR VERDICT THERE WAS A FLUTTER AN EXCITED MURMUR A DEATHLIKE HUSH", "subset": "test_other", "task_type": "understanding", "prediction": "the jury returned from considering their verdict there was a flutter an excited murmur a death like hush", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5085, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0022.flac", "answer": "IS PLATTERBAFF OUT YET", "subset": "test_other", "task_type": "understanding", "prediction": "is splatter bath out yet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5086, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0017.flac", "answer": "HE EXCLAIMED WON'T GO", "subset": "test_other", "task_type": "understanding", "prediction": "he exclaimed wont go", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5087, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0040.flac", "answer": "THE SEAT WAS LOST AFTER ALL BY A NARROW MAJORITY", "subset": "test_other", "task_type": "understanding", "prediction": "the seat was lost after all by a narrow majority", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5088, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0027.flac", "answer": "I'LL TRY SAID THE HOME SECRETARY AND WENT TO THE TELEPHONE", "subset": "test_other", "task_type": "understanding", "prediction": "i will try said the home secretary and went to the telephone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5089, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0020.flac", "answer": "ANYWAY HE WON'T GO UNLESS HE HAS A BAND", "subset": "test_other", "task_type": "understanding", "prediction": "anyway he won t go unless he has a band", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5090, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0010.flac", "answer": "AND MAY THE LORD HAVE MERCY ON THE POLL A JUNIOR COUNSEL EXCLAIMED IRREVERENTLY", "subset": "test_other", "task_type": "understanding", "prediction": "and may the lord have mercy on the pole a junior counsel exclaimed irreverently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5091, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0008.flac", "answer": "THE JURY FIND THE PRISONER GUILTY OF BLOWING UP THE ALBERT HALL", "subset": "test_other", "task_type": "understanding", "prediction": "the jury find the prisoner guilty of blowing up the albert hall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5092, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0036.flac", "answer": "LEND US THE INSTRUMENTS SAID THE CHIEF ORGANISER", "subset": "test_other", "task_type": "understanding", "prediction": "lend us the instruments said the chief organizer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5093, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0024.flac", "answer": "THE CHIEF ORGANISER RANG OFF", "subset": "test_other", "task_type": "understanding", "prediction": "the chief organizer ran off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5094, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0013.flac", "answer": "SEVEN THIRTY AMENDED THE PRIME MINISTER WE MUST AVOID ANY APPEARANCE OF PRECIPITANCY", "subset": "test_other", "task_type": "understanding", "prediction": "seven thirty amended the prime minister we must avoid any appearance of precipitancy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5095, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0002.flac", "answer": "THE JURY COULD NOT POSSIBLY FIND THAT THE PRISONER HAD NOT DELIBERATELY AND INTENTIONALLY BLOWN UP THE ALBERT HALL THE QUESTION WAS COULD THEY FIND ANY EXTENUATING CIRCUMSTANCES WHICH WOULD PERMIT OF AN ACQUITTAL", "subset": "test_other", "task_type": "understanding", "prediction": "the jury could not possibly find that the prisoner had not deliberately and intentionally blown up the albert hall the question was could they find any extenuating circumstances which would permit of an acquittal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5096, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0015.flac", "answer": "HE SAID IT WAS OUR ONLY CHANCE OF GETTING A TELEGRAM RADPROP IS IN TO NIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "he said it was our only chance of getting a telegram red rabbis in to night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5097, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0007.flac", "answer": "THE FOREMAN DELIVERED HIS MESSAGE", "subset": "test_other", "task_type": "understanding", "prediction": "the foreman delivered his message", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5098, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0030.flac", "answer": "IT WAS FROM THE CENTRAL COMMITTEE ROOMS AT NEMESIS", "subset": "test_other", "task_type": "understanding", "prediction": "it was from the central committee rooms at nemesis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5099, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/7105/2330/7105-2330-0019.flac", "answer": "SAID THE PRIME MINISTER WE CAN HARDLY BE SUPPOSED TO SUPPLY A RELEASED PRISONER WITH A BRASS BAND HOW ON EARTH COULD WE DEFEND IT ON THE ESTIMATES", "subset": "test_other", "task_type": "understanding", "prediction": "said a prime minister we can hardly be supposed to supply our latest prisoner with a brass band how on earth could we defend it on the estimates", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0003.flac", "answer": "BLACKBURN ARCHBISHOP OF YORK WAS A GREAT SMOKER", "subset": "test_other", "task_type": "understanding", "prediction": "blackburn archbishop of york was a great smoker", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0010.flac", "answer": "THEN LET THEM SING THE HUNDRED AND NINETEENTH REPLIED THE CURATE", "subset": "test_other", "task_type": "understanding", "prediction": "then let them sing the hundred and nineteenth replied the curate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0000.flac", "answer": "EVIDENTLY THE INTENTION WAS TO MAKE THINGS PLEASANT FOR THE ROYAL FOE OF TOBACCO DURING HIS VISIT", "subset": "test_other", "task_type": "understanding", "prediction": "evidently the intention was to make things pleasant for the royal folk at tobacco during his visit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0011.flac", "answer": "SIX ARMS THE NEAREST WITHIN REACH PRESENTED WITH AN OBEDIENT START AS MANY TOBACCO POUCHES TO THE MAN OF OFFICE", "subset": "test_other", "task_type": "understanding", "prediction": "six arms the nearest within reach presented without impediment start and as many tobacco pouches to the man of office", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0004.flac", "answer": "ON ONE OCCASION HE WAS AT SAINT MARY'S CHURCH NOTTINGHAM FOR A CONFIRMATION", "subset": "test_other", "task_type": "understanding", "prediction": "on one occasion he was at st marys church nonnenham for a confirmation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0006.flac", "answer": "PARR WAS SUCH A CONTINUAL SMOKER THAT ANYONE WHO CAME INTO HIS COMPANY IF HE HAD NEVER SMOKED BEFORE HAD TO LEARN THE USE OF A PIPE AS A MEANS OF SELF DEFENCE", "subset": "test_other", "task_type": "understanding", "prediction": "parr was such a continuous smoker that any one who came into his company if he had never smoked before soon learned the use of a pipe as a means of self defence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0014.flac", "answer": "WHEN THESE MEN IN THE COURSE OF MY REMONSTRANCE FOUND THAT I WAS NOT GOING TO CONTINUE THE CUSTOM THEY NO LONGER CARED TO BE COMMUNICANTS", "subset": "test_other", "task_type": "understanding", "prediction": "when these men in the course of my remonstrance found out that i was not going to continue the custom they no longer cared to be communicants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0012.flac", "answer": "DAVID DEANS HOWEVER DID NOT AT ALL APPROVE THIS IRREVERENCE", "subset": "test_other", "task_type": "understanding", "prediction": "david deems however did not at all improve this irreverence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0002.flac", "answer": "SOMETIMES TOBACCO WAS USED IN CHURCH FOR DISINFECTING OR DEODORIZING PURPOSES", "subset": "test_other", "task_type": "understanding", "prediction": "sometimes tobacco is used in church for disinfectant and odorizing purposes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0008.flac", "answer": "LET THEM SING ANOTHER PSALM SAID THE CURATE", "subset": "test_other", "task_type": "understanding", "prediction": "them them sing another song said the curate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0001.flac", "answer": "THE PROHIBITION IN THE REGULATION QUOTED OF SMOKING IN SAINT MARY'S CHURCH REFERRED IT MAY BE NOTED TO THE ACT WHICH WAS HELD THEREIN", "subset": "test_other", "task_type": "understanding", "prediction": "the prohibition and the regulating quoted as smoking in st marys church referred it may be noted to the act which was held therein", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0013.flac", "answer": "GOING TO CHURCH AT HAYES IN THOSE DAYS MUST HAVE BEEN QUITE AN EXCITING EXPERIENCE", "subset": "test_other", "task_type": "understanding", "prediction": "going to church at hayes in those days must have been quite an astounding experience", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0005.flac", "answer": "ANOTHER EIGHTEENTH CENTURY CLERICAL WORTHY THE FAMOUS DOCTOR PARR AN INVETERATE SMOKER WAS ACCUSTOMED TO DO WHAT MISTER DISNEY PREVENTED ARCHBISHOP BLACKBURN FROM DOING HE SMOKED IN HIS VESTRY AT HATTON", "subset": "test_other", "task_type": "understanding", "prediction": "another eighteenth century clerical worthy the famous dr parr an inveterate smoker was accustomed to do what mr disney prevented archbishop blackburne from doing he smoked in his vestry at hertford", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0009.flac", "answer": "THEY HAVE SIR REPLIED THE CLERK", "subset": "test_other", "task_type": "understanding", "prediction": "they have sir replied the clerk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/157645/2609-157645-0007.flac", "answer": "ONE SUNDAY SAYS MISTER DITCHFIELD HE HAD AN EXTRA PIPE AND JOSHUA THE CLERK TOLD HIM THAT THE PEOPLE WERE GETTING IMPATIENT", "subset": "test_other", "task_type": "understanding", "prediction": "one sunday says mr datcherd he hadnt natcher pipe and joshua the clerk told him that the people were getting impatient", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0019.flac", "answer": "THE WILDERNESS TO THE EAST OF EGYPT HAD FOR CENTURIES BEEN THE PLACE OF REFUGE FOR EGYPTIAN FUGITIVES", "subset": "test_other", "task_type": "understanding", "prediction": "the wilderness to the east of egypt had for centuries been the place of refuge for egyptian fugitives", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0031.flac", "answer": "DO THE EARLIEST HEBREW TRADITIONS IMPLY THAT THE ANCESTORS OF THE ISRAELITES WERE WORSHIPPERS OF JEHOVAH", "subset": "test_other", "task_type": "understanding", "prediction": "do the uriet sebu traditions imply that the ancestors of the israelites were worshippers of jehovah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0022.flac", "answer": "THESE SAND WANDERERS SENT HIM ON FROM TRIBE TO TRIBE UNTIL HE REACHED THE LAND OF KEDEM EAST OF THE DEAD SEA WHERE HE REMAINED FOR A YEAR AND A HALF", "subset": "test_other", "task_type": "understanding", "prediction": "these sand wanderers sent him on from tribe to tribe until he reached the land of kedom east of the dead sea where he remained for a year and a half", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0015.flac", "answer": "THE STORY OF MOSES BIRTH AND EARLY CHILDHOOD IS ONE OF THE MOST INTERESTING CHAPTERS IN BIBLICAL HISTORY", "subset": "test_other", "task_type": "understanding", "prediction": "the story of moses birth and early childhood is one of the most interesting chapters in biblical history", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0035.flac", "answer": "HIS QUEST WAS FOR A JUST AND STRONG GOD ABLE TO DELIVER THE OPPRESSED", "subset": "test_other", "task_type": "understanding", "prediction": "his praise was for a just and strong god able to deliver the oppressed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0011.flac", "answer": "A CONTEMPORARY INSCRIPTION ALSO STATES THAT HE FOUNDED NEAR PITHUM THE HOUSE OF RAMSES A CITY WITH A ROYAL RESIDENCE AND TEMPLES", "subset": "test_other", "task_type": "understanding", "prediction": "a contemporary inscription answers states that he founded near pittham the house of rameses a city with the royal residence since then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0007.flac", "answer": "THE STORIES REGARDING JOSEPH THE TRADITIONAL FATHER OF EPHRAIM AND MANASSEH IMPLY THAT THESE STRONG CENTRAL TRIBES POSSIBLY TOGETHER WITH THE SOUTHERN TRIBES OF BENJAMIN AND JUDAH WERE THE CHIEF ACTORS IN THIS OPENING SCENE IN ISRAEL'S HISTORY", "subset": "test_other", "task_type": "understanding", "prediction": "the stories regarding joseph their traditional founder ephraim and manasseh imply that these strong central tribes possibly together with the southern tribes of benjamin and judah were the chief actors in this opening scene in israel s history", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0026.flac", "answer": "THE PRIEST OF THE SUB TRIBE OF THE KENITES RECEIVED HIM INTO HIS HOME AND GAVE HIM HIS DAUGHTER IN MARRIAGE", "subset": "test_other", "task_type": "understanding", "prediction": "the priest of the sub tribe of the kenites received him into his home and gave him his daughter in marriage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0004.flac", "answer": "EVERY ONE WHO IS TURBULENT HAS BEEN FOUND BY KING MERNEPTAH THE TESTIMONY OF THE OLDEST BIBLICAL NARRATIVES REGARDING THE SOJOURN OF THE HEBREWS IN EGYPT IS ALSO IN PERFECT ACCORD WITH THE PICTURE WHICH THE CONTEMPORARY EGYPTIAN INSCRIPTIONS GIVE OF THE PERIOD", "subset": "test_other", "task_type": "understanding", "prediction": "every one who is turbulent has been found by him in that path the testimony of the oldest biblical narrative regarding the sojourn of the hebrews in egypt is also in perfect accord with the picture which the contemporary egyptian inscriptions give of the period", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0018.flac", "answer": "NATURALLY HE WENT TO THE LAND OF MIDIAN", "subset": "test_other", "task_type": "understanding", "prediction": "naturally he went to the land of medion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0021.flac", "answer": "ON THE BORDERS OF THE WILDERNESS HE FOUND CERTAIN BEDOUIN HERDSMEN WHO RECEIVED HIM HOSPITABLY", "subset": "test_other", "task_type": "understanding", "prediction": "on the borders of the wilderness he found certain bedouin herdsmen who received him hospitably", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0009.flac", "answer": "THE LATER TRADITIONS TEND TO EXTEND THE PERIOD", "subset": "test_other", "task_type": "understanding", "prediction": "the later traditions tend to extend the period", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0006.flac", "answer": "IT SEEMS PROBABLE THAT NOT ALL BUT ONLY PART OF THE TRIBES WHICH ULTIMATELY COALESCED INTO THE HEBREW NATION FOUND THEIR WAY TO EGYPT", "subset": "test_other", "task_type": "understanding", "prediction": "it seems probable that not all but only part of the transitz ultimate colonists into the hebrew nation found their way to egypt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0028.flac", "answer": "HERE MOSES LEARNED THE LESSONS THAT WERE ESSENTIAL FOR HIS TRAINING AS THE LEADER AND DELIVERER OF HIS PEOPLE", "subset": "test_other", "task_type": "understanding", "prediction": "here moses learned the lessons that were essential for his training as the leader and deliverer of his people", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0036.flac", "answer": "THE WILDERNESS WITH ITS LURKING FOES AND THE EVER PRESENT DREAD OF HUNGER AND THIRST DEEPENED HIS SENSE OF NEED AND OF DEPENDENCE UPON A POWER ABLE TO GUIDE THE DESTINIES OF MEN", "subset": "test_other", "task_type": "understanding", "prediction": "the wilderness with its lurking foes and the ever present dread of hunger and thirst deepens his sense of need and of dependence upon a power able to guide the destitute man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0020.flac", "answer": "FROM ABOUT TWO THOUSAND B C", "subset": "test_other", "task_type": "understanding", "prediction": "from about two thousand b c", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0037.flac", "answer": "THE PEASANTS OF THE VAST ANTOLIAN PLAIN IN CENTRAL ASIA MINOR STILL CALL EVERY LIFE GIVING SPRING GOD HATH GIVEN", "subset": "test_other", "task_type": "understanding", "prediction": "the peasants of the vast antonian plain of central asia minor still call every life giving spring god hath given", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0030.flac", "answer": "MANY MODERN SCHOLARS DRAW THE CONCLUSION FROM THE BIBLICAL NARRATIVE THAT IT WAS FROM THE KENITES THAT MOSES FIRST LEARNED OF YAHWEH OR AS THE DISTINCTIVE NAME OF ISRAEL'S GOD WAS TRANSLATED BY LATER JEWISH SCRIBES JEHOVAH", "subset": "test_other", "task_type": "understanding", "prediction": "many modern scholars draw the conclusion from the biblical narrative that it was from the canaanites that moses first learned of yahweh or as the distinctive name of israels god was transmuted by later jewish scribes jehovah", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0005.flac", "answer": "THE ABSENCE OF DETAILED REFERENCE TO THE HEBREWS IS THEREFORE PERFECTLY NATURAL", "subset": "test_other", "task_type": "understanding", "prediction": "the absence of detailed references to the hebrews is therefore perfectly natural", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0010.flac", "answer": "HERE WERE FOUND SEVERAL INSCRIPTIONS BEARING THE EGYPTIAN NAME OF THE CITY P ATUM HOUSE OF THE GOD ATUM", "subset": "test_other", "task_type": "understanding", "prediction": "here were found several inscriptions bearing the egyptian name of the city pataum house of the god atum", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0034.flac", "answer": "THE CRUEL FATE OF HIS PEOPLE AND THE PAINFUL EXPERIENCE IN EGYPT THAT HAD DRIVEN HIM INTO THE WILDERNESS PREPARED HIS MIND TO RECEIVE THIS TRAINING", "subset": "test_other", "task_type": "understanding", "prediction": "the cruel fate of this people and the painful experience in egypt that had driven him into the wilderness prepared his mind to receive this training", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0002.flac", "answer": "LET US HAVE FAITH THAT RIGHT MAKES MIGHT AND IN THAT FAITH LET US DARE TO DO OUR DUTY AS WE UNDERSTAND IT LINCOLN", "subset": "test_other", "task_type": "understanding", "prediction": "let us have faith that right makes might and in that faith let us dare to do our duty as we understand it linton", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0003.flac", "answer": "THE EGYPTIAN BACKGROUND OF THE BONDAGE", "subset": "test_other", "task_type": "understanding", "prediction": "the egyptian background of the bondage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0023.flac", "answer": "LATER HE FOUND HIS WAY TO THE COURT OF ONE OF THE LOCAL KINGS IN CENTRAL PALESTINE WHERE HE MARRIED AND BECAME IN TIME A PROSPEROUS LOCAL PRINCE", "subset": "test_other", "task_type": "understanding", "prediction": "later he found his way to the court of one of the local kings in central palestine where he married and became in time a prosperous local prince", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0033.flac", "answer": "MOSES IN THE HOME OF THE MIDIAN PRIEST WAS BROUGHT INTO DIRECT AND CONSTANT CONTACT WITH THE JEHOVAH WORSHIP", "subset": "test_other", "task_type": "understanding", "prediction": "moses in the home of the midian priest was brought into direct and constant contact with the jehovah worship", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0014.flac", "answer": "THE MAKING OF A LOYAL PATRIOT", "subset": "test_other", "task_type": "understanding", "prediction": "the making of a loyal patriot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0029.flac", "answer": "AFTER THE CAPTURE OF JERICHO CERTAIN OF THEM WENT UP WITH THE SOUTHERN TRIBES TO CONQUER SOUTHERN PALESTINE", "subset": "test_other", "task_type": "understanding", "prediction": "after the capture of jericho certain of them went up with the southern tribes to conquer southern palestine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0025.flac", "answer": "THE STORY OF MOSES IS IN MANY WAYS CLOSELY PARALLEL TO THAT OF SINUHIT", "subset": "test_other", "task_type": "understanding", "prediction": "the story of moses is in many ways closely parallel to that of sinewit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0027.flac", "answer": "NOTE THE CHARACTERISTIC ORIENTAL IDEA OF MARRIAGE", "subset": "test_other", "task_type": "understanding", "prediction": "note the care of reverend sticke oriental idea of marriage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0001.flac", "answer": "HOLD ON HOLD FAST HOLD OUT PATIENCE IS GENIUS", "subset": "test_other", "task_type": "understanding", "prediction": "hold on hold fast hold out patience is genius", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0017.flac", "answer": "IS PEONAGE ALWAYS DISASTROUS NOT ONLY TO ITS VICTIMS BUT ALSO TO THE GOVERNMENT IMPOSING IT", "subset": "test_other", "task_type": "understanding", "prediction": "is pinioned always disastrous not only to its victims but also to the government imposing it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0032.flac", "answer": "THE TITLE OF HIS FATHER IN LAW IMPLIES THAT THIS PRIEST MINISTERED AT SOME WILDERNESS SANCTUARY", "subset": "test_other", "task_type": "understanding", "prediction": "the title of his fundin law implies that this priest ministered at some wilderness sanctuary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0012.flac", "answer": "THAT THE HEBREWS WERE RESTIVE UNDER THIS TYRANNY WAS NATURAL INEVITABLE", "subset": "test_other", "task_type": "understanding", "prediction": "that the hebrews were restive under this tyranny was naturally inevitable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0008.flac", "answer": "THE BIBLICAL NARRATIVES APPARENTLY DISAGREE REGARDING THE DURATION OF THE SOJOURN IN EGYPT", "subset": "test_other", "task_type": "understanding", "prediction": "the biblical narratives apparently disagree regarding the duration of the sojourn in egypt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0038.flac", "answer": "THE CONSTANT NECESSITY OF MEETING THE DANGERS OF THE WILDERNESS AND OF DEFENDING THE FLOCKS ENTRUSTED TO MOSES CARE DEVELOPED HIS COURAGE AND POWER OF LEADERSHIP AND ACTION", "subset": "test_other", "task_type": "understanding", "prediction": "the constant necessity of meeting the dangers of the wilderness and of defending the flocks entroused jemadis care developed his courage and power of leadership and action", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0000.flac", "answer": "THEN MOSES WAS AFRAID AND SAID SURELY THE THING IS KNOWN", "subset": "test_other", "task_type": "understanding", "prediction": "then moses was afraid and said surely the thing is known", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0013.flac", "answer": "WAS ANY OTHER PROCEDURE TO BE EXPECTED FROM A DESPOTIC RULER OF THAT LAND AND DAY", "subset": "test_other", "task_type": "understanding", "prediction": "was any other procedure to be expected from it the hispanic roar of that land and day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0024.flac", "answer": "THE SCHOOL OF THE WILDERNESS", "subset": "test_other", "task_type": "understanding", "prediction": "the school of the wilderness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/156975/2609-156975-0016.flac", "answer": "WAS MOSES JUSTIFIED IN RESISTING THE EGYPTIAN TASKMASTER", "subset": "test_other", "task_type": "understanding", "prediction": "was moses justified in resisting the egyptian taskmaster", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0017.flac", "answer": "THE JOHN BEHAVED BEAUTIFULLY AND CAME ROUND LIKE A TOP", "subset": "test_other", "task_type": "understanding", "prediction": "the jar behaved beautifully he came round like a top", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0011.flac", "answer": "MISTER KITE OBSERVED THIS ALSO AND REMARKED THAT OUR MOVEMENTS HAD BEEN SO PROMPT AS TO TAKE THE RASCALS ABACK", "subset": "test_other", "task_type": "understanding", "prediction": "mr kite observed this also and remarked that our movements had been so prompt as to take the rascals aback", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0004.flac", "answer": "MISTER MARBLE HE I DO BELIEVE WAS FAIRLY SNOOZING ON THE HEN COOPS BEING LIKE THE SAILS AS ONE MIGHT SAY BARELY ASLEEP", "subset": "test_other", "task_type": "understanding", "prediction": "mr marble he on de breet was fairly snoozing on de hinkoops bein like de sailors as one might say very asleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0005.flac", "answer": "AT THAT MOMENT I HEARD A NOISE ONE FAMILIAR TO SEAMEN THAT OF AN OAR FALLING IN A BOAT", "subset": "test_other", "task_type": "understanding", "prediction": "at that moment i heard a noise well familiar to seamen that of an oar falling in a boat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0019.flac", "answer": "THE CAPTAIN BEHAVED PERFECTLY WELL IN THIS CRITICAL INSTANT COMMANDING A DEAD SILENCE AND THE CLOSEST ATTENTION TO HIS ORDERS", "subset": "test_other", "task_type": "understanding", "prediction": "the captain behaved perfec tually well in this critical instant commanding a dead silence and the closest attention to his orders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0010.flac", "answer": "I SOON SAW BOTH PROAS AND GLAD ENOUGH WAS I TO PERCEIVE THAT THEY HAD NOT APPROACHED MATERIALLY NEARER", "subset": "test_other", "task_type": "understanding", "prediction": "i soon saw both prats and glad enough was i to perceive that they had not approached materially near", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0018.flac", "answer": "THE QUESTION WAS NOW WHETHER WE COULD PASS THEM OR NOT BEFORE THEY GOT NEAR ENOUGH TO GRAPPLE", "subset": "test_other", "task_type": "understanding", "prediction": "the question was now whether we could pass them or not before they got nearing up to grapple", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0015.flac", "answer": "KITE WENT AFT AND RETURNED WITH THREE OR FOUR MUSKETS AND AS MANY PIKES", "subset": "test_other", "task_type": "understanding", "prediction": "kite went aft and returned with three or four muskets and as many pikes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0016.flac", "answer": "THE STILLNESS THAT REIGNED ON BOTH SIDES WAS LIKE THAT OF DEATH", "subset": "test_other", "task_type": "understanding", "prediction": "the stillness that reigned on boat sides was like that of death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0001.flac", "answer": "AN HOUR AFTER THE SUN HAD SET THE WIND FELL TO A LIGHT AIR THAT JUST KEPT STEERAGE WAY ON THE SHIP", "subset": "test_other", "task_type": "understanding", "prediction": "now and after the sun had set the wind fell to a light air the jitsuk steered his way on the ship", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0008.flac", "answer": "ALTHOUGH THEY WENT THREE FEET TO OUR TWO THIS GAVE US A MOMENT OF BREATHING TIME", "subset": "test_other", "task_type": "understanding", "prediction": "although they went three feet to our two this gave us a moment of breathing time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0020.flac", "answer": "NOT A SOUL ON BOARD THE JOHN WAS HURT", "subset": "test_other", "task_type": "understanding", "prediction": "not a soul aboard the john was hurt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0003.flac", "answer": "I NEVER WAS IN A BETTER STEERING SHIP MOST ESPECIALLY IN MODERATE WEATHER", "subset": "test_other", "task_type": "understanding", "prediction": "i never was in a better steering ship particularly in moderate weather", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0012.flac", "answer": "A BREATHLESS STILLNESS SUCCEEDED", "subset": "test_other", "task_type": "understanding", "prediction": "a breath of its stillness succeeded", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0014.flac", "answer": "I HEARD THE RATTLING OF THE BOARDING PIKES TOO AS THEY WERE CUT ADRIFT FROM THE SPANKER BOOM AND FELL UPON THE DECKS", "subset": "test_other", "task_type": "understanding", "prediction": "i heard the rattling of the boarding pikes too as they were cut adrift from the spanker boom and fell upon the decks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0021.flac", "answer": "ON OUR SIDE WE GAVE THE GENTLEMEN THE FOUR SIXES TWO AT THE NEAREST AND TWO AT THE STERN MOST PROA WHICH WAS STILL NEAR A CABLE'S LENGTH DISTANT", "subset": "test_other", "task_type": "understanding", "prediction": "when our side we gave the gentleman the four sixes two at the nearest and two at the sternmost prow which was still near a cables length distant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0023.flac", "answer": "I DOUBT IF WE TOUCHED A MAN IN THE NEAREST PROA", "subset": "test_other", "task_type": "understanding", "prediction": "i doubt if we d touched a man in the nearish part", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0024.flac", "answer": "IN THIS STATE THE SHIP PASSED AHEAD ALL HER CANVAS BEING FULL LEAVING THE PROA MOTIONLESS IN HER WAKE", "subset": "test_other", "task_type": "understanding", "prediction": "in this state the ship pouts ahead all of her canvas is being full leaving the prow most immersed in her wake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0013.flac", "answer": "THE PROAS DID NOT ALTER THEIR COURSE BUT NEARED US FAST", "subset": "test_other", "task_type": "understanding", "prediction": "the proaets did not alter their course but neared us fast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0007.flac", "answer": "HE WAS TOO MUCH OF A SEAMAN TO REQUIRE A SECOND LOOK IN ORDER TO ASCERTAIN WHAT WAS TO BE DONE", "subset": "test_other", "task_type": "understanding", "prediction": "he was too much of a seaman to require a second look and ordered to ascertain what was to be done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0000.flac", "answer": "PROAS IN THAT QUARTER WERE USUALLY DISTRUSTED BY SHIPS IT IS TRUE BUT THE SEA IS FULL OF THEM AND FAR MORE ARE INNOCENT THAN ARE GUILTY OF ANY ACTS OF VIOLENCE", "subset": "test_other", "task_type": "understanding", "prediction": "parrots in that quarter were easily distrusted by the ships it is true but there see us forward them and far more are innocent than are guilty of any acts of violence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0002.flac", "answer": "FORTUNATELY THE JOHN WAS NOT ONLY FAST BUT SHE MINDED HER HELM AS A LIGHT FOOTED GIRL TURNS IN A LIVELY DANCE", "subset": "test_other", "task_type": "understanding", "prediction": "fortunately the gyne was not only fats but she minded her helm as the light footed girl turned in a lively dance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0022.flac", "answer": "THEY WERE LIKE THE YELLS OF FIENDS IN ANGUISH", "subset": "test_other", "task_type": "understanding", "prediction": "they were like the yells of fiends in anguish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0006.flac", "answer": "I SANG OUT SAIL HO AND CLOSE ABOARD", "subset": "test_other", "task_type": "understanding", "prediction": "i say yet sail ho and close aboard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2609/169640/2609-169640-0009.flac", "answer": "AS OUR SHEETS WERE ALL FLYING FORWARD AND REMAINED SO FOR A FEW MINUTES IT GAVE ME LEISURE TO LOOK ABOUT", "subset": "test_other", "task_type": "understanding", "prediction": "as our seats were all flying forward and remained so for a few minutes it gave me a leisure to look about", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0012.flac", "answer": "I'M WORKING IN THE INTERESTS OF THE YOUNG MAN", "subset": "test_other", "task_type": "understanding", "prediction": "i am working in the interest of the young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0059.flac", "answer": "AND THERE'S NO REASON YOU SHOULDN'T KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "and there is no reason you shouldnt know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0055.flac", "answer": "WHAT IS IT PERHAPS I CAN HELP YOU", "subset": "test_other", "task_type": "understanding", "prediction": "what is it perhaps i can help you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0002.flac", "answer": "I'M GOING OFF FISHING I MAY NOT CATCH ANYTHING I MAY NOT WANT TO AFTER I GET THERE", "subset": "test_other", "task_type": "understanding", "prediction": "i am going off fishing i may not catch anything and may not want to after i get there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0031.flac", "answer": "AND DONOVAN'S VOICE WAS PLAINLY SKEPTICAL", "subset": "test_other", "task_type": "understanding", "prediction": "and donovan s voice was plainly skeptical", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0028.flac", "answer": "AND THE WATCH HAVE YOU IT YES IT'S HERE", "subset": "test_other", "task_type": "understanding", "prediction": "and the watch have you it yes it is here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0029.flac", "answer": "THAT'S THE WATCH ANNOUNCED THE HEADQUARTERS DETECTIVE REACHING IN FOR IT GOING YET SEE", "subset": "test_other", "task_type": "understanding", "prediction": "thats the watch announced the headquarters detective reaching in for it going at see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0043.flac", "answer": "ALL RIGHT BE THERE IN A SECOND", "subset": "test_other", "task_type": "understanding", "prediction": "all right be there in a second", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0047.flac", "answer": "RATHER A HYPOTHETICAL QUESTION COLONEL BUT I SHOULD SAY IT MIGHT BE A FIFTY FIFTY PROPOSITION", "subset": "test_other", "task_type": "understanding", "prediction": "rather a hypothetical question colonel but i should say it might be a fifty fifty proposition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0017.flac", "answer": "LOOK HERE COLONEL DO YOU KNOW ANYTHING ABOUT THIS", "subset": "test_other", "task_type": "understanding", "prediction": "look here colonel do you know anything about this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0011.flac", "answer": "YOU'RE ON THE DARCY CASE THEY TELL ME IN A WAY YES", "subset": "test_other", "task_type": "understanding", "prediction": "you are on the darcy case they tell me in a way yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0014.flac", "answer": "BUSTED HIS HEAD IN WITH A HEAVY CANDLESTICK ONE OF A PAIR", "subset": "test_other", "task_type": "understanding", "prediction": "busted his head in with a heavy candlestick one of a pair", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0021.flac", "answer": "PHUT I DON'T KNOW WHETHER THAT'S HIS FIRST OR HIS LAST NAME ANYHOW HE HAD A PARTNER NAMED SHERE ALI", "subset": "test_other", "task_type": "understanding", "prediction": "thot i dunno whether that is his first or his last name anyhow he had a partner named shirali", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0030.flac", "answer": "YOU'RE NOT AS SQUEAMISH AS ALL THAT ARE YOU JUST BECAUSE IT WAS IN A DEAD MAN'S HAND AND IN A WOMAN'S", "subset": "test_other", "task_type": "understanding", "prediction": "you are not as squeamish as all that are you just because it was in a dead man s hands and a woman s", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0015.flac", "answer": "GAD EXCLAIMED THE COLONEL", "subset": "test_other", "task_type": "understanding", "prediction": "gad exclaimed the colonel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0036.flac", "answer": "THAT'S RIGHT AGREED THE COLONEL AS HE CONTINUED TO MOVE HIS MAGNIFYING GLASS OVER THE SURFACE OF THE STILL TICKING WATCH", "subset": "test_other", "task_type": "understanding", "prediction": "that is right agreed the colonel as he continued to move his magnifying glass over the surface of the still ticking watch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0034.flac", "answer": "IF YOU DON'T MIND I SHOULD LIKE TO EXAMINE THIS A BIT", "subset": "test_other", "task_type": "understanding", "prediction": "if you dont mind i should like to examine this a bit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0056.flac", "answer": "THE OLD ADAGE OF TWO HEADS YOU KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "the old adage of two heads you know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0040.flac", "answer": "DON'T SCRATCH YOURSELF ON IT WHATEVER YOU DO WHY NOT", "subset": "test_other", "task_type": "understanding", "prediction": "dont scratch yourself on it whatever you do why not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0033.flac", "answer": "AND I'VE READ ENOUGH ABOUT GERMS TO KNOW THE DANGER I'D ADVISE YOU TO BE CAREFUL", "subset": "test_other", "task_type": "understanding", "prediction": "and i have read enough about germs to know the danger i would advise you to be careful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0018.flac", "answer": "AND THE DETECTIVE'S PROFESSIONAL INSTINCTS GOT THE UPPER HAND OF HIS FRIENDLINESS NOT THE LEAST IN THE WORLD NOT AS MUCH AS YOU DO WAS THE COOL ANSWER", "subset": "test_other", "task_type": "understanding", "prediction": "and the detective s professional instincts got the upper hand of his friendliness not the least in the world not as much as you do was the cool answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0004.flac", "answer": "AND HAVING PUT HIMSELF IN A FAIR WAY AS HE HOPED TO SOLVE SOME OF THE PROBLEMS CONNECTED WITH THE DARCY CASE COLONEL ASHLEY WENT DOWN TO POLICE HEADQUARTERS TO LEARN MORE FACTS IN CONNECTION WITH THE MURDER OF THE EAST INDIAN", "subset": "test_other", "task_type": "understanding", "prediction": "and having put himself in a fair way as he hoped to solve some of the problems connected with the darcy case colonel ashley went down to police headquarters to learn more facts in the connection with the murder of the east indian", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0009.flac", "answer": "PERHAPS NOT ADMITTED COLONEL ASHLEY", "subset": "test_other", "task_type": "understanding", "prediction": "perhaps not admitted colonel ashley", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0042.flac", "answer": "SOME ONE OUT HERE TO SEE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "someone out here to see you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0022.flac", "answer": "ANYHOW HE AND PHUT DIDN'T GET ALONG VERY WELL IT SEEMS", "subset": "test_other", "task_type": "understanding", "prediction": "anyhow he and phutt didn't get along very well it seems", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0005.flac", "answer": "PINKUS AND DONOVAN HAVEN'T THEY CARROLL YEP", "subset": "test_other", "task_type": "understanding", "prediction": "pinkus and donovan haven t they carol yep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0038.flac", "answer": "AND DONOVAN TAKE A FRIEND'S ADVICE AND DON'T BE TOO FREE WITH THAT WATCH TOO FREE WITH IT", "subset": "test_other", "task_type": "understanding", "prediction": "and donovan take a friend s advice and don t be too free with that watch too free with it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0013.flac", "answer": "IT'S JUST ONE OF THEM COINCIDENCES LIKE", "subset": "test_other", "task_type": "understanding", "prediction": "its just one of them coincidences like", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0006.flac", "answer": "CARROLL WAS TOO MUCH ENGAGED IN WATCHING THE BLUE SMOKE CURL LAZILY UPWARD FROM HIS CIGAR JUST THEN TO SAY MORE", "subset": "test_other", "task_type": "understanding", "prediction": "carroll was too much engaged in watching the blue smoke curl lazily upward from his cigar just then to say more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0016.flac", "answer": "THE VERY PAIR I WAS GOING TO BUY", "subset": "test_other", "task_type": "understanding", "prediction": "the very pair i was going to buy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0051.flac", "answer": "BUT I NEED TO DO A LITTLE MORE SMOKING OUT FIRST NOW I WANT TO THINK", "subset": "test_other", "task_type": "understanding", "prediction": "but i need to do a little more smoking out first now i want to think", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0010.flac", "answer": "WE'VE GOT OUR MAN AND THAT'S ALL WE WANT", "subset": "test_other", "task_type": "understanding", "prediction": "we have got our man and that is all we want", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0058.flac", "answer": "NO ALIMONY REPEATED THE COLONEL PUZZLED YES JUST THAT", "subset": "test_other", "task_type": "understanding", "prediction": "no alimony replied the colonel puzzled yes just that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0037.flac", "answer": "AND A CLOSE OBSERVER MIGHT HAVE OBSERVED THAT HE DID NOT TOUCH HIS BARE FINGERS TO THE TIMEPIECE BUT POKED IT ABOUT AND TOUCHED IT HERE AND THERE WITH THE END OF A LEADPENCIL", "subset": "test_other", "task_type": "understanding", "prediction": "and a close observer might have observed that he did not touch his bare fingers to the timepiece but poked it about and touched it here and there with the end of a lead pencil", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0053.flac", "answer": "IN FACT I HAVE A FEELING THAT I'LL LAND MY FISH", "subset": "test_other", "task_type": "understanding", "prediction": "in fact i have a feeling that i will land my fish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0020.flac", "answer": "NOW I'M AFRAID I WON'T BUT HOW DID IT HAPPEN", "subset": "test_other", "task_type": "understanding", "prediction": "now i am afraid i won t but how did it happen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0026.flac", "answer": "SURE HELD SO TIGHT WE COULD HARDLY GET IT OUT", "subset": "test_other", "task_type": "understanding", "prediction": "shore held so tight we could hardly get it out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0032.flac", "answer": "YES IT MAY HAVE SOME ROUGH EDGES ON IT", "subset": "test_other", "task_type": "understanding", "prediction": "yes it may have some rough edges on it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0008.flac", "answer": "BUT HE HADN'T ANY MORE TO DO WITH IT COLONEL THAN THAT CAT", "subset": "test_other", "task_type": "understanding", "prediction": "but he hadnt any more to do with it colonel than that cat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0045.flac", "answer": "I WANT TO TALK OVER DARCY'S CASE WITH YOU THE COLONEL HAD SAID AND THE TWO HAD TALKED HAD THOUGHT HAD TALKED AGAIN AND NOW WERE SILENT FOR A TIME", "subset": "test_other", "task_type": "understanding", "prediction": "i want to talk over darcy s case with you the colonel had said and the two had talked had thought had talked again and now were silent for a time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0057.flac", "answer": "YES IT STILL HOLDS GOOD", "subset": "test_other", "task_type": "understanding", "prediction": "yes it still holds good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0035.flac", "answer": "BEFORE THE BIG WIND IN IRELAND SUGGESTED THONG WITH A NOD AT HIS IRISH COMPATRIOT SLIGHTLY LAUGHED THE COLONEL", "subset": "test_other", "task_type": "understanding", "prediction": "before the big wind in ireland suggested thong with a nod at his irish compatriot slightly it will have the colonel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0003.flac", "answer": "GET READY SHAG YES SAH COLONEL", "subset": "test_other", "task_type": "understanding", "prediction": "get ready shag yes sir colonel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0039.flac", "answer": "ASKED THE SURPRISED DETECTIVE YES", "subset": "test_other", "task_type": "understanding", "prediction": "asked the surprised detective yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0041.flac", "answer": "SIMPLY BECAUSE THIS WATCH", "subset": "test_other", "task_type": "understanding", "prediction": "simply because this watch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0019.flac", "answer": "I HAPPENED TO SEE THOSE CANDLESTICKS IN THE WINDOW OF SINGA PHUT'S SHOP THE OTHER DAY AND I MADE UP MY MIND TO BUY THEM WHEN I HAD A CHANCE", "subset": "test_other", "task_type": "understanding", "prediction": "i happened to see those candlesticks in the window of singa fudds shop the other day and i made up my mind to buy them when i had a chance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0048.flac", "answer": "AT BEST HE WOULD GET OFF WITH A SCOTCH VERDICT OF NOT PROVEN BUT HE DOESN'T WANT THAT NOR DO I", "subset": "test_other", "task_type": "understanding", "prediction": "at best he would get off with a scotch verdict of not proven but he does not want that nor do i", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0024.flac", "answer": "TOWARD DARK A MAN WENT IN TO BUY A LAMP", "subset": "test_other", "task_type": "understanding", "prediction": "toward dark a man went in to buy a lamp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0046.flac", "answer": "WHAT ARE THE CHANCES OF GETTING HIM OFF LEGALLY IF WE GO AT IT FROM A NEGATIVE STANDPOINT ASKED THE COLONEL", "subset": "test_other", "task_type": "understanding", "prediction": "what are the chances of getting him off legally if we go at it from a negative standpoint asked the colonel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0025.flac", "answer": "HE FOUND THE PLACE WITHOUT A LIGHT IN IT STUMBLED OVER SOMETHING ON THE FLOOR AND THERE WAS ALI'S BODY WITH THE HEAD BUSTED IN AND THIS HEAVY CANDLESTICK NEAR IT", "subset": "test_other", "task_type": "understanding", "prediction": "he found the place without a light in it stumbled over something on the floor and there was allie s body with the head busted in and this heavy candlestick near it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0000.flac", "answer": "BUT SCUSE ME DIDN'T YO FIGGER ON DOIN SOME DETECTIN AN GIVE UP FISHIN", "subset": "test_other", "task_type": "understanding", "prediction": "but scuse me daniel feggan doing some detecting and giving up fishing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0054.flac", "answer": "I'D RECOMMEND HIM TO YOU INSTEAD OF BLACKSTONE THANKS LAUGHED KENNETH", "subset": "test_other", "task_type": "understanding", "prediction": "i recommend him to you instead of blackstone thanks laughed kenneth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0044.flac", "answer": "SINGA PHUT WAS THE PANTING ANSWER", "subset": "test_other", "task_type": "understanding", "prediction": "shinga phut was the panting answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0052.flac", "answer": "IF YOU'LL EXCUSE ME I'LL PRETEND I'M FISHING AND I MAY CATCH SOMETHING", "subset": "test_other", "task_type": "understanding", "prediction": "if you ll excuse me i ll pretend i m fishing and i may catch something", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0027.flac", "answer": "MAYBE THE FIGHT WAS ABOUT WHO OWNED THE WATCH FOR THE DAGOS TALKED IN THEIR FOREIGN LINGO AND NONE OF THE NEIGHBORS COULD TELL WHAT THEY WERE SAYIN I SEE", "subset": "test_other", "task_type": "understanding", "prediction": "maybe the fight was about who owned the watch for the dagos talked in their foreign lingo and none of the neighbors could tell what they were saying i see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0023.flac", "answer": "NEIGHBORS OFTEN HEARD EM SCRAPPIN A LOT AND THIS AFTERNOON THEY WENT AT IT AGAIN HOT AND HEAVY", "subset": "test_other", "task_type": "understanding", "prediction": "neighbors often heard them scrapin a lot and this afternoon they went at it again hot and heavy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0050.flac", "answer": "BUT I WANT TO KNOW JUST WHERE WE STAND NOW I KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "but i want to know just where we stand now i know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0007.flac", "answer": "ARE YOU GOING TO WORK ON THAT CASE COLONEL", "subset": "test_other", "task_type": "understanding", "prediction": "are you going to work on that case colonel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0049.flac", "answer": "AND YOU I DON'T WANT IT EITHER", "subset": "test_other", "task_type": "understanding", "prediction": "and you i don t want it either", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63722/6432-63722-0001.flac", "answer": "AND SHAG WITH THE FREEDOM OF AN OLD SERVANT STOOD LOOKING AT HIS MASTER AS IF NOT QUITE UNDERSTANDING THE NEW TWIST THE AFFAIRS HAD TAKEN", "subset": "test_other", "task_type": "understanding", "prediction": "and shag with the freedom of an old servant stood looking at his master as if not quite understanding the new twist the affairs had taken", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0008.flac", "answer": "YOU DON'T MEAN THAT LARCH STRUCK HER THAT THERE WAS PHYSICAL ABUSE DO YOU ASKED THE COLONEL THAT'S WHAT HE DID", "subset": "test_other", "task_type": "understanding", "prediction": "you dont mean that larch struck her that there was physical abuse do you asked the colonel thats what he did", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0011.flac", "answer": "HE REMEMBERED THAT CYNTHIA AND GRAFTON HAD ONCE BEEN IN LOVE WITH EACH OTHER", "subset": "test_other", "task_type": "understanding", "prediction": "he remembered that cynthia and grafton had once been in love with each other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0046.flac", "answer": "THERE WERE THREE OF THEM THE CENTER FIGURE BEING THAT OF HARRY KING AND HE WAS VERY MUCH INTOXICATED", "subset": "test_other", "task_type": "understanding", "prediction": "there were three of them the centre figure being that of harry king and he was very much intoxicated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0002.flac", "answer": "THE REASON SHE ASKED NO ALIMONY INQUIRED KENNETH", "subset": "test_other", "task_type": "understanding", "prediction": "the reason she asked no alimony inquired kenneth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0036.flac", "answer": "SO KING GOT BAIL WHO PUT IT UP", "subset": "test_other", "task_type": "understanding", "prediction": "so king got bail who put it up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0030.flac", "answer": "BUT IT WAS NOTICED THAT THE OLDER AND MORE CONSERVATIVE FAMILIES WERE LESS OFTEN REPRESENTED AND WHEN THEY WERE IT WAS BY SOME OF THE YOUNGER MEMBERS WHOSE REPUTATIONS WERE ALREADY SMIRCHED OR WHO HAD NOT YET ACQUIRED ANY AND WERE WILLING TO TAKE A CHANCE", "subset": "test_other", "task_type": "understanding", "prediction": "but it was noticed that the older and more conservative families were less often represented and when they were it was by some of the younger members whose reputations were already smirched or who had not yet acquired any and were willing to take a chance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0042.flac", "answer": "THANK YOU NO", "subset": "test_other", "task_type": "understanding", "prediction": "thank you no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0031.flac", "answer": "IT WOULDN'T DO YOU KNOW AFTER THAT STORY CAME OUT FOR ME AND THE VICE CHANCELLOR WHO SAT IN THE CASE AS WELL AS OTHER JUDGES AND MEMBERS OF THE BAR TO BE SEEN THERE KENNETH EXPLAINED TO THE COLONEL", "subset": "test_other", "task_type": "understanding", "prediction": "it wouldn t do you know after that story came out for me and the vice chancellor who sat in the case as well as other judges and members of the bar to be seen there kenneth explained to the colonel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0015.flac", "answer": "SO I HAD TO LET HER HAVE HER WAY AND WE DID NOT ASK THE COURT FOR MONEY THOUGH I HAD NO SUCH SQUEAMISH FEELINGS WHEN IT CAME TO MY COUNSEL FEE", "subset": "test_other", "task_type": "understanding", "prediction": "so i had to let her have her way and we did not ask the court for money though i had no such squeamish feelings when it came to my counsel fee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0003.flac", "answer": "NO I WASN'T THINKING OF THAT", "subset": "test_other", "task_type": "understanding", "prediction": "no i wasnt thinking of that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0012.flac", "answer": "SHE SAID HE HAD STRUCK HER MORE THAN ONCE AND SHE COULD STAND IT NO LONGER", "subset": "test_other", "task_type": "understanding", "prediction": "she said he had struck her more than once and she could stand it no longer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0010.flac", "answer": "AARON GRAFTON'S STATEMENT WAS BEING UNEXPECTEDLY CONFIRMED", "subset": "test_other", "task_type": "understanding", "prediction": "aaron grafton s statement was being unexpectedly confirmed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0039.flac", "answer": "BUT HIS ARE PRETTY UNCERTAIN SHOES TO BE IN JUST THE SAME", "subset": "test_other", "task_type": "understanding", "prediction": "but his are pretty uncertain shoes to be in just the same", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0004.flac", "answer": "HOWEVER DON'T THINK I'M NOT INTERESTED IN YOUR CASE I'VE FISHED ENOUGH FOR TO DAY", "subset": "test_other", "task_type": "understanding", "prediction": "however dont think i am not interested in your case i have finished enough for to day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0000.flac", "answer": "CHUCKLED THE COLONEL AS HE SKILFULLY PLAYED THE LUCKLESS TROUT NOW STRUGGLING TO GET LOOSE FROM THE HOOK", "subset": "test_other", "task_type": "understanding", "prediction": "chuckled the colonel as he skillfully played the luckless trout now struggling to get loose from the hook", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0047.flac", "answer": "THAT IS NOT ALWAYS BUT SOMETIMES IT HAPPENED TO BE SO NOW", "subset": "test_other", "task_type": "understanding", "prediction": "that is not always but sometimes it happened to be so now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0001.flac", "answer": "AND WHEN THE FISH WAS LANDED PANTING ON THE GRASS AND SHAG HAD BEEN ROUSED FROM HIS SLUMBER TO SLIP THE NOW LIMP FISH INTO THE CREEL COLONEL ASHLEY GAVE A SIGH OF RELIEF AND REMARKED I THINK I SEE IT NOW", "subset": "test_other", "task_type": "understanding", "prediction": "and when the fish was landed panting on the grass and shag had been roused from his slumber to slip the now limp fish into the creel colonel ashley gave a sigh of relief and remarked i think i see it now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0049.flac", "answer": "I SAID WHERE HAVE YOU BEEN REMARKED THE OTHER WE'VE MISSED YOU", "subset": "test_other", "task_type": "understanding", "prediction": "i said where have you been remarked the other we have missed you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0019.flac", "answer": "THE MURDER OF MISSUS DARCY HAD SOME TIME AGO BEEN SHIFTED OFF THE FRONT PAGE THOUGH IT WOULD GET BACK THERE WHEN THE YOUNG JEWELER WAS TRIED", "subset": "test_other", "task_type": "understanding", "prediction": "the murder of mrs darcy had some time ago been shifted off the front page though it would get back there when the young jeweller was tried", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0043.flac", "answer": "I'M AFRAID MY DIGESTION ISN'T QUITE UP TO THAT AS I'VE HAD TO CUT OUT MY FISHING OF LATE", "subset": "test_other", "task_type": "understanding", "prediction": "i am afraid my digestion is not quite up to that as i have had to cut out my fishing of late", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0032.flac", "answer": "MEANWHILE COLONEL ASHLEY WAS A VERY BUSY MAN AND TO NO ONE DID HE TELL VERY MUCH ABOUT HIS ACTIVITIES HE SAW DARCY FREQUENTLY AT THE JAIL AND TO THAT YOUNG MAN'S PLEADINGS THAT SOMETHING BE DONE ALWAYS RETURNED THE ANSWER", "subset": "test_other", "task_type": "understanding", "prediction": "meanwhile colonel ashley was a very busy man and to no one did he tell very much about his activities he saw darcy frequently at the jail and to that young man s pleadings that something be done always returned the answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0013.flac", "answer": "BECAUSE LARCH MADE NO DEFENSE", "subset": "test_other", "task_type": "understanding", "prediction": "because larch made no defence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0034.flac", "answer": "I'M GOING TO RECTIFY THEM BUT IT WILL TAKE TIME", "subset": "test_other", "task_type": "understanding", "prediction": "i am going to rectify them but it will take time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0035.flac", "answer": "IT'S HARD FOR MISS MASON TOO ALTHOUGH SHE'S BEARING UP LIKE A MAJOR", "subset": "test_other", "task_type": "understanding", "prediction": "its hard for miss mason too although she is bearing up like a major", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0028.flac", "answer": "AFTER THE MARRIAGE WHICH WAS A BRILLIANT AND GAY ONE IF NOT HAPPY THE LARCH HOTEL IT COULD HARDLY BE CALLED A HOME BECAME THE SCENE OF MANY FESTIVE OCCASIONS", "subset": "test_other", "task_type": "understanding", "prediction": "after the marriage which was a brilliant and gay one if not happy the large hotel it could hardly be called a home became the scene of many festive occasions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0027.flac", "answer": "SHE ALSO SAW AN OPPORTUNITY OF PAYING OLD DEBTS AND REAPING SOME REVENGES", "subset": "test_other", "task_type": "understanding", "prediction": "she also saw an opportunity of paying old debts and reaping some revenges", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0022.flac", "answer": "LARCH HIMSELF WAS A PECULIAR CHARACTER", "subset": "test_other", "task_type": "understanding", "prediction": "larch himself was a peculiar character", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0048.flac", "answer": "I BEG YOUR PARDON HE SAID IN THE CULTURED TONES HE KNEW SO WELL HOW TO USE YET OF WHICH HE MADE SO LITTLE USE OF LATE", "subset": "test_other", "task_type": "understanding", "prediction": "i beg your pardon he said in the cultured tones he knew so well how to use yet of which he made so little use of late", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0023.flac", "answer": "IN A SMALLER PLACE HE WOULD HAVE BEEN CALLED A SALOON KEEPER", "subset": "test_other", "task_type": "understanding", "prediction": "in a smaller place he would have been called a saloon keeper", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0038.flac", "answer": "THEY TOOK HARRY AWAY A WHILE AGO", "subset": "test_other", "task_type": "understanding", "prediction": "they took harry away a while ago", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0029.flac", "answer": "THEN IT WAS SAID OF LARCH THAT SOON AFTER THE ECHOES OF THE WEDDING CHIMES HAD DIED AWAY HE HAD BEGUN TO TREAT HIS WIFE WITH REFINED CRUELTY THAT HIDDEN AWAY FROM THE PUBLIC UNDERNEATH HIS HABITUAL MANNER THERE WAS THE RAWNESS OF THE BRUTE", "subset": "test_other", "task_type": "understanding", "prediction": "then it was said of larch that soon after the echoes of the wedding chimes had died away he had begun to treat his wife with a refined cruelty that hidden away from the public underneath his habitual manner there was the rawness of the brute", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0007.flac", "answer": "IT WAS ONE OF WHAT AT FIRST MIGHT BE CALLED REFINED CRUELTY ON HER HUSBAND'S PART DEGENERATING GRADUALLY INTO THAT OF THE BASER SORT", "subset": "test_other", "task_type": "understanding", "prediction": "it was one of what at first might be called refined cruelty on her husband s part degenerating gradually into that of a baser sort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0026.flac", "answer": "AND IN A WAY IT WAS TRUE", "subset": "test_other", "task_type": "understanding", "prediction": "and in a way it was true", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0009.flac", "answer": "THE COLONEL DID NOT DISCLOSE THE FACT THAT IT WAS NO NEWS TO HIM", "subset": "test_other", "task_type": "understanding", "prediction": "the colonel did not disclose the fact that it was no news to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0018.flac", "answer": "STILL I WOULD LIKE TO KNOW", "subset": "test_other", "task_type": "understanding", "prediction": "still i would like to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0054.flac", "answer": "IT'S IT'S AN ODD COIN AN OLD ROMAN ONE THAT MISSUS DARCY HAD IN HER PRIVATE COLLECTION KEPT IN THE JEWELRY STORE SAFE WAS THE WHISPERED ANSWER", "subset": "test_other", "task_type": "understanding", "prediction": "its its an odd coin an old roman one that mrs darcy had in her private collection kept in the jewelry store safe was the whispered answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0006.flac", "answer": "IT ISN'T GENERALLY KNOWN WENT ON THE LAWYER THAT THE HOTEL KEEPER'S WIFE HAS LEFT HIM", "subset": "test_other", "task_type": "understanding", "prediction": "it isn t generally known went on the lawyer that the hotel keepers wife has left him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0053.flac", "answer": "THERE WAS A RATTLE OF COINS ON THE MAHOGANY BAR AS KING SOUGHT TO DISENTANGLE A SINGLE BILL FROM THE WADDED UP CURRENCY IN HIS POCKET", "subset": "test_other", "task_type": "understanding", "prediction": "there was a rattle of coins on the mahogany bar as king sought to disentangle a single bill from the wadded up currency in his pocket", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0052.flac", "answer": "BECAUSE DEAR FRIEND REPLIED KING SOFTLY HE SOMEWHAT RESEMBLES A CERTAIN PERSON HERE WHO TALKS TOO MUCH BUT WHO IS NOT SO WISE AS HE THINKS", "subset": "test_other", "task_type": "understanding", "prediction": "because dear friend replied king softly he somewhat resembles a certain person here who talks too much but who is not so wise as he thinks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0021.flac", "answer": "GRAVE AND EVEN REVEREND CONVENTIONS ASSEMBLED IN ITS BALLROOM AND POLITICIANS OF THE UPPER IF NOT BETTER CLASS WERE FREQUENTLY SEEN IN ITS DINING ROOM OR CAFE", "subset": "test_other", "task_type": "understanding", "prediction": "grave and even reverend the conventions assembled in its ballroom and politicians of the upper if not better class were frequently seen in its dining room or cafe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0056.flac", "answer": "THAT WAS HERS WENT ON THE JEWELER", "subset": "test_other", "task_type": "understanding", "prediction": "that was hers went on the jeweler", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0024.flac", "answer": "AND IT WAS THIS MAN RICH IT WAS SAID HANDSOME CERTAINLY THAT CYNTHIA RATCHFORD HAD MARRIED", "subset": "test_other", "task_type": "understanding", "prediction": "and it was this man rich over said handsome certainly that cynthia ratchford had married", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0033.flac", "answer": "DON'T WORRY IT WILL COME OUT ALL RIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "dont worry it will come out all right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0055.flac", "answer": "I WENT OVER THEM THE OTHER DAY AND NOTICED SOME WERE MISSING THOUGH I SAW THEM ALL WHEN I PAID A VISIT TO HER JUST A SHORT TIME BEFORE SHE WAS KILLED", "subset": "test_other", "task_type": "understanding", "prediction": "i went over them near the day and noticed some were missing though i saw them all when i paid a visit to her just a short time before she was killed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0016.flac", "answer": "NO BUT HE WILL OR I'LL SUE HIM AND GET JUDGMENT OH HE'LL PAY ALL RIGHT", "subset": "test_other", "task_type": "understanding", "prediction": "no but he will or i ll sue him and get judgment oh he ll pay all right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0041.flac", "answer": "GOOD EVENING COLONEL HE CALLED GENIALLY WILL YOU JOIN ME IN A WELSH RABBIT", "subset": "test_other", "task_type": "understanding", "prediction": "good evening colonel he called genially will you join me in a welsh rabbit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0025.flac", "answer": "TO THIS WAS THE ANSWER WHISPERED MONEY", "subset": "test_other", "task_type": "understanding", "prediction": "to this was the answer whispered money", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0045.flac", "answer": "THE STOPPED CLOCKS FOR INSTANCE HAVE YOU ANY THEORY", "subset": "test_other", "task_type": "understanding", "prediction": "the stopped clocks for instance have you any theory", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0014.flac", "answer": "LARCH BY REFUSING TO APPEAR PRACTICALLY ADMITTED THE CHARGES AGAINST HIM AND DID NOT OPPOSE THE SEPARATION", "subset": "test_other", "task_type": "understanding", "prediction": "larch by refusing to appear practically admitted the charges against him and did not oppose the separation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0057.flac", "answer": "NOW HARRY KING HAS IT EXCLAIMED COLONEL ASHLEY", "subset": "test_other", "task_type": "understanding", "prediction": "now harry king has it exclaimed colonel ashley", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0040.flac", "answer": "ONLY THAT I DARCY HESITATED AND GREW RED", "subset": "test_other", "task_type": "understanding", "prediction": "only that i darcy hesitated and grew red", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0044.flac", "answer": "NOW AS TO CERTAIN MATTERS IN THE STORE ON THE MORNING OF THE MURDER", "subset": "test_other", "task_type": "understanding", "prediction": "now as to certain matters in the store on the morning of the murder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0051.flac", "answer": "WHY POLONIUS SOME ONE ASKED", "subset": "test_other", "task_type": "understanding", "prediction": "why polonius some one asked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0020.flac", "answer": "IT HAD A DOUBLE REPUTATION SO TO SPEAK", "subset": "test_other", "task_type": "understanding", "prediction": "it had a double reputation so to speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0037.flac", "answer": "IT WAS HIGH LARCH", "subset": "test_other", "task_type": "understanding", "prediction": "it was high large", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0017.flac", "answer": "AND IT TAKES ALL SORTS OF PERSONS TO MAKE IT UP", "subset": "test_other", "task_type": "understanding", "prediction": "and it takes all sorts of persons to make it up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0050.flac", "answer": "I SAID I WAS GOLFING HE WENT ON EXCEEDINGLY DISTINCTLY THOUGH WITH AN EFFORT", "subset": "test_other", "task_type": "understanding", "prediction": "i said i was golfing he went on exceedingly distinctly though with an effort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6432/63723/6432-63723-0005.flac", "answer": "WELL I DON'T KNOW THAT YOU CAN", "subset": "test_other", "task_type": "understanding", "prediction": "well i don t know that you can", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0017.flac", "answer": "THEY SAY THAT IT IS QUITE FAIR AND THAT SOWING SO MUCH RED YOU OUGHT TO REAP A LITTLE BLUE", "subset": "test_other", "task_type": "understanding", "prediction": "they say that it is quite fair and that sowing so much red you ought to reap a little blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0019.flac", "answer": "WITH YOUR TALENTS YOU WOULD MAKE YOUR FORTUNE IN THREE OR FOUR YEARS", "subset": "test_other", "task_type": "understanding", "prediction": "with your talents you would make your fortune in three or four years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0010.flac", "answer": "YES HE HAS NOT MUCH TO COMPLAIN OF BOURGES IS THE CAPITAL OF CHARLES SEVEN", "subset": "test_other", "task_type": "understanding", "prediction": "yes he has not much to complain of bourges is the capital of charles the seventh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0000.flac", "answer": "THEN SHOULD ANYTHING APPEAR TO MERIT A MORE MINUTE EXAMINATION ALBERT DE MORCERF COULD FOLLOW UP HIS RESEARCHES BY MEANS OF A SMALL GATE SIMILAR TO THAT CLOSE TO THE CONCIERGE'S DOOR AND WHICH MERITS A PARTICULAR DESCRIPTION", "subset": "test_other", "task_type": "understanding", "prediction": "then should anything appear to merit a more minute examination albert de morcerf could follow up his researches by means of a small gate similar to that close to the concierge s door and which merits a particular description", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0012.flac", "answer": "I RETURNED HOME AT DAYBREAK AND STROVE TO SLEEP BUT MY HEAD ACHED AND I GOT UP TO HAVE A RIDE FOR AN HOUR", "subset": "test_other", "task_type": "understanding", "prediction": "i returned home at daybreak and strove to sleep but my head ached and i got up to have a ride for an hour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0011.flac", "answer": "IT IS FOR THAT REASON YOU SEE ME SO EARLY", "subset": "test_other", "task_type": "understanding", "prediction": "it is for that reason you see me so early", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0013.flac", "answer": "PESTE I WILL DO NOTHING OF THE KIND THE MOMENT THEY COME FROM GOVERNMENT YOU WOULD FIND THEM EXECRABLE", "subset": "test_other", "task_type": "understanding", "prediction": "pests i will do nothing of the kind the moment they come from government you would find them execrable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0016.flac", "answer": "IN THE ENTIRE POLITICAL WORLD OF WHICH YOU ARE ONE OF THE LEADERS", "subset": "test_other", "task_type": "understanding", "prediction": "in the entire political world of which you are one of the leaders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0009.flac", "answer": "NO NO MY DEAR FELLOW DO NOT CONFOUND OUR PLANS", "subset": "test_other", "task_type": "understanding", "prediction": "no no my dear fellow do not confound our plans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0014.flac", "answer": "BESIDES THAT DOES NOT CONCERN THE HOME BUT THE FINANCIAL DEPARTMENT", "subset": "test_other", "task_type": "understanding", "prediction": "besides that does not concern the home but the financial department", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0008.flac", "answer": "YOU WHOM I EXPECTED LAST YOU ARRIVE AT FIVE MINUTES TO TEN WHEN THE TIME FIXED WAS HALF PAST", "subset": "test_other", "task_type": "understanding", "prediction": "you whom i expected last you arrive at five minutes to ten when the time fixed was half past", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0006.flac", "answer": "THE VALET LEFT THE ROOM", "subset": "test_other", "task_type": "understanding", "prediction": "the valet left the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0007.flac", "answer": "GOOD MORNING LUCIEN GOOD MORNING SAID ALBERT YOUR PUNCTUALITY REALLY ALARMS ME", "subset": "test_other", "task_type": "understanding", "prediction": "good morning lucien good morning said albert your punctuality really alarms me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0004.flac", "answer": "VERY WELL AT HALF PAST TEN", "subset": "test_other", "task_type": "understanding", "prediction": "very well at half past ten", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0005.flac", "answer": "IS THE COUNTESS UP YET", "subset": "test_other", "task_type": "understanding", "prediction": "is the countess up yet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0003.flac", "answer": "WAIT THEN DURING THE DAY TELL ROSA THAT WHEN I LEAVE THE OPERA I WILL SUP WITH HER AS SHE WISHES", "subset": "test_other", "task_type": "understanding", "prediction": "wait then during the day tell rosa that when i leave the opera i will sup with her as she wishes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0001.flac", "answer": "SHRUBS AND CREEPING PLANTS COVERED THE WINDOWS AND HID FROM THE GARDEN AND COURT THESE TWO APARTMENTS THE ONLY ROOMS INTO WHICH AS THEY WERE ON THE GROUND FLOOR THE PRYING EYES OF THE CURIOUS COULD PENETRATE", "subset": "test_other", "task_type": "understanding", "prediction": "shrubs and creeping plants covered the windows and hid from the garden and court these two apartments the only rooms into which as they were on the ground floor the prying eyes of the curious could penetrate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0015.flac", "answer": "ABOUT WHAT ABOUT THE PAPERS", "subset": "test_other", "task_type": "understanding", "prediction": "about what about the papers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0002.flac", "answer": "AT A QUARTER TO TEN A VALET ENTERED HE COMPOSED WITH A LITTLE GROOM NAMED JOHN AND WHO ONLY SPOKE ENGLISH ALL ALBERT'S ESTABLISHMENT ALTHOUGH THE COOK OF THE HOTEL WAS ALWAYS AT HIS SERVICE AND ON GREAT OCCASIONS THE COUNT'S CHASSEUR ALSO", "subset": "test_other", "task_type": "understanding", "prediction": "at a quarter to ten a valet entered he composed with a little groom named john and who only spoke english all alberts establishment although the cook of the hotel was always at his service and on great occasions the count s chasseur also", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86745/6070-86745-0018.flac", "answer": "COME COME THAT IS NOT BAD SAID LUCIEN", "subset": "test_other", "task_type": "understanding", "prediction": "come come that is not bad said lucien", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0011.flac", "answer": "WRETCH I DO NOT SEEK HIS LIFE REPLIED SARAH TO THE SCHOOLMASTER", "subset": "test_other", "task_type": "understanding", "prediction": "wretch i do not seek his life replied sarah to the schoolmaster", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0016.flac", "answer": "BETWEEN SAINT OUEN AND THE ROAD OF LA REVOLTE AT THE END OF THE ROAD AGREED", "subset": "test_other", "task_type": "understanding", "prediction": "between saint oen and the road of la rivolte at the end of the road agreed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0017.flac", "answer": "HE HAD FORGOTTEN THE ADDRESS OF THE SELF STYLED FAN PAINTER", "subset": "test_other", "task_type": "understanding", "prediction": "he had forgotten the address of the self styled fan painter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0012.flac", "answer": "LET'S GO AND MEET HIM", "subset": "test_other", "task_type": "understanding", "prediction": "lets go and meet him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0007.flac", "answer": "OH AH TO LAY A TRAP TO CATCH US REPLIED THE THIEF", "subset": "test_other", "task_type": "understanding", "prediction": "ooh aah to lay a trap to catch us replied the thief", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0000.flac", "answer": "THEY'RE DONE FOR SAID THE SCHOOLMASTER IN A LOW KEY TO THE CHOUETTE OUT WITH YOUR VITRIOL AND MIND YOUR EYE", "subset": "test_other", "task_type": "understanding", "prediction": "there dun far said the schoolmaster in a low key to the schweitz out with your vitriol and mind your eye", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0006.flac", "answer": "TOM SEYTON DID NOT LOSE HIS PRESENCE OF MIND DURING THIS SCENE RAPIDLY AND UNEXPECTEDLY AS IT HAD OCCURRED", "subset": "test_other", "task_type": "understanding", "prediction": "tom seaton did not lose his presence of mind during this scene rapidly and unexpectedly as it had occurred", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0005.flac", "answer": "NO SAID THE OLD BRUTE GRUMBLINGLY NO NOT ONE RING WHAT A SHAME", "subset": "test_other", "task_type": "understanding", "prediction": "no said the old brute grumblingly no not one ring what a shame", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0014.flac", "answer": "WELL MY WIFE SHALL BE THERE SAID THE SCHOOLMASTER YOU WILL TELL HER WHAT YOU WANT AND I SHALL SEE", "subset": "test_other", "task_type": "understanding", "prediction": "well my wife shall be there said the schoolmaster you will tell her what you want and i shall see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0010.flac", "answer": "CRIED THE SCHOOLMASTER A THOUSAND FRANCS AND I'LL KILL HIM", "subset": "test_other", "task_type": "understanding", "prediction": "cried the schoolmaster a thousand francs and i will kill him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0001.flac", "answer": "THE TWO MONSTERS TOOK OFF THEIR SHOES AND MOVED STEALTHILY ALONG KEEPING IN THE SHADOWS OF THE HOUSES", "subset": "test_other", "task_type": "understanding", "prediction": "the two monsters took off their shoes and moved stealthily along keeping in the shadows of the houses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0018.flac", "answer": "THE FIACRE STARTED", "subset": "test_other", "task_type": "understanding", "prediction": "the fiacre started", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0013.flac", "answer": "OLD BOY IT WILL PAY FOR LOOKING AFTER", "subset": "test_other", "task_type": "understanding", "prediction": "old boy it will pay for looking after", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0008.flac", "answer": "THEN ADDRESSING THOMAS SEYTON YOU KNOW THE PLAIN OF SAINT DENIS", "subset": "test_other", "task_type": "understanding", "prediction": "then addressing thomas seaton you know the plain of saint denis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0009.flac", "answer": "DID YOU SEE IN THE CABARET WE HAVE JUST LEFT FOR I KNOW YOU AGAIN THE MAN WHOM THE CHARCOAL MAN CAME TO SEEK", "subset": "test_other", "task_type": "understanding", "prediction": "did you see in the cabaret we have just left for i know you again the man whom the charcoal man came to seek", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0003.flac", "answer": "SARAH AND HER BROTHER HAVING AGAIN PASSED BY THE TAPIS FRANC ARRIVED CLOSE TO THE DILAPIDATED HOUSE WHICH WAS PARTLY IN RUINS AND ITS OPENED CELLARS FORMED A KIND OF GULF ALONG WHICH THE STREET RAN IN THAT DIRECTION", "subset": "test_other", "task_type": "understanding", "prediction": "sarah and her brother having again passed by the tapi franck arrived close to the dilapidated house which was partly in ruins and its open cellars formed a kind of gulf along which the street ran in that direction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0002.flac", "answer": "BY MEANS OF THIS STRATAGEM THEY FOLLOWED SO CLOSELY THAT ALTHOUGH WITHIN A FEW STEPS OF SARAH AND TOM THEY DID NOT HEAR THEM", "subset": "test_other", "task_type": "understanding", "prediction": "by means of this stratagem they followed so closely that although within a few steps of cyren tom they did not hear them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0015.flac", "answer": "IN THE PLAIN OF SAINT DENIS", "subset": "test_other", "task_type": "understanding", "prediction": "in the plain of saint denis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/63485/6070-63485-0004.flac", "answer": "IN AN INSTANT THE SCHOOLMASTER WITH A LEAP RESEMBLING IN STRENGTH AND AGILITY THE SPRING OF A TIGER SEIZED SEYTON WITH ONE HAND BY THE THROAT AND EXCLAIMED YOUR MONEY OR I WILL FLING YOU INTO THIS HOLE", "subset": "test_other", "task_type": "understanding", "prediction": "in an instant the schoolmaster with a leap resembling in strength and agility the spring of a tiger seized seaton with one hand by the throat and exclaimed your money or i will fling you into this hole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0003.flac", "answer": "I CAN SCARCELY CREDIT IT", "subset": "test_other", "task_type": "understanding", "prediction": "i can scarcely credit it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0012.flac", "answer": "I FEAR I SHALL NOT HAVE THAT HONOR", "subset": "test_other", "task_type": "understanding", "prediction": "i fear i shall not have that honour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0000.flac", "answer": "FRANZ WHO SEEMED ATTRACTED BY SOME INVISIBLE INFLUENCE TOWARDS THE COUNT IN WHICH TERROR WAS STRANGELY MINGLED FELT AN EXTREME RELUCTANCE TO PERMIT HIS FRIEND TO BE EXPOSED ALONE TO THE SINGULAR FASCINATION THAT THIS MYSTERIOUS PERSONAGE SEEMED TO EXERCISE OVER HIM AND THEREFORE MADE NO OBJECTION TO ALBERT'S REQUEST BUT AT ONCE ACCOMPANIED HIM TO THE DESIRED SPOT AND AFTER A SHORT DELAY THE COUNT JOINED THEM IN THE SALON", "subset": "test_other", "task_type": "understanding", "prediction": "franz who seemed attracted by some invisible influence towards the count in which terror was strangely mingled felt an extreme reluctance to permit his friend to be exposed alone to the singular fascination that this mysterious personage seemed to exercise over him and therefore made no objection to alberts request but at once accompanied him to the desired spot and after a short delay the count joined them in the salon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0018.flac", "answer": "HE DWELT WITH CONSIDERABLE FORCE AND ENERGY ON THE ALMOST MAGICAL HOSPITALITY HE HAD RECEIVED FROM THE COUNT AND THE MAGNIFICENCE OF HIS ENTERTAINMENT IN THE GROTTO OF THE THOUSAND AND ONE NIGHTS HE RECOUNTED WITH CIRCUMSTANTIAL EXACTITUDE ALL THE PARTICULARS OF THE SUPPER THE HASHISH THE STATUES THE DREAM AND HOW AT HIS AWAKENING THERE REMAINED NO PROOF OR TRACE OF ALL THESE EVENTS SAVE THE SMALL YACHT SEEN IN THE DISTANT HORIZON DRIVING UNDER FULL SAIL TOWARD PORTO VECCHIO", "subset": "test_other", "task_type": "understanding", "prediction": "he dwelt with considerable force and energy on the almost magical hospitality he had received from the count and the magnificence of his entertainment in the grotto of the thousand and one nights he recounted with circumstantial exactitude all the particulars of the supper the hashish the statues the dream and how at his awakening there remained no proof or trace of all these events save the small yacht seen in the distant horizon driving under full sail toward port au vecchio", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0029.flac", "answer": "AND NOW MY DEAR FRANZ LET US TALK OF SOMETHING ELSE", "subset": "test_other", "task_type": "understanding", "prediction": "and now my dear franz let us talk of something else", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0006.flac", "answer": "SO BE IT THEN REPLIED THE COUNT AND EXTENDING HIS HAND TOWARDS A CALENDAR SUSPENDED NEAR THE CHIMNEY PIECE HE SAID TO DAY IS THE TWENTY FIRST OF FEBRUARY AND DRAWING OUT HIS WATCH ADDED IT IS EXACTLY HALF PAST TEN O'CLOCK NOW PROMISE ME TO REMEMBER THIS AND EXPECT ME THE TWENTY FIRST OF MAY AT THE SAME HOUR IN THE FORENOON", "subset": "test_other", "task_type": "understanding", "prediction": "so be it then replied the count and extending his hand towards a calendar suspended near the chimney piece he said to day is the twenty first of february and drawing out his watch added it is exactly half past ten o clock now promise me to remember this and expect me the twenty first of may at the same hour in the forenoon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0001.flac", "answer": "MY VERY GOOD FRIEND AND EXCELLENT NEIGHBOR REPLIED THE COUNT WITH A SMILE YOU REALLY EXAGGERATE MY TRIFLING EXERTIONS", "subset": "test_other", "task_type": "understanding", "prediction": "my very good friend and excellent neighbor replied the count with a smile you really exaggerate my trifling exertions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0027.flac", "answer": "AND THIS TIME IT MUST BE CONFESSED THAT CONTRARY TO THE USUAL STATE OF AFFAIRS IN DISCUSSIONS BETWEEN THE YOUNG MEN THE EFFECTIVE ARGUMENTS WERE ALL ON ALBERT'S SIDE", "subset": "test_other", "task_type": "understanding", "prediction": "and this time it must be confessed that contrary to the usual state of affairs in discussions between the young man the effective arguments were all on alberts side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0008.flac", "answer": "NOW THEN SAID THE COUNT RETURNING HIS TABLETS TO HIS POCKET MAKE YOURSELF PERFECTLY EASY THE HAND OF YOUR TIME PIECE WILL NOT BE MORE ACCURATE IN MARKING THE TIME THAN MYSELF", "subset": "test_other", "task_type": "understanding", "prediction": "now then said the count returning his tablets to his pocket make yourself perfectly easy the hand of your timepiece will not be more accurate in marking the time than myself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0002.flac", "answer": "MY FATHER THE COMTE DE MORCERF ALTHOUGH OF SPANISH ORIGIN POSSESSES CONSIDERABLE INFLUENCE BOTH AT THE COURT OF FRANCE AND MADRID AND I UNHESITATINGLY PLACE THE BEST SERVICES OF MYSELF AND ALL TO WHOM MY LIFE IS DEAR AT YOUR DISPOSAL", "subset": "test_other", "task_type": "understanding", "prediction": "my father the comte de morcerf although of spanish origin possesses considerable influence both at the court of france and madrid and i unhesitatingly place the best services of myself and all to whom my life is dear at your disposal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0016.flac", "answer": "DID YOU EVER MEET HIM PREVIOUSLY TO COMING HITHER", "subset": "test_other", "task_type": "understanding", "prediction": "did you ever meet him previously to coming hither", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0009.flac", "answer": "THAT DEPENDS WHEN DO YOU LEAVE", "subset": "test_other", "task_type": "understanding", "prediction": "that depends when do you leave", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0024.flac", "answer": "MY DEAR FRANZ REPLIED ALBERT WHEN UPON RECEIPT OF MY LETTER YOU FOUND THE NECESSITY OF ASKING THE COUNT'S ASSISTANCE YOU PROMPTLY WENT TO HIM SAYING MY FRIEND ALBERT DE MORCERF IS IN DANGER HELP ME TO DELIVER HIM", "subset": "test_other", "task_type": "understanding", "prediction": "my dear franz replied albert when upon receipt of my letter you found the necessity of asking the count s assistance you promptly went to him saying my friend albert de morcerf is in danger help me to deliver him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0010.flac", "answer": "FOR FRANCE NO FOR VENICE I SHALL REMAIN IN ITALY FOR ANOTHER YEAR OR TWO", "subset": "test_other", "task_type": "understanding", "prediction": "for france no for venice i shall remain in italy for another year or two", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0023.flac", "answer": "CERTAINLY THESE ARE QUESTIONS THAT IN YOUR PLACE I SHOULD LIKE TO HAVE ANSWERED", "subset": "test_other", "task_type": "understanding", "prediction": "certainly these are questions that in your place i should like to have answered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0004.flac", "answer": "THEN IT IS SETTLED SAID THE COUNT AND I GIVE YOU MY SOLEMN ASSURANCE THAT I ONLY WAITED AN OPPORTUNITY LIKE THE PRESENT TO REALIZE PLANS THAT I HAVE LONG MEDITATED", "subset": "test_other", "task_type": "understanding", "prediction": "then it is settled said the count and i give you my solemn assurance that i only waited an opportunity like the present to realize plans that i have long meditated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0025.flac", "answer": "WHAT ARE HIS MEANS OF EXISTENCE WHAT IS HIS BIRTHPLACE OF WHAT COUNTRY IS HE A NATIVE", "subset": "test_other", "task_type": "understanding", "prediction": "what are his means of existence what is his birthplace of what country is he a native", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0017.flac", "answer": "UPON MY HONOR THEN LISTEN TO ME", "subset": "test_other", "task_type": "understanding", "prediction": "upon my honor then listen to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0015.flac", "answer": "I WILL CONFESS TO YOU ALBERT REPLIED FRANZ THE COUNT IS A VERY SINGULAR PERSON AND THE APPOINTMENT YOU HAVE MADE TO MEET HIM IN PARIS FILLS ME WITH A THOUSAND APPREHENSIONS", "subset": "test_other", "task_type": "understanding", "prediction": "i will confess to you albert replied franz the count is a very singular person and the appointment you have made to meet him in paris fills me with a thousand apprehensions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0007.flac", "answer": "I RESIDE IN MY FATHER'S HOUSE BUT OCCUPY A PAVILION AT THE FARTHER SIDE OF THE COURT YARD ENTIRELY SEPARATED FROM THE MAIN BUILDING", "subset": "test_other", "task_type": "understanding", "prediction": "i reside in my father s house but occupy a pavilion at the farther side of the courtyard and tightly separated from the main building", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0013.flac", "answer": "WELL SINCE WE MUST PART SAID THE COUNT HOLDING OUT A HAND TO EACH OF THE YOUNG MEN ALLOW ME TO WISH YOU BOTH A SAFE AND PLEASANT JOURNEY", "subset": "test_other", "task_type": "understanding", "prediction": "well since we must part said the count holding out a hand to each of the young men allow me to wish you both a safe and pleasant journey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0019.flac", "answer": "THEN HE DETAILED THE CONVERSATION OVERHEARD BY HIM AT THE COLOSSEUM BETWEEN THE COUNT AND VAMPA IN WHICH THE COUNT HAD PROMISED TO OBTAIN THE RELEASE OF THE BANDIT PEPPINO AN ENGAGEMENT WHICH AS OUR READERS ARE AWARE HE MOST FAITHFULLY FULFILLED", "subset": "test_other", "task_type": "understanding", "prediction": "then he detailed the conversation overheard by him at the coliseum between the count and vampa in which the count had promised to obtain the release of the bandit peppino an engagement which as our readers are aware he most faithfully fulfilled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0028.flac", "answer": "WELL SAID FRANZ WITH A SIGH DO AS YOU PLEASE MY DEAR VISCOUNT FOR YOUR ARGUMENTS ARE BEYOND MY POWERS OF REFUTATION", "subset": "test_other", "task_type": "understanding", "prediction": "well said franz with a sigh do as you please my dear viscount for your arguments are beyond my powers of refutation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0011.flac", "answer": "THEN WE SHALL NOT MEET IN PARIS", "subset": "test_other", "task_type": "understanding", "prediction": "then we shall not meet in paris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0014.flac", "answer": "WHAT IS THE MATTER ASKED ALBERT OF FRANZ WHEN THEY HAD RETURNED TO THEIR OWN APARTMENTS YOU SEEM MORE THAN COMMONLY THOUGHTFUL", "subset": "test_other", "task_type": "understanding", "prediction": "what is the matter asked albert of franz when they had returned to their own apartments you seem more than commonly thoughtful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0020.flac", "answer": "BUT SAID FRANZ THE CORSICAN BANDITS THAT WERE AMONG THE CREW OF HIS VESSEL", "subset": "test_other", "task_type": "understanding", "prediction": "but said franz the corsican bandits that were among the crew of his vessel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0022.flac", "answer": "TALKING OF COUNTRIES REPLIED FRANZ OF WHAT COUNTRY IS THE COUNT WHAT IS HIS NATIVE TONGUE WHENCE DOES HE DERIVE HIS IMMENSE FORTUNE AND WHAT WERE THOSE EVENTS OF HIS EARLY LIFE A LIFE AS MARVELLOUS AS UNKNOWN THAT HAVE TINCTURED HIS SUCCEEDING YEARS WITH SO DARK AND GLOOMY A MISANTHROPY", "subset": "test_other", "task_type": "understanding", "prediction": "talking of countries replied franz of what countries the count what is his native tongue whence does he derive his immense fortune and what were those events of his early life a life as marvellous as unknown that hath tinctured his succeeding years with so dark and gloomy a misanthropy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0026.flac", "answer": "I CONFESS HE ASKED ME NONE NO HE MERELY CAME AND FREED ME FROM THE HANDS OF SIGNOR VAMPA WHERE I CAN ASSURE YOU IN SPITE OF ALL MY OUTWARD APPEARANCE OF EASE AND UNCONCERN I DID NOT VERY PARTICULARLY CARE TO REMAIN", "subset": "test_other", "task_type": "understanding", "prediction": "i confess he asked me none no he merely came and freed me from the hands of signor vampa where i can assure you in spite of all my outward appearance of ease and unconcern i did not very particularly care to remain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0005.flac", "answer": "SHALL WE MAKE A POSITIVE APPOINTMENT FOR A PARTICULAR DAY AND HOUR INQUIRED THE COUNT ONLY LET ME WARN YOU THAT I AM PROVERBIAL FOR MY PUNCTILIOUS EXACTITUDE IN KEEPING MY ENGAGEMENTS DAY FOR DAY HOUR FOR HOUR SAID ALBERT THAT WILL SUIT ME TO A DOT", "subset": "test_other", "task_type": "understanding", "prediction": "shall we make a positive appointment for a particular day and hour inquired the count only let me warn you that i am proverbial for my punctilious exactitude in keeping my engagements day for day hour for hour said albert that will suit me to a dot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/6070/86744/6070-86744-0021.flac", "answer": "WHY REALLY THE THING SEEMS TO ME SIMPLE ENOUGH", "subset": "test_other", "task_type": "understanding", "prediction": "why really the thing seems to me simple enough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0012.flac", "answer": "IS IT FAIR THAT HE SHOULD DO SO OR NOT", "subset": "test_other", "task_type": "understanding", "prediction": "is it fair that he should do so or not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0005.flac", "answer": "SO THE BRAHMAN AND THE TIGER WALKED ON TILL THEY CAME TO A BANYAN TREE AND THE BRAHMAN SAID TO IT BANYAN TREE BANYAN TREE HEAR AND GIVE JUDGMENT", "subset": "test_other", "task_type": "understanding", "prediction": "so the brahmin and the tiger walked on till they came to a banyan tree and the brahmin said to it banyan tree banyan tree hear and give judgment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0011.flac", "answer": "AT A LITTLE DISTANCE THEY FOUND A BULLOCK LYING BY THE ROADSIDE", "subset": "test_other", "task_type": "understanding", "prediction": "at a little distance they found a bullock lying by the roadside", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0029.flac", "answer": "VERY GOOD SAID THE JACKAL BUT I CANNOT JUDGE WITHOUT UNDERSTANDING THE WHOLE MATTER EXACTLY", "subset": "test_other", "task_type": "understanding", "prediction": "very good said the jackal but i cannot judge without understanding the whole matter exactly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0030.flac", "answer": "SHUT AND BOLTED SAID THE BRAHMAN", "subset": "test_other", "task_type": "understanding", "prediction": "shut and bolted said the brahmin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0027.flac", "answer": "WHERE WAS THE TIGER THEN", "subset": "test_other", "task_type": "understanding", "prediction": "where was the tiger then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0013.flac", "answer": "LET THE TIGER EAT THE MAN FOR MEN HAVE NO PITY", "subset": "test_other", "task_type": "understanding", "prediction": "let the tiger eat the man for men have no pity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0031.flac", "answer": "THEN SHUT AND BOLT IT SAID THE JACKAL", "subset": "test_other", "task_type": "understanding", "prediction": "then shut and bolt it said the jackal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0035.flac", "answer": "YOUR ROAD LIES THAT WAY AND MINE THIS", "subset": "test_other", "task_type": "understanding", "prediction": "your road lies that way and mine this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0019.flac", "answer": "BUT THE ALLIGATOR SAID WHENEVER I PUT MY NOSE OUT OF THE WATER MEN TORMENT ME AND TRY TO KILL ME", "subset": "test_other", "task_type": "understanding", "prediction": "but the alligator said whenever i put my nose out of the water men torment me and try to kill me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0026.flac", "answer": "EXACTLY HERE REPLIED THE BRAHMAN", "subset": "test_other", "task_type": "understanding", "prediction": "exactly here replied the brahmin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0032.flac", "answer": "WHEN THE BRAHMAN HAD DONE THIS THE JACKAL SAID OH YOU WICKED AND UNGRATEFUL TIGER", "subset": "test_other", "task_type": "understanding", "prediction": "when the brahmin had done this the jackal said oh you wicked and ungrateful tiger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0009.flac", "answer": "LET THE TIGER EAT THE MAN FOR MEN ARE AN UNGRATEFUL RACE", "subset": "test_other", "task_type": "understanding", "prediction": "let the tiger eat the man for men are an ungrateful race", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0034.flac", "answer": "PROCEED ON YOUR JOURNEY FRIEND BRAHMAN", "subset": "test_other", "task_type": "understanding", "prediction": "proceed on your journey friend ramen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0010.flac", "answer": "SIR CAMEL SIR CAMEL CRIED THE BRAHMAN HEAR AND GIVE JUDGMENT", "subset": "test_other", "task_type": "understanding", "prediction": "sir camel sir camel cried the brahmin hear and give judgment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0028.flac", "answer": "WHY I STOOD SO SAID THE TIGER JUMPING INTO THE CAGE AND MY HEAD WAS ON THIS SIDE", "subset": "test_other", "task_type": "understanding", "prediction": "why i stood so said the tiger jumping into the cage and my head was on this side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0018.flac", "answer": "AFTER THIS THEY SAW AN ALLIGATOR AND THE BRAHMAN RELATED THE MATTER TO HIM HOPING FOR A MORE FAVORABLE VERDICT", "subset": "test_other", "task_type": "understanding", "prediction": "after this they saw an alligator and the brahman related the matter to him hoping for a more favourable verdict", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0020.flac", "answer": "THE BRAHMAN GAVE HIMSELF UP AS LOST BUT AGAIN HE PRAYED THE TIGER TO HAVE PATIENCE AND LET HIM ASK THE OPINION OF THE SIXTH JUDGE", "subset": "test_other", "task_type": "understanding", "prediction": "the brahman gave himself up as lost but again he prayed the tiger to have patience and let him ask the opinion of the sixth judge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0014.flac", "answer": "THREE OUT OF THE SIX HAD GIVEN JUDGMENT AGAINST THE BRAHMAN BUT STILL HE DID NOT LOSE ALL HOPE AND DETERMINED TO ASK THE OTHER THREE", "subset": "test_other", "task_type": "understanding", "prediction": "three out of the six had given judgment against the brahmin but still he did not lose all hope and determined to ask the other three", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0022.flac", "answer": "THE BRAHMAN TOLD HIS STORY AND SAID TO HIM UNCLE JACKAL UNCLE JACKAL SAY WHAT IS YOUR JUDGMENT", "subset": "test_other", "task_type": "understanding", "prediction": "the brahmin told his story and said to him uncle jackal uncle jackal say what is your judgment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0016.flac", "answer": "THE BRAHMAN STATED THE CASE AND THE EAGLE ANSWERED WHENEVER MEN SEE ME THEY TRY TO SHOOT ME THEY CLIMB THE ROCKS AND STEAL AWAY MY LITTLE ONES", "subset": "test_other", "task_type": "understanding", "prediction": "the brahman stated the case and the eagle answered whenever men see me they try to shoot me they climb the rocks and steal away my little ones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0024.flac", "answer": "WHEN THEY GOT THERE THE JACKAL SAID NOW BRAHMAN SHOW ME EXACTLY WHERE YOU STOOD", "subset": "test_other", "task_type": "understanding", "prediction": "and the guard there the jackal said now brahmin show me exactly where you stood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0000.flac", "answer": "ONCE UPON A TIME A BRAHMAN WHO WAS WALKING ALONG THE ROAD CAME UPON AN IRON CAGE IN WHICH A GREAT TIGER HAD BEEN SHUT UP BY THE VILLAGERS WHO CAUGHT HIM", "subset": "test_other", "task_type": "understanding", "prediction": "once upon a time a brahmin who was walking along the road came upon an iron cage in which a great tiger had been shut up by the villagers who caught him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0001.flac", "answer": "THE BRAHMAN ANSWERED NO I WILL NOT FOR IF I LET YOU OUT OF THE CAGE YOU WILL EAT ME", "subset": "test_other", "task_type": "understanding", "prediction": "the brahmin answered no avil lot for if i let you out of the cage you will eat me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0008.flac", "answer": "IS IT JUST THAT HE SHOULD DO SO OR NO", "subset": "test_other", "task_type": "understanding", "prediction": "it is just that he should do so i know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0007.flac", "answer": "THIS TIGER SAID THE BRAHMAN BEGGED ME TO LET HIM OUT OF HIS CAGE TO DRINK A LITTLE WATER AND HE PROMISED NOT TO HURT ME IF I DID SO BUT NOW THAT I HAVE LET HIM OUT HE WISHES TO EAT ME", "subset": "test_other", "task_type": "understanding", "prediction": "this tiger said the brahmin begged me to let him out of his cage to drink a little water and he promised not to hurt me if i did so but now that i have let him out he wishes to eat me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0015.flac", "answer": "ON WHAT MUST I GIVE JUDGMENT ASKED THE EAGLE", "subset": "test_other", "task_type": "understanding", "prediction": "on what must i give judgment asked the eagle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0025.flac", "answer": "EXACTLY THERE WAS IT ASKED THE JACKAL", "subset": "test_other", "task_type": "understanding", "prediction": "exactly there was it asked the jackal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0006.flac", "answer": "ON WHAT MUST I GIVE JUDGMENT ASKED THE BANYAN TREE", "subset": "test_other", "task_type": "understanding", "prediction": "on what must i give judgment asked the bent tree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0017.flac", "answer": "THEN THE TIGER BEGAN TO ROAR AND SAID THE JUDGMENT OF ALL IS AGAINST YOU O BRAHMAN", "subset": "test_other", "task_type": "understanding", "prediction": "then the tiger began to roar and said judgment of all is against you o brahman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0004.flac", "answer": "THEN THE BRAHMAN TOOK PITY ON HIM AND OPENED THE CAGE DOOR BUT NO SOONER HAD HE DONE SO THAN THE TIGER JUMPING OUT SAID NOW I WILL EAT YOU FIRST AND DRINK THE WATER AFTERWARDS", "subset": "test_other", "task_type": "understanding", "prediction": "then the brahmin took pity on him and opened the cage door but no sooner had he done so than the tiger jumping out said now i will eat you first and drink the water afterwards", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0003.flac", "answer": "I WILL NEVER BE SO UNGRATEFUL ONLY LET ME OUT THAT I MAY DRINK SOME WATER AND RETURN", "subset": "test_other", "task_type": "understanding", "prediction": "i will never be so ungrateful only let me out that i may drink some water and return", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0021.flac", "answer": "NOW THE SIXTH WAS A JACKAL", "subset": "test_other", "task_type": "understanding", "prediction": "and the sixth was a jackal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0033.flac", "answer": "WHEN THE GOOD BRAHMAN OPENED YOUR CAGE DOOR IS TO EAT HIM THE ONLY RETURN YOU WOULD MAKE", "subset": "test_other", "task_type": "understanding", "prediction": "when a good brahmin opened your cage door is to eat him the only return you would make", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0002.flac", "answer": "OH FATHER OF MERCY ANSWERED THE TIGER IN TRUTH THAT I WILL NOT", "subset": "test_other", "task_type": "understanding", "prediction": "o father of mercy answered the tiger in truth that i will not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/159411/2414-159411-0023.flac", "answer": "SHOW ME THE PLACE", "subset": "test_other", "task_type": "understanding", "prediction": "show me the place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0014.flac", "answer": "O EARTH THOU HAST BECOME TOO ROUND FOR ME", "subset": "test_other", "task_type": "understanding", "prediction": "o earth thou hast become too round for me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0027.flac", "answer": "THEY SLEEP QUIETLY THEY ENJOY THEIR NEW SECURITY", "subset": "test_other", "task_type": "understanding", "prediction": "they sleep quietly they enjoy their new security", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0018.flac", "answer": "THEN ONLY DID I HIT THE TRUTH", "subset": "test_other", "task_type": "understanding", "prediction": "then only did i hit that truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0006.flac", "answer": "NOW DO I HEAR SIX OLD FOOLS LEGS RATTLING BEHIND ONE ANOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "now do i hear six old fools legs rattling behind one another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0000.flac", "answer": "WHITHER HATH MY LONESOMENESS GONE SPAKE HE", "subset": "test_other", "task_type": "understanding", "prediction": "whither hath my lonesomeness gone spake he", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0028.flac", "answer": "BEWARE LEST IN THE END A NARROW FAITH CAPTURE THEE A HARD RIGOROUS DELUSION", "subset": "test_other", "task_type": "understanding", "prediction": "beware lest in the end a narrow fate capture thee a hard rigorous delusion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0008.flac", "answer": "ALSO METHINKETH THAT AFTER ALL IT HATH LONGER LEGS THAN MINE", "subset": "test_other", "task_type": "understanding", "prediction": "also me thinketh that after all it hath longer lees than mine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0026.flac", "answer": "THY DANGER IS NOT SMALL THOU FREE SPIRIT AND WANDERER", "subset": "test_other", "task_type": "understanding", "prediction": "thy danger is not small thou free spirit and wanderer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0001.flac", "answer": "MY SHADOW CALLETH ME", "subset": "test_other", "task_type": "understanding", "prediction": "my shadow calleth me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0012.flac", "answer": "THOU ART NOT PLEASING UNTO ME", "subset": "test_other", "task_type": "understanding", "prediction": "thou art not pleasing unto me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0010.flac", "answer": "ASKED ZARATHUSTRA VEHEMENTLY WHAT DOEST THOU HERE", "subset": "test_other", "task_type": "understanding", "prediction": "asked the twister vehemently what doest thou here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0005.flac", "answer": "VERILY MY FOLLY HATH GROWN BIG IN THE MOUNTAINS", "subset": "test_other", "task_type": "understanding", "prediction": "verily my folly hath grown big in the mountains", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0030.flac", "answer": "THOU HAST LOST THY GOAL", "subset": "test_other", "task_type": "understanding", "prediction": "thou hast lost thy gold", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0025.flac", "answer": "SAID HE AT LAST SADLY", "subset": "test_other", "task_type": "understanding", "prediction": "said he at last sadly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0017.flac", "answer": "SOMETIMES I MEANT TO LIE AND BEHOLD", "subset": "test_other", "task_type": "understanding", "prediction": "sometimes i meant to lie and behold", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0013.flac", "answer": "MUST I EVER BE ON THE WAY", "subset": "test_other", "task_type": "understanding", "prediction": "must i ever be on the way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0002.flac", "answer": "WHAT MATTER ABOUT MY SHADOW", "subset": "test_other", "task_type": "understanding", "prediction": "what matter about my shadow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0007.flac", "answer": "BUT DOTH ZARATHUSTRA NEED TO BE FRIGHTENED BY HIS SHADOW", "subset": "test_other", "task_type": "understanding", "prediction": "by dods zartustra need to be frightened by his shadow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0009.flac", "answer": "FOR WHEN ZARATHUSTRA SCRUTINISED HIM WITH HIS GLANCE HE WAS FRIGHTENED AS BY A SUDDEN APPARITION SO SLENDER SWARTHY HOLLOW AND WORN OUT DID THIS FOLLOWER APPEAR", "subset": "test_other", "task_type": "understanding", "prediction": "who when there to his dress scrutinized him with his glance he was frighted as by a sudden apparition so slender swarthy hollow and worn out did his follower appear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0003.flac", "answer": "LET IT RUN AFTER ME I RUN AWAY FROM IT", "subset": "test_other", "task_type": "understanding", "prediction": "let it run after me i run away from it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0020.flac", "answer": "HAVE I STILL A GOAL", "subset": "test_other", "task_type": "understanding", "prediction": "have i still a goal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0023.flac", "answer": "O ETERNAL EVERYWHERE O ETERNAL NOWHERE O ETERNAL IN VAIN", "subset": "test_other", "task_type": "understanding", "prediction": "o eternal everywhere o eternal nowhere o eternal in vain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0024.flac", "answer": "THOU ART MY SHADOW", "subset": "test_other", "task_type": "understanding", "prediction": "thou art my shadow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0021.flac", "answer": "A HAVEN TOWARDS WHICH MY SAIL IS SET", "subset": "test_other", "task_type": "understanding", "prediction": "a haven towards which my sail is set", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0019.flac", "answer": "HOW HAVE I STILL INCLINATION", "subset": "test_other", "task_type": "understanding", "prediction": "how have i still inclinations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0031.flac", "answer": "THOU POOR ROVER AND RAMBLER THOU TIRED BUTTERFLY", "subset": "test_other", "task_type": "understanding", "prediction": "thou poor rover and rambler thou tired butterfly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0004.flac", "answer": "THUS SPAKE ZARATHUSTRA TO HIS HEART AND RAN AWAY", "subset": "test_other", "task_type": "understanding", "prediction": "thus pegs her two strides to his heart and ran away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0016.flac", "answer": "THE DEVIL HIMSELF IS PERHAPS SKIN", "subset": "test_other", "task_type": "understanding", "prediction": "the devil himself is perhaps skin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0011.flac", "answer": "AND WHY CALLEST THOU THYSELF MY SHADOW", "subset": "test_other", "task_type": "understanding", "prediction": "and why callest thou thyself my shadow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0032.flac", "answer": "WILT THOU HAVE A REST AND A HOME THIS EVENING", "subset": "test_other", "task_type": "understanding", "prediction": "wilt thou have a rest and a home this evening", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0029.flac", "answer": "FOR NOW EVERYTHING THAT IS NARROW AND FIXED SEDUCETH AND TEMPTETH THEE", "subset": "test_other", "task_type": "understanding", "prediction": "for now everything that is narrow and fixed seduceth and tempteth thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0022.flac", "answer": "FOR IT DO I ASK AND SEEK AND HAVE SOUGHT BUT HAVE NOT FOUND IT", "subset": "test_other", "task_type": "understanding", "prediction": "for it too i ask and seek and have sought but have not found it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128292/2414-128292-0015.flac", "answer": "WHEN THE DEVIL CASTETH HIS SKIN DOTH NOT HIS NAME ALSO FALL AWAY IT IS ALSO SKIN", "subset": "test_other", "task_type": "understanding", "prediction": "when the devil casteth his skin doth not his name also fall away it is also skinned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/165385/2414-165385-0000.flac", "answer": "THUS ACCOMPLISHED HE EXCITED THE ADMIRATION OF EVERY SILLY COQUETTE AND THE ENVY OF EVERY FLUTTERING COXCOMB BUT BY ALL YOUNG GENTLEMEN AND LADIES OF UNDERSTANDING HE WAS HEARTILY DESPISED AS A MERE CIVILIZED MONKEY", "subset": "test_other", "task_type": "understanding", "prediction": "thus accomplished he excited the admiration of every silly coquette and the envy of every flattering coxcomb but by all young gentlemen and ladies of understanding he was heartily despised as a mere civilized monkey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/165385/2414-165385-0001.flac", "answer": "THAT HIS SOUL MIGHT AFTERWARDS OCCUPY SUCH A STATION AS WOULD BE MOST SUITABLE TO HIS CHARACTER IT WAS SENTENCED TO INHABIT THE BODY OF THAT FINICAL GRINNING AND MISCHIEVOUS LITTLE MIMICK WITH FOUR LEGS WHICH YOU NOW BEHOLD BEFORE YOU", "subset": "test_other", "task_type": "understanding", "prediction": "that his soul might afterwards occupy such a station as would be most suitable to his character it was sentenced to inhabit the body of that finical grinning and mischievous little mimic with four legs which you now behold before you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0015.flac", "answer": "ANSWERED THE OTHER", "subset": "test_other", "task_type": "understanding", "prediction": "answered the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0009.flac", "answer": "BUT BEHOLD THESE KINE", "subset": "test_other", "task_type": "understanding", "prediction": "but behold these kinds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0023.flac", "answer": "NOW HOWEVER TAKE LEAVE AT ONCE OF THY KINE THOU STRANGE ONE", "subset": "test_other", "task_type": "understanding", "prediction": "now however take leave it was of their kind thou strange one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0002.flac", "answer": "WHEN HOWEVER ZARATHUSTRA WAS QUITE NIGH UNTO THEM THEN DID HE HEAR PLAINLY THAT A HUMAN VOICE SPAKE IN THE MIDST OF THE KINE AND APPARENTLY ALL OF THEM HAD TURNED THEIR HEADS TOWARDS THE SPEAKER", "subset": "test_other", "task_type": "understanding", "prediction": "when however zarathustra was quite nigh unto them then did he hear plainly that human voice spake in the midst of the kine and apparently all of them had turned their heads towards the speaker", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0008.flac", "answer": "THOU ALSO THOU ALSO", "subset": "test_other", "task_type": "understanding", "prediction": "thou also thou also", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0013.flac", "answer": "THE KINGDOM OF HEAVEN HOWEVER IS WITH THE KINE AND WHY IS IT NOT WITH THE RICH", "subset": "test_other", "task_type": "understanding", "prediction": "the kingdom of heaven however is with the kind and why is it not with the rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0025.flac", "answer": "FOR THEY ARE THY WARMEST FRIENDS AND PRECEPTORS", "subset": "test_other", "task_type": "understanding", "prediction": "for they are thy warmest friends and preceptors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0003.flac", "answer": "WHAT DO I HERE SEEK", "subset": "test_other", "task_type": "understanding", "prediction": "what do i here seek", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0022.flac", "answer": "AND TALK TO MINE ANIMALS OF THE HAPPINESS OF ANIMALS", "subset": "test_other", "task_type": "understanding", "prediction": "and talk to mine animals of the happiness of animals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0016.flac", "answer": "THOU KNOWEST IT THYSELF BETTER EVEN THAN I", "subset": "test_other", "task_type": "understanding", "prediction": "thou knowest it thyself better even than i", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0024.flac", "answer": "THOU AMIABLE ONE", "subset": "test_other", "task_type": "understanding", "prediction": "thou amiable one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0001.flac", "answer": "HE ASKED HIMSELF SOMETHING WARM AND LIVING QUICKENETH ME IT MUST BE IN THE NEIGHBOURHOOD", "subset": "test_other", "task_type": "understanding", "prediction": "he asked himself something warm and living quickeneth me it must be in thy neighbourhood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0021.flac", "answer": "SAID ZARATHUSTRA THOU SHOULDST ALSO SEE MINE ANIMALS MINE EAGLE AND MY SERPENT THEIR LIKE DO NOT AT PRESENT EXIST ON EARTH", "subset": "test_other", "task_type": "understanding", "prediction": "cesare aegyptiorum thou shouldst also see mine animals my eagle and my serpent their like do not at present exist on earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0014.flac", "answer": "WHY DOST THOU TEMPT ME", "subset": "test_other", "task_type": "understanding", "prediction": "why thou dost thou tempt me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0010.flac", "answer": "THE KINE HOWEVER GAZED AT IT ALL AND WONDERED", "subset": "test_other", "task_type": "understanding", "prediction": "the kind however gazed at it all and wondered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0004.flac", "answer": "ANSWERED HE THE SAME THAT THOU SEEKEST THOU MISCHIEF MAKER THAT IS TO SAY HAPPINESS UPON EARTH", "subset": "test_other", "task_type": "understanding", "prediction": "answered he the same that thou seekest thou mischief maker that is to say happiness upon earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0007.flac", "answer": "WHO HATH NOT AT PRESENT HIS HEART HIS MOUTH AND HIS EYES FULL OF DISGUST", "subset": "test_other", "task_type": "understanding", "prediction": "who had not at present his heart his mouth and his eyes full of disgust", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0000.flac", "answer": "WHAT HATH HAPPENED UNTO ME", "subset": "test_other", "task_type": "understanding", "prediction": "what hath happened to me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0012.flac", "answer": "IT IS NO LONGER TRUE THAT THE POOR ARE BLESSED", "subset": "test_other", "task_type": "understanding", "prediction": "it is no longer true that the poor are blessed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0026.flac", "answer": "THOU EVIL FLATTERER", "subset": "test_other", "task_type": "understanding", "prediction": "thou eatest slater", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0006.flac", "answer": "HE WOULD NOT BE RID OF HIS AFFLICTION", "subset": "test_other", "task_type": "understanding", "prediction": "he would not be rid of his affliction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0020.flac", "answer": "WELL", "subset": "test_other", "task_type": "understanding", "prediction": "well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0011.flac", "answer": "WANTON AVIDITY BILIOUS ENVY CAREWORN REVENGE POPULACE PRIDE ALL THESE STRUCK MINE EYE", "subset": "test_other", "task_type": "understanding", "prediction": "wanton avidity bilious envy careworn revenge populous pride all these struck my eye", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0017.flac", "answer": "THUS SPAKE THE PEACEFUL ONE AND PUFFED HIMSELF AND PERSPIRED WITH HIS WORDS SO THAT THE KINE WONDERED ANEW", "subset": "test_other", "task_type": "understanding", "prediction": "thus spake the peaceful one and puffed himself and perspired with his words so that the kind one dude anew", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0005.flac", "answer": "FOR I TELL THEE THAT I HAVE ALREADY TALKED HALF A MORNING UNTO THEM AND JUST NOW WERE THEY ABOUT TO GIVE ME THEIR ANSWER", "subset": "test_other", "task_type": "understanding", "prediction": "for i tell thee it i have alreadie talkt halfe a morning unto them and just now were they about to give me their answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0018.flac", "answer": "THOU DOEST VIOLENCE TO THYSELF THOU PREACHER ON THE MOUNT WHEN THOU USEST SUCH SEVERE WORDS", "subset": "test_other", "task_type": "understanding", "prediction": "thou doest woe to thyself thou preacher on the mount and thou usest such severe words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/2414/128291/2414-128291-0019.flac", "answer": "THEY ALSO ABSTAIN FROM ALL HEAVY THOUGHTS WHICH INFLATE THE HEART", "subset": "test_other", "task_type": "understanding", "prediction": "they also abstain from all heavy thoughts which inflate the heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0018.flac", "answer": "AH WELL IN THAT CASE TO BE SURE LET THEM GO ONLY THOSE GERMAN QUACKS ARE MISCHIEVOUS", "subset": "test_other", "task_type": "understanding", "prediction": "ah well in that case to be sure let them go only those german quacks are mischievous", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0011.flac", "answer": "HE ASKED AH IT IS", "subset": "test_other", "task_type": "understanding", "prediction": "he asked ah it is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0028.flac", "answer": "NERVOUS IRRITABILITY HE SAID TO THE PRINCESS WHEN KITTY HAD LEFT THE ROOM HOWEVER I HAD FINISHED", "subset": "test_other", "task_type": "understanding", "prediction": "nervous irritability he said to the princess when kitty had left the room however i had finished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0014.flac", "answer": "WHAT IS WANTED IS MEANS OF IMPROVING NUTRITION AND NOT FOR LOWERING IT", "subset": "test_other", "task_type": "understanding", "prediction": "what is wanted is the means of improving nutrition and not of lowering it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0031.flac", "answer": "FINALLY HIS DECISION WAS PRONOUNCED THEY WERE TO GO ABROAD BUT TO PUT NO FAITH IN FOREIGN QUACKS AND TO APPLY TO HIM IN ANY NEED", "subset": "test_other", "task_type": "understanding", "prediction": "finally his decision was pronounced they were to go abroad but to put no faith in foreign quacks and to apply to him in any need", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0008.flac", "answer": "THE QUESTION STANDS THUS IN PRESENCE OF INDICATIONS OF TUBERCULOUS PROCESS WHAT IS TO BE DONE TO MAINTAIN NUTRITION", "subset": "test_other", "task_type": "understanding", "prediction": "the question stands thus in presence of indications of tuberculous process what is to be done to maintain nutrition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0003.flac", "answer": "WELL DOCTOR DECIDE OUR FATE SAID THE PRINCESS TELL ME EVERYTHING", "subset": "test_other", "task_type": "understanding", "prediction": "well doctor decide our fate said the princess tell me everything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0009.flac", "answer": "YES THAT'S AN UNDERSTOOD THING RESPONDED THE CELEBRATED PHYSICIAN AGAIN GLANCING AT HIS WATCH", "subset": "test_other", "task_type": "understanding", "prediction": "yes that is an understood thing responded the celebrated physician again glancing at his watch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0030.flac", "answer": "AT THE QUESTION SHOULD THEY GO ABROAD THE DOCTOR PLUNGED INTO DEEP MEDITATION AS THOUGH RESOLVING A WEIGHTY PROBLEM", "subset": "test_other", "task_type": "understanding", "prediction": "at the question should they go abroad the doctor plunged into deep meditation as though resolving a weighty problem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0010.flac", "answer": "BEG PARDON IS THE YAUSKY BRIDGE DONE YET OR SHALL I HAVE TO DRIVE AROUND", "subset": "test_other", "task_type": "understanding", "prediction": "beg pardon is the yoske bridge done yet or shall i have to drive around", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0029.flac", "answer": "AND THE DOCTOR BEGAN SCIENTIFICALLY EXPLAINING TO THE PRINCESS AS AN EXCEPTIONALLY INTELLIGENT WOMAN THE CONDITION OF THE YOUNG PRINCESS AND CONCLUDED BY INSISTING ON THE DRINKING OF THE WATERS WHICH WERE CERTAINLY HARMLESS", "subset": "test_other", "task_type": "understanding", "prediction": "and the doctor began scientifically explaining to the princess as an exceptionally intelligent woman the condition of the young princess and concluded by insisting on the drinking of the waters which were certainly harmless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0025.flac", "answer": "EXCUSE ME DOCTOR BUT THERE IS REALLY NO OBJECT IN THIS", "subset": "test_other", "task_type": "understanding", "prediction": "excuse me doctor but there is really no object in this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0024.flac", "answer": "SHE ANSWERED HIM AND ALL AT ONCE GOT UP FURIOUS", "subset": "test_other", "task_type": "understanding", "prediction": "she answered him and all at once got up furious", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0033.flac", "answer": "THE MOTHER WAS MUCH MORE CHEERFUL WHEN SHE WENT BACK TO HER DAUGHTER AND KITTY PRETENDED TO BE MORE CHEERFUL", "subset": "test_other", "task_type": "understanding", "prediction": "the mother was much more cheerful when she went back to her daughter and kitty pretended to be more cheerful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0004.flac", "answer": "IS THERE HOPE SHE MEANT TO SAY BUT HER LIPS QUIVERED AND SHE COULD NOT UTTER THE QUESTION WELL DOCTOR", "subset": "test_other", "task_type": "understanding", "prediction": "is there hope she meant to say but her lips quivered and she could not utter the question well doctor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0019.flac", "answer": "OH TIME'S UP ALREADY AND HE WENT TO THE DOOR", "subset": "test_other", "task_type": "understanding", "prediction": "oh time is up already and he went to the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0015.flac", "answer": "THE FAMILY DOCTOR LISTENED ATTENTIVELY AND RESPECTFULLY", "subset": "test_other", "task_type": "understanding", "prediction": "the family doctor listened attentively and respectfully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0032.flac", "answer": "IT SEEMED AS THOUGH SOME PIECE OF GOOD FORTUNE HAD COME TO PASS AFTER THE DOCTOR HAD GONE", "subset": "test_other", "task_type": "understanding", "prediction": "it seemed as though some piece of good fortune had come to pass after the doctor had gone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0000.flac", "answer": "HE PERCEIVED THAT IT WAS NO GOOD TALKING TO THE OLD MAN AND THAT THE PRINCIPAL PERSON IN THE HOUSE WAS THE MOTHER", "subset": "test_other", "task_type": "understanding", "prediction": "he perceived that it was no good talking to the old man and that the principal person in the house was the mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0026.flac", "answer": "THIS IS THE THIRD TIME YOU'VE ASKED ME THE SAME THING", "subset": "test_other", "task_type": "understanding", "prediction": "this is the third time you have asked me the same thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0021.flac", "answer": "OH NO ONLY A FEW DETAILS PRINCESS COME THIS WAY", "subset": "test_other", "task_type": "understanding", "prediction": "oh no only a few details princess come this way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0016.flac", "answer": "BUT IN FAVOR OF FOREIGN TRAVEL I WOULD URGE THE CHANGE OF HABITS THE REMOVAL FROM CONDITIONS CALLING UP REMINISCENCES", "subset": "test_other", "task_type": "understanding", "prediction": "but in favor of foreign travel i would urge the change of habits the removal from conditions calling up reminiscences", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0002.flac", "answer": "THE PRINCESS WAS DISTRACTED AND DID NOT KNOW WHAT TO DO SHE FELT SHE HAD SINNED AGAINST KITTY", "subset": "test_other", "task_type": "understanding", "prediction": "the princess was distracted and did not know what to do she felt she had sinned against kitty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0017.flac", "answer": "AND THEN THE MOTHER WISHES IT HE ADDED", "subset": "test_other", "task_type": "understanding", "prediction": "and then the mother wishes it he added", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0013.flac", "answer": "AND HOW ABOUT A TOUR ABROAD ASKED THE FAMILY DOCTOR", "subset": "test_other", "task_type": "understanding", "prediction": "and how about a tour abroad asked the family doctor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0023.flac", "answer": "WHEN THE DOCTOR CAME IN SHE FLUSHED CRIMSON AND HER EYES FILLED WITH TEARS", "subset": "test_other", "task_type": "understanding", "prediction": "when the doctor came in she flushed crimson and her eyes filled with tears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0020.flac", "answer": "THE CELEBRATED DOCTOR ANNOUNCED TO THE PRINCESS A FEELING OF WHAT WAS DUE FROM HIM DICTATED HIS DOING SO THAT HE OUGHT TO SEE THE PATIENT ONCE MORE", "subset": "test_other", "task_type": "understanding", "prediction": "the celebrated doctor announced to the princess a feeling of what was due from him dictated his doing so that he ought to see the patient once more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0012.flac", "answer": "OH WELL THEN I CAN DO IT IN TWENTY MINUTES", "subset": "test_other", "task_type": "understanding", "prediction": "oh well then i can do it in twenty minutes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0027.flac", "answer": "THE CELEBRATED DOCTOR DID NOT TAKE OFFENSE", "subset": "test_other", "task_type": "understanding", "prediction": "the celebrated doctor did not take offence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0022.flac", "answer": "AND THE MOTHER ACCOMPANIED BY THE DOCTOR WENT INTO THE DRAWING ROOM TO KITTY", "subset": "test_other", "task_type": "understanding", "prediction": "and the mother accompanied by the doctor went into the drawing room to kitty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0005.flac", "answer": "AS YOU PLEASE THE PRINCESS WENT OUT WITH A SIGH", "subset": "test_other", "task_type": "understanding", "prediction": "as you please the princess went out with a sigh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0006.flac", "answer": "THE FAMILY DOCTOR RESPECTFULLY CEASED IN THE MIDDLE OF HIS OBSERVATIONS", "subset": "test_other", "task_type": "understanding", "prediction": "the family doctor respectfully ceased in the middle of his observations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0001.flac", "answer": "BEFORE HER HE DECIDED TO SCATTER HIS PEARLS", "subset": "test_other", "task_type": "understanding", "prediction": "before her he decided to scatter his pearls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/10919/4350-10919-0007.flac", "answer": "AND THERE ARE INDICATIONS MALNUTRITION NERVOUS EXCITABILITY AND SO ON", "subset": "test_other", "task_type": "understanding", "prediction": "and there are indications malnutrition nervous excitability and so on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0002.flac", "answer": "IN THE SOCIAL CONCEPTION OF LIFE IT IS SUPPOSED THAT SINCE THE AIM OF LIFE IS FOUND IN GROUPS OF INDIVIDUALS INDIVIDUALS WILL VOLUNTARILY SACRIFICE THEIR OWN INTERESTS FOR THE INTERESTS OF THE GROUP", "subset": "test_other", "task_type": "understanding", "prediction": "in the social conception of life it is supposed that since the aim of life is found in groups of individuals individuals will voluntarily sacrifice their own interests for the interests of the group", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0046.flac", "answer": "EXCEPT FOR THE STATE THEY SAY WE SHOULD BE EXPOSED TO THE ATTACKS OF EVIL DISPOSED PERSONS IN OUR OWN COUNTRY", "subset": "test_other", "task_type": "understanding", "prediction": "except with the state they say we should be exposed to the attacks of evil disposed persons in our own country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0057.flac", "answer": "EVEN LOOKING AT IT PRACTICALLY WEIGHING THAT IS TO SAY ALL THE BURDENS LAID ON HIM BY THE STATE NO MAN CAN FAIL TO SEE THAT FOR HIM PERSONALLY TO COMPLY WITH STATE DEMANDS AND SERVE IN THE ARMY WOULD IN THE MAJORITY OF CASES BE MORE DISADVANTAGEOUS THAN TO REFUSE TO DO SO", "subset": "test_other", "task_type": "understanding", "prediction": "even looking at it practically weighing that is to say all the burdens laid on him by the state no man can fail to see that for him personally to comply with the state demands and serve in the army would in the majority of cases be more disadvantageous than to refuse to do so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0016.flac", "answer": "AFTER CONQUEST THE POWER OF THE EMPEROR PUTS AN END TO INTERNAL DISSENSIONS AND SO THE STATE CONCEPTION OF LIFE JUSTIFIES ITSELF", "subset": "test_other", "task_type": "understanding", "prediction": "after conquest the power of the emperor puts an end to internal dissensions and so the state conception of life justifies itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0015.flac", "answer": "IT WAS PRODUCED ON ONE HAND BY THE NATURAL GROWTH OF POPULATION AND ON THE OTHER BY STRUGGLE AND CONQUEST", "subset": "test_other", "task_type": "understanding", "prediction": "it was produced on one hand by the natural growth of population and on the other by struggle and conquest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0037.flac", "answer": "BUT WITH UNIVERSAL MILITARY SERVICE IT COMES TO PASS THAT MEN AFTER MAKING EVERY SACRIFICE TO GET RID OF THE CRUELTY OF STRIFE AND THE INSECURITY OF EXISTENCE ARE CALLED UPON TO FACE ALL THE PERILS THEY HAD MEANT TO AVOID", "subset": "test_other", "task_type": "understanding", "prediction": "but with universal military service it comes to pass that men after making every sacrifice to get rid of the cruelty of strife and the insecurity of existence are called upon to face all the perils they had meant to avoid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0018.flac", "answer": "INTERNAL DISSENSIONS DISAPPEAR ONLY IN PROPORTION TO THE DEGREE OF OPPRESSION EXERTED BY THE AUTHORITY OVER THE DISSENTIENT INDIVIDUALS", "subset": "test_other", "task_type": "understanding", "prediction": "internal dissensions disappear only in proportion to the degree of oppression exerted by the authority over the dissentient individuals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0035.flac", "answer": "THIS INCONSISTENCY HAS BECOME OBVIOUS IN UNIVERSAL MILITARY SERVICE", "subset": "test_other", "task_type": "understanding", "prediction": "this inconsistency has become obvious in universal military service", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0017.flac", "answer": "BUT THIS JUSTIFICATION IS NEVER MORE THAN TEMPORARY", "subset": "test_other", "task_type": "understanding", "prediction": "but this justification is never more than temporary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0020.flac", "answer": "AND THEREFORE THE OPPRESSION OF THE OPPRESSED ALWAYS GOES ON GROWING UP TO THE FURTHEST LIMIT BEYOND WHICH IT CANNOT GO WITHOUT KILLING THE GOOSE WITH THE GOLDEN EGGS", "subset": "test_other", "task_type": "understanding", "prediction": "and therefore the oppression of the oppressed always goes on growing up to the furthest limit beyond which it cannot go without killing the goose with the golden eggs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0043.flac", "answer": "THEY ARE NEEDED PRINCIPALLY AGAINST THEIR SUBJECTS AND EVERY MAN UNDER UNIVERSAL MILITARY SERVICE BECOMES AN ACCOMPLICE IN ALL THE ACTS OF VIOLENCE OF THE GOVERNMENT AGAINST THE CITIZENS WITHOUT ANY CHOICE OF HIS OWN", "subset": "test_other", "task_type": "understanding", "prediction": "they are needed principally against their subjects and every man under universal military service becomes an accomplice in all the acts of violence of the government against the citizens without any choice of his own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0049.flac", "answer": "EXCEPT FOR THE STATE THEY TELL US WE SHOULD NOT HAVE ANY RELIGION EDUCATION CULTURE MEANS OF COMMUNICATION AND SO ON", "subset": "test_other", "task_type": "understanding", "prediction": "except for the state they tell us we should not have any religion education culture means of communication and so on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0014.flac", "answer": "BETWEEN THE MEMBERS OF ONE STATE SUBJECT TO A SINGLE AUTHORITY THE STRIFE BETWEEN INDIVIDUALS SEEMS STILL LESS AND THE LIFE OF THE STATE SEEMS EVEN MORE SECURE", "subset": "test_other", "task_type": "understanding", "prediction": "between the members of one state subject to a single authority the strife between the individuals seems still less and the life of the state seems even more secure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0041.flac", "answer": "BUT THE FATAL SIGNIFICANCE OF UNIVERSAL MILITARY SERVICE AS THE MANIFESTATION OF THE CONTRADICTION INHERENT IN THE SOCIAL CONCEPTION OF LIFE IS NOT ONLY APPARENT IN THAT", "subset": "test_other", "task_type": "understanding", "prediction": "but the fatal significance of universal military service as the manifestation of the contradiction inherent in the social conception of life is not only apparent in that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0040.flac", "answer": "THE DANGER OF WAR EVER READY TO BREAK OUT RENDERS ALL REFORMS OF LIFE SOCIAL LIFE VAIN AND FRUITLESS", "subset": "test_other", "task_type": "understanding", "prediction": "the danger of war ever ready to break out renders all reforms of life social life vain and fruitless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0001.flac", "answer": "THIS IS ABSOLUTELY INCORRECT", "subset": "test_other", "task_type": "understanding", "prediction": "this is absolutely incorrect", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0050.flac", "answer": "WITHOUT THE STATE MEN WOULD NOT HAVE BEEN ABLE TO FORM THE SOCIAL INSTITUTIONS NEEDED FOR DOING ANY THING", "subset": "test_other", "task_type": "understanding", "prediction": "without the state men would not have been able to form the social institutions needed for doing anything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0029.flac", "answer": "AND SO EVERY GOVERNMENT NEEDS AN ARMY ALSO TO PROTECT ITS BOOTY FROM ITS NEIGHBOR BRIGANDS", "subset": "test_other", "task_type": "understanding", "prediction": "and so every government needs an army also to protect its booty from its neighbor brigands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0023.flac", "answer": "FOOTNOTE THE FACT THAT IN AMERICA THE ABUSES OF AUTHORITY EXIST IN SPITE OF THE SMALL NUMBER OF THEIR TROOPS NOT ONLY FAILS TO DISPROVE THIS POSITION BUT POSITIVELY CONFIRMS IT", "subset": "test_other", "task_type": "understanding", "prediction": "footnote the fact that in america the abuses of authority exist in spite of the small number of their troops not only fails to disprove this position but positively confirms it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0025.flac", "answer": "THE REASON TO WHICH HE GAVE EXPRESSION IS ESSENTIALLY THE SAME AS THAT WHICH MADE THE FRENCH KINGS AND THE POPES ENGAGE SWISS AND SCOTCH GUARDS AND MAKES THE RUSSIAN AUTHORITIES OF TO DAY SO CAREFULLY DISTRIBUTE THE RECRUITS SO THAT THE REGIMENTS FROM THE FRONTIERS ARE STATIONED IN CENTRAL DISTRICTS AND THE REGIMENTS FROM THE CENTER ARE STATIONED ON THE FRONTIERS", "subset": "test_other", "task_type": "understanding", "prediction": "the reason to which he gave expression is essentially the same as that which made the french kings and the popes engage swiss and scotch guards and makes the russian authorities of to day so carefully distribute the recruits so that the regiments from the frontier are stationed in central districts and the regiments from the center are stationed on the frontiers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0008.flac", "answer": "THE ARMY HAS ALWAYS BEEN AND STILL IS THE BASIS OF POWER", "subset": "test_other", "task_type": "understanding", "prediction": "the army has always been and still is the basis of power", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0048.flac", "answer": "SO THAT THE JUSTIFICATION OF STATE VIOLENCE ON THE GROUND OF THE PROTECTION IT GIVES US FROM EVIL DISPOSED PERSONS EVEN IF IT HAD SOME FOUNDATION THREE OR FOUR CENTURIES AGO HAS NONE WHATEVER NOW", "subset": "test_other", "task_type": "understanding", "prediction": "so that the justification of state violence on the ground of the protection it gives us from evil disposed persons even if it had some foundation three or four centuries ago has none whatever now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0006.flac", "answer": "THE POSSIBILITY OF APPLYING BODILY VIOLENCE TO PEOPLE IS PROVIDED ABOVE ALL BY AN ORGANIZATION OF ARMED MEN TRAINED TO ACT IN UNISON IN SUBMISSION TO ONE WILL", "subset": "test_other", "task_type": "understanding", "prediction": "the possibility of applying bodily violence to people is provided above all by an organization of armed men trained to act in unison in submission to one will", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0000.flac", "answer": "EDUCATED PEOPLE OF THE UPPER CLASSES ARE TRYING TO STIFLE THE EVER GROWING SENSE OF THE NECESSITY OF TRANSFORMING THE EXISTING SOCIAL ORDER", "subset": "test_other", "task_type": "understanding", "prediction": "educated people of the upper classes are trying to stifle the ever growing sense of the necessity of transforming the existing social order", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0005.flac", "answer": "THE BASIS OF AUTHORITY IS BODILY VIOLENCE", "subset": "test_other", "task_type": "understanding", "prediction": "the basis of authority is bodily violence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0054.flac", "answer": "THE GOVERNMENT THEY TELL US WITH ITS ARMY IS NECESSARY TO DEFEND US FROM NEIGHBORING STATES WHO MIGHT ENSLAVE US", "subset": "test_other", "task_type": "understanding", "prediction": "the government they tell us with its army is necessary to defend us from neighboring states who might enslave us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0024.flac", "answer": "THE UPPER CLASSES KNOW THAT AN ARMY OF FIFTY THOUSAND WILL SOON BE INSUFFICIENT AND NO LONGER RELYING ON PINKERTON'S MEN THEY FEEL THAT THE SECURITY OF THEIR POSITION DEPENDS ON THE INCREASED STRENGTH OF THE ARMY", "subset": "test_other", "task_type": "understanding", "prediction": "the upper classes know that an army of fifty thousand will soon be insufficient and no longer relying on pinkertons men they feel that the security of their position depends on the increased strength of the army", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0047.flac", "answer": "WE KNOW NOW THAT THREATS AND PUNISHMENTS CANNOT DIMINISH THEIR NUMBER THAT THAT CAN ONLY BE DONE BY CHANGE OF ENVIRONMENT AND MORAL INFLUENCE", "subset": "test_other", "task_type": "understanding", "prediction": "we now know that threats and punishments cannot diminish their number that that can only be done by change of environment and moral influence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0019.flac", "answer": "GOVERNMENT AUTHORITY EVEN IF IT DOES SUPPRESS PRIVATE VIOLENCE ALWAYS INTRODUCES INTO THE LIFE OF MEN FRESH FORMS OF VIOLENCE WHICH TEND TO BECOME GREATER AND GREATER IN PROPORTION TO THE DURATION AND STRENGTH OF THE GOVERNMENT", "subset": "test_other", "task_type": "understanding", "prediction": "government authority even if it does suppress private violence always introduces into the life of men fresh forms of violence which tend to become greater and greater in proportion to the duration and strength of the government", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0058.flac", "answer": "TO RESIST WOULD NEED INDEPENDENT THOUGHT AND EFFORT OF WHICH EVERY MAN IS NOT CAPABLE", "subset": "test_other", "task_type": "understanding", "prediction": "to resist would need independent thought and effort of which every man is not capable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0012.flac", "answer": "BUT SINCE THIS IS NOT THE CASE AND ON THE CONTRARY MEN IN POWER ARE ALWAYS FAR FROM BEING SAINTS THROUGH THE VERY FACT OF THEIR POSSESSION OF POWER THE SOCIAL ORGANIZATION BASED ON POWER HAS NO JUSTIFICATION", "subset": "test_other", "task_type": "understanding", "prediction": "but since this is not the case and on the contrary men in power are always far from being saints through the very fact of their possession of power the social organization based on power has no justification", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0053.flac", "answer": "WITHOUT GOVERNMENTS NATIONS WOULD BE ENSLAVED BY THEIR NEIGHBORS", "subset": "test_other", "task_type": "understanding", "prediction": "without governments nations would be enslaved by their neighbors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0045.flac", "answer": "I AM EXPECTED FOR THE SAKE OF THE STATE TO MAKE THESE SACRIFICES TO RENOUNCE EVERYTHING THAT CAN BE PRECIOUS TO MAN PEACE FAMILY SECURITY AND HUMAN DIGNITY", "subset": "test_other", "task_type": "understanding", "prediction": "i am expected for the sake of the state to make these sacrifices to renounce everything that can be precious to man peace family security and human dignity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0007.flac", "answer": "THESE BANDS OF ARMED MEN SUBMISSIVE TO A SINGLE WILL ARE WHAT CONSTITUTE THE ARMY", "subset": "test_other", "task_type": "understanding", "prediction": "these bands of armed men submissive to a single will are what constitute the army", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0028.flac", "answer": "BUT THERE IS NOT ONLY ONE GOVERNMENT THERE ARE OTHER GOVERNMENTS EXPLOITING THEIR SUBJECTS BY VIOLENCE IN THE SAME WAY AND ALWAYS READY TO POUNCE DOWN ON ANY OTHER GOVERNMENT AND CARRY OFF THE FRUITS OF THE TOIL OF ITS ENSLAVED SUBJECTS", "subset": "test_other", "task_type": "understanding", "prediction": "but there is not only one government there are other governments exploiting their subjects by violence in the same way and are always ready to pounce down on any other government and carry off the fruits of the toil of its enslaved subjects", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0011.flac", "answer": "ONLY UNDER THOSE CONDITIONS COULD THE SOCIAL ORGANIZATION BE JUSTIFIED", "subset": "test_other", "task_type": "understanding", "prediction": "only under those conditions could the social organization be justified", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0052.flac", "answer": "THE GREAT EXTENSION OF MEANS OF COMMUNICATION AND INTERCHANGE OF IDEAS HAS MADE MEN COMPLETELY ABLE TO DISPENSE WITH STATE AID IN FORMING SOCIETIES ASSOCIATIONS CORPORATIONS AND CONGRESSES FOR SCIENTIFIC ECONOMIC AND POLITICAL OBJECTS", "subset": "test_other", "task_type": "understanding", "prediction": "the great extension of means of communication and interchange of ideas has made men completely able to dispense with state aid in forming societies associations corporations and congresses for scientific economic and political objects", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0039.flac", "answer": "THE TAXES RAISED FROM THE PEOPLE FOR WAR PREPARATIONS ABSORB THE GREATER PART OF THE PRODUCE OF LABOR WHICH THE ARMY OUGHT TO DEFEND", "subset": "test_other", "task_type": "understanding", "prediction": "the taxes raised from the people for war preparations absorb the greater part of the produce of labor which the army ought to defend", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0055.flac", "answer": "AND IF DEFENSE AGAINST BARBAROUS NATIONS IS MEANT ONE THOUSANDTH PART OF THE TROOPS NOW UNDER ARMS WOULD BE AMPLY SUFFICIENT FOR THAT PURPOSE", "subset": "test_other", "task_type": "understanding", "prediction": "and if defense against barbarous nations is meant one thousandth part of the troops now under arms would be amply sufficient for that purpose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0056.flac", "answer": "THE POWER OF THE STATE FAR FROM BEING A SECURITY AGAINST THE ATTACKS OF OUR NEIGHBORS EXPOSES US ON THE CONTRARY TO MUCH GREATER DANGER OF SUCH ATTACKS", "subset": "test_other", "task_type": "understanding", "prediction": "the power of the state far from being a security against the attacks of our neighbors exposes us on the contrary to much greater danger of such attacks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0004.flac", "answer": "THE MAN WHO IS CONTROLLED BY MORAL INFLUENCE ACTS IN ACCORDANCE WITH HIS OWN DESIRES", "subset": "test_other", "task_type": "understanding", "prediction": "the man who is controlled by moral influence acts in accordance with his own desires", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0044.flac", "answer": "AND FOR THE SAKE OF WHAT AM I MAKING THEM", "subset": "test_other", "task_type": "understanding", "prediction": "and for the sake of what am i making them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0038.flac", "answer": "BUT INSTEAD OF DOING THAT THEY EXPOSE THE INDIVIDUALS TO THE SAME NECESSITY OF STRIFE SUBSTITUTING STRIFE WITH INDIVIDUALS OF OTHER STATES FOR STRIFE WITH NEIGHBORS", "subset": "test_other", "task_type": "understanding", "prediction": "but instead of doing that they expose the individuals to the same necessity of strife substituting strife with individuals of other states for strife with neighbours", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0026.flac", "answer": "THE MEANING OF CAPRIVI'S SPEECH PUT INTO PLAIN LANGUAGE IS THAT FUNDS ARE NEEDED NOT TO RESIST FOREIGN FOES BUT TO BUY UNDER OFFICERS TO BE READY TO ACT AGAINST THE ENSLAVED TOILING MASSES", "subset": "test_other", "task_type": "understanding", "prediction": "the meaning of caprivi s speech put into plain language is that funds are needed not to resist foreign foes but to buy under officers to be ready to act against the enslaved toiling masses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0013.flac", "answer": "EVEN IF THERE WAS ONCE A TIME WHEN OWING TO THE LOW STANDARD OF MORALS AND THE DISPOSITION OF MEN TO VIOLENCE THE EXISTENCE OF AN AUTHORITY TO RESTRAIN SUCH VIOLENCE WAS AN ADVANTAGE BECAUSE THE VIOLENCE OF GOVERNMENT WAS LESS THAN THE VIOLENCE OF INDIVIDUALS ONE CANNOT BUT SEE THAT THIS ADVANTAGE COULD NOT BE LASTING", "subset": "test_other", "task_type": "understanding", "prediction": "even if there was once a time when owing to the low standard of morals and the disposition of men to violence the existence of an authority to restrain such violence was an advantage because the violence of the government was less than the violence of individuals one cannot but see that this advantage could not be lasting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0033.flac", "answer": "THE RIVALRY OF THE EUROPEAN STATES IN CONSTANTLY INCREASING THEIR FORCES HAS REDUCED THEM TO THE NECESSITY OF HAVING RECOURSE TO UNIVERSAL MILITARY SERVICE SINCE BY THAT MEANS THE GREATEST POSSIBLE NUMBER OF SOLDIERS IS OBTAINED AT THE LEAST POSSIBLE EXPENSE", "subset": "test_other", "task_type": "understanding", "prediction": "the rivalry of the european states in constantly increasing their forces has reduced them to the necessity of having recourse to universal military service since by that means the greatest possible number of soldiers is obtained at the least possible expense", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0010.flac", "answer": "INDEED IT COULD NOT BE OTHERWISE", "subset": "test_other", "task_type": "understanding", "prediction": "indeed it could not be otherwise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0027.flac", "answer": "AND THIS ABNORMAL ORDER OF THINGS IS MAINTAINED BY THE ARMY", "subset": "test_other", "task_type": "understanding", "prediction": "and this abnormal order of things is maintained by the army", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0003.flac", "answer": "THE CHAMPIONS OF THE SOCIAL CONCEPTION OF LIFE USUALLY TRY TO CONNECT THE IDEA OF AUTHORITY THAT IS OF VIOLENCE WITH THE IDEA OF MORAL INFLUENCE BUT THIS CONNECTION IS QUITE IMPOSSIBLE", "subset": "test_other", "task_type": "understanding", "prediction": "the champions of the social conception of life usually try to connect the idea of authority that is of violence with the idea of moral influence but this connection is quite impossible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0036.flac", "answer": "IN FACT THE WHOLE SIGNIFICANCE OF THE SOCIAL CONCEPTION OF LIFE CONSISTS IN MAN'S RECOGNITION OF THE BARBARITY OF STRIFE BETWEEN INDIVIDUALS AND THE TRANSITORINESS OF PERSONAL LIFE ITSELF AND THE TRANSFERENCE OF THE AIM OF LIFE TO GROUPS OF PERSONS", "subset": "test_other", "task_type": "understanding", "prediction": "in fact the whole significance of the social conception of life consists in man s recognition of the barbarity of strife between individuals and the transitoriness of personal life itself and the transference of the aim of life to groups of persons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0030.flac", "answer": "THIS INCREASE IS CONTAGIOUS AS MONTESQUIEU POINTED OUT ONE HUNDRED FIFTY YEARS AGO", "subset": "test_other", "task_type": "understanding", "prediction": "this increase is contagious as montesquieu pointed out one hundred and fifty years ago", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0034.flac", "answer": "AND BY THIS MEANS ALL CITIZENS ARE UNDER ARMS TO SUPPORT THE INIQUITIES PRACTICED UPON THEM ALL CITIZENS HAVE BECOME THEIR OWN OPPRESSORS", "subset": "test_other", "task_type": "understanding", "prediction": "and by this means all citizens are under arms to support the iniquities practised upon them all citizens have become their own oppressors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0022.flac", "answer": "SO IT HAS ALWAYS BEEN", "subset": "test_other", "task_type": "understanding", "prediction": "so it has always been", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0032.flac", "answer": "THE DESPOTISM OF A GOVERNMENT ALWAYS INCREASES WITH THE STRENGTH OF THE ARMY AND ITS EXTERNAL SUCCESSES AND THE AGGRESSIVENESS OF A GOVERNMENT INCREASES WITH ITS INTERNAL DESPOTISM", "subset": "test_other", "task_type": "understanding", "prediction": "the despotism of a government always increases with the strength of the army and its external successes and the aggressiveness of a government increases with its internal despotism", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0042.flac", "answer": "GOVERNMENTS ASSERT THAT ARMIES ARE NEEDED ABOVE ALL FOR EXTERNAL DEFENSE BUT THAT IS NOT TRUE", "subset": "test_other", "task_type": "understanding", "prediction": "governments assert that armies are needed above all for external defense but that is not true", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0031.flac", "answer": "EVERY INCREASE IN THE ARMY OF ONE STATE WITH THE AIM OF SELF DEFENSE AGAINST ITS SUBJECTS BECOMES A SOURCE OF DANGER FOR NEIGHBORING STATES AND CALLS FOR A SIMILAR INCREASE IN THEIR ARMIES", "subset": "test_other", "task_type": "understanding", "prediction": "every increase in the army of one state with the aim of self defense against its subjects becomes a source of danger for neighboring states and calls for a similar increase in their armies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0051.flac", "answer": "THIS ARGUMENT TOO WAS WELL FOUNDED ONLY SOME CENTURIES AGO", "subset": "test_other", "task_type": "understanding", "prediction": "this argument too was well founded only some centuries ago", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0021.flac", "answer": "THE MOST CONVINCING EXAMPLE OF THIS IS TO BE FOUND IN THE CONDITION OF THE WORKING CLASSES OF OUR EPOCH WHO ARE IN REALITY NO BETTER THAN THE SLAVES OF ANCIENT TIMES SUBDUED BY CONQUEST", "subset": "test_other", "task_type": "understanding", "prediction": "the most convincing example of this is to be found in the condition of the working classes of our epoch who are in reality no better than the slaves of ancient times subdued by conquest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0060.flac", "answer": "FOR A MAN OF THE POOR WORKING CLASS THE ADVANTAGES AND DISADVANTAGES WILL BE THE SAME BUT WITH A GREAT INCREASE OF DISADVANTAGES", "subset": "test_other", "task_type": "understanding", "prediction": "for a man of the poor working class the advantages and disadvantages will be the same but with a great increase of disadvantages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0059.flac", "answer": "SO MUCH FOR THE ADVANTAGES AND DISADVANTAGES OF BOTH LINES OF CONDUCT FOR A MAN OF THE WEALTHY CLASSES AN OPPRESSOR", "subset": "test_other", "task_type": "understanding", "prediction": "so much for the advantages and disadvantages of both lines of conduct for a man of the wealthy class an oppressor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-other/4350/9170/4350-9170-0009.flac", "answer": "POWER IS ALWAYS IN THE HANDS OF THOSE WHO CONTROL THE ARMY AND ALL MEN IN POWER FROM THE ROMAN CAESARS TO THE RUSSIAN AND GERMAN EMPERORS TAKE MORE INTEREST IN THEIR ARMY THAN IN ANYTHING AND COURT POPULARITY IN THE ARMY KNOWING THAT IF THAT IS ON THEIR SIDE THEIR POWER IS SECURE", "subset": "test_other", "task_type": "understanding", "prediction": "power is always in the hands of those who control the army and all men in power from the roman caesars to the russian and german emperors take more interest in their army than in anything and court popularity in the army knowing that if that is on their side their power is secure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank0.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank0.log
new file mode 100644
index 0000000000000000000000000000000000000000..ac66d697e27e166d0133b4cebcf2e8753c17b04a
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank0.log
@@ -0,0 +1,7 @@
+2025-12-21 06:50:07 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: LibriSpeech
+2025-12-21 06:50:07 | INFO | Msg example: {'index': 0, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0003.flac'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'LibriSpeech', 'dataset_name': 'LibriSpeech', 'lang': 'en', 'subset': 'test_clean'}}
+2025-12-21 06:50:08 | INFO | Prompt: You are a speech recognition model.
+Transcribe the English audio into text without any punctuation marks.
+2025-12-21 06:56:38 | INFO | waiting for other ranks to finish, time elapsed: 10s
+2025-12-21 06:56:38 | INFO | model Qwen2.5-Omni-7B-lora2, data LibriSpeech, all 8 result merged to no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/Qwen2.5-Omni-7B-lora2_LibriSpeech.jsonl.
+2025-12-21 06:56:38 | INFO | skip eval for LibriSpeech
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank1.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank1.log
new file mode 100644
index 0000000000000000000000000000000000000000..30beb5ebd14e17a0cde7c51420eaadcd1cc6bfb0
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank1.log
@@ -0,0 +1,4 @@
+2025-12-21 06:50:06 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: LibriSpeech
+2025-12-21 06:50:06 | INFO | Msg example: {'index': 1, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0012.flac'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'LibriSpeech', 'dataset_name': 'LibriSpeech', 'lang': 'en', 'subset': 'test_clean'}}
+2025-12-21 06:50:07 | INFO | Prompt: You are a speech recognition model.
+Transcribe the English audio into text without any punctuation marks.
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank2.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank2.log
new file mode 100644
index 0000000000000000000000000000000000000000..9723fc344c12e4f1deebedcd4863f06f268e8bf6
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank2.log
@@ -0,0 +1,4 @@
+2025-12-21 06:50:06 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: LibriSpeech
+2025-12-21 06:50:06 | INFO | Msg example: {'index': 2, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0026.flac'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'LibriSpeech', 'dataset_name': 'LibriSpeech', 'lang': 'en', 'subset': 'test_clean'}}
+2025-12-21 06:50:07 | INFO | Prompt: You are a speech recognition model.
+Transcribe the English audio into text without any punctuation marks.
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank4.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank4.log
new file mode 100644
index 0000000000000000000000000000000000000000..11fb5b06bfc5aec8e6c0a210d159d9f9ae5a61e7
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank4.log
@@ -0,0 +1,4 @@
+2025-12-21 06:50:06 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: LibriSpeech
+2025-12-21 06:50:06 | INFO | Msg example: {'index': 4, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0002.flac'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'LibriSpeech', 'dataset_name': 'LibriSpeech', 'lang': 'en', 'subset': 'test_clean'}}
+2025-12-21 06:50:07 | INFO | Prompt: You are a speech recognition model.
+Transcribe the English audio into text without any punctuation marks.
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank5.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank5.log
new file mode 100644
index 0000000000000000000000000000000000000000..aa523298389653a39273a3c95e89e953f1dbecd7
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank5.log
@@ -0,0 +1,4 @@
+2025-12-21 06:50:06 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: LibriSpeech
+2025-12-21 06:50:06 | INFO | Msg example: {'index': 5, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0025.flac'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'LibriSpeech', 'dataset_name': 'LibriSpeech', 'lang': 'en', 'subset': 'test_clean'}}
+2025-12-21 06:50:07 | INFO | Prompt: You are a speech recognition model.
+Transcribe the English audio into text without any punctuation marks.
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank6.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank6.log
new file mode 100644
index 0000000000000000000000000000000000000000..0d002b54ce7c636a7d405bf76249d78fc57715fa
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank6.log
@@ -0,0 +1,4 @@
+2025-12-21 06:50:05 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: LibriSpeech
+2025-12-21 06:50:05 | INFO | Msg example: {'index': 6, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0010.flac'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'LibriSpeech', 'dataset_name': 'LibriSpeech', 'lang': 'en', 'subset': 'test_clean'}}
+2025-12-21 06:50:06 | INFO | Prompt: You are a speech recognition model.
+Transcribe the English audio into text without any punctuation marks.
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank7.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank7.log
new file mode 100644
index 0000000000000000000000000000000000000000..2af585df833efac1f776f3f2cda55060df191e38
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/LibriSpeech/logs/rank7.log
@@ -0,0 +1,4 @@
+2025-12-21 06:50:05 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: LibriSpeech
+2025-12-21 06:50:05 | INFO | Msg example: {'index': 7, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/dataset/LibriSpeech/librispeech/LibriSpeech/test-clean/1320/122617/1320-122617-0001.flac'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'LibriSpeech', 'dataset_name': 'LibriSpeech', 'lang': 'en', 'subset': 'test_clean'}}
+2025-12-21 06:50:06 | INFO | Prompt: You are a speech recognition model.
+Transcribe the English audio into text without any punctuation marks.
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi.jsonl b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8aa4b1664fa114feb985db9db632a50ea5ea68bf
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi.jsonl
@@ -0,0 +1,1320 @@
+{"index": 1, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C0202_BUS.wav", "answer": "the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years", "subset": "bus", "task_type": "understanding", "prediction": "The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C0204_BUS.wav", "answer": "r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.", "subset": "bus", "task_type": "understanding", "prediction": "Rli Corporation, a Peoria, Illinois, based insurance holding company, will begin trading Friday on the big board under the symbol Rli.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C0209_BUS.wav", "answer": "a p. b. g. c. spokeswoman declined comment", "subset": "bus", "task_type": "understanding", "prediction": "a p b g c spokesman declined to comment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020E_BUS.wav", "answer": "the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last week", "subset": "bus", "task_type": "understanding", "prediction": "The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at the previous auction last week.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020F_BUS.wav", "answer": "the average rate on new twenty six week bills rose to six point one six percent from six point one two percent", "subset": "bus", "task_type": "understanding", "prediction": "The error rate on new 26 C bills rose to 6.16 from 6.12.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 6, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020G_BUS.wav", "answer": "analysts too generally played down the effect on banks", "subset": "bus", "task_type": "understanding", "prediction": "Analysts, too, generally played down the effect on banks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 7, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020H_BUS.wav", "answer": "in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks", "subset": "bus", "task_type": "understanding", "prediction": "In a fundamental sense, the equity markets have very little to do with the portfolios on in the commercial banks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 8, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020I_BUS.wav", "answer": "there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company", "subset": "bus", "task_type": "understanding", "prediction": "there shouldnt be any risk to the banks in this sort of stuff said lawrence cohen a banking analyst in maryland", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 9, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020O_BUS.wav", "answer": "unable to agree on friday the board must meet again at least by phone to register its choice", "subset": "bus", "task_type": "understanding", "prediction": "unable to agree on friday the board must meet again at least by phone to register its choice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 10, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020P_BUS.wav", "answer": "commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models", "subset": "bus", "task_type": "understanding", "prediction": "Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories of new models.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 11, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020T_BUS.wav", "answer": "rates fell on short term treasury bills", "subset": "bus", "task_type": "understanding", "prediction": "rates fell on short term treasury notes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 12, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C0210_BUS.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "bus", "task_type": "understanding", "prediction": "Yesterday, Moody s Investors Service raised Lilco s credit ratings, indicating recognition of the improved outlook and steady financial recovery.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 13, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_441C0207_BUS.wav", "answer": "in japan it's all greek so to speak", "subset": "bus", "task_type": "understanding", "prediction": "in japan it is all greek so to speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 14, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_441C020T_BUS.wav", "answer": "has exposure really been reduced", "subset": "bus", "task_type": "understanding", "prediction": "has exposure really been reduced", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 15, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_441C0214_BUS.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "bus", "task_type": "understanding", "prediction": "He also said that the company, for the first time, is developing drugs specifically for the over the counter consumer healthcare market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 16, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C0201_BUS.wav", "answer": "bids totaling five hundred twenty five point five million dollars were submitted", "subset": "bus", "task_type": "understanding", "prediction": "Its totaling $525.5 million, were submitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 17, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020A_BUS.wav", "answer": "under terms previously reported the italian agricultural concern assumed about one hundred ninety five million dollars in subordinated debt as part of the transaction", "subset": "bus", "task_type": "understanding", "prediction": "Under terms previously reported, the Italian agricultural concern assumed about $195 million in subordinated debt as part of the transaction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 18, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020H_BUS.wav", "answer": "we just received the suit and the document is massive it's two hundred pages", "subset": "bus", "task_type": "understanding", "prediction": "We just received the suit, and the document is massive. It is 200 pages.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 19, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020I_BUS.wav", "answer": "but on the first read through the case is without merit and we intend to fight it", "subset": "bus", "task_type": "understanding", "prediction": "but on the first read through the case stood without merit and we intend to fight it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 20, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020N_BUS.wav", "answer": "we're going to be bidders said a top official of a major oil company", "subset": "bus", "task_type": "understanding", "prediction": "we are going to be bidders said a top official of a major oil company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 21, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020P_BUS.wav", "answer": "the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding", "subset": "bus", "task_type": "understanding", "prediction": "The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26 per cent of its shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 22, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020T_BUS.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "bus", "task_type": "understanding", "prediction": "Volume was modest, as 326.7 million shares changed hands compared to 396.5 million Friday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 23, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020W_BUS.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "bus", "task_type": "understanding", "prediction": "Yesterday, Moody S. Investors Service raised Locus credit ratings in recognition of the improved outlook for steady financial recovery.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 24, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020X_BUS.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "bus", "task_type": "understanding", "prediction": "about three point five billion dollars of securities are affected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 25, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020Y_BUS.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "bus", "task_type": "understanding", "prediction": "He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 26, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C020Z_BUS.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "bus", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 27, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_442C0210_BUS.wav", "answer": "he declined to name specific products", "subset": "bus", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 28, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C0202_BUS.wav", "answer": "the department previously said jobs rose by four hundred forty eight thousand in january", "subset": "bus", "task_type": "understanding", "prediction": "The department previously said jobs rose by 448000 in January", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 29, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C0203_BUS.wav", "answer": "using a measure that counts the military among the employed the rate was unchanged at six point six percent last month", "subset": "bus", "task_type": "understanding", "prediction": "Using a measure that counts the military among the employed, the rate was unchanged at 6.6% last month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 30, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C0205_BUS.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "bus", "task_type": "understanding", "prediction": "MICC said it intends to pay the dividend to holders on July 31 to stock of record July 2.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 31, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C0206_BUS.wav", "answer": "the toronto based company provides mortgage guarantees to the canadian real estate industry", "subset": "bus", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to the Canadian real estate industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 32, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C0207_BUS.wav", "answer": "it isn't clear yet whether the campaign works", "subset": "bus", "task_type": "understanding", "prediction": "isn clear yet whether the campaign works", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 33, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C020D_BUS.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty", "subset": "bus", "task_type": "understanding", "prediction": "Among export LED electrical and computer makers. Japan Victor Company fell 50 to 2320.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 34, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C020G_BUS.wav", "answer": "the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "bus", "task_type": "understanding", "prediction": "The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 35, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C020I_BUS.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "bus", "task_type": "understanding", "prediction": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of 1987", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 36, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C020J_BUS.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "bus", "task_type": "understanding", "prediction": "Companies are listed where transactions generally aggregate 10000 shares or 100 or less dollars.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 37, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_443C0210_BUS.wav", "answer": "the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share", "subset": "bus", "task_type": "understanding", "prediction": "The companies are followed by at least three analysts who had a minimum 5 cent change in actual earnings per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 38, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C0201_BUS.wav", "answer": "in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share", "subset": "bus", "task_type": "understanding", "prediction": "In the 1985 quarter, the owner and operator of health maintenance organizations earned $6.9 million or 24 cents a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 39, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C0202_BUS.wav", "answer": "it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars", "subset": "bus", "task_type": "understanding", "prediction": "It had forecast a 1986 fourth quarter loss of $18 million to $22 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 40, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C020B_BUS.wav", "answer": "monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference", "subset": "bus", "task_type": "understanding", "prediction": "Monday's crash is likely to affect at least one other piece of pending legislation, the sweeping trade bill that is now the subject of a House Senate conference.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 41, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C020C_BUS.wav", "answer": "senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash", "subset": "bus", "task_type": "understanding", "prediction": "Senate Finance Chairman Lloyd Bentsen of D. Texas said he would speed up work on the package, because of the crash.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 42, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C020D_BUS.wav", "answer": "it adds to the support for the trade bill getting through he said", "subset": "bus", "task_type": "understanding", "prediction": "it adds to the support for the trade bill getting through he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 43, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C020F_BUS.wav", "answer": "so far they have declined to comment publicly on their plans", "subset": "bus", "task_type": "understanding", "prediction": "so far they have declined to comment publicly on their plans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 44, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C020G_BUS.wav", "answer": "state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do", "subset": "bus", "task_type": "understanding", "prediction": "State officials, however, say the airlines have indicated they will comply with most of the standards as long as competitors do.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 45, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C020H_BUS.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty", "subset": "bus", "task_type": "understanding", "prediction": "Among export led computer makers Japan Victor Company sold 50 to 2320.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 46, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C020Y_BUS.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday", "subset": "bus", "task_type": "understanding", "prediction": "Volume was 18190000 shares compared with 10550000 Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 47, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C0210_BUS.wav", "answer": "the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent", "subset": "bus", "task_type": "understanding", "prediction": "The institute said earned premiums showed 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 48, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C0214_BUS.wav", "answer": "money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "subset": "bus", "task_type": "understanding", "prediction": "Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 49, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_444C0215_BUS.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "bus", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts with incentives aimed at reducing their output", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 50, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C0208_BUS.wav", "answer": "their business isn't just a job but their investment", "subset": "bus", "task_type": "understanding", "prediction": "their business isn t just a job it s their investment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 51, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020I_BUS.wav", "answer": "the airline imposed the contract without union bargaining", "subset": "bus", "task_type": "understanding", "prediction": "The airline imposed the contract, without union bargaining.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 52, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020J_BUS.wav", "answer": "yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling", "subset": "bus", "task_type": "understanding", "prediction": "Yesterday session began with a sharp, quick decline in the industrial average of more than 45 points, which some market analysts attributed to foreign selling.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 53, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020M_BUS.wav", "answer": "gillette is again a target of a major corporate raider", "subset": "bus", "task_type": "understanding", "prediction": "gillette is again a target of a major corporate raid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 54, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020O_BUS.wav", "answer": "a lengthy fight is likely", "subset": "bus", "task_type": "understanding", "prediction": "a lengthy fight is likely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 55, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020P_BUS.wav", "answer": "about all the businessman can count on is that policy will be pretty volatile", "subset": "bus", "task_type": "understanding", "prediction": "About all that businessmen can count on is that policy will be pretty volatile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 56, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020R_BUS.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "bus", "task_type": "understanding", "prediction": "if the fed pushes the dollar higher it may curb the demand for u s exports", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 57, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020X_BUS.wav", "answer": "continental started the appeal process but recently settled the case", "subset": "bus", "task_type": "understanding", "prediction": "Continental started the appeal process for a recently settled case", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 58, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C020Y_BUS.wav", "answer": "neither side would disclose terms", "subset": "bus", "task_type": "understanding", "prediction": "neither side would disclose terms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 59, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_445C0213_BUS.wav", "answer": "from america china looked good", "subset": "bus", "task_type": "understanding", "prediction": "from america china looks good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 60, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C0206_BUS.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "bus", "task_type": "understanding", "prediction": "we are not prepared to be advocates for the kgb", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 61, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020B_BUS.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "bus", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 62, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020C_BUS.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "bus", "task_type": "understanding", "prediction": "The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 63, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020E_BUS.wav", "answer": "fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments", "subset": "bus", "task_type": "understanding", "prediction": "Fidelity had contended that Gen Corp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 64, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020I_BUS.wav", "answer": "he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year", "subset": "bus", "task_type": "understanding", "prediction": "He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 65, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020K_BUS.wav", "answer": "in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty", "subset": "bus", "task_type": "understanding", "prediction": "in many ways that is just what ubs has done since mr sanders became president in may today", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 66, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020L_BUS.wav", "answer": "assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven", "subset": "bus", "task_type": "understanding", "prediction": "Assets more than doubled since then to 160.4 million Swiss francs. $115.6 billion in 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 67, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020N_BUS.wav", "answer": "the real estate investment trust said it was still hoping to reach a new credit arrangement", "subset": "bus", "task_type": "understanding", "prediction": "The real estate investment trust said it was still hoping to reach a new credit arrangement.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 68, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020S_BUS.wav", "answer": "among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women", "subset": "bus", "task_type": "understanding", "prediction": "Among men,41% supported boosting the space exploration budget compared with 19% of women.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 69, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020T_BUS.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "bus", "task_type": "understanding", "prediction": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u s durable goods rose two point four percent last month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 70, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020V_BUS.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "bus", "task_type": "understanding", "prediction": "The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 71, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_446C020W_BUS.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "bus", "task_type": "understanding", "prediction": "durable goods reports frequently are highly volatile from month to month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 72, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C0201_BUS.wav", "answer": "i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month", "subset": "bus", "task_type": "understanding", "prediction": "I dont mean there couldnt be some improvements in the retroactive 1986, which took effect this month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 73, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C0206_BUS.wav", "answer": "he cites the law of large numbers can you really expect it to grow at large numbers very long", "subset": "bus", "task_type": "understanding", "prediction": "He cites the law of large numbers. Can you really expect it to grow at large numbers very long.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 74, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C0209_BUS.wav", "answer": "washington national is a financial services concern", "subset": "bus", "task_type": "understanding", "prediction": "Washington National is a financial services company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 75, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C020E_BUS.wav", "answer": "northgate exploration limited said it sold four million common shares at eight dollars each", "subset": "bus", "task_type": "understanding", "prediction": "northgate exploration limited said it sold four million common shares at eight dollars each", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 76, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C020H_BUS.wav", "answer": "the toronto based gold mining concern said proceeds would be used for general purposes", "subset": "bus", "task_type": "understanding", "prediction": "The Toronto based gold mining concern said proceeds would be used for general purposes.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 77, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C020M_BUS.wav", "answer": "envirodyne said it expects sales to be the highest for any third quarter in the company's history", "subset": "bus", "task_type": "understanding", "prediction": "Envirodyne said it expects sales to be the highest for any third quarter in the company s history", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 78, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C020Q_BUS.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "bus", "task_type": "understanding", "prediction": "The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 79, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C020S_BUS.wav", "answer": "but while the fed stands pat it is coming under increasing attack from both sides", "subset": "bus", "task_type": "understanding", "prediction": "but while the fed stands pat it is coming under increasing attack from both sides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 80, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C020T_BUS.wav", "answer": "some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year", "subset": "bus", "task_type": "understanding", "prediction": "Some critics, including high Reagan administration officials. Are raising the alarm that the Fed policy is too tight and could cause a recession next year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 81, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C020Y_BUS.wav", "answer": "increasingly people who test positive join the support groups that have sprung up across the country in the past year", "subset": "bus", "task_type": "understanding", "prediction": "increasingly people who test positive join the support groups that have sprung up across the country in the past year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 82, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C0210_BUS.wav", "answer": "founded last october new york's body positive already has sixteen groups meeting every two weeks", "subset": "bus", "task_type": "understanding", "prediction": "Founded last October, New Yorks body positive already has 16 groups meeting every two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 83, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_447C0211_BUS.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "bus", "task_type": "understanding", "prediction": "lately computer retailing has been tough on him and his", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 84, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C0206_BUS.wav", "answer": "two other issues began trading recently on the big board", "subset": "bus", "task_type": "understanding", "prediction": "Two other issues began trading recently, on the big board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 85, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C0208_BUS.wav", "answer": "union officials expect ratification", "subset": "bus", "task_type": "understanding", "prediction": "Union officials expect ratification.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 86, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C020A_BUS.wav", "answer": "despite the july decline durable goods orders remained seven point seven percent above the year earlier level", "subset": "bus", "task_type": "understanding", "prediction": "Despite the July decline, durable goods orders remain 7.7% above the year earlier level.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 87, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C020B_BUS.wav", "answer": "economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment", "subset": "bus", "task_type": "understanding", "prediction": "Economists were encouraged by a 1.6% increase in new orders for nondefense capital goods. An important indicator of future business investment.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 88, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C020K_BUS.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "bus", "task_type": "understanding", "prediction": "The transaction requires approval of a majority of shares of the holders, not affiliated with Mr. Icahn.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 89, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C020Q_BUS.wav", "answer": "the rise in auto imports also reflects higher prices for imported cars", "subset": "bus", "task_type": "understanding", "prediction": "The rise in auto imports also reflects higher prices for imported cars.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 90, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C020R_BUS.wav", "answer": "prices are going up said george c. eads vice president and chief economist at general motors corporation", "subset": "bus", "task_type": "understanding", "prediction": "Prices are going up, said George C. Ives, vice president and chief economist at General Motors Corporation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 91, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C020Z_BUS.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "bus", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 92, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C0211_BUS.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "bus", "task_type": "understanding", "prediction": "about three point five billion dollars of securities are affected", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 93, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_440C0212_BUS.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "bus", "task_type": "understanding", "prediction": "He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 94, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C0203_BUS.wav", "answer": "first commodity officials couldn't be reached for comment", "subset": "bus", "task_type": "understanding", "prediction": "First commodity officials couldn't be reached for comment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 95, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C0204_BUS.wav", "answer": "and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort", "subset": "bus", "task_type": "understanding", "prediction": "And then there is the explanation why Taro Danes growth in Japan is slow, despite 15 years of effort.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 96, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C020G_BUS.wav", "answer": "elders finance and elders agribusiness will remain based in australia", "subset": "bus", "task_type": "understanding", "prediction": "Elders finance and elders agribusiness will remain based in Australia.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 97, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C020K_BUS.wav", "answer": "the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "bus", "task_type": "understanding", "prediction": "The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 98, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C020R_BUS.wav", "answer": "too much focus is placed on reduction of cross country loans mr. meyerman said", "subset": "bus", "task_type": "understanding", "prediction": "Too much focus is placed on reductionist cross country lanes, Mr. Mayerman said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 99, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C020U_BUS.wav", "answer": "our guess is no", "subset": "bus", "task_type": "understanding", "prediction": "our guess is no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C020Z_BUS.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "bus", "task_type": "understanding", "prediction": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C0215_BUS.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "bus", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in the field.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_441C0216_BUS.wav", "answer": "he declined to name specific products", "subset": "bus", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C0202_BUS.wav", "answer": "accepted bids ranged from six point two percent to six point two two five percent", "subset": "bus", "task_type": "understanding", "prediction": "Accepted bids ranged from 6.2 per cent to 6.225 per cent.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C020E_BUS.wav", "answer": "under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents", "subset": "bus", "task_type": "understanding", "prediction": "Under Tokyo trading rules, the maximum one day drop for Sony is 500 yen, about $3.50.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C020M_BUS.wav", "answer": "even some bigger companies caution that they are leery of paying too big a premium", "subset": "bus", "task_type": "understanding", "prediction": "Even some bigger companies are cautious. They are leery of paying too big a dividend.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C020Q_BUS.wav", "answer": "in a dutch auction holders tender their shares at prices within a stated range in this case between twenty eight dollars and thirty three dollars a share", "subset": "bus", "task_type": "understanding", "prediction": "In a Dutch auction, holders tender their shares at prices within a stated range in this case between $28 and $33 a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C020S_BUS.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "bus", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower,1418.6.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C020V_BUS.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "bus", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C0212_BUS.wav", "answer": "foreigners are back and negotiating with the chinese will be as tough as ever", "subset": "bus", "task_type": "understanding", "prediction": "Foreigners are back and negotiating with the Chinese will be as tough as ever", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C0213_BUS.wav", "answer": "that's fine", "subset": "bus", "task_type": "understanding", "prediction": "that is fine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_442C0216_BUS.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "bus", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts with incentives aimed at reducing their costs.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_443C0204_BUS.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "bus", "task_type": "understanding", "prediction": "MICC Investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_443C020T_BUS.wav", "answer": "visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards", "subset": "bus", "task_type": "understanding", "prediction": "Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020A_BUS.wav", "answer": "in addition banks in general are being pushed by regulators to boost their capital positions", "subset": "bus", "task_type": "understanding", "prediction": "In addition, banks in general are being pushed by regulators to boost their capital position.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020E_BUS.wav", "answer": "several airlines have also opposed the standards and may fight some aspects in court", "subset": "bus", "task_type": "understanding", "prediction": "several airlines have also opposed the standards and may fight some aspects in court", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020I_BUS.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "bus", "task_type": "understanding", "prediction": "Yahoo, Sierra was up 60 at 5260.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020J_BUS.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "bus", "task_type": "understanding", "prediction": "70, which lost points in previous sessions, is being rebound at 80 to 5130.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020N_BUS.wav", "answer": "we didn't like that", "subset": "bus", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020Q_BUS.wav", "answer": "the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding", "subset": "bus", "task_type": "understanding", "prediction": "The offer is indicative of a price for the company exceeding $800 million based on 17.2 million shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020X_BUS.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "bus", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 308.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C020Z_BUS.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "bus", "task_type": "understanding", "prediction": "There were 256 issues advancing,303 declining and 292 unchanged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C0211_BUS.wav", "answer": "however investment income which represents thirteen percent of the industry's revenues rose eleven percent in the quarter reflecting gains from the rising stock market", "subset": "bus", "task_type": "understanding", "prediction": "However, investment income, which represents 13% of the industry's revenues, rose 11% in the quarter. Reflecting gains from the rising stock market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_444C0213_BUS.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "bus", "task_type": "understanding", "prediction": "A change in the firms ownership also should turn on a bright warning light.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C0201_BUS.wav", "answer": "owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged", "subset": "bus", "task_type": "understanding", "prediction": "Owens Illinois, that its share purchases will be financed by existing credit lines and new ones to be arranged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C0202_BUS.wav", "answer": "if all twenty million shares were purchased the company's equity would be reduced by about one third", "subset": "bus", "task_type": "understanding", "prediction": "If all 20 million shares were purchased. The company's equity would be reduced by about one third.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C0203_BUS.wav", "answer": "a spokesman said the company has about sixty million shares outstanding", "subset": "bus", "task_type": "understanding", "prediction": "a spokesman said the company had 60 million shares outstanding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C020B_BUS.wav", "answer": "but it is mr. west upon whom the outcome probably depends most", "subset": "bus", "task_type": "understanding", "prediction": "But it is Mr. West upon whom the outcome probably depends most.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C020C_BUS.wav", "answer": "testimony concluded this week and closing arguments are scheduled to begin monday", "subset": "bus", "task_type": "understanding", "prediction": "Testimony continues this week. Closing arguments are scheduled to begin, Sunday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C020D_BUS.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "bus", "task_type": "understanding", "prediction": "Grand autos,3 to 15 and 1.8 on the American Stock Market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C020N_BUS.wav", "answer": "coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board", "subset": "bus", "task_type": "understanding", "prediction": "Coniston Partners of New York said it has a 6.8% stake in Gillette and may seek to acquire the company or gain seats on its board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C020U_BUS.wav", "answer": "we had to sustain some modest operating losses", "subset": "bus", "task_type": "understanding", "prediction": "We had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C020V_BUS.wav", "answer": "we didn't like that", "subset": "bus", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C020Z_BUS.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "bus", "task_type": "understanding", "prediction": "NCI plans to begin offering the service at the end of this month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C0211_BUS.wav", "answer": "a print media campaign will begin the following day", "subset": "bus", "task_type": "understanding", "prediction": "A print media campaign will begin the following day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C0212_BUS.wav", "answer": "the real change though is in how china looks", "subset": "bus", "task_type": "understanding", "prediction": "The real change, though, is in how China looks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C0214_BUS.wav", "answer": "the numbers looked amazingly good industrial growth rates above ten percent per year year after year", "subset": "bus", "task_type": "understanding", "prediction": "The numbers looked amazingly good. Industrial growth rate of 10% per year, year after year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_445C0215_BUS.wav", "answer": "and after a temporary downturn in the next couple of years the numbers probably will go back up", "subset": "bus", "task_type": "understanding", "prediction": "And after a temporary downturn in the next couple of years. The numbers probably will go up.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C0201_BUS.wav", "answer": "here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva", "subset": "bus", "task_type": "understanding", "prediction": "Here are price trends on the world's major stock markets, as calculated by Morgan Stanley, Capital International Perspective, Geneva.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C0204_BUS.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "bus", "task_type": "understanding", "prediction": "The consensus was that a new piece of paper isn't required to send one US diplomat.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C0205_BUS.wav", "answer": "no one at the state department wants to let spies in", "subset": "bus", "task_type": "understanding", "prediction": "no one at the state department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C0208_BUS.wav", "answer": "but the investigation could make some lenders wary", "subset": "bus", "task_type": "understanding", "prediction": "but the investigation could make some lenders wary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C0209_BUS.wav", "answer": "mr. icahn and an investor group he heads hold seventy two point seven percent of t. w. a.'s shares", "subset": "bus", "task_type": "understanding", "prediction": "Mr. Icahn and an investor group he heads hold 72.7% of TWA shares.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020A_BUS.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "bus", "task_type": "understanding", "prediction": "Separately, New York State sold about $77.1 million of certificates of participation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020D_BUS.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "bus", "task_type": "understanding", "prediction": "The issue is rated single A by Moody S and single A minus by S P.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020J_BUS.wav", "answer": "in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars", "subset": "bus", "task_type": "understanding", "prediction": "In fiscal 1987, Wang had a loss of $78.7 million, or $2.84 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020M_BUS.wav", "answer": "net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in the period", "subset": "bus", "task_type": "understanding", "prediction": "Net income rose 125% to 753 million Swiss francs in the period.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020O_BUS.wav", "answer": "we're not ready to say we're in technical default a spokesman said", "subset": "bus", "task_type": "understanding", "prediction": "we are not ready to say we are in this type of default a spokesman said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020R_BUS.wav", "answer": "among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agreed", "subset": "bus", "task_type": "understanding", "prediction": "Among men,56% said the US was doing too little in space exploration. Only a quarter of women agreed.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020X_BUS.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "bus", "task_type": "understanding", "prediction": "Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C020Z_BUS.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "bus", "task_type": "understanding", "prediction": "Republic of New York, where his wife suffered a hemorrhage of 45 and 7/8.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_446C0210_BUS.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "bus", "task_type": "understanding", "prediction": "The company said its European banking affiliate in the Czech Republic plans to raise more than $450 million through an international offering.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C0202_BUS.wav", "answer": "i have my list of changes i'd like to see", "subset": "bus", "task_type": "understanding", "prediction": "i have my list of changes i would like to see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C0205_BUS.wav", "answer": "he doesn't", "subset": "bus", "task_type": "understanding", "prediction": "He doesn't.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C0208_BUS.wav", "answer": "before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company", "subset": "bus", "task_type": "understanding", "prediction": "Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C020G_BUS.wav", "answer": "the underwriting group has a thirty day option to acquire an additional five hundred thousand shares at eight dollars each", "subset": "bus", "task_type": "understanding", "prediction": "The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C020I_BUS.wav", "answer": "it had fourteen point five million common shares outstanding before the issue", "subset": "bus", "task_type": "understanding", "prediction": "It had 14 plus 5 million common shares outstanding before the issue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C020J_BUS.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "bus", "task_type": "understanding", "prediction": "In the efforts to restore market confidence. Administration officials have emphasized that the economy is fundamentally sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C020K_BUS.wav", "answer": "that was certainly true last week", "subset": "bus", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C020N_BUS.wav", "answer": "it had sales of ninety one point five million dollars in the nineteen eighty six third quarter", "subset": "bus", "task_type": "understanding", "prediction": "It had sales of 91.5 million dollars in the 1986 third quarter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C020P_BUS.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "bus", "task_type": "understanding", "prediction": "The independent committee will require that holders accept the offer at a meeting expected to be held in December, T D Direct said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C020Z_BUS.wav", "answer": "several cities have versions of the british organization body positive", "subset": "bus", "task_type": "understanding", "prediction": "Several cities have versions of the British Organisation, Body Positivity.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C0212_BUS.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "bus", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C0213_BUS.wav", "answer": "we had to sustain some modest operating losses", "subset": "bus", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C0214_BUS.wav", "answer": "we didn't like that", "subset": "bus", "task_type": "understanding", "prediction": "we did not like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F06_447C0217_BUS.wav", "answer": "the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight", "subset": "bus", "task_type": "understanding", "prediction": "The low was 1270.19, and the high was 1273.88.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C0203_BUS.wav", "answer": "about half these managers are in the u. s.", "subset": "bus", "task_type": "understanding", "prediction": "About half these managers are in the US.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C0207_BUS.wav", "answer": "the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks", "subset": "bus", "task_type": "understanding", "prediction": "The agency isn't likely to take any action until the unions rank and file votes on the contract in 2 to three weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C020C_BUS.wav", "answer": "the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture", "subset": "bus", "task_type": "understanding", "prediction": "the rise in that category in july was led by increased orders for aircraft and parts non electrical machinery lumber and furniture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C020D_BUS.wav", "answer": "interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction", "subset": "bus", "task_type": "understanding", "prediction": "Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C020J_BUS.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "bus", "task_type": "understanding", "prediction": "The independent committee will recommend that holders accept the offer at a meeting expected to be held this summer. T W A said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C020L_BUS.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "bus", "task_type": "understanding", "prediction": "The investor now owns 73% of the company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C020M_BUS.wav", "answer": "texaco has three choices a company adviser says", "subset": "bus", "task_type": "understanding", "prediction": "Texaco has three choices, a company adviser says.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C020S_BUS.wav", "answer": "what we don't know is how much is price and how much is volume", "subset": "bus", "task_type": "understanding", "prediction": "We don't know how much is price and how much is volume.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_440C020Y_BUS.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "bus", "task_type": "understanding", "prediction": "Estimates for the gain ranged from 2% to 3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0201_BUS.wav", "answer": "first commodity appealed the expulsion and fine to the c. f. t. c.", "subset": "bus", "task_type": "understanding", "prediction": "First commodity appealed the expulsion and fine to the CFTC.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0202_BUS.wav", "answer": "a commission spokesman said a decision on the appeal is expected soon", "subset": "bus", "task_type": "understanding", "prediction": "a commission spokesman said a decision on the appeal is expected soon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0205_BUS.wav", "answer": "the language is a big problem", "subset": "bus", "task_type": "understanding", "prediction": "the language is a big problem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0206_BUS.wav", "answer": "in europe an american can at least read street signs", "subset": "bus", "task_type": "understanding", "prediction": "in europe an american can at least read street signs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0208_BUS.wav", "answer": "the overall gain the fifth in the past seven months followed a revised four point one percent increase in february", "subset": "bus", "task_type": "understanding", "prediction": "The overall gain, the fifth in the past seven months, followed a revised 4.1% increase in February.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020B_BUS.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "bus", "task_type": "understanding", "prediction": "Brand Otto, slip 3 to 15 at 1,8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020C_BUS.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "bus", "task_type": "understanding", "prediction": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020D_BUS.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "bus", "task_type": "understanding", "prediction": "It received no proposals that were in the best interests of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020E_BUS.wav", "answer": "elders brewing will be based outside australia because seventy percent of its assets are in britain and canada", "subset": "bus", "task_type": "understanding", "prediction": "Elders Brewing will be based outside Australia because 70% of its assets are in Britain and Canada.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020H_BUS.wav", "answer": "two years ago b. a. s. f. made three separate acquisitions in the u. s.", "subset": "bus", "task_type": "understanding", "prediction": "Two years ago, BASF made three separate acquisitions in the US.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020I_BUS.wav", "answer": "its biggest was the one billion dollar purchase of the united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry", "subset": "bus", "task_type": "understanding", "prediction": "Its biggest was the $1 billion purchase of a United Technologies Corporation. Inmont subsidiary, a major supplier of paint to the auto industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020J_BUS.wav", "answer": "today ninety percent of the four billion dollars of b. a. s. f. sales in the u. s. is produced there", "subset": "bus", "task_type": "understanding", "prediction": "today ninety percent of the four billion dollars of basf sales in the us is produced there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020L_BUS.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "bus", "task_type": "understanding", "prediction": "Those identified as beneficial owners hold at least 10% of a company's equity securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020M_BUS.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "bus", "task_type": "understanding", "prediction": "Unless otherwise noted, the changes involved direct holdings of common stock and took place in September and October 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020P_BUS.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "bus", "task_type": "understanding", "prediction": "if the dollar starts to plunge the fed may step up its defense of the currency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020Q_BUS.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "bus", "task_type": "understanding", "prediction": "If the Fed pushes the dollar higher. It may curb the demand for US exports.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020W_BUS.wav", "answer": "although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year", "subset": "bus", "task_type": "understanding", "prediction": "although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020X_BUS.wav", "answer": "the bond funds in particular provide robust yields for investors and hefty fees for underwriters", "subset": "bus", "task_type": "understanding", "prediction": "The bond funds, in particular, provide robust yields for investors and hefty fees for underwriters.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C020Y_BUS.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "bus", "task_type": "understanding", "prediction": "Republic, New York, rose one and one quarter to 45 and 7/8.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0210_BUS.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "bus", "task_type": "understanding", "prediction": "After the offering, Republic New York will hold about 49% of the affiliate.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0211_BUS.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "bus", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower at 1418.7.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_441C0213_BUS.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "bus", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C0204_BUS.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "bus", "task_type": "understanding", "prediction": "MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C0205_BUS.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "bus", "task_type": "understanding", "prediction": "MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C0206_BUS.wav", "answer": "the toronto based company provides mortgage guarantees to the canadian real estate industry", "subset": "bus", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to the Canadian real estate industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C0208_BUS.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "bus", "task_type": "understanding", "prediction": "The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C0209_BUS.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "bus", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C020B_BUS.wav", "answer": "shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said", "subset": "bus", "task_type": "understanding", "prediction": "Shamrock's pretax profit from the sale was $125 million, a spokeswoman said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C020D_BUS.wav", "answer": "sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday", "subset": "bus", "task_type": "understanding", "prediction": "Sony Corporation, for example, closed at $4950.50 a share yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C020O_BUS.wav", "answer": "but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders", "subset": "bus", "task_type": "understanding", "prediction": "But if the winning bids are as high as they were in some deals earlier this year, then we are not going to be winning bidders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C020R_BUS.wav", "answer": "the company then accepts the shares tendered at the lowest price needed to reach its total then pays that amount for all shares it purchases", "subset": "bus", "task_type": "understanding", "prediction": "The company then accepts the shares tendered at the lowest price needed to reach its total, then pays that amount for all shares in purchases.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C0211_BUS.wav", "answer": "so normalcy has returned", "subset": "bus", "task_type": "understanding", "prediction": "so normalcy has returned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_442C0215_BUS.wav", "answer": "money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "subset": "bus", "task_type": "understanding", "prediction": "Money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C0209_BUS.wav", "answer": "nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics", "subset": "bus", "task_type": "understanding", "prediction": "nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020A_BUS.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "bus", "task_type": "understanding", "prediction": "In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020B_BUS.wav", "answer": "that was certainly true last week", "subset": "bus", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020C_BUS.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "bus", "task_type": "understanding", "prediction": "Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020F_BUS.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "bus", "task_type": "understanding", "prediction": "Sony, which lost points in previous sessions this week, rebounded 80 to 5130.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020N_BUS.wav", "answer": "the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains", "subset": "bus", "task_type": "understanding", "prediction": "The official declined to elaborate on projections for non telephone operations. But cited several indicators of recent gains.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020O_BUS.wav", "answer": "he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force", "subset": "bus", "task_type": "understanding", "prediction": "He said the company has entered 16 smaller cellular markets this year and has expanded its financial services workforce.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020Q_BUS.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "bus", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020S_BUS.wav", "answer": "a print media campaign will begin the following day", "subset": "bus", "task_type": "understanding", "prediction": "A print media campaign will begin the following day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020V_BUS.wav", "answer": "in certain cases the cards are given free to subscribers", "subset": "bus", "task_type": "understanding", "prediction": "in certain cases the cards are given free to subscribers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C020W_BUS.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "bus", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 380.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_443C0214_BUS.wav", "answer": "nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty", "subset": "bus", "task_type": "understanding", "prediction": "Nissan lost 30 to 1520, and Toyota was down 30 to end the day at 2620.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C0207_BUS.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "bus", "task_type": "understanding", "prediction": "The issue is rated single A by Moody S and single A minus by F and P.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C0208_BUS.wav", "answer": "citicorp had twenty one point five billion dollars in capital at the end of last year", "subset": "bus", "task_type": "understanding", "prediction": "Citicorp had $21.5 billion in capital at the end of last year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C0209_BUS.wav", "answer": "as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions", "subset": "bus", "task_type": "understanding", "prediction": "as one of the most acquisition hungry of major banks the city corp is often required by regulators to raise additional capital as a condition of making acquisitions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C020K_BUS.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "bus", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C020L_BUS.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "bus", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C020P_BUS.wav", "answer": "in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday", "subset": "bus", "task_type": "understanding", "prediction": "In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C020R_BUS.wav", "answer": "the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year", "subset": "bus", "task_type": "understanding", "prediction": "The mid July increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C020S_BUS.wav", "answer": "incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst", "subset": "bus", "task_type": "understanding", "prediction": "Incentives can move around sales, but not create them, says Charles Brady, an Oppenheimer and Company auto stock analyst.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_444C0212_BUS.wav", "answer": "realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars", "subset": "bus", "task_type": "understanding", "prediction": "Realized capital gains increased 42% to $909 million from $640.9 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_445C0204_BUS.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "bus", "task_type": "understanding", "prediction": "the consensus was that a new piece of paper isn t required said one u s diplomat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_445C0209_BUS.wav", "answer": "and both mortgaged their homes to secure the loans they needed to start the business", "subset": "bus", "task_type": "understanding", "prediction": "And both mortgaged their homes to secure the loans they needed to start the business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_445C020A_BUS.wav", "answer": "a long list of other witnesses have also testified in the trial now in its fourth month", "subset": "bus", "task_type": "understanding", "prediction": "A long list of other witnesses have also testified in the trial now in its fourth month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_445C020G_BUS.wav", "answer": "the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists", "subset": "bus", "task_type": "understanding", "prediction": "the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_445C020Q_BUS.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "bus", "task_type": "understanding", "prediction": "if the dollar starts to plunge the fed may step up its defense of the currency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_445C020W_BUS.wav", "answer": "the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed", "subset": "bus", "task_type": "understanding", "prediction": "The judge awarded Mr. Sharonberg $105 million, a figure based on 10 years of profit. Had his project been completed.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_445C0216_BUS.wav", "answer": "where else in the third world is there so much energy and progress as in china", "subset": "bus", "task_type": "understanding", "prediction": "where else in the third world is there so much energy and progress as china", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_446C020F_BUS.wav", "answer": "under the proposed transaction the los angeles group would acquire the k. h. j. license and then sell itself to disney", "subset": "bus", "task_type": "understanding", "prediction": "under the proposed transaction the los angeles group would acquire the khj license and then sell itself to disney", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_446C020G_BUS.wav", "answer": "the closely held group doesn't have any significant assets according to william g. simon its president", "subset": "bus", "task_type": "understanding", "prediction": "The closely held group doesn't have any significant assets, according to William G. Simon, its president.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_446C020H_BUS.wav", "answer": "he said that for the full year wang is aiming for an after tax profit equal to three percent to five percent of sales", "subset": "bus", "task_type": "understanding", "prediction": "He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_446C0212_BUS.wav", "answer": "closely held times publishing also owns two washington based publications congressional quarterly which covers capitol hill and governing which covers state and local governments", "subset": "bus", "task_type": "understanding", "prediction": "Closely held times publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and governing, which covers state and local governments.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_446C0214_BUS.wav", "answer": "industry analysts value the company at about six hundred fifty million dollars", "subset": "bus", "task_type": "understanding", "prediction": "Industry analysts value the company at about $650 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C0203_BUS.wav", "answer": "and i'm sure you have your own list", "subset": "bus", "task_type": "understanding", "prediction": "and i am sure you have your own playlist", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C020A_BUS.wav", "answer": "united presidential is a life insurance company", "subset": "bus", "task_type": "understanding", "prediction": "United presidential is a life insurance company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C020B_BUS.wav", "answer": "these are uneducated people he says in english so the patients won't understand", "subset": "bus", "task_type": "understanding", "prediction": "These are uneducated people, he says, in English. So the patients won't understand.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C020D_BUS.wav", "answer": "i will tell you what i think in my office", "subset": "bus", "task_type": "understanding", "prediction": "i will tell you what i think in my office", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C020F_BUS.wav", "answer": "they were sold to underwriters led by prudential bache securities incorporated", "subset": "bus", "task_type": "understanding", "prediction": "they were sold to underwriters led by prudential bache securities incorporated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C020R_BUS.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "bus", "task_type": "understanding", "prediction": "The investor now owns 73% of the company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C020V_BUS.wav", "answer": "manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid", "subset": "bus", "task_type": "understanding", "prediction": "Manhattan Industries continued to trade above the offer price yesterday, indicating the market expects a higher bid.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M05_447C0215_BUS.wav", "answer": "shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level", "subset": "bus", "task_type": "understanding", "prediction": "The Shearson Lehman Incorporateds index of long term Treasury bonds stayed in a very small range yesterday, finishing very close to Wednesday's closing level.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C0201_BUS.wav", "answer": "at n. e. c. the need for international managers will keep rising", "subset": "bus", "task_type": "understanding", "prediction": "At NEC, the need for international managers will keep rising.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C0205_BUS.wav", "answer": "the company previously traded over the counter", "subset": "bus", "task_type": "understanding", "prediction": "the company previously traded over the counter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C020N_BUS.wav", "answer": "it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan", "subset": "bus", "task_type": "understanding", "prediction": "It can sign on to the plan. File a competing plan or take a completely passive role that neither endorses nor opposes the plan.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C020U_BUS.wav", "answer": "the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction", "subset": "bus", "task_type": "understanding", "prediction": "The rate on the latest three month bill declined to 6.43%. Bid from an average of 6.53%. at a Tuesday auction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C020V_BUS.wav", "answer": "the rate on six month bills fell to six point seven three percent from six point eight three percent", "subset": "bus", "task_type": "understanding", "prediction": "The rate on six month bills fell to 6.73% from 6.8%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C020W_BUS.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "bus", "task_type": "understanding", "prediction": "Durable goods reports frequently are highly volatile, from month to month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C020X_BUS.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "bus", "task_type": "understanding", "prediction": "Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated jump increase.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C0213_BUS.wav", "answer": "he said such product would be marketed by other companies with experience in that business", "subset": "bus", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_440C0214_BUS.wav", "answer": "he declined to name specific products", "subset": "bus", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C0209_BUS.wav", "answer": "the earlier rise was previously reported as four point three percent", "subset": "bus", "task_type": "understanding", "prediction": "The earlier rise was previously reported, as 4.3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C020A_BUS.wav", "answer": "if defense is excluded march orders rose one percent after a three percent increase in february", "subset": "bus", "task_type": "understanding", "prediction": "If defenses excluded, March orders rose 1% after a 3% increase in February.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C020F_BUS.wav", "answer": "also a move to base it abroad will have tax advantages", "subset": "bus", "task_type": "understanding", "prediction": "also a move to base abroad will have tax advantages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C020N_BUS.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "bus", "task_type": "understanding", "prediction": "Companies are listed where transactions generally aggregate 10000 shares, or $100000.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C020O_BUS.wav", "answer": "about all businessmen can count on is that policy will be pretty volatile", "subset": "bus", "task_type": "understanding", "prediction": "About all the business in can count on is that policy will be pretty volatile.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C020S_BUS.wav", "answer": "analysts haven't focused on what happened to them", "subset": "bus", "task_type": "understanding", "prediction": "analysts have been focused on what happened today", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C020V_BUS.wav", "answer": "closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities", "subset": "bus", "task_type": "understanding", "prediction": "Closed end funds are traded on exchanges like stocks, but invest in a wide portfolio of other securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_441C0212_BUS.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "bus", "task_type": "understanding", "prediction": "Volume was modest, as 326.7 million shares changed hands, compared with 396.5 million Friday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C0203_BUS.wav", "answer": "the bank holding company slated another fifty million dollar sale next tuesday", "subset": "bus", "task_type": "understanding", "prediction": "The bank holding company slated another $50 million sale next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C0207_BUS.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "bus", "task_type": "understanding", "prediction": "Grand Auto slid 3 to 15 and 1/8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C020C_BUS.wav", "answer": "shamrock has interests in television and radio stations energy services real estate and venture capital", "subset": "bus", "task_type": "understanding", "prediction": "The shamrock has interests in television and radio stations, energy services. real estate and venture capital.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C020F_BUS.wav", "answer": "this morning the asking price for the stock was four thousand eight hundred fifty but there are were no buyers", "subset": "bus", "task_type": "understanding", "prediction": "this morning we asked price for this stock four thousand eight hundred and fifty but there were no buyers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C020G_BUS.wav", "answer": "a monsanto spokesman said there's very little we can say", "subset": "bus", "task_type": "understanding", "prediction": "a monsanto spokesman said there is very little weakness in the company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C020J_BUS.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "bus", "task_type": "understanding", "prediction": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for US durable goods rose two point four percent last month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C020K_BUS.wav", "answer": "that would follow a two point two percent drop in may", "subset": "bus", "task_type": "understanding", "prediction": "That would follow a 2.2% drop in May.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C020L_BUS.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "bus", "task_type": "understanding", "prediction": "The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C020U_BUS.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "bus", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_442C0214_BUS.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "bus", "task_type": "understanding", "prediction": "A change in the firms ownership also should turn one of the right corner.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C0201_BUS.wav", "answer": "the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before", "subset": "bus", "task_type": "understanding", "prediction": "The Labor Department said nonfarm payroll employment increased a robust 337000 last month after a revised 319000 gain the month before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C0208_BUS.wav", "answer": "local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members", "subset": "bus", "task_type": "understanding", "prediction": "Local membership jumped 22 per cent but the union has already lost 28 of the 73 new members", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020E_BUS.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "bus", "task_type": "understanding", "prediction": "Kyocera was up 60 at 5. Now it is at 260.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020H_BUS.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "bus", "task_type": "understanding", "prediction": "Those identified as beneficial owners hold at least 10% of the company securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020K_BUS.wav", "answer": "after the third period ashland's coal operations began a process of becoming an independent company", "subset": "bus", "task_type": "understanding", "prediction": "After the third period, Ashland's coal operations began a process of becoming an independent company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020L_BUS.wav", "answer": "when its initial public offering is completed ashland is expected to retain a forty six percent stake", "subset": "bus", "task_type": "understanding", "prediction": "When its initial public offering is completed. Ashland is expected to retain a 46% stake.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020M_BUS.wav", "answer": "the new company ashland coal incorporated is listed on the new york stock exchange", "subset": "bus", "task_type": "understanding", "prediction": "The new company, Ashton, Cullum Corporation, is listed on the New York Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020P_BUS.wav", "answer": "in addition u. s. west data solutions business applied communications incorporated is working out well and performing ahead of all our schedules", "subset": "bus", "task_type": "understanding", "prediction": "In addition, US West data solutions business applied communications incorporated is working out well and performing ahead of all of our schedules.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020R_BUS.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "bus", "task_type": "understanding", "prediction": "As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020U_BUS.wav", "answer": "fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards", "subset": "bus", "task_type": "understanding", "prediction": "Fees range up to about $40 annually for basic cards and $60 a year for gold cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020X_BUS.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday", "subset": "bus", "task_type": "understanding", "prediction": "Volume was 18119000 shares, compared with 10550000 today.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020Y_BUS.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "bus", "task_type": "understanding", "prediction": "there were two hundred and fifty six issues advancing three hundred and three declining and two hundred and ninety two unchanged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C020Z_BUS.wav", "answer": "companies listed below reported quarterly profit substantially different from the average of analysts' estimates", "subset": "bus", "task_type": "understanding", "prediction": "Companies listed in the lab report quarterly profit substantially different from the average of analysts estimates.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C0211_BUS.wav", "answer": "estimated and actual results involving losses are omitted", "subset": "bus", "task_type": "understanding", "prediction": "Estimated and actual results in bolded boxes are omitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C0212_BUS.wav", "answer": "yesterday's losers included automobiles", "subset": "bus", "task_type": "understanding", "prediction": "yesterday s losers included automobiles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_443C0213_BUS.wav", "answer": "honda was down ten to one thousand nine hundred thirty", "subset": "bus", "task_type": "understanding", "prediction": "Honda was down 10 to 1930.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C0203_BUS.wav", "answer": "revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars", "subset": "bus", "task_type": "understanding", "prediction": "Revenue in the quarter more than doubled to $362.4 million from $149.2 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C0204_BUS.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "bus", "task_type": "understanding", "prediction": "Separately, New York State sold about $77.1 million in certificates of anticipation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C0205_BUS.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "bus", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5 percent in 1997 to 5.5 percent in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C0206_BUS.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "bus", "task_type": "understanding", "prediction": "The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers company underwriter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C020M_BUS.wav", "answer": "we had to sustain some modest operating losses", "subset": "bus", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C020O_BUS.wav", "answer": "the company declined to identify the bidders but said it received offers in the high forty dollars per share", "subset": "bus", "task_type": "understanding", "prediction": "The company declined to identify the bidders. But said it received offers in the high $40 per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C020T_BUS.wav", "answer": "the market's strength may show that demand isn't all a creation of incentives", "subset": "bus", "task_type": "understanding", "prediction": "The market strength may show that demand is in all a creation of incentives.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C020U_BUS.wav", "answer": "m. c. i. plans to begin offering the service at the end of the month", "subset": "bus", "task_type": "understanding", "prediction": "NCI plans to begin offering the service at the end of this month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C020V_BUS.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "bus", "task_type": "understanding", "prediction": "As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_444C020W_BUS.wav", "answer": "a print media campaign will begin the following day", "subset": "bus", "task_type": "understanding", "prediction": "A print media campaign will begin the following day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C0205_BUS.wav", "answer": "no one at the state department wants to let spies in", "subset": "bus", "task_type": "understanding", "prediction": "no one at the state department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C0206_BUS.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "bus", "task_type": "understanding", "prediction": "were not prepared to be advocates for the kentucky bank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C0207_BUS.wav", "answer": "but the penalties for failure are real", "subset": "bus", "task_type": "understanding", "prediction": "but the pallidus profile your heart", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C020E_BUS.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "bus", "task_type": "understanding", "prediction": "Company, which runs retail, one of its stores, told Shearson, Lehman Brothers, its financial adviser to terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C020F_BUS.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "bus", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C020H_BUS.wav", "answer": "the suit seeks to block the contract which would have raised pay levels but cut benefits", "subset": "bus", "task_type": "understanding", "prediction": "The suit seeks to block the contract. Which would have raised pay levels, but cut benefits.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C020K_BUS.wav", "answer": "but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close", "subset": "bus", "task_type": "understanding", "prediction": "but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday s close", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C020L_BUS.wav", "answer": "although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading", "subset": "bus", "task_type": "understanding", "prediction": "Although those gains eroded during the afternoon. Stock prices stayed within a narrow range of the past half hour of trading.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C020S_BUS.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "bus", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C020T_BUS.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "bus", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_445C0210_BUS.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "bus", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C0202_BUS.wav", "answer": "to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred", "subset": "bus", "task_type": "understanding", "prediction": "To make them directly comparable, each index is based on the close of 1969,100.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C0203_BUS.wav", "answer": "the percentage change is since year end", "subset": "bus", "task_type": "understanding", "prediction": "the percentage change is since year end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C0207_BUS.wav", "answer": "that doesn't mean mr. icahn has committed any wrongdoing", "subset": "bus", "task_type": "understanding", "prediction": "that does not mean mr akon has committed any wrongdoing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C020P_BUS.wav", "answer": "it's still unclear", "subset": "bus", "task_type": "understanding", "prediction": "it still unclear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C020Q_BUS.wav", "answer": "there was a striking split between the sexes with men more likely than women to favor space programs", "subset": "bus", "task_type": "understanding", "prediction": "There was a striking split between the sexes, with men more than likely to have went to favour space programmes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C020U_BUS.wav", "answer": "that would follow a two point two percent drop in may", "subset": "bus", "task_type": "understanding", "prediction": "that would follow a two point two percent drop in may", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C020Y_BUS.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "bus", "task_type": "understanding", "prediction": "estimates for the gain range from two percent to three percent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C0211_BUS.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "bus", "task_type": "understanding", "prediction": "After the offering, Republic near will hold about 49% of the company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_446C0213_BUS.wav", "answer": "it also owns three state business magazines in florida georgia and arizona", "subset": "bus", "task_type": "understanding", "prediction": "It also owns three state business magazines in Florida, Georgia and Arizona.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C0204_BUS.wav", "answer": "mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent", "subset": "bus", "task_type": "understanding", "prediction": "Mr. Robertson says he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C0207_BUS.wav", "answer": "washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own", "subset": "bus", "task_type": "understanding", "prediction": "Washington National paid $19 a share for the 2.6 million United presidential shares it didn't already own.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C020C_BUS.wav", "answer": "sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days", "subset": "bus", "task_type": "understanding", "prediction": "Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C020L_BUS.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "bus", "task_type": "understanding", "prediction": "Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C020O_BUS.wav", "answer": "the company expects to report its results in about two weeks", "subset": "bus", "task_type": "understanding", "prediction": "The company expects to report its results in about two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C020U_BUS.wav", "answer": "other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation", "subset": "bus", "task_type": "understanding", "prediction": "Other analysts say the Fed needs to tighten policy further to support the dollar and prevent inflation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C020W_BUS.wav", "answer": "the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape", "subset": "bus", "task_type": "understanding", "prediction": "The shares closed at $18.25, up 25 cents on the New York Stock Exchange composite tape.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C020X_BUS.wav", "answer": "salant shares closed unchanged on the big board at nine dollars and seventy five cents", "subset": "bus", "task_type": "understanding", "prediction": "Salon shares closed unchanged on the big board at $9.75.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/M06_447C0216_BUS.wav", "answer": "the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight", "subset": "bus", "task_type": "understanding", "prediction": "The index ended with a decline of 0.3,5.2,1272.18.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_440C0203_CAF.wav", "answer": "about half these managers are in the u. s.", "subset": "caf", "task_type": "understanding", "prediction": "about half these managers are in the us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_440C0207_CAF.wav", "answer": "the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks", "subset": "caf", "task_type": "understanding", "prediction": "The agency isn't likely to take any action until the unions rank and file votes on the contracts in 2 to three weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_440C020C_CAF.wav", "answer": "the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture", "subset": "caf", "task_type": "understanding", "prediction": "The rise in that category in July was LED by increased orders for aircraft and parts. Non electrical machinery, lumber and furniture.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_440C020D_CAF.wav", "answer": "interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction", "subset": "caf", "task_type": "understanding", "prediction": "Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_440C020L_CAF.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "caf", "task_type": "understanding", "prediction": "the investor now owns seventy three percent of the company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_440C020M_CAF.wav", "answer": "texaco has three choices a company adviser says", "subset": "caf", "task_type": "understanding", "prediction": "Texaco has three choices a company adviser says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_440C020S_CAF.wav", "answer": "what we don't know is how much is price and how much is volume", "subset": "caf", "task_type": "understanding", "prediction": "what we dont know is how much is price and how much is volume", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C0201_CAF.wav", "answer": "first commodity appealed the expulsion and fine to the c. f. t. c.", "subset": "caf", "task_type": "understanding", "prediction": "First, commodity appealed the expulsion and fine to the CFTC.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C0202_CAF.wav", "answer": "a commission spokesman said a decision on the appeal is expected soon", "subset": "caf", "task_type": "understanding", "prediction": "a commission spokesman said a decision on the appeal is expected soon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C0205_CAF.wav", "answer": "the language is a big problem", "subset": "caf", "task_type": "understanding", "prediction": "the language is a big problem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C0206_CAF.wav", "answer": "in europe an american can at least read street signs", "subset": "caf", "task_type": "understanding", "prediction": "in europe an american can at least use credit cards", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C0208_CAF.wav", "answer": "the overall gain the fifth in the past seven months followed a revised four point one percent increase in february", "subset": "caf", "task_type": "understanding", "prediction": "The overall gain, the fifth in the past seven months, followed a revised 4.1% increase in February.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C020E_CAF.wav", "answer": "elders brewing will be based outside australia because seventy percent of its assets are in britain and canada", "subset": "caf", "task_type": "understanding", "prediction": "Elders Brewing will be based outside Australia because 70% of its assets are in Britain and Canada.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C020H_CAF.wav", "answer": "two years ago b. a. s. f. made three separate acquisitions in the u. s.", "subset": "caf", "task_type": "understanding", "prediction": "Two years ago, B, A S, F made three separate acquisitions in the US.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C020I_CAF.wav", "answer": "its biggest was the one billion dollar purchase of united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry", "subset": "caf", "task_type": "understanding", "prediction": "Its biggest was the $1 billion purchase of United Technologies Corporation's Inmont subsidiary, a major supplier of paint to the auto industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C020J_CAF.wav", "answer": "today ninety percent of the four billion dollars of b. a. s. f. sales in the u. s. is produced there", "subset": "caf", "task_type": "understanding", "prediction": "today ninety percent of the four billion dollars of basf sales in the us is produced there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C020P_CAF.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "caf", "task_type": "understanding", "prediction": "if the dollar starts to plunge the fed may step up its defense of the currency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C020W_CAF.wav", "answer": "although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year", "subset": "caf", "task_type": "understanding", "prediction": "Although closed end funds have been around since at least the 1920s. They have boomed in popularity this year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_441C020X_CAF.wav", "answer": "the bond funds in particular provide robust yields for investors and hefty fees for underwriters", "subset": "caf", "task_type": "understanding", "prediction": "The bond funds in particular provide robust yields for investors and hefty fees for underwriters", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C0208_CAF.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "caf", "task_type": "understanding", "prediction": "The company, which runs retail automotive stores. Told shearson, Lehman Brothers, its financial adviser to terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C0209_CAF.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "caf", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C020B_CAF.wav", "answer": "shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said", "subset": "caf", "task_type": "understanding", "prediction": "Shamrock's pretax profit from the sale was $125 million, the spokesman said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C020D_CAF.wav", "answer": "sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday", "subset": "caf", "task_type": "understanding", "prediction": "Sony Corporation, for example, closed at ¥4950. $34.50 a share yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C020O_CAF.wav", "answer": "but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders", "subset": "caf", "task_type": "understanding", "prediction": "but if the winning bids are as high as they were in some deals earlier this year then we are not going to be winning bidders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C020R_CAF.wav", "answer": "the company then accepts the shares tendered at the lowest price needed to reach its total then pays that amount for all shares it purchases", "subset": "caf", "task_type": "understanding", "prediction": "The company then accepts the shares tendered at the lowest price needed to reach its total, then pays that amount for all shares it purchases.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C020S_CAF.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "caf", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C020U_CAF.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "caf", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_442C0211_CAF.wav", "answer": "so normalcy has returned", "subset": "caf", "task_type": "understanding", "prediction": "so normalcy has returned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C0204_CAF.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "caf", "task_type": "understanding", "prediction": "MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C0205_CAF.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "caf", "task_type": "understanding", "prediction": "MICC said it intends to pay the dividend arrears on July 31 to stock of record, July 7.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C0206_CAF.wav", "answer": "the toronto based company provides mortgage guarantees to the canadian real estate industry", "subset": "caf", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to the Canadian real estate industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C0209_CAF.wav", "answer": "nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics", "subset": "caf", "task_type": "understanding", "prediction": "Nonetheless, the union has moved the experiment to Richmond, Virginia, and has received inquiries from other unions about its tactics", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C020H_CAF.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "caf", "task_type": "understanding", "prediction": "Those identified as beneficial owners hold at least 10% of a company s equity securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C020I_CAF.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "caf", "task_type": "understanding", "prediction": "Unless otherwise noted, changes involve direct holdings of common stock and took place in September and October 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C020N_CAF.wav", "answer": "the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains", "subset": "caf", "task_type": "understanding", "prediction": "The official declined to elaborate on projections for Nontelephone operations, but cited several indicators of recent gains.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C020O_CAF.wav", "answer": "he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force", "subset": "caf", "task_type": "understanding", "prediction": "He said the company has entered 16 smaller cellular markets this year and has expanded its financial services portfolio.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C020V_CAF.wav", "answer": "in certain cases the cards are given free to subscribers", "subset": "caf", "task_type": "understanding", "prediction": "in certain cases the cards are given free to subscribers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_443C0214_CAF.wav", "answer": "nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty", "subset": "caf", "task_type": "understanding", "prediction": "Nissan lost 30 to 1520, and Toyota was down 30 to end the day at 2620.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C0208_CAF.wav", "answer": "citicorp had twenty one point five billion dollars in capital at the end of last year", "subset": "caf", "task_type": "understanding", "prediction": "Sydney Corp had $21.5 billion in capital at the end of last year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C0209_CAF.wav", "answer": "as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions", "subset": "caf", "task_type": "understanding", "prediction": "As one of the most acquisition hungry of major banks, Citicorp is often required by regulators to raise additional capital as a condition of making acquisitions.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C020J_CAF.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "caf", "task_type": "understanding", "prediction": "Sony, which lost points in previous sessions this week, rebounded 80 to 5103.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C020P_CAF.wav", "answer": "in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday", "subset": "caf", "task_type": "understanding", "prediction": "In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C020R_CAF.wav", "answer": "the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year", "subset": "caf", "task_type": "understanding", "prediction": "The mid july increase came even though automakers are offering incentives on fewer cars this year than they did last year or earlier this year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C020S_CAF.wav", "answer": "incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst", "subset": "caf", "task_type": "understanding", "prediction": "Incentives can move around sales, but not create them, said Charles Brady, an Oppenheimer and company auto stock analyst.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C020X_CAF.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "caf", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 380.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C0212_CAF.wav", "answer": "realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars", "subset": "caf", "task_type": "understanding", "prediction": "Realized capital gains increased 42% to $909 million from $640.9 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_444C0214_CAF.wav", "answer": "money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "subset": "caf", "task_type": "understanding", "prediction": "Money managers who sell their firms but then continue working for them may be less dedicated to the new ownership, they said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C0209_CAF.wav", "answer": "and both mortgaged their homes to secure the loans they needed to start the business", "subset": "caf", "task_type": "understanding", "prediction": "and both mortgaged their homes to secure the loans they needed to start the business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020A_CAF.wav", "answer": "a long list of other witnesses have also testified in the trial now in its fourth month", "subset": "caf", "task_type": "understanding", "prediction": "A long list of other witnesses have also testified in the trial, now in its fourth month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020D_CAF.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "caf", "task_type": "understanding", "prediction": "Grandada slid 3 to 15 and 1.8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020E_CAF.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "caf", "task_type": "understanding", "prediction": "The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020F_CAF.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "caf", "task_type": "understanding", "prediction": "They received no proposals that were in the best interest of the shareholders, the company said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020G_CAF.wav", "answer": "the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists", "subset": "caf", "task_type": "understanding", "prediction": "The order issued late Wednesday by Judge Sianna Murphy stems from a suit filed in federal court last month by the union representing the machinists.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020Q_CAF.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "caf", "task_type": "understanding", "prediction": "if the dollar starts to plunge the fed may step up its defense of the currency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020R_CAF.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "caf", "task_type": "understanding", "prediction": "if the fed pushes the dollar higher it may curb the demand for u s exports", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020W_CAF.wav", "answer": "the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed", "subset": "caf", "task_type": "understanding", "prediction": "The jury awarded Mr. Sharonberg $105 million, a figure based on 10 years of profits had his project been completed.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C020Z_CAF.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "caf", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C0211_CAF.wav", "answer": "a print media campaign will begin the following day", "subset": "caf", "task_type": "understanding", "prediction": "a print media campaign will begin the following day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_445C0216_CAF.wav", "answer": "where else in the third world is there so much energy and progress as in china", "subset": "caf", "task_type": "understanding", "prediction": "Where else in the third world is there so much energy and progress as in China.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C0204_CAF.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "caf", "task_type": "understanding", "prediction": "The consensus was that a new piece of paper isn't required, said one US diplomat.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C020D_CAF.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "caf", "task_type": "understanding", "prediction": "The issue is rated single A by Moody s and single A minus by S and P.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C020F_CAF.wav", "answer": "under the proposed transaction the los angeles group would acquire the k. h. j. license and then sell itself to disney", "subset": "caf", "task_type": "understanding", "prediction": "Under the proposed transaction, the Los Angeles group would acquire the KH Day license and then sell itself to Disney.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C020G_CAF.wav", "answer": "the closely held group doesn't have any significant assets according to william g. simon its president", "subset": "caf", "task_type": "understanding", "prediction": "The closely held group doesn't have any significant assets, according to William G. Hyman, its president.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C020H_CAF.wav", "answer": "he said that for the full year wang is aiming for an after tax profit equal to three percent to five percent of sales", "subset": "caf", "task_type": "understanding", "prediction": "He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C020Y_CAF.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "caf", "task_type": "understanding", "prediction": "Estimates for the gain range from 2% to 3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C020Z_CAF.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "caf", "task_type": "understanding", "prediction": "Republic, New York, rose 1 and 1 quarter to 45 and 7/8.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C0211_CAF.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "caf", "task_type": "understanding", "prediction": "after the offering republic new york will hold about forty nine percent of the affiliate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C0212_CAF.wav", "answer": "closely held times publishing also owns two washington based publications congressional quarterly which covers capitol hill and governing which covers state and local governments", "subset": "caf", "task_type": "understanding", "prediction": "Closely held times publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and Governing, which covers state and local governments.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_446C0214_CAF.wav", "answer": "industry analysts value the company at about six hundred fifty million dollars", "subset": "caf", "task_type": "understanding", "prediction": "Industry analysts value the company at about $650 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C0203_CAF.wav", "answer": "and i'm sure you have your own list", "subset": "caf", "task_type": "understanding", "prediction": "and i am sure you have your own list", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020A_CAF.wav", "answer": "united presidential is a life insurance company", "subset": "caf", "task_type": "understanding", "prediction": "united presidential is a life insurance company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020B_CAF.wav", "answer": "these are uneducated people he says in english so the patients won't understand", "subset": "caf", "task_type": "understanding", "prediction": "These are uneducated people, he says, in English. So the patients won't understand.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020D_CAF.wav", "answer": "i will tell you what i think in my office", "subset": "caf", "task_type": "understanding", "prediction": "i will tell you what i think in my office", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020F_CAF.wav", "answer": "they were sold to underwriters led by prudential bache securities incorporated", "subset": "caf", "task_type": "understanding", "prediction": "they were sold to underwriters led by prudential bache securities incorporated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020J_CAF.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "caf", "task_type": "understanding", "prediction": "In their efforts to restore market confidence. Administration officials have emphasized that the economy is fundamentally sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020K_CAF.wav", "answer": "that was certainly true last week", "subset": "caf", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020L_CAF.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "caf", "task_type": "understanding", "prediction": "Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020P_CAF.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "caf", "task_type": "understanding", "prediction": "The independent committee will recommend that holders accept the offer at a meeting expected to be held in December, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020R_CAF.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "caf", "task_type": "understanding", "prediction": "the investor now owns seventy three percent of the company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C020V_CAF.wav", "answer": "manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid", "subset": "caf", "task_type": "understanding", "prediction": "Manhattan Industries continued to trade above the offer price yesterday, indicating a market expects a higher bid.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C0211_CAF.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "caf", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C0212_CAF.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "caf", "task_type": "understanding", "prediction": "no one is making very much money on it acknowledges brian j kelly chairman of bell atlantic s investment development unit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F05_447C0215_CAF.wav", "answer": "shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level", "subset": "caf", "task_type": "understanding", "prediction": "Shearson, Lehman Hutton Incorporated index of long term Treasury bonds stayed in a very small range yesterday, finishing very close to Wednesdays closing level.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_440C0201_CAF.wav", "answer": "at n. e. c. the need for international managers will keep rising", "subset": "caf", "task_type": "understanding", "prediction": "At M, E, C, the need for international managers would keep rising.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_440C0205_CAF.wav", "answer": "the company previously traded over the counter", "subset": "caf", "task_type": "understanding", "prediction": "The company previously traded over the counter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_440C020N_CAF.wav", "answer": "it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan", "subset": "caf", "task_type": "understanding", "prediction": "It can sign on to the plan. File a competing plan or take a completely passive role that neither endorses nor opposes the plan.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_440C020U_CAF.wav", "answer": "the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction", "subset": "caf", "task_type": "understanding", "prediction": "The rate on the latest three month bills declined to 6.43% bid from an average of 6.53% set at the Tuesday auction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_440C020V_CAF.wav", "answer": "the rate on six month bills fell to six point seven three percent from six point eight three percent", "subset": "caf", "task_type": "understanding", "prediction": "The rate on six month bills fell to 6.73% from 6.83%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_440C020Y_CAF.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "caf", "task_type": "understanding", "prediction": "Estimates for the gain range from 2% to 3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C0209_CAF.wav", "answer": "the earlier rise was previously reported as four point three percent", "subset": "caf", "task_type": "understanding", "prediction": "the earlier rise was previously reported as four point three percent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C020A_CAF.wav", "answer": "if defense is excluded march orders rose one percent after a three percent increase in february", "subset": "caf", "task_type": "understanding", "prediction": "If defence excluded March orders rose 1% after a 3% increase in February.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C020C_CAF.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "caf", "task_type": "understanding", "prediction": "The company, which runs retail and automotive stores, told shearson Lehman Brothers, its financial adviser, to terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C020D_CAF.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "caf", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C020F_CAF.wav", "answer": "also a move to base it abroad will have tax advantages", "subset": "caf", "task_type": "understanding", "prediction": "Also, a move to base abroad will have tax advantages.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C020L_CAF.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "caf", "task_type": "understanding", "prediction": "Those identified as beneficial owners of at least 10% of the company face equity securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C020S_CAF.wav", "answer": "analysts haven't focused on what happened to them", "subset": "caf", "task_type": "understanding", "prediction": "analysts have focused on what happened to them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C020V_CAF.wav", "answer": "closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities", "subset": "caf", "task_type": "understanding", "prediction": "Closed end funds are traded on exchanges like stocks that invest in a wide portfolio of other securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C0210_CAF.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "caf", "task_type": "understanding", "prediction": "After the offering, Republic New York will hold about 49% of the unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_441C0213_CAF.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "caf", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C0203_CAF.wav", "answer": "the bank holding company slated another fifty million dollar sale next tuesday", "subset": "caf", "task_type": "understanding", "prediction": "The bank holding company slated another $50 million sale next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C0207_CAF.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "caf", "task_type": "understanding", "prediction": "Grant Auto slipped 3 to 15 and 1,8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C020C_CAF.wav", "answer": "shamrock has interests in television and radio stations energy services real estate and venture capital", "subset": "caf", "task_type": "understanding", "prediction": "Shamrock has interests in television and radio stations. Energy services, real estate and venture capital.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C020F_CAF.wav", "answer": "this morning the asking price for the stock was four thousand eight hundred fifty but there were no buyers", "subset": "caf", "task_type": "understanding", "prediction": "This morning, the asking price for the stock was 4850, but there were no buyers.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C020G_CAF.wav", "answer": "a monsanto spokesman said there's very little we can say", "subset": "caf", "task_type": "understanding", "prediction": "a monsanto spokesman said there is very little we can say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C020K_CAF.wav", "answer": "that would follow a two point two percent drop in may", "subset": "caf", "task_type": "understanding", "prediction": "That would follow a 2.2 per cent drop in May.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C020T_CAF.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "caf", "task_type": "understanding", "prediction": "Volume was modest, as 326.7 million shares changed hands, compared with 396.5 million Friday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C020Z_CAF.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "caf", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_442C0210_CAF.wav", "answer": "he declined to name specific products", "subset": "caf", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C0201_CAF.wav", "answer": "the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before", "subset": "caf", "task_type": "understanding", "prediction": "The Labor Department said non farm payroll employment increased to their best 337000 last month after revised 319000 gain the month before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C0208_CAF.wav", "answer": "local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members", "subset": "caf", "task_type": "understanding", "prediction": "Local membership jumped 22 per cent, but the union has already lost 28 of the 73 new members.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020C_CAF.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "caf", "task_type": "understanding", "prediction": "Employment looks strong, inflation is low, and consumer spending and investment are holding up reasonably well.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020J_CAF.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "caf", "task_type": "understanding", "prediction": "companies are listed where transactions generally aggregate ten thousand shares for one hundred thousand dollars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020K_CAF.wav", "answer": "after the third period ashland's coal operations began a process of becoming an independent company", "subset": "caf", "task_type": "understanding", "prediction": "After the third period, Ashland's coal operations began a process of becoming an independent company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020L_CAF.wav", "answer": "when its initial public offering is completed ashland is expected to retain a forty six percent stake", "subset": "caf", "task_type": "understanding", "prediction": "When its initial public offering is completed. Ashland is expected to retain a 46% stake.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020M_CAF.wav", "answer": "the new company ashland coal incorporated is listed on the new york stock exchange", "subset": "caf", "task_type": "understanding", "prediction": "The new company, Ashton, Cole Incorporated, is listed on the New York Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020P_CAF.wav", "answer": "in addition u. s. west's data solutions business applied communications incorporated is working out well and performed ahead of all our schedules", "subset": "caf", "task_type": "understanding", "prediction": "In addition, US West data solutions, business applied communications incorporated is working out well and performed ahead of all our schedules.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020R_CAF.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "caf", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020U_CAF.wav", "answer": "fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards", "subset": "caf", "task_type": "understanding", "prediction": "Fees range up to about $40 annually for basic cards and $60 a year for gold cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C020Z_CAF.wav", "answer": "companies listed below reported quarterly profit substantially different from the average of analysts' estimates", "subset": "caf", "task_type": "understanding", "prediction": "Companies listed below reported quarterly profit substantially different from the average of analyst estimates.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C0211_CAF.wav", "answer": "estimated and actual results involving losses are omitted", "subset": "caf", "task_type": "understanding", "prediction": "Estimating the actual results involving losses are omitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C0212_CAF.wav", "answer": "yesterday's losers included automobiles", "subset": "caf", "task_type": "understanding", "prediction": "yesterday s losers included automakers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_443C0213_CAF.wav", "answer": "honda was down ten to one thousand nine hundred thirty", "subset": "caf", "task_type": "understanding", "prediction": "Honda was down 10 to 1930.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C0203_CAF.wav", "answer": "revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars", "subset": "caf", "task_type": "understanding", "prediction": "Revenue in the quarter more than doubled to $362.4 million from $149.2 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020I_CAF.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "caf", "task_type": "understanding", "prediction": "Kyocera was up 60, at 5260.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020O_CAF.wav", "answer": "the company declined to identify the bidders but said it received offers in the high forty dollars per share", "subset": "caf", "task_type": "understanding", "prediction": "The company declined to identify the bidders. But said it received offers in the high $40 per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020T_CAF.wav", "answer": "the market's strength may show that demand isn't all a creation of incentives", "subset": "caf", "task_type": "understanding", "prediction": "The market strength may show that demand isn't all a creation of incentives.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020U_CAF.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "caf", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020V_CAF.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "caf", "task_type": "understanding", "prediction": "As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020W_CAF.wav", "answer": "a print media campaign will begin the following day", "subset": "caf", "task_type": "understanding", "prediction": "A print media campaign will begin the following day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020Y_CAF.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday", "subset": "caf", "task_type": "understanding", "prediction": "Volume was 18190000 shares, compared with 10550000 Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C020Z_CAF.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "caf", "task_type": "understanding", "prediction": "There were 256 issues advancing,303 declining and 292 unchanged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_444C0213_CAF.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "caf", "task_type": "understanding", "prediction": "A change in the firms ownership also should turn on the right warning light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C0207_CAF.wav", "answer": "but the penalties for failure are real", "subset": "caf", "task_type": "understanding", "prediction": "but the penalties for failure are real", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C020H_CAF.wav", "answer": "the suit seeks to block the contract which would have raised pay levels but cut benefits", "subset": "caf", "task_type": "understanding", "prediction": "The suit seeks to block the contract. Which would have raised pay levels, but cut benefits.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C020K_CAF.wav", "answer": "but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close", "subset": "caf", "task_type": "understanding", "prediction": "But to the surprise of almost everyone. Stock prices began a steady climb that pushed the average above 160.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C020L_CAF.wav", "answer": "although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading", "subset": "caf", "task_type": "understanding", "prediction": "Although gains eroded during the afternoon, stock prices stayed within a narrow range until the last half hour of trading.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C020P_CAF.wav", "answer": "about all the businessman can count on is that policy will be pretty volatile", "subset": "caf", "task_type": "understanding", "prediction": "About all the businessman can count on is that policy will be pretty volatile.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C020S_CAF.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "caf", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C020T_CAF.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "caf", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's Investment Development Unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_445C0210_CAF.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "caf", "task_type": "understanding", "prediction": "As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C0202_CAF.wav", "answer": "to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred", "subset": "caf", "task_type": "understanding", "prediction": "To make them directly comparable, each index is based on the close of 1969, equaling 100.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C0203_CAF.wav", "answer": "the percentage change is since year end", "subset": "caf", "task_type": "understanding", "prediction": "the percentage change is since year end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C0205_CAF.wav", "answer": "no one at the state department wants to let spies in", "subset": "caf", "task_type": "understanding", "prediction": "No one at the State Department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C0206_CAF.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "caf", "task_type": "understanding", "prediction": "were not prepared to be advocates for the kgb", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C0207_CAF.wav", "answer": "that doesn't mean mr. icahn has committed any wrongdoing", "subset": "caf", "task_type": "understanding", "prediction": "that does not mean mr aykcin has committed any wrongdoing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020A_CAF.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "caf", "task_type": "understanding", "prediction": "Separately, New York State sold about $77.1 million of certificates of participation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020B_CAF.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "caf", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020C_CAF.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "caf", "task_type": "understanding", "prediction": "The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers lead underwriter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020P_CAF.wav", "answer": "it's still unclear", "subset": "caf", "task_type": "understanding", "prediction": "it still unclear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020Q_CAF.wav", "answer": "there was a striking split between the sexes with men more likely than women to favor space programs", "subset": "caf", "task_type": "understanding", "prediction": "There was a striking split between the sexes, with men more likely than women to favour space programs.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020T_CAF.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "caf", "task_type": "understanding", "prediction": "According to the average estimate of 7 economists surveyed by Dow Jones, capital markets report new orders for US durable goods rose 2.4% last month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020U_CAF.wav", "answer": "that would follow a two point two percent drop in may", "subset": "caf", "task_type": "understanding", "prediction": "That would follow a 2.2% drop in May.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020V_CAF.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "caf", "task_type": "understanding", "prediction": "The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020W_CAF.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "caf", "task_type": "understanding", "prediction": "Durable goods reports frequently are highly volatile, from month to month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C020X_CAF.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "caf", "task_type": "understanding", "prediction": "Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_446C0213_CAF.wav", "answer": "it also owns three state business magazines in florida georgia and arizona", "subset": "caf", "task_type": "understanding", "prediction": "It also owns three state fairgrounds in Florida, Georgia and Arizona.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C0204_CAF.wav", "answer": "mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent", "subset": "caf", "task_type": "understanding", "prediction": "Mr. Robertson says he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C0207_CAF.wav", "answer": "washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own", "subset": "caf", "task_type": "understanding", "prediction": "Washington National paid $19 a share for the 2.6 million United Pacific shares. it didn't already own.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C020C_CAF.wav", "answer": "sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days", "subset": "caf", "task_type": "understanding", "prediction": "Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C020O_CAF.wav", "answer": "the company expects to report its results in about two weeks", "subset": "caf", "task_type": "understanding", "prediction": "The company expects to report its results in about two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C020U_CAF.wav", "answer": "other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation", "subset": "caf", "task_type": "understanding", "prediction": "Other analysts say the Fed needs to tighten policy further to support the dollar and prevent inflation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C020W_CAF.wav", "answer": "the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape", "subset": "caf", "task_type": "understanding", "prediction": "The shares closed $18.25,25 cents on the New York Stock Exchange composite tape.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C020X_CAF.wav", "answer": "salant shares closed unchanged on the big board at nine dollars and seventy five cents", "subset": "caf", "task_type": "understanding", "prediction": "Salant shares closed unchanged on the big board at $9.75.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C0213_CAF.wav", "answer": "we had to sustain some modest operating losses", "subset": "caf", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/F06_447C0216_CAF.wav", "answer": "the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight", "subset": "caf", "task_type": "understanding", "prediction": "The index ended with a decline of 0.35 point to 1272.18.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C0206_CAF.wav", "answer": "two other issues began trading recently on the big board", "subset": "caf", "task_type": "understanding", "prediction": "Two other issues began trading recently, on the big board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C0208_CAF.wav", "answer": "union officials expect ratification", "subset": "caf", "task_type": "understanding", "prediction": "union officials expect ratification", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020A_CAF.wav", "answer": "despite the july decline durable goods orders remained seven point seven percent above the year earlier level", "subset": "caf", "task_type": "understanding", "prediction": "Despite the July decline durable goods orders remained 7.7% above the year earlier level", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020B_CAF.wav", "answer": "economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment", "subset": "caf", "task_type": "understanding", "prediction": "economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020J_CAF.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "caf", "task_type": "understanding", "prediction": "The independent committee will recommend that holders accept the offer at a meeting expected to be held in December. Twa said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020K_CAF.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "caf", "task_type": "understanding", "prediction": "The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020Q_CAF.wav", "answer": "the rise in auto imports also reflects higher prices for imported cars", "subset": "caf", "task_type": "understanding", "prediction": "The rise in auto imports also reflects higher prices for imported cars.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020R_CAF.wav", "answer": "prices are going up said george c. eads vice president and chief economist at general motors corporation", "subset": "caf", "task_type": "understanding", "prediction": "Prices are going up, said George C. Eads, vice president and chief economist at General Motors Corporation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020X_CAF.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "caf", "task_type": "understanding", "prediction": "Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C020Z_CAF.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "caf", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C0211_CAF.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "caf", "task_type": "understanding", "prediction": "About $3.5 billion of securities are affected.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C0212_CAF.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "caf", "task_type": "understanding", "prediction": "He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C0213_CAF.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "caf", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_440C0214_CAF.wav", "answer": "he declined to name specific products", "subset": "caf", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C0203_CAF.wav", "answer": "first commodity officials couldn't be reached for comment", "subset": "caf", "task_type": "understanding", "prediction": "First commodity officials couldn't be reached for comment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C0204_CAF.wav", "answer": "and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort", "subset": "caf", "task_type": "understanding", "prediction": "and then there is the explanation of why teradyne s growth in japan is slow despite fifteen years of effort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C020B_CAF.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "caf", "task_type": "understanding", "prediction": "Grand Auto slid 3 to 15 and 1/8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C020G_CAF.wav", "answer": "elders finance and elders agribusiness will remain based in australia", "subset": "caf", "task_type": "understanding", "prediction": "elders finance and elders agribusiness will remain based in australia", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C020K_CAF.wav", "answer": "the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "caf", "task_type": "understanding", "prediction": "The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C020R_CAF.wav", "answer": "too much focus is placed on reduction of cross country loans mr. meyerman said", "subset": "caf", "task_type": "understanding", "prediction": "Too much focus is placed on reduction of cross country loans, Mr. Meyerman said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C020U_CAF.wav", "answer": "our guess is no", "subset": "caf", "task_type": "understanding", "prediction": "Our guess is, no.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C020Y_CAF.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "caf", "task_type": "understanding", "prediction": "Republic, New York, rose 1 and 1 quarter to 45, and 7/8.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C020Z_CAF.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "caf", "task_type": "understanding", "prediction": "The company said its European Banking affiliate. Safra Republic plans to raise more than $450 million through an international offering.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_441C0211_CAF.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "caf", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C0202_CAF.wav", "answer": "accepted bids ranged from six point two percent to six point two two five percent", "subset": "caf", "task_type": "understanding", "prediction": "Accepted bids ranged from 6.2% to 6.225%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C0204_CAF.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "caf", "task_type": "understanding", "prediction": "MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C020E_CAF.wav", "answer": "under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents", "subset": "caf", "task_type": "understanding", "prediction": "Under Tokyo trading rules the maximum one day drop for Sony is ¥500 about $3.50.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C020M_CAF.wav", "answer": "even some bigger companies caution that they are leery of paying too big a premium", "subset": "caf", "task_type": "understanding", "prediction": "Even some bigger companies caution that they are leery of paying too big a premium.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C020Q_CAF.wav", "answer": "in a dutch auction holders tender their shares at prices within a stated range in this case between twenty eight dollars and thirty three dollars a share", "subset": "caf", "task_type": "understanding", "prediction": "In a Dutch auction, holders tender their shares at prices within a stated range. In this case, between $28 and $33 a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C020V_CAF.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "caf", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C0212_CAF.wav", "answer": "foreigners are back and negotiating with the chinese will be as tough as ever", "subset": "caf", "task_type": "understanding", "prediction": "Foreigners are back and negotiating with the Chinese will be as tough as ever.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C0213_CAF.wav", "answer": "that's fine", "subset": "caf", "task_type": "understanding", "prediction": "thats fine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C0214_CAF.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "caf", "task_type": "understanding", "prediction": "A change in the firms ownership also should turn on a bright warning light.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_442C0216_CAF.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "caf", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts with incentives aimed at reducing that problem.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020A_CAF.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "caf", "task_type": "understanding", "prediction": "In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020B_CAF.wav", "answer": "that was certainly true last week", "subset": "caf", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020E_CAF.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "caf", "task_type": "understanding", "prediction": "Kyocera was up 60 at 5216.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020F_CAF.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "caf", "task_type": "understanding", "prediction": "Sony, which lost points in previous sessions this week, rebounded 80 to 5130.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020Q_CAF.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "caf", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020S_CAF.wav", "answer": "a print media campaign will begin the following day", "subset": "caf", "task_type": "understanding", "prediction": "A print media campaign will begin the following day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020T_CAF.wav", "answer": "visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards", "subset": "caf", "task_type": "understanding", "prediction": "Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020W_CAF.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "caf", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 380.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_443C020Y_CAF.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "caf", "task_type": "understanding", "prediction": "There were 256 issues advancing,303 declining and 292 unchanged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C0204_CAF.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "caf", "task_type": "understanding", "prediction": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C0207_CAF.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "caf", "task_type": "understanding", "prediction": "The issue is rated single A by Moody S and single A minus by S M T.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C020A_CAF.wav", "answer": "in addition banks in general are being pushed by regulators to boost their capital positions", "subset": "caf", "task_type": "understanding", "prediction": "In addition, banks in general are being pushed by regulators to boost their capital positions.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C020E_CAF.wav", "answer": "several airlines have also opposed the standards and may fight some aspects in court", "subset": "caf", "task_type": "understanding", "prediction": "Several airlines have also opposed the standards and may fight some aspects in court", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C020L_CAF.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "caf", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C020M_CAF.wav", "answer": "we had to sustain some modest operating losses", "subset": "caf", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C020N_CAF.wav", "answer": "we didn't like that", "subset": "caf", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C020Q_CAF.wav", "answer": "the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding", "subset": "caf", "task_type": "understanding", "prediction": "The offers indicate a total price for the company exceeding $800 million based on 17.2 million shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_444C0211_CAF.wav", "answer": "however investment income which represents thirteen percent of the industry's revenue rose eleven percent in the quarter reflecting gains from the rising stock market", "subset": "caf", "task_type": "understanding", "prediction": "however investment income which represents thirteen percent of the industry s revenue rose eleven percent in the quarter reflecting gains from the rising stock market", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0201_CAF.wav", "answer": "owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged", "subset": "caf", "task_type": "understanding", "prediction": "Owens Illinois said its share purchases would be financed by existing credit lines and new ones to be arranged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0202_CAF.wav", "answer": "if all twenty million shares were purchased the company's equity would be reduced by about one third", "subset": "caf", "task_type": "understanding", "prediction": "If all 20 million shares were purchased. The company's equity would be reduced by about one third.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0203_CAF.wav", "answer": "a spokesman said the company has about sixty million shares outstanding", "subset": "caf", "task_type": "understanding", "prediction": "A spokesman said the company has about 60 million shares outstanding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0204_CAF.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "caf", "task_type": "understanding", "prediction": "The consensus was that a new piece of paper isn't required, said one US diplomat.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0205_CAF.wav", "answer": "no one at the state department wants to let spies in", "subset": "caf", "task_type": "understanding", "prediction": "no one at the state department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C020B_CAF.wav", "answer": "but it is mr. west upon whom the outcome probably depends the most", "subset": "caf", "task_type": "understanding", "prediction": "But it is Mr. West upon whom the outcome probably depends the most.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C020C_CAF.wav", "answer": "testimony concluded this week and closing arguments are scheduled to begin monday", "subset": "caf", "task_type": "understanding", "prediction": "Testimony concluded this week, and closing arguments are scheduled to begin Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C020N_CAF.wav", "answer": "coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board", "subset": "caf", "task_type": "understanding", "prediction": "Coniston Partners of New York said it has a 6.8% stake in Gillette and may seek to acquire the company or gain seats on its board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C020U_CAF.wav", "answer": "we had to sustain some modest operating losses", "subset": "caf", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C020V_CAF.wav", "answer": "we didn't like that", "subset": "caf", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0212_CAF.wav", "answer": "the real change though is in how china looks", "subset": "caf", "task_type": "understanding", "prediction": "The real change, though, is in how China looks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0214_CAF.wav", "answer": "the numbers looked amazingly good industrial growth rates above ten percent per year year after year", "subset": "caf", "task_type": "understanding", "prediction": "The numbers looked amazingly good. Industrial growth rates above 10% per year, year after year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_445C0215_CAF.wav", "answer": "and after a temporary downturn in the next couple of years the numbers probably will go back up", "subset": "caf", "task_type": "understanding", "prediction": "and after a temporary downturn in the next couple of years the numbers probably will go back down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C0201_CAF.wav", "answer": "here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva", "subset": "caf", "task_type": "understanding", "prediction": "here are price trends on the worlds major stock markets as calculated by morgan stanley capital international perspective geneva", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C0208_CAF.wav", "answer": "but the investigation could make some lenders wary", "subset": "caf", "task_type": "understanding", "prediction": "but the investigation could make some lenders wary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C0209_CAF.wav", "answer": "mr. icahn and an investor group he heads hold seventy two point seven percent of t. w. a.'s shares", "subset": "caf", "task_type": "understanding", "prediction": "Mr. Icahn and an investor group he heads hold 72.7% of T W A s shares.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C020J_CAF.wav", "answer": "in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars", "subset": "caf", "task_type": "understanding", "prediction": "In fiscal 1987, Wang had a loss of $78.7 million on revenue of $2.84 billion.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C020M_CAF.wav", "answer": "net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in the period", "subset": "caf", "task_type": "understanding", "prediction": "Net income rose 125% to 753 million Swiss francs in the period.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C020O_CAF.wav", "answer": "we're not ready to say we're in technical default a spokesman said", "subset": "caf", "task_type": "understanding", "prediction": "We are not ready to say we are in technical default a spokesman said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C020R_CAF.wav", "answer": "among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agreed", "subset": "caf", "task_type": "understanding", "prediction": "among men fifty six percent said the u s was doing too little in space exploration only a quarter of women agreed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_446C0210_CAF.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "caf", "task_type": "understanding", "prediction": "The company said its European banking affiliate. Saffra Republic plans to raise more than $450 million through an international offering.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C0202_CAF.wav", "answer": "i have my list of changes i'd like to see", "subset": "caf", "task_type": "understanding", "prediction": "i have my list of changes i d like to see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C0205_CAF.wav", "answer": "he doesn't", "subset": "caf", "task_type": "understanding", "prediction": "he does not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C0208_CAF.wav", "answer": "before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company", "subset": "caf", "task_type": "understanding", "prediction": "Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C020G_CAF.wav", "answer": "the underwriting group has a thirty day option to acquire an additional six hundred thousand shares at eight dollars each", "subset": "caf", "task_type": "understanding", "prediction": "The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C020I_CAF.wav", "answer": "it had fourteen point five million common shares outstanding before the issue", "subset": "caf", "task_type": "understanding", "prediction": "It had 14.5 million common shares outstanding before the issue.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C020N_CAF.wav", "answer": "it had sales of ninety one point five million dollars in the nineteen eighty six third quarter", "subset": "caf", "task_type": "understanding", "prediction": "it had sales of ninety one point five million dollars in the nineteen eighty six third quarter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C020Z_CAF.wav", "answer": "several cities have versions of the british organization body positive", "subset": "caf", "task_type": "understanding", "prediction": "several cities have versions of the british organization body positive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C0214_CAF.wav", "answer": "we didn't like that", "subset": "caf", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M05_447C0217_CAF.wav", "answer": "the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight", "subset": "caf", "task_type": "understanding", "prediction": "The low was 1270.19, and the high was 1273.88.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C0202_CAF.wav", "answer": "the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years", "subset": "caf", "task_type": "understanding", "prediction": "The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C0204_CAF.wav", "answer": "r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.", "subset": "caf", "task_type": "understanding", "prediction": "Rli Corporation, a Peoria, Illinois, based insurance holding company, will begin trading Friday on the big board under the symbol Rli.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C0209_CAF.wav", "answer": "a p. b. g. c. spokeswoman declined comment", "subset": "caf", "task_type": "understanding", "prediction": "a p b g c spokesman declined comment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020E_CAF.wav", "answer": "the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last week", "subset": "caf", "task_type": "understanding", "prediction": "The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at the previous auction last week.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020F_CAF.wav", "answer": "the average rate on new twenty six week bills rose to six point one six percent from six point one two percent", "subset": "caf", "task_type": "understanding", "prediction": "The average rate on new 26 week bills rose to 6.16% from 6.12%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020G_CAF.wav", "answer": "analysts too generally played down the effect on banks", "subset": "caf", "task_type": "understanding", "prediction": "analysts too can make a point on the capital banks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020H_CAF.wav", "answer": "in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks", "subset": "caf", "task_type": "understanding", "prediction": "In a fundamental sense, the equity markets have very little to do with what goes on in the commercial banks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020I_CAF.wav", "answer": "there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company", "subset": "caf", "task_type": "understanding", "prediction": "There shouldnt be any risk to the banks in this sort of stuff said Lawrence Cohn a banking analyst at Merrill Lynch and Company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020O_CAF.wav", "answer": "unable to agree on friday the board must meet again at least by phone to register its choice", "subset": "caf", "task_type": "understanding", "prediction": "Unable to agree on Friday, the board must meet again, at least by phone, to register its choice.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020P_CAF.wav", "answer": "commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models", "subset": "caf", "task_type": "understanding", "prediction": "Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories with new models.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020T_CAF.wav", "answer": "rates fell on short term treasury bills", "subset": "caf", "task_type": "understanding", "prediction": "rates fell on short term treasury bills", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C020W_CAF.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "caf", "task_type": "understanding", "prediction": "Durable goods reports frequently are highly volatile, from month to month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_440C0210_CAF.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "caf", "task_type": "understanding", "prediction": "Yesterday, Moody S. Investor Service raised Lilco S credit rating in recognition of the improved outlook for steady financial recovery.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C0207_CAF.wav", "answer": "in japan it's all greek so to speak", "subset": "caf", "task_type": "understanding", "prediction": "in japan it is all greek so to speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C020M_CAF.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "caf", "task_type": "understanding", "prediction": "Unless otherwise noted, changes involved direct holdings of common stock and took place in September and October of 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C020N_CAF.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "caf", "task_type": "understanding", "prediction": "Companies are listed where transactions generally aggregate 10000 shares, or $100000.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C020O_CAF.wav", "answer": "about all businessmen can count on is that policy will be pretty volatile", "subset": "caf", "task_type": "understanding", "prediction": "About all businessmen can count on is that policy will be pretty volatile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C020Q_CAF.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "caf", "task_type": "understanding", "prediction": "If the Fed pushes the dollar higher. It may curb the demand for US exports.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C020T_CAF.wav", "answer": "has exposure really been reduced", "subset": "caf", "task_type": "understanding", "prediction": "has exposure really been reduced", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C0212_CAF.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "caf", "task_type": "understanding", "prediction": "The volume was modest, as 326.7 million shares changed hands, compared with 396.5 million Friday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C0214_CAF.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "caf", "task_type": "understanding", "prediction": "He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C0215_CAF.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "caf", "task_type": "understanding", "prediction": "It said such products would be marketed by other companies with experience in the business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_441C0216_CAF.wav", "answer": "he declined to name specific products", "subset": "caf", "task_type": "understanding", "prediction": "He declined to name specific products.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C0201_CAF.wav", "answer": "bids totaling five hundred twenty five point five million dollars were submitted", "subset": "caf", "task_type": "understanding", "prediction": "Bids totaling $525.5 million, were submitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C0205_CAF.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "caf", "task_type": "understanding", "prediction": "MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C0206_CAF.wav", "answer": "the toronto based company provides mortgage guarantees to the canadian real estate industry", "subset": "caf", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to the Canadian real estate industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020A_CAF.wav", "answer": "under terms previously reported the italian agricultural concern assumed that about one hundred ninety five million dollars in subordinated debt as part of the transaction", "subset": "caf", "task_type": "understanding", "prediction": "Under term, previously reported, the Italian agricultural concern assumed about $195 million in subordinated debt as part of the transaction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020H_CAF.wav", "answer": "we just received the suit and the document is is massive it's two hundred pages", "subset": "caf", "task_type": "understanding", "prediction": "We just received the suit and the document is massive. It is 200 pages.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020I_CAF.wav", "answer": "but on the first read through the case is without merit and we intend to fight it", "subset": "caf", "task_type": "understanding", "prediction": "But on the first read, through the case is without merit. And we intend to fight it.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020J_CAF.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "caf", "task_type": "understanding", "prediction": "According to the average estimate of 7 economists surveyed by Dow Jones Capital Markets Report. New orders for US durable goods rose 2.4% last month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020L_CAF.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "caf", "task_type": "understanding", "prediction": "The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020N_CAF.wav", "answer": "we're going to be bidders said a top official of a major oil company", "subset": "caf", "task_type": "understanding", "prediction": "We are going to be generous, said a top official of a major oil company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020P_CAF.wav", "answer": "the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding", "subset": "caf", "task_type": "understanding", "prediction": "The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26 of its shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020W_CAF.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "caf", "task_type": "understanding", "prediction": "Yesterday, Moody s investor service raised Lilco s credit rating in recognition of an improved outlook for steady financial recovery.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020X_CAF.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "caf", "task_type": "understanding", "prediction": "About $3.5 billion in securities are affected.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C020Y_CAF.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "caf", "task_type": "understanding", "prediction": "He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_442C0215_CAF.wav", "answer": "money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "subset": "caf", "task_type": "understanding", "prediction": "Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, he said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_443C0202_CAF.wav", "answer": "the department previously said jobs rose by four hundred forty eight thousand in january", "subset": "caf", "task_type": "understanding", "prediction": "The department previously said jobs rose by 448000 in January.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_443C0203_CAF.wav", "answer": "using a measure that counts the military among the employed the rate was unchanged at six point six percent last month", "subset": "caf", "task_type": "understanding", "prediction": "using a measure that counts the military among the employed the rate was unchanged at six point six percent last month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_443C0207_CAF.wav", "answer": "it isn't clear yet whether the campaign works", "subset": "caf", "task_type": "understanding", "prediction": "It isn't clear yet, whether the campaign works.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_443C020D_CAF.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty", "subset": "caf", "task_type": "understanding", "prediction": "Among export LED electrical and distributor makers. Japan Victor Company fell 52 to 2320.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_443C020G_CAF.wav", "answer": "the following officers directors and large stakeholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "caf", "task_type": "understanding", "prediction": "The following officers, directors and large stakeholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_443C020X_CAF.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday", "subset": "caf", "task_type": "understanding", "prediction": "volume was eighteen million one hundred and ninety thousand shares compared to ten million five hundred and fifty thousand monday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_443C0210_CAF.wav", "answer": "the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share", "subset": "caf", "task_type": "understanding", "prediction": "The companies are followed by at least three analysts and had a minimum 5 cent change in actual earnings per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C0201_CAF.wav", "answer": "in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share", "subset": "caf", "task_type": "understanding", "prediction": "In the 1985 quarter, the owner and operator of health maintenance organizations spent $6.9 million or 24 cents a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C0202_CAF.wav", "answer": "it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars", "subset": "caf", "task_type": "understanding", "prediction": "it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C0205_CAF.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "caf", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C0206_CAF.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "caf", "task_type": "understanding", "prediction": "The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C020B_CAF.wav", "answer": "monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference", "subset": "caf", "task_type": "understanding", "prediction": "mondays crashes likely as you affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C020C_CAF.wav", "answer": "senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash", "subset": "caf", "task_type": "understanding", "prediction": "Senate Finance Chairman Boyd Benson, D. Texas said he would speed up work on the package because of the crash.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C020D_CAF.wav", "answer": "it adds to the support for the trade bill getting through he said", "subset": "caf", "task_type": "understanding", "prediction": "It adds to the support for the trade bill getting through, he said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C020F_CAF.wav", "answer": "so far they have declined to comment publicly on their plans", "subset": "caf", "task_type": "understanding", "prediction": "So far, they have declined to comment publicly on their plans.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C020G_CAF.wav", "answer": "state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do", "subset": "caf", "task_type": "understanding", "prediction": "State officials, however, say the airlines have indicated they will comply with most of the standards as long as the competitors do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C020H_CAF.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty", "subset": "caf", "task_type": "understanding", "prediction": "Among export LED electrical and computer makers. Japan Vector Company fell 15 to 2320.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C020K_CAF.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "caf", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C0210_CAF.wav", "answer": "the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent", "subset": "caf", "task_type": "understanding", "prediction": "The institute said earned premiums rose 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_444C0215_CAF.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "caf", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts with incentives aimed at reducing that problem.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C0206_CAF.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "caf", "task_type": "understanding", "prediction": "whenever prepared to be advocates for the case you made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C0208_CAF.wav", "answer": "their business isn't just a job but their investment", "subset": "caf", "task_type": "understanding", "prediction": "Their business isn't just a job, but their investment.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C020I_CAF.wav", "answer": "the airline imposed the contract without union bargaining", "subset": "caf", "task_type": "understanding", "prediction": "The airline imposed the contract, without union bargaining.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C020J_CAF.wav", "answer": "yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling", "subset": "caf", "task_type": "understanding", "prediction": "Yesterday session began with a sharp, quick decline in the industrial average of more than 45 points, which some market analysts attributed to foreign selling.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C020M_CAF.wav", "answer": "gillette is again a target of a major corporate raider", "subset": "caf", "task_type": "understanding", "prediction": "Gillette is, again, a target of a major corporate.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C020O_CAF.wav", "answer": "a lengthy fight is likely", "subset": "caf", "task_type": "understanding", "prediction": "a lengthy fight is likely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C020X_CAF.wav", "answer": "continental started the appeal process but recently settled the case", "subset": "caf", "task_type": "understanding", "prediction": "Continental started the appeal process but recently set up the case", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C020Y_CAF.wav", "answer": "neither side would disclose terms", "subset": "caf", "task_type": "understanding", "prediction": "neither side would disclose terms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_445C0213_CAF.wav", "answer": "from america china looked good", "subset": "caf", "task_type": "understanding", "prediction": "From America, China looks good.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_446C020E_CAF.wav", "answer": "fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments", "subset": "caf", "task_type": "understanding", "prediction": "Fidelity had contended that Gen Corp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_446C020I_CAF.wav", "answer": "he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year", "subset": "caf", "task_type": "understanding", "prediction": "He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_446C020K_CAF.wav", "answer": "in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty", "subset": "caf", "task_type": "understanding", "prediction": "In many ways, that is just what UBS has done since Mr. Sanders became president in 1980.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_446C020L_CAF.wav", "answer": "assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven", "subset": "caf", "task_type": "understanding", "prediction": "Assets more than doubled since then to 160.4 million Swiss francs. $115.6 billion in 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_446C020N_CAF.wav", "answer": "the real estate investment trust said it was still hoping to reach a new credit arrangement", "subset": "caf", "task_type": "understanding", "prediction": "The real estate investment trust said it was still hoping to reach a new credit arrangement.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_446C020S_CAF.wav", "answer": "among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women", "subset": "caf", "task_type": "understanding", "prediction": "Among men,41% supported boosting the space exploration budget, compared with 90% of women.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C0201_CAF.wav", "answer": "i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month", "subset": "caf", "task_type": "understanding", "prediction": "i do not mean there could not be some improvements in the revenue act of nineteen eighty six which took effect last month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C0206_CAF.wav", "answer": "he cites the law of large numbers can you really expect it to grow at large numbers very long", "subset": "caf", "task_type": "understanding", "prediction": "He cites the law of large numbers. Can you really expect it to grow in large numbers, very long.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C0209_CAF.wav", "answer": "washington national is a financial services concern", "subset": "caf", "task_type": "understanding", "prediction": "Washington National is a financial services concern.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C020E_CAF.wav", "answer": "northgate exploration limited said it sold four million common shares at eight dollars each", "subset": "caf", "task_type": "understanding", "prediction": "Northgate Exploration Limited said it sold 4 million common shares at $8 each.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C020H_CAF.wav", "answer": "the toronto based gold mining concern said proceeds would be used for general purposes", "subset": "caf", "task_type": "understanding", "prediction": "The Toronto based gold mining concern said proceeds would be used for general purposes.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C020M_CAF.wav", "answer": "envirodyne said it expects sales to be the highest for any third quarter in the company's history", "subset": "caf", "task_type": "understanding", "prediction": "Envirodyne said it expects sales to be the highest for any third quarter in the company s history", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C020Q_CAF.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "caf", "task_type": "understanding", "prediction": "The transaction requires approval by a majority of the shares of the holders, not affiliated with Mr. Akon.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C020S_CAF.wav", "answer": "but while the fed stands pat it is coming under increasing attack from both sides", "subset": "caf", "task_type": "understanding", "prediction": "But while the Fed stands pat, it is coming under increasing attack from both sides.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C020T_CAF.wav", "answer": "some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year", "subset": "caf", "task_type": "understanding", "prediction": "Some critics, including high Reagan administration officials. Are raising the alarm that the Fed policy is too tight and could cause a recession next year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C020Y_CAF.wav", "answer": "increasingly people who test positive join the support groups that have sprung across the country in the past year", "subset": "caf", "task_type": "understanding", "prediction": "Increasingly, people who test positive join the support groups that have sprung across the country in the past year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_caf_real/M06_447C0210_CAF.wav", "answer": "founded last october new york's body positive already has sixteen groups meeting every two weeks", "subset": "caf", "task_type": "understanding", "prediction": "Nonetheless, October Newlands body positive already has 16 groups meeting every two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_440C0201_PED.wav", "answer": "at n. e. c. the need for international managers will keep rising", "subset": "ped", "task_type": "understanding", "prediction": "at nec the need for international mergers will keep rising", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_440C0205_PED.wav", "answer": "the company previously traded over the counter", "subset": "ped", "task_type": "understanding", "prediction": "the company previously traded over the counter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_440C020N_PED.wav", "answer": "it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan", "subset": "ped", "task_type": "understanding", "prediction": "It can sign on to the plan. File a competing plan or take a completely passive role that neither endorses nor opposes the plan.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_440C020U_PED.wav", "answer": "the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction", "subset": "ped", "task_type": "understanding", "prediction": "The rate on the latest three month bills declined to 6.43% bid from an average of 6.53% set at Tuesday auction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_440C020V_PED.wav", "answer": "the rate on six month bills fell to six point seven three percent from six point eight three percent", "subset": "ped", "task_type": "understanding", "prediction": "the rate on six month bills fell to six point seven three percent from six point eight three percent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_441C0209_PED.wav", "answer": "the earlier rise was previously reported as four point three percent", "subset": "ped", "task_type": "understanding", "prediction": "The earlier rise was previously reported, as 4.3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_441C020A_PED.wav", "answer": "if defense is excluded march orders rose one percent after a three percent increase in february", "subset": "ped", "task_type": "understanding", "prediction": "If defense is excluded March orders rose 1% after a 3% increase in February.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_441C020F_PED.wav", "answer": "also a move to base it abroad will have tax advantages", "subset": "ped", "task_type": "understanding", "prediction": "also a move to base of abroad will have tax advantages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_441C020S_PED.wav", "answer": "analysts haven't focused on what happened to them", "subset": "ped", "task_type": "understanding", "prediction": "analysts haven t focused on what happened to the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_441C020V_PED.wav", "answer": "closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities", "subset": "ped", "task_type": "understanding", "prediction": "Closed end funds are traded on exchanges like stocks, but invest in a wide portfolio of other securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C0203_PED.wav", "answer": "the bank holding company slated another fifty million dollar sale next tuesday", "subset": "ped", "task_type": "understanding", "prediction": "The bank holding company slated another $50 million sale next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C020C_PED.wav", "answer": "shamrock has interests in television and radio stations energy services real estate and venture capital", "subset": "ped", "task_type": "understanding", "prediction": "Chairman Lee is interested in television and radio stations, energy services. real estate and venture capital.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C020F_PED.wav", "answer": "this morning the asking price for the stock was four thousand eight hundred fifty but there were no buyers", "subset": "ped", "task_type": "understanding", "prediction": "This morning, the asking price for the stock was 4850, but there were no buyers.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C020G_PED.wav", "answer": "a monsanto spokesman said there's very little we can say", "subset": "ped", "task_type": "understanding", "prediction": "a monsanto spokesman said there is very little we can say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C020K_PED.wav", "answer": "that would follow a two point two percent drop in may", "subset": "ped", "task_type": "understanding", "prediction": "that would follow a two point two percent drop in may", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C020T_PED.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "ped", "task_type": "understanding", "prediction": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C020U_PED.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "ped", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C020Z_PED.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "ped", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies, with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_442C0210_PED.wav", "answer": "he declined to name specific products", "subset": "ped", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C0201_PED.wav", "answer": "the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before", "subset": "ped", "task_type": "understanding", "prediction": "The Labor Department said nonfarm payroll employment increased a robust 337000 last month after revised 319000 gain the month before.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C0208_PED.wav", "answer": "local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members", "subset": "ped", "task_type": "understanding", "prediction": "Local membership jumped 22 per cent but the union has already lost 28 of the 73 new members", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020H_PED.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "ped", "task_type": "understanding", "prediction": "Those identified as beneficial owners hold at least 10% of the company's equity securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020J_PED.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "ped", "task_type": "understanding", "prediction": "Companies are listed where transactions generally aggregate 10000 shares, or $100000.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020K_PED.wav", "answer": "after the third period ashland's coal operations began a process of becoming an independent company", "subset": "ped", "task_type": "understanding", "prediction": "After the third period, Ashland's coal operations began a process of becoming an independent company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020L_PED.wav", "answer": "when its initial public offering is completed ashland is expected to retain a forty six percent stake", "subset": "ped", "task_type": "understanding", "prediction": "When its initial public offering is completed Ashland is expected to retain a 46% stake", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020M_PED.wav", "answer": "the new company ashland coal incorporated is listed on the new york stock exchange", "subset": "ped", "task_type": "understanding", "prediction": "The new company, Ashland, Co. Incorporated is listed on the New York Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020P_PED.wav", "answer": "in addition u. s. west's data solutions business applied communications incorporated is working out well and performing ahead of all our schedules", "subset": "ped", "task_type": "understanding", "prediction": "In addition, US West data solutions, business applied communications, Incorporated, is working out well and performing ahead of all our schedules.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020R_PED.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "ped", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020U_PED.wav", "answer": "fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards", "subset": "ped", "task_type": "understanding", "prediction": "Fees range up to about $40 annually for basic cards and $60 a year for gold cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C020Z_PED.wav", "answer": "companies listed below reported quarterly profit substantially different from the average of analysts' estimates", "subset": "ped", "task_type": "understanding", "prediction": "Companies listed below reported quarterly profits substantially different from the average of analyst estimates.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C0211_PED.wav", "answer": "estimated and actual results involving losses are omitted", "subset": "ped", "task_type": "understanding", "prediction": "Estimated and actual results involving losses are omitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C0212_PED.wav", "answer": "yesterday's losers included automobiles", "subset": "ped", "task_type": "understanding", "prediction": "yesterday s losers included automobiles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_443C0213_PED.wav", "answer": "honda was down ten to one thousand nine hundred thirty", "subset": "ped", "task_type": "understanding", "prediction": "Honda was down 10 to 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C0203_PED.wav", "answer": "revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars", "subset": "ped", "task_type": "understanding", "prediction": "Revenue in the quarter more than doubled to $362.4 million from $149.2 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C020I_PED.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "ped", "task_type": "understanding", "prediction": "Kyocera was up 60 at 5260.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C020O_PED.wav", "answer": "the company declined to identify the bidders but said it received offers in the high forty dollars per share", "subset": "ped", "task_type": "understanding", "prediction": "The company declined to identify the bidders. But said it received offers in the high $40 per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C020T_PED.wav", "answer": "the market's strength may show that demand isn't all a creation of incentives", "subset": "ped", "task_type": "understanding", "prediction": "The market strength may show that demand isn't all a creation of incentives.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C020V_PED.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "ped", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C020Y_PED.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday", "subset": "ped", "task_type": "understanding", "prediction": "Volume was 18190000 shares, compared with 10550000 Wednesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C020Z_PED.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "ped", "task_type": "understanding", "prediction": "There were 256 issues advancing,303 declining and 292 unchanged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_444C0213_PED.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "ped", "task_type": "understanding", "prediction": "A change in the firms ownership also should turn on the bright warning light.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C0207_PED.wav", "answer": "but the penalties for failure are real", "subset": "ped", "task_type": "understanding", "prediction": "but the penalties for failure are real", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020D_PED.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "ped", "task_type": "understanding", "prediction": "Grand Auto slid 3 to 15 and 1,8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020E_PED.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "ped", "task_type": "understanding", "prediction": "The company, which runs retail automotive stores. Told shearson, Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020F_PED.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "ped", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020H_PED.wav", "answer": "the suit seeks to block the contract which would have raised pay levels but cut benefits", "subset": "ped", "task_type": "understanding", "prediction": "The suit seeks to block the contract. Which would have raised pay levels and cut benefits.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020K_PED.wav", "answer": "but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close", "subset": "ped", "task_type": "understanding", "prediction": "But to the surprise of almost everyone. Stock prices began a steady climb that pushed the average above Wednesday's close.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020L_PED.wav", "answer": "although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading", "subset": "ped", "task_type": "understanding", "prediction": "although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trade", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020P_PED.wav", "answer": "about all the businessman can count on is that policy will be pretty volatile", "subset": "ped", "task_type": "understanding", "prediction": "About all that businessmen can count on is that policy will be pretty volatile.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C020Z_PED.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "ped", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C0210_PED.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "ped", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_445C0211_PED.wav", "answer": "a print media campaign will begin the following day", "subset": "ped", "task_type": "understanding", "prediction": "a print media campaign will begin the following day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C0202_PED.wav", "answer": "to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred", "subset": "ped", "task_type": "understanding", "prediction": "To make them directly comparable, each index is based on the close of 1969, equaling 100.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C0203_PED.wav", "answer": "the percentage change is since year end", "subset": "ped", "task_type": "understanding", "prediction": "the percentage change is since year end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C0205_PED.wav", "answer": "no one at the state department wants to let spies in", "subset": "ped", "task_type": "understanding", "prediction": "no one at the state department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C0206_PED.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "ped", "task_type": "understanding", "prediction": "we are not prepared to be advocates for the cagey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C0207_PED.wav", "answer": "that doesn't mean mr. icahn has committed any wrongdoing", "subset": "ped", "task_type": "understanding", "prediction": "that does not mean mr icon has committed any wrongdoing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020A_PED.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "ped", "task_type": "understanding", "prediction": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020B_PED.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "ped", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5 percent in 1987 to 5.5 percent in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020C_PED.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "ped", "task_type": "understanding", "prediction": "The unspent balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020P_PED.wav", "answer": "it's still unclear", "subset": "ped", "task_type": "understanding", "prediction": "it is still unclear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020Q_PED.wav", "answer": "there was a striking split between the sexes with men more likely than women to favor space programs", "subset": "ped", "task_type": "understanding", "prediction": "There was a striking split between the sexes, with men more likely than women to favour space programs.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020T_PED.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "ped", "task_type": "understanding", "prediction": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u.s durable goods rose two point four percent last month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020U_PED.wav", "answer": "that would follow a two point two percent drop in may", "subset": "ped", "task_type": "understanding", "prediction": "that would follow a two point two percent drop in may", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020V_PED.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "ped", "task_type": "understanding", "prediction": "The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020W_PED.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "ped", "task_type": "understanding", "prediction": "Durable goods reports frequently are highly volatile, from month to month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020X_PED.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "ped", "task_type": "understanding", "prediction": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C020Y_PED.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "ped", "task_type": "understanding", "prediction": "Estimates for the gain range from 2% to 3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C0211_PED.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "ped", "task_type": "understanding", "prediction": "after the offering republic new york will hold about forty nine percent of the affiliate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_446C0213_PED.wav", "answer": "it also owns three state business magazines in florida georgia and arizona", "subset": "ped", "task_type": "understanding", "prediction": "It also owns three state business magazines in Florida, Georgia and Arizona.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C0204_PED.wav", "answer": "mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent", "subset": "ped", "task_type": "understanding", "prediction": "Mr. Robertson says he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C0207_PED.wav", "answer": "washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own", "subset": "ped", "task_type": "understanding", "prediction": "Washington National paid $19 a share for the 2.6 million United presidential shares it didn't already own.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C020C_PED.wav", "answer": "sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days", "subset": "ped", "task_type": "understanding", "prediction": "Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C020L_PED.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "ped", "task_type": "understanding", "prediction": "Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C020O_PED.wav", "answer": "the company expects to report its results in about two weeks", "subset": "ped", "task_type": "understanding", "prediction": "The company expects to report its results in about two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C020U_PED.wav", "answer": "other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation", "subset": "ped", "task_type": "understanding", "prediction": "Other analysts say the Fed needs to tighten policy further to support the dollar and spending growth.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C020W_PED.wav", "answer": "the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape", "subset": "ped", "task_type": "understanding", "prediction": "The share closed at $18.25, up 25 cents on the New York Stock Exchange composite tape.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C020X_PED.wav", "answer": "salant shares closed unchanged on the big board at nine dollars and seventy five cents", "subset": "ped", "task_type": "understanding", "prediction": "Salad shares closed unchanged on the big board at $9.75.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C0211_PED.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "ped", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C0212_PED.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "ped", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's Investment Development Unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C0213_PED.wav", "answer": "we had to sustain some modest operating losses", "subset": "ped", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F05_447C0216_PED.wav", "answer": "the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight", "subset": "ped", "task_type": "understanding", "prediction": "The index ended with a decline of 0.35 point to 1272.18.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C0203_PED.wav", "answer": "and half these managers are in the u. s.", "subset": "ped", "task_type": "understanding", "prediction": "and half these managers are in the us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C0207_PED.wav", "answer": "the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks", "subset": "ped", "task_type": "understanding", "prediction": "The agency isn't likely to take any action until the union's rank and file votes on the contract in 2 to three weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C020C_PED.wav", "answer": "the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture", "subset": "ped", "task_type": "understanding", "prediction": "The rise in that category in July was LED by increased orders for aircraft and parts, non electrical machinery, lumber and furniture.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C020D_PED.wav", "answer": "interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction", "subset": "ped", "task_type": "understanding", "prediction": "Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C020L_PED.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "ped", "task_type": "understanding", "prediction": "the investor now owns seventy three percent of the company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C020M_PED.wav", "answer": "texaco has three choices a company adviser says", "subset": "ped", "task_type": "understanding", "prediction": "Texaco has three choices, economy adviser says.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C020S_PED.wav", "answer": "what we don't know is how much is price and how much is volume", "subset": "ped", "task_type": "understanding", "prediction": "What we don't know is how much is price and how much is volume.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_440C020Y_PED.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "ped", "task_type": "understanding", "prediction": "Estimates for the gain range from 2% to 3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C0201_PED.wav", "answer": "first commodity appealed the expulsion and fine to the c. f. t. c.", "subset": "ped", "task_type": "understanding", "prediction": "First, commodity appealed the expulsion and fine to the CFTC.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C0202_PED.wav", "answer": "a commission spokesman said a decision on the appeal is expected soon", "subset": "ped", "task_type": "understanding", "prediction": "A commission spokesman said a decision on the appeal is expected soon.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C0205_PED.wav", "answer": "the language is a big problem", "subset": "ped", "task_type": "understanding", "prediction": "the language is a big problem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C0206_PED.wav", "answer": "in europe an american can at least read street signs", "subset": "ped", "task_type": "understanding", "prediction": "in europe an american can at least read street signs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C0208_PED.wav", "answer": "the overall gain the fifth in the past seven months followed a revised four point one percent increase in february", "subset": "ped", "task_type": "understanding", "prediction": "The overall gain this past 7 months followed a revised 4.1% increase in January.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020C_PED.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "ped", "task_type": "understanding", "prediction": "The company, which runs retail automotive strips. Told Shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020D_PED.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "ped", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020E_PED.wav", "answer": "elders brewing will be based outside australia because seventy percent of its assets are in britain and canada", "subset": "ped", "task_type": "understanding", "prediction": "Elders Brewing will be based outside Australia because 70 per cent of its assets are in Britain and Canada", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020H_PED.wav", "answer": "two years ago b. a. f. f. made three separate acquisitions in the u. s.", "subset": "ped", "task_type": "understanding", "prediction": "Two years ago, BASF made three separate acquisitions in the US.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020I_PED.wav", "answer": "its biggest was the one billion dollar purchase of united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry", "subset": "ped", "task_type": "understanding", "prediction": "Its biggest was the $1 billion purchase of United Technologies Corporation's Inmont subsidiary, a major supplier of paint to the auto industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020J_PED.wav", "answer": "today ninety percent of the four billion dollars of b. a. f. f. sales in the u. s. is produced there", "subset": "ped", "task_type": "understanding", "prediction": "today ninety percent of the four billion dollars of b a s f sales in the u s is produced there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020L_PED.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "ped", "task_type": "understanding", "prediction": "Those identified as beneficial owners hold at least 10% of the company's equity securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020P_PED.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "ped", "task_type": "understanding", "prediction": "If the dollar starts to plunge, the Fed may step up its defence of the currency.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020W_PED.wav", "answer": "although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year", "subset": "ped", "task_type": "understanding", "prediction": "Although closed, end funds have been around since at least the 1920s. They have boomed in popularity, this year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C020X_PED.wav", "answer": "the bond funds in particular provide robust yields for investors and hefty fees for underwriters", "subset": "ped", "task_type": "understanding", "prediction": "The bond funds, in particular, provide robust yields for the investors and hefty fees for underwriters.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C0210_PED.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "ped", "task_type": "understanding", "prediction": "After the offering, Republic, New York will hold about 49% of the affiliate.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_441C0213_PED.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "ped", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C0207_PED.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "ped", "task_type": "understanding", "prediction": "Grand Auto slid 3 to 15 and 1/8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C0208_PED.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "ped", "task_type": "understanding", "prediction": "The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C0209_PED.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "ped", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C020B_PED.wav", "answer": "shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said", "subset": "ped", "task_type": "understanding", "prediction": "Shamrock's pretax profit on the sale was $125 million, a spokesman said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C020D_PED.wav", "answer": "sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday", "subset": "ped", "task_type": "understanding", "prediction": "Sony Corporation, for example, closed at ¥4950,$34.50 a share yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C020O_PED.wav", "answer": "but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders", "subset": "ped", "task_type": "understanding", "prediction": "But if the winning bids are as high as they were in some deals earlier this year, then we are not going to be winning bidders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C020R_PED.wav", "answer": "the company then accepts the shares tendered on the lowest price needed to reach its total then pays that amount for all shares it purchases", "subset": "ped", "task_type": "understanding", "prediction": "The company then accepts the shares tendered on the lowest price needed to reach its total, then pays that amount for all shares it purchases.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C020S_PED.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "ped", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_442C0211_PED.wav", "answer": "so normalcy has returned", "subset": "ped", "task_type": "understanding", "prediction": "so normalcy has returned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C0204_PED.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "ped", "task_type": "understanding", "prediction": "M, I, C, C Investments has three series of publicly traded preferred shares and three series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C0205_PED.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "ped", "task_type": "understanding", "prediction": "MICC said it intends to pay the dividend arrears on July 31 to stock of records, July 2.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C0206_PED.wav", "answer": "the toronto based company provides mortgage guarantees to canadian real estate industries", "subset": "ped", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to Canadian real estate industries.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C0209_PED.wav", "answer": "nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics", "subset": "ped", "task_type": "understanding", "prediction": "Nonetheless, the union has moved the experiment to Richmond, Virginia, and has received inquiries from other unions about its tactics.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C020C_PED.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "ped", "task_type": "understanding", "prediction": "Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C020I_PED.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "ped", "task_type": "understanding", "prediction": "Unless otherwise noted, changes involved direct holdings of common stock and took place in September and October 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C020N_PED.wav", "answer": "the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains", "subset": "ped", "task_type": "understanding", "prediction": "The official declined to elaborate on projections for Nontelephone operations, but cited several indicators of recent gains.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C020O_PED.wav", "answer": "he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force", "subset": "ped", "task_type": "understanding", "prediction": "He said the company has entered 16 smaller cellular markets this year and has expanded its financial services workforce.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C020V_PED.wav", "answer": "in certain cases the cards are given free to subscribers", "subset": "ped", "task_type": "understanding", "prediction": "in certain cases the cards are given free to subscribers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_443C0214_PED.wav", "answer": "nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty", "subset": "ped", "task_type": "understanding", "prediction": "Mitsubishi lost 30 to 1520, and Toyota was down 30 to end the day at 2620.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C0208_PED.wav", "answer": "citicorp had twenty one point five billion dollars in capital at the end of last year", "subset": "ped", "task_type": "understanding", "prediction": "Citicorp had $21.5 billion in capital at the end of last year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C0209_PED.wav", "answer": "as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions", "subset": "ped", "task_type": "understanding", "prediction": "As one of the most acquisition hungry of major banks, Citicorp is often required by regulators to raise additional capital as a condition of making acquisitions.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C020J_PED.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "ped", "task_type": "understanding", "prediction": "Sony, which lost points in previous sessions this week, rebounded 80 to 5130.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C020P_PED.wav", "answer": "in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday", "subset": "ped", "task_type": "understanding", "prediction": "In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C020R_PED.wav", "answer": "the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year", "subset": "ped", "task_type": "understanding", "prediction": "The mid July increase came even though automakers are offering incentives on fewer cars this year than they did last year or earlier this year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C020S_PED.wav", "answer": "incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst", "subset": "ped", "task_type": "understanding", "prediction": "Incentives can move around sales, but not create them, said Charles Brady, an Oppenheimer and Company auto stock analyst.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C020U_PED.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "ped", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C020W_PED.wav", "answer": "a print media campaign will begin the following day", "subset": "ped", "task_type": "understanding", "prediction": "A print media campaign will begin the following day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C020X_PED.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "ped", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 380.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C0212_PED.wav", "answer": "realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars", "subset": "ped", "task_type": "understanding", "prediction": "Realized capital gains increased 42% to $909 million from $640.9 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_444C0214_PED.wav", "answer": "money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "subset": "ped", "task_type": "understanding", "prediction": "Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C0209_PED.wav", "answer": "and both mortgaged their homes to secure the loans they needed to start the business", "subset": "ped", "task_type": "understanding", "prediction": "And both mortgaged their homes to secure the loans they needed to start the business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C020A_PED.wav", "answer": "a long list of other witnesses have also testified in the trial now in its fourth month", "subset": "ped", "task_type": "understanding", "prediction": "A long list of other witnesses have also testified in the trial now in its fourth month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C020G_PED.wav", "answer": "the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists", "subset": "ped", "task_type": "understanding", "prediction": "The order issued late Wednesday by Judge Diana Murphy stems from a suit filed in federal court last month by the union representing machinists.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C020Q_PED.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "ped", "task_type": "understanding", "prediction": "If the dollar starts to plunge, the Fed may step up its defense of the currency.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C020R_PED.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "ped", "task_type": "understanding", "prediction": "If the Fed pushes the dollar higher. It may curb demand for US exports.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C020S_PED.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "ped", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C020T_PED.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "ped", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C020W_PED.wav", "answer": "the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed", "subset": "ped", "task_type": "understanding", "prediction": "The jury awarded Mr. Sharonberg $105 million, a figure based on 10 years of profits. Had his project been completed.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_445C0216_PED.wav", "answer": "where else in the third world is there so much energy and progress as in china", "subset": "ped", "task_type": "understanding", "prediction": "Where else in the third world is there so much energy and progress as in China.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C0204_PED.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "ped", "task_type": "understanding", "prediction": "The consensus was the new piece of paper isn't required, said one US diplomat.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C020D_PED.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "ped", "task_type": "understanding", "prediction": "The issue is rated single A by Moody S and single A minus by S P.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C020F_PED.wav", "answer": "under the proposed transaction the los angeles group would acquire the k. h. j. license and then sell itself to disney", "subset": "ped", "task_type": "understanding", "prediction": "Under the proposed transaction, the Los Angeles group would acquire the KHJ licence and then sell itself to Disney.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C020G_PED.wav", "answer": "the closely held group doesn't have any significant assets according to william g. simon its president", "subset": "ped", "task_type": "understanding", "prediction": "The closely held group does not have any significant assets. According to William G. Simon, its president.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C020H_PED.wav", "answer": "he said that for the full year wang is aiming for an after tax profit equal to three percent to five percent of sales", "subset": "ped", "task_type": "understanding", "prediction": "He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C020Z_PED.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "ped", "task_type": "understanding", "prediction": "Republic, New York, rose one and one quarter to 4 to 5 and 78.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C0212_PED.wav", "answer": "closely held times publishing also owns two washington based publications congressional quarterly which covers capitol hill and governing which covers state and local governments", "subset": "ped", "task_type": "understanding", "prediction": "Closely held Times Publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and Governing, which covers state and local government.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_446C0214_PED.wav", "answer": "industry analysts value the company at about six hundred fifty million dollars", "subset": "ped", "task_type": "understanding", "prediction": "Industry analysts value the company at about $650 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C0203_PED.wav", "answer": "i'm not sure what you have on your own list", "subset": "ped", "task_type": "understanding", "prediction": "i am not sure what you have on your list", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020A_PED.wav", "answer": "united presidential is a life insurance company", "subset": "ped", "task_type": "understanding", "prediction": "united presidential is a life insurance company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020B_PED.wav", "answer": "these are uneducated people he says in english so the patients won't understand", "subset": "ped", "task_type": "understanding", "prediction": "These are uneducated people, he says, in English. So the patients won't understand.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020D_PED.wav", "answer": "i will tell you what i think in my office", "subset": "ped", "task_type": "understanding", "prediction": "i will tell you what i think in my office", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020F_PED.wav", "answer": "they were sold to underwriters led by prudential bache securities incorporated", "subset": "ped", "task_type": "understanding", "prediction": "They were sold to underwriters, LED by Prudential Bache Securities Incorporated.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020J_PED.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "ped", "task_type": "understanding", "prediction": "In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020K_PED.wav", "answer": "that was certainly true last week", "subset": "ped", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020P_PED.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "ped", "task_type": "understanding", "prediction": "The independent committee will recommend that holders accept the offer at a meeting expected to be held in December, T W Y said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020R_PED.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "ped", "task_type": "understanding", "prediction": "the investor now owns seventy three percent of the company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C020V_PED.wav", "answer": "manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid", "subset": "ped", "task_type": "understanding", "prediction": "Manhattan Industries continued to trade above the offer price yesterday, indicating the market expects a higher bid.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/F06_447C0215_PED.wav", "answer": "shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level", "subset": "ped", "task_type": "understanding", "prediction": "shearson lehman huttons incorporateds index of longterm treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0202_PED.wav", "answer": "the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years", "subset": "ped", "task_type": "understanding", "prediction": "The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0204_PED.wav", "answer": "r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.", "subset": "ped", "task_type": "understanding", "prediction": "Rli Corporation, a Peoria, Illinois, based insurance holding company, will be trading Friday on the big board under the symbol RLI.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0209_PED.wav", "answer": "a p. b. g. c. spokeswoman declined comment", "subset": "ped", "task_type": "understanding", "prediction": "A P, BGC spokeswoman declined comment.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020E_PED.wav", "answer": "the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last week", "subset": "ped", "task_type": "understanding", "prediction": "The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at the previous auction last week.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020F_PED.wav", "answer": "the average rate on new twenty six week bills rose to six point one six percent from six point one two percent", "subset": "ped", "task_type": "understanding", "prediction": "The average rate on new 26 week bills rose to 6.16% from 6.12%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020G_PED.wav", "answer": "analysts too generally played down the effect on banks", "subset": "ped", "task_type": "understanding", "prediction": "analysts too generally played down the effect on banks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020H_PED.wav", "answer": "in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks", "subset": "ped", "task_type": "understanding", "prediction": "In a fundamental sense, the equity markets have very little to do with what goes on in the commercial banks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020I_PED.wav", "answer": "there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company", "subset": "ped", "task_type": "understanding", "prediction": "There shouldn't be any risk to the banks in this sort of stuff, said Lawrence Coe, a banking analyst at Merrill Lynch and Company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020K_PED.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "ped", "task_type": "understanding", "prediction": "The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020O_PED.wav", "answer": "unable to agree on friday the board must meet again at least by phone to register its choice", "subset": "ped", "task_type": "understanding", "prediction": "Unable to agree on Friday, the board must meet again, at least by phone, to register its choice.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020P_PED.wav", "answer": "commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models", "subset": "ped", "task_type": "understanding", "prediction": "Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories with new models.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020T_PED.wav", "answer": "rates fell on short term treasury bills", "subset": "ped", "task_type": "understanding", "prediction": "Rates fell on short term Treasury bills.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C020W_PED.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "ped", "task_type": "understanding", "prediction": "durable goods reports frequently are highly volatile from month to month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0210_PED.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "ped", "task_type": "understanding", "prediction": "Yesterday, Moody s Investors Service raised Lilco s credit rating in recognition of the improved outlook for steady financial recovery.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 840, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0211_PED.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "ped", "task_type": "understanding", "prediction": "About $3.5 billion of securities are affected.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 841, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0212_PED.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "ped", "task_type": "understanding", "prediction": "He said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 842, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0213_PED.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "ped", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 843, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_440C0214_PED.wav", "answer": "he declined to name specific products", "subset": "ped", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 844, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C0207_PED.wav", "answer": "in japan it's all greek so to speak", "subset": "ped", "task_type": "understanding", "prediction": "in japan it is all greek so to speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 845, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C020K_PED.wav", "answer": "the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "ped", "task_type": "understanding", "prediction": "The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 846, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C020M_PED.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "ped", "task_type": "understanding", "prediction": "Unless otherwise noted changes involved direct holdings of common stock and took place in September and October of 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 847, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C020N_PED.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "ped", "task_type": "understanding", "prediction": "Companies are listed where transactions generally aggregate 10000 shares, or $100000.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 848, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C020O_PED.wav", "answer": "about all the businessman can count on is that policy will be pretty volatile", "subset": "ped", "task_type": "understanding", "prediction": "About all the businessmen can count on is that the policy will be volatile.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 849, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C020Q_PED.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "ped", "task_type": "understanding", "prediction": "If the Fed pushes the dollar higher. It may curb the demand for US exports.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 850, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C020T_PED.wav", "answer": "has exposure really been reduced", "subset": "ped", "task_type": "understanding", "prediction": "has exposure really been fixed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 851, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C0212_PED.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "ped", "task_type": "understanding", "prediction": "Volume was modest as 326.7 million shares changed hands, compared with 396.5 million Friday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 852, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_441C0214_PED.wav", "answer": "he said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "ped", "task_type": "understanding", "prediction": "He said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 853, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C0201_PED.wav", "answer": "bids totaling five hundred twenty five point five million dollars were submitted", "subset": "ped", "task_type": "understanding", "prediction": "Bids totaling $525.5 million, were submitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 854, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C0205_PED.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "ped", "task_type": "understanding", "prediction": "MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 855, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C0206_PED.wav", "answer": "the toronto based company provides mortgage guarantees to the canadian real estate industry", "subset": "ped", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to the Canadian real estate industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 856, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020A_PED.wav", "answer": "under terms previously reported the italian agricultural concern assumed about one hundred ninety five million dollars in subordinated debt as part of the transaction", "subset": "ped", "task_type": "understanding", "prediction": "Under terms previously reported, the Italian agricultural concern assumed about $195 million in subordinated debt as part of the transaction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 857, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020H_PED.wav", "answer": "we just received the suit and the document is massive it's two hundred pages", "subset": "ped", "task_type": "understanding", "prediction": "we just received a suit and the document is massive its two hundred pages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 858, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020I_PED.wav", "answer": "but on the first read through the case is without merit and we intend to fight it", "subset": "ped", "task_type": "understanding", "prediction": "But on first read through, the case is without merit. And we intend to fight it.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 859, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020J_PED.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "ped", "task_type": "understanding", "prediction": "According to the average estimate of 7 economists surveyed by Dow Jones, capital markets report new orders for US durable goods rose 2.4% last month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 860, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020L_PED.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "ped", "task_type": "understanding", "prediction": "The May slump reported June 22, came as a big surprise to most analysts and helped trigger a powerful bond rally that day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 861, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020N_PED.wav", "answer": "we're going to be bidders said a top official of a major oil company", "subset": "ped", "task_type": "understanding", "prediction": "We are going to be bidders, said a top official of a major oil company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 862, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020P_PED.wav", "answer": "the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding", "subset": "ped", "task_type": "understanding", "prediction": "The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26% of its shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 863, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C020W_PED.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "ped", "task_type": "understanding", "prediction": "Yesterday, Moody s Investors Service raised local credit rating in recognition of the improved outlook for steady financial recovery.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 864, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C0215_PED.wav", "answer": "money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "subset": "ped", "task_type": "understanding", "prediction": "Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 865, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_442C0216_PED.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "ped", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 866, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_443C0202_PED.wav", "answer": "the department previously said jobs rose by four hundred forty eight thousand in january", "subset": "ped", "task_type": "understanding", "prediction": "The Department previously said jobs rose by 448000 in January.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 867, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_443C0203_PED.wav", "answer": "using a measure that counts the military among the employed the rate was unchanged at six point six percent last month", "subset": "ped", "task_type": "understanding", "prediction": "Using a measure that counts the military among the employed the rate was unchanged at 6.6% last month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 868, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_443C0207_PED.wav", "answer": "it isn't clear yet whether the campaign works", "subset": "ped", "task_type": "understanding", "prediction": "it isn t clear yet whether the campaign works", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 869, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_443C020D_PED.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty", "subset": "ped", "task_type": "understanding", "prediction": "Among export LED electrical and computer makers. Japan Victor Company fell 50 to 2320.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 870, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_443C020X_PED.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday", "subset": "ped", "task_type": "understanding", "prediction": "Volume was 18190000 shares, compared with 10550000 Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 871, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_443C0210_PED.wav", "answer": "the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share", "subset": "ped", "task_type": "understanding", "prediction": "The companies are followed by at least three analysts and had a minimum 5 cent change in actual earnings per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 872, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C0201_PED.wav", "answer": "in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share", "subset": "ped", "task_type": "understanding", "prediction": "In the 1985 quarter, the owner and operator of health maintenance organizations earned $6.9 million or 24 cents a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 873, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C0202_PED.wav", "answer": "it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars", "subset": "ped", "task_type": "understanding", "prediction": "It had forecast a 1986 fourth quarter loss of $18 million to $22 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 874, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C0205_PED.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "ped", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5 in 1987 to 5.5 in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 875, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C0206_PED.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "ped", "task_type": "understanding", "prediction": "The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 876, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C020B_PED.wav", "answer": "monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference", "subset": "ped", "task_type": "understanding", "prediction": "mondays crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 877, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C020C_PED.wav", "answer": "senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash", "subset": "ped", "task_type": "understanding", "prediction": "senate finance chairman lloyd bentsen d texas said he would speed up work on the package because of the crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 878, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C020D_PED.wav", "answer": "it adds to the support for the trade bill getting through he said", "subset": "ped", "task_type": "understanding", "prediction": "It adds to the support for the trade bill getting through, he said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 879, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C020F_PED.wav", "answer": "so far they have declined to comment publicly on their plans", "subset": "ped", "task_type": "understanding", "prediction": "So far, they have declined to comment publicly on their plans.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 880, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C020G_PED.wav", "answer": "state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do", "subset": "ped", "task_type": "understanding", "prediction": "State officials, however, say the airlines have indicated they will comply with most of the standards as long as competitors do.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 881, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C020H_PED.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty", "subset": "ped", "task_type": "understanding", "prediction": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred and twenty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 882, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C020K_PED.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "ped", "task_type": "understanding", "prediction": "Lately, computer retailing has been tough on everybody.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 883, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_444C0210_PED.wav", "answer": "the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent", "subset": "ped", "task_type": "understanding", "prediction": "The institute said earned premiums rose 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 884, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C0206_PED.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "ped", "task_type": "understanding", "prediction": "were not prepared to be advocates for the kgb", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 885, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C0208_PED.wav", "answer": "their business isn't just a job but their investment", "subset": "ped", "task_type": "understanding", "prediction": "Their business isn't just a job, but their investment.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 886, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C020I_PED.wav", "answer": "the airline imposed the contract without union bargaining", "subset": "ped", "task_type": "understanding", "prediction": "The airline imposed the contract, without union bargaining.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 887, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C020J_PED.wav", "answer": "yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling", "subset": "ped", "task_type": "understanding", "prediction": "yesterday session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to ford and salomon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 888, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C020M_PED.wav", "answer": "gillette is again a target of a major corporate raider", "subset": "ped", "task_type": "understanding", "prediction": "Gillette is, again, a target of a major corporate raider.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 889, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C020O_PED.wav", "answer": "a lengthy flight is likely", "subset": "ped", "task_type": "understanding", "prediction": "a lengthy flight is like", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 890, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C020X_PED.wav", "answer": "continental started the appeal process but recently settled the case", "subset": "ped", "task_type": "understanding", "prediction": "continental started the appeal process but recently settled the case", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 891, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C020Y_PED.wav", "answer": "neither side would disclose terms", "subset": "ped", "task_type": "understanding", "prediction": "neither side would disclose terms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 892, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_445C0213_PED.wav", "answer": "from america china looks good", "subset": "ped", "task_type": "understanding", "prediction": "from america china looks good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 893, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_446C020E_PED.wav", "answer": "fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments", "subset": "ped", "task_type": "understanding", "prediction": "fidelity has contended that gencorp isn t a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and for that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 894, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_446C020I_PED.wav", "answer": "he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year", "subset": "ped", "task_type": "understanding", "prediction": "He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 895, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_446C020K_PED.wav", "answer": "in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty", "subset": "ped", "task_type": "understanding", "prediction": "In many ways, that is just what UBS has done since Mr. Santelli was named president in 1980.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 896, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_446C020L_PED.wav", "answer": "assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven", "subset": "ped", "task_type": "understanding", "prediction": "Assets more than doubled since then to 160.4 billion Swiss francs.115.6 billion dollars in 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 897, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_446C020N_PED.wav", "answer": "the real estate investment trust said it was still hoping to reach a new credit arrangement", "subset": "ped", "task_type": "understanding", "prediction": "The real estate investment trust said it was still hoping to reach a new credit arrangement.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 898, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_446C020S_PED.wav", "answer": "among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women", "subset": "ped", "task_type": "understanding", "prediction": "Among men,41% supported boosting space exploration budget compared to 19% of women.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 899, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C0201_PED.wav", "answer": "i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month", "subset": "ped", "task_type": "understanding", "prediction": "I don't mean there couldn't be some improvements in the Revenue Act of 1986, which took effect this month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 900, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C0206_PED.wav", "answer": "he cites the law of large numbers can you really expect it to grow at large numbers very long", "subset": "ped", "task_type": "understanding", "prediction": "he cites the law of large numbers can you really expect it to grow at large numbers very long", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 901, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C0209_PED.wav", "answer": "washington national is a financial services concern", "subset": "ped", "task_type": "understanding", "prediction": "Washington National is a financial services concern.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 902, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C020E_PED.wav", "answer": "northgate exploration limited said it sold four million common shares at eight dollars each", "subset": "ped", "task_type": "understanding", "prediction": "Northgate Exploration Limited said it sold 4 million common shares at $8 each.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 903, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C020H_PED.wav", "answer": "the toronto based gold mining concern said proceeds would be used for general purposes", "subset": "ped", "task_type": "understanding", "prediction": "The Toronto based gold mining concern said proceeds would be used for general purposes.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 904, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C020M_PED.wav", "answer": "envirodyne said it expects sales to be the highest for any third quarter in the company's history", "subset": "ped", "task_type": "understanding", "prediction": "Envirodime said it expects sales to be the highest for any third quarter in the company's history.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 905, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C020S_PED.wav", "answer": "but while the fed stands pat it is coming under increasing attack from both sides", "subset": "ped", "task_type": "understanding", "prediction": "but while the fed stands pat it is coming under increasing attack from both sides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 906, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C020T_PED.wav", "answer": "some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year", "subset": "ped", "task_type": "understanding", "prediction": "Some critics including high Reagan administration officials are raising the alarm that the Feds policy is too tight and could cause a recession next year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 907, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C020Y_PED.wav", "answer": "increasingly people who test positive join the support groups that have sprung up across the country in the past year", "subset": "ped", "task_type": "understanding", "prediction": "Increasingly people who test positive join the support groups that have sprung up across the country in the past year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 908, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M05_447C0210_PED.wav", "answer": "founded last october new york's body positive already has sixteen groups meeting every two weeks", "subset": "ped", "task_type": "understanding", "prediction": "Founded last October, New Yorks body positive already has 16 groups meeting every two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 909, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C0206_PED.wav", "answer": "two other issues began trading recently on the big board", "subset": "ped", "task_type": "understanding", "prediction": "Two other issues began trading recently, on the big board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 910, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C0208_PED.wav", "answer": "union officials expect ratification", "subset": "ped", "task_type": "understanding", "prediction": "union officials expect ratification", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 911, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C020A_PED.wav", "answer": "despite the july decline durable goods orders remained seven point seven percent above the year earlier level", "subset": "ped", "task_type": "understanding", "prediction": "Despite the July decline, durable goods orders remained 7.7% above the year earlier level.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 912, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C020B_PED.wav", "answer": "economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment", "subset": "ped", "task_type": "understanding", "prediction": "Economists were encouraged by a 1.6% increase in new orders for nondefense capital goods, an important indicator of future business investing.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 913, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C020J_PED.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "ped", "task_type": "understanding", "prediction": "The independent committee will recommend that holders accept the offer at a meeting expected to be held in December 2007.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 914, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C020Q_PED.wav", "answer": "the rise in auto imports also reflects higher prices for imported cars", "subset": "ped", "task_type": "understanding", "prediction": "The rise in auto imports must reflect higher prices for imported cars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 915, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C020R_PED.wav", "answer": "prices are going up said george c. eads vice president and chief economist at general motors corporation", "subset": "ped", "task_type": "understanding", "prediction": "Prices are going up, said George C. Yads, vice president and chief economist at General Motors Corporation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 916, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C020X_PED.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "ped", "task_type": "understanding", "prediction": "Many analysts cite an expected increase in aircraft orders as a big reason for the notes pending June increase.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 917, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_440C020Z_PED.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "ped", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 918, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C0203_PED.wav", "answer": "first commodity officials couldn't be reached for comment", "subset": "ped", "task_type": "understanding", "prediction": "First commodity officials couldn be reached for comment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 919, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C0204_PED.wav", "answer": "and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort", "subset": "ped", "task_type": "understanding", "prediction": "And then there is the explanation of why Terradyns growth in Japan is slow, despite 15 years of effort.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 920, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C020B_PED.wav", "answer": "grand auto slid three to fifteen and one eighth in the american stock exchange", "subset": "ped", "task_type": "understanding", "prediction": "Grand author, Slade 3 to 15 and 1,8 in the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 921, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C020G_PED.wav", "answer": "elders finance and elders agribusiness will remain based in australia", "subset": "ped", "task_type": "understanding", "prediction": "Elders finance and elders agribusiness will remain based in Australia.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 922, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C020R_PED.wav", "answer": "too much focus is placed on reduction of cross country loans mr. meyerman said", "subset": "ped", "task_type": "understanding", "prediction": "Too much focus is placed on reduction of cross country loans, Mr. Meyer said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 923, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C020U_PED.wav", "answer": "our guess is no", "subset": "ped", "task_type": "understanding", "prediction": "our guess is no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 924, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C020Y_PED.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "ped", "task_type": "understanding", "prediction": "Republic near rose 1 and one quarter to 45, and 7/8.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 925, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C020Z_PED.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "ped", "task_type": "understanding", "prediction": "The company said its European Banking affiliate. Saffron Republic plans to raise more than $450 million through an international offering.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 926, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C0211_PED.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "ped", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 927, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C0215_PED.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "ped", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 928, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_441C0216_PED.wav", "answer": "he declined to name specific products", "subset": "ped", "task_type": "understanding", "prediction": "He declined to name specific clients.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 929, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C0202_PED.wav", "answer": "accepted bids ranged from six point two percent to six point two two five percent", "subset": "ped", "task_type": "understanding", "prediction": "Accepted bids ranged from 6.2% to 6.225%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 930, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C0204_PED.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "ped", "task_type": "understanding", "prediction": "MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 931, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C020E_PED.wav", "answer": "under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents", "subset": "ped", "task_type": "understanding", "prediction": "Under Tokyo trading rules, the maximum one day drop for Sony is ¥500 about $3.50.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 932, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C020M_PED.wav", "answer": "even some bigger companies caution that they are leery of paying too big a premium", "subset": "ped", "task_type": "understanding", "prediction": "Even some bigger companies caution that they are leery of paying too big a premium.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 933, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C020Q_PED.wav", "answer": "in a dutch auction holders tender their shares at prices within the stated range in this case between twenty eight dollars and thirty three dollars a share", "subset": "ped", "task_type": "understanding", "prediction": "In a Dutch auction, holders tender their shares at prices within the stated range. In this case, between $28 and $33 a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 934, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C020V_PED.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "ped", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 935, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C020X_PED.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "ped", "task_type": "understanding", "prediction": "About $3.5 billion in securities are affected.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 936, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C020Y_PED.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "ped", "task_type": "understanding", "prediction": "He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 937, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C0212_PED.wav", "answer": "foreigners are back and negotiating with the chinese will be as tough as ever", "subset": "ped", "task_type": "understanding", "prediction": "Foreigners are back and negotiating with the Chinese will be as tough as ever.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 938, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C0213_PED.wav", "answer": "that's fine", "subset": "ped", "task_type": "understanding", "prediction": "that is fine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 939, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_442C0214_PED.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "ped", "task_type": "understanding", "prediction": "A change in the firms ownership also should turn on a light bulb.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 940, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020A_PED.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "ped", "task_type": "understanding", "prediction": "And in the effort to restore market confidence, administration officials have emphasized that the economy's fundamentals remain sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 941, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020B_PED.wav", "answer": "that was certainly true last week", "subset": "ped", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 942, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020E_PED.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "ped", "task_type": "understanding", "prediction": "Your Sarah was at 60,5260.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 943, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020F_PED.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "ped", "task_type": "understanding", "prediction": "Sony, which lost points in the previous session this week, rebounded 80 to 5130.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 944, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020G_PED.wav", "answer": "the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "ped", "task_type": "understanding", "prediction": "Filing officers, directors and large stakeholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 945, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020Q_PED.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "ped", "task_type": "understanding", "prediction": "Mci plans to begin offering the service at the end of the month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 946, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020S_PED.wav", "answer": "a print media campaign will begin the following day", "subset": "ped", "task_type": "understanding", "prediction": "A print media campaign will begin following that.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 947, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020T_PED.wav", "answer": "visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards", "subset": "ped", "task_type": "understanding", "prediction": "Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 948, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020W_PED.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "ped", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 380.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 949, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_443C020Y_PED.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "ped", "task_type": "understanding", "prediction": "There were 256 issues advancing,303 declining and 292 unchanged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 950, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C0204_PED.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "ped", "task_type": "understanding", "prediction": "Separately, the estate sold about $77.1 million in certificates of participation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 951, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C0207_PED.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "ped", "task_type": "understanding", "prediction": "The issue is rated single A by Moody S and single A minus by S and P.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 952, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C020A_PED.wav", "answer": "in addition banks in general are being pushed by regulators to boost their capital positions", "subset": "ped", "task_type": "understanding", "prediction": "In addition, banks in general are being pushed by regulators to boost their capital positions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 953, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C020E_PED.wav", "answer": "several airlines have also opposed the standards and may fight some aspects in court", "subset": "ped", "task_type": "understanding", "prediction": "several airlines have also opposed the standards and may fight some aspects in court", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 954, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C020L_PED.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "ped", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic Investment Development.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 955, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C020M_PED.wav", "answer": "we had to sustain some modest operating losses", "subset": "ped", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 956, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C020N_PED.wav", "answer": "we didn't like that", "subset": "ped", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 957, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C020Q_PED.wav", "answer": "the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding", "subset": "ped", "task_type": "understanding", "prediction": "The offers indicate a total price for the company exceeding $800 million based on 17.2 million shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 958, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C0211_PED.wav", "answer": "however investment income which represents thirteen percent of the industry's revenues rose eleven percent in the quarter reflecting gains from the rising stock market", "subset": "ped", "task_type": "understanding", "prediction": "However, investment income, which represents 13% of the industry s revenues. Grows 11% in the quarter, reflecting gains from the rise in stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 959, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_444C0215_PED.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "ped", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 960, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0201_PED.wav", "answer": "owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged", "subset": "ped", "task_type": "understanding", "prediction": "Owens and Minor said its share purchases would be financed by existing credit lines and new ones to be arranged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 961, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0202_PED.wav", "answer": "if all twenty million shares were purchased the company's equity would be reduced by about one third", "subset": "ped", "task_type": "understanding", "prediction": "If all 20 million shares are purchased the companys equity would be reduced by about one third", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 962, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0203_PED.wav", "answer": "a spokesman said the company has about sixty million shares outstanding", "subset": "ped", "task_type": "understanding", "prediction": "A spokesman said the company has about 60 million shares outstanding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 963, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0204_PED.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "ped", "task_type": "understanding", "prediction": "The consensus was that a new piece of paper isn't required, said one US diplomat.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 964, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0205_PED.wav", "answer": "no one at the state department wants to let spies in", "subset": "ped", "task_type": "understanding", "prediction": "no one at the state department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 965, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C020B_PED.wav", "answer": "but it is mr. west upon whom the outcome probably depends most", "subset": "ped", "task_type": "understanding", "prediction": "But it is Mr. West, upon whom the outcome probably depends most.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 966, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C020C_PED.wav", "answer": "testimony concluded this week and closing arguments are scheduled to begin monday", "subset": "ped", "task_type": "understanding", "prediction": "Testimony concluded this week, and closing arguments are scheduled for Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 967, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C020N_PED.wav", "answer": "coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board", "subset": "ped", "task_type": "understanding", "prediction": "Coniston Partners of New York said it has a 6.8 cent stake in Gillette and may seek to acquire the company or gain seats on its board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 968, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C020U_PED.wav", "answer": "we had to sustain some modest operating losses", "subset": "ped", "task_type": "understanding", "prediction": "We had to sustain some modest operating losses.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 969, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C020V_PED.wav", "answer": "we didn't like that", "subset": "ped", "task_type": "understanding", "prediction": "we didn like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 970, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0212_PED.wav", "answer": "the real change though is in how china looks", "subset": "ped", "task_type": "understanding", "prediction": "The real change, though, is in how China looks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 971, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0214_PED.wav", "answer": "the numbers looked amazingly good industrial growth rates above ten percent per year year after year", "subset": "ped", "task_type": "understanding", "prediction": "The numbers looked amazingly good. Industrial growth rates above 10% per year, year after year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 972, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_445C0215_PED.wav", "answer": "and after a temporary downturn in the next couple of years the numbers probably will go back up", "subset": "ped", "task_type": "understanding", "prediction": "and after a temporary downturn in the next couple of years the numbers probably will go back up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 973, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C0201_PED.wav", "answer": "here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva", "subset": "ped", "task_type": "understanding", "prediction": "Here are price trends on the worlds major stock markets as calculated by Morgan Stanley Capital International in Geneva.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 974, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C0208_PED.wav", "answer": "but the investigation could make some lenders wary", "subset": "ped", "task_type": "understanding", "prediction": "But the investigation could make some lenders wary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 975, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C0209_PED.wav", "answer": "mr. icahn an investor group he heads hold seventy two point seven percent of t. w. a.'s shares", "subset": "ped", "task_type": "understanding", "prediction": "Mr. Hekman and an investor group he heads hold 72.7 of T W A shares.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 976, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C020J_PED.wav", "answer": "in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars", "subset": "ped", "task_type": "understanding", "prediction": "In fiscal 1987, Wang had a loss of $70.7 million on revenue of 2.8 billion dollars.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 977, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C020M_PED.wav", "answer": "net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in the period", "subset": "ped", "task_type": "understanding", "prediction": "Net income rose 125% to 753 million Swiss francs in the period.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 978, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C020O_PED.wav", "answer": "we're not ready to say we're in technical default a spokesman said", "subset": "ped", "task_type": "understanding", "prediction": "We are not ready to say we are in technical default a spokesman said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 979, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C020R_PED.wav", "answer": "among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agree", "subset": "ped", "task_type": "understanding", "prediction": "among men 26 percent said the US was doing too little in space exploration only a quarter of women agreed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 980, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_446C0210_PED.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "ped", "task_type": "understanding", "prediction": "The company said its European Bank affiliate. Sapporo Public plans to raise more than $450 million through an international offering.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 981, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C0202_PED.wav", "answer": "i have my list of changes i'd like to see", "subset": "ped", "task_type": "understanding", "prediction": "i have my list of changes i d like to see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 982, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C0205_PED.wav", "answer": "he doesn't", "subset": "ped", "task_type": "understanding", "prediction": "he doesn", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 983, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C0208_PED.wav", "answer": "before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company", "subset": "ped", "task_type": "understanding", "prediction": "Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 984, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C020G_PED.wav", "answer": "the underwriting group has a thirty day option to acquire an additional six hundred thousand shares at eight dollars each", "subset": "ped", "task_type": "understanding", "prediction": "The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 985, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C020I_PED.wav", "answer": "it had fourteen point five million common shares outstanding before the issue", "subset": "ped", "task_type": "understanding", "prediction": "It had 14.5 million common shares, outstanding before the issue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 986, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C020N_PED.wav", "answer": "it had sales of nineteen one point five million dollars in the nineteen eighty six third quarter", "subset": "ped", "task_type": "understanding", "prediction": "It had sales of the 19$1.5 million in the 1986 third quarter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 987, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C020Q_PED.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "ped", "task_type": "understanding", "prediction": "The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Kong.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 988, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C020Z_PED.wav", "answer": "several cities have versions of the british organization body positive", "subset": "ped", "task_type": "understanding", "prediction": "several cities have versions of the british organization body positive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 989, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C0214_PED.wav", "answer": "we didn't like that", "subset": "ped", "task_type": "understanding", "prediction": "we didnt like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 990, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_ped_real/M06_447C0217_PED.wav", "answer": "the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight", "subset": "ped", "task_type": "understanding", "prediction": "The low was 1270.19, and the high was 1273.88.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 991, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_440C0206_STR.wav", "answer": "two other issues began trading recently on the big board", "subset": "str", "task_type": "understanding", "prediction": "Two other issues began trading recently, on the big board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 992, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_440C0208_STR.wav", "answer": "union officials expect ratification", "subset": "str", "task_type": "understanding", "prediction": "union officials expect ratification", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 993, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_440C020A_STR.wav", "answer": "despite the july decline durable goods orders remained seven point seven percent above the year earlier level", "subset": "str", "task_type": "understanding", "prediction": "Despite the July decline, durable goods orders remain 7.7% above the year earlier level.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 994, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_440C020B_STR.wav", "answer": "economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment", "subset": "str", "task_type": "understanding", "prediction": "economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 995, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_440C020Q_STR.wav", "answer": "the rise in auto imports also reflects higher prices for imported cars", "subset": "str", "task_type": "understanding", "prediction": "The rise in auto imports also reflects higher prices for imported cars.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 996, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_440C020R_STR.wav", "answer": "prices are going up said george c. eads vice president and chief economist at general motors corporation", "subset": "str", "task_type": "understanding", "prediction": "Prices are going up, said George C. Eads, vice president and chief economist at General Motors Corporation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 997, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_440C020Z_STR.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "str", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 998, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_441C0203_STR.wav", "answer": "first commodity officials couldn't be reached for comment", "subset": "str", "task_type": "understanding", "prediction": "First commodity officials couldn't be reached for comment.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 999, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_441C0204_STR.wav", "answer": "and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort", "subset": "str", "task_type": "understanding", "prediction": "And then there is the explanation of why Teradaya s growth in Japan is slow, despite 15 years of effort.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1000, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_441C020G_STR.wav", "answer": "elders finance and elders agribusiness will remain based in australia", "subset": "str", "task_type": "understanding", "prediction": "Elders finance and elders agribusiness will remain based in Australia.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1001, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_441C020R_STR.wav", "answer": "too much focus is placed on reduction of cross country loans mr. meyerman said", "subset": "str", "task_type": "understanding", "prediction": "Too much focus is placed on reduction of cross country loans, Mr. Meyer said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1002, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_441C020U_STR.wav", "answer": "our guess is no", "subset": "str", "task_type": "understanding", "prediction": "our guess is no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1003, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_441C020Z_STR.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "str", "task_type": "understanding", "prediction": "The company said its European Banking affiliate. Safra Republic plans to raise more than $450 million through an international offering.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1004, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C0202_STR.wav", "answer": "accepted bids ranged from six point two percent to six point two two five percent", "subset": "str", "task_type": "understanding", "prediction": "Accepted bids ranged from 6.2% to 6.225%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1005, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020E_STR.wav", "answer": "under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents", "subset": "str", "task_type": "understanding", "prediction": "Under Tokyo trading rules, the maximum one day drop for Sony is ¥500 about $3.50.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1006, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020M_STR.wav", "answer": "even some bigger companies caution that they are leery of paying too big a premium", "subset": "str", "task_type": "understanding", "prediction": "Even some bigger companies cautioned that they are leery of paying too big a premium.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1007, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020Q_STR.wav", "answer": "in a dutch auction holders tender their shares at prices within a stated range in this case between twenty eight dollars and thirty three dollars a share", "subset": "str", "task_type": "understanding", "prediction": "In a Dutch auction, holders tender their shares at prices within a stated range. In this case, between $28 and $33 a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1008, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020S_STR.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "str", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1009, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020V_STR.wav", "answer": "utility analysts however expect the agreement to be completed without much difficulty", "subset": "str", "task_type": "understanding", "prediction": "Utility analysts, however, expect the agreement to be completed without much difficulty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1010, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020X_STR.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "str", "task_type": "understanding", "prediction": "About $3.5 billion of securities are affected.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1011, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020Y_STR.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "str", "task_type": "understanding", "prediction": "He also said the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1012, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C020Z_STR.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "str", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1013, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C0210_STR.wav", "answer": "he declined to name specific products", "subset": "str", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1014, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C0212_STR.wav", "answer": "foreigners are back and negotiating with the chinese will be as tough as ever", "subset": "str", "task_type": "understanding", "prediction": "foreigners are back and negotiating with the chinese will be as tough as ever", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1015, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_442C0213_STR.wav", "answer": "that's fine", "subset": "str", "task_type": "understanding", "prediction": "thats fine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1016, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_443C0204_STR.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "str", "task_type": "understanding", "prediction": "MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1017, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_443C020G_STR.wav", "answer": "the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "str", "task_type": "understanding", "prediction": "The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1018, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_443C020T_STR.wav", "answer": "visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards", "subset": "str", "task_type": "understanding", "prediction": "Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1019, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020A_STR.wav", "answer": "in addition banks in general are being pushed by regulators to boost their capital positions", "subset": "str", "task_type": "understanding", "prediction": "In addition, banks in general are being pushed by regulators to boost their capital positions.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1020, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020E_STR.wav", "answer": "several airlines have also opposed the standards and may fight some aspects in court", "subset": "str", "task_type": "understanding", "prediction": "several airlines have also opposed the standards and may fight some aspects in court", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1021, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020I_STR.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "str", "task_type": "understanding", "prediction": "Kyocera was up 60 at 5260.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1022, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020J_STR.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "str", "task_type": "understanding", "prediction": "Sony, which lost points in previous sessions this week, rebounded 80 to 5130.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1023, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020N_STR.wav", "answer": "we didn't like that", "subset": "str", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1024, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020Q_STR.wav", "answer": "the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding", "subset": "str", "task_type": "understanding", "prediction": "The offers indicated total price for the company exceeding $800 million based on 17.2 million shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1025, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020X_STR.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "str", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 380.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1026, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C020Z_STR.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "str", "task_type": "understanding", "prediction": "There were 256 issues advancing,303 declining, and 292 unchanged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1027, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C0211_STR.wav", "answer": "however investment income which represents thirteen percent of the industry's revenues rose eleven percent in the quarter reflecting gains from the rising stock market", "subset": "str", "task_type": "understanding", "prediction": "however investment income which represents thirteen percent of the industry s revenues rose eleven percent in the quarter reflecting gains from the rising stock market", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1028, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C0213_STR.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "str", "task_type": "understanding", "prediction": "A change in the firms ownership also should turn on a bright warning light.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1029, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_444C0215_STR.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "str", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1030, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C0201_STR.wav", "answer": "owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged", "subset": "str", "task_type": "understanding", "prediction": "Owens Illinois said its share purchases would be financed by existing credit lines and new ones to be arranged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1031, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C0202_STR.wav", "answer": "if all twenty million shares were purchased the company's equity would be reduced by about one third", "subset": "str", "task_type": "understanding", "prediction": "If all 20 million shares were purchased. The company's equity would be reduced by about one third.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1032, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C0203_STR.wav", "answer": "a spokesman said the company has about sixty million shares outstanding", "subset": "str", "task_type": "understanding", "prediction": "A spokesman said the company has about 60 million shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1033, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C020B_STR.wav", "answer": "but it is mr. west upon whom the outcome probably depends most", "subset": "str", "task_type": "understanding", "prediction": "but it is mr west upon whom the outcome probably depends most", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1034, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C020C_STR.wav", "answer": "testimony concluded this week and closing arguments are scheduled to begin monday", "subset": "str", "task_type": "understanding", "prediction": "Testimony concluded this week, and closing arguments are scheduled to begin Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1035, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C020D_STR.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "str", "task_type": "understanding", "prediction": "Grand Auto slid 3 to 15 and 1.8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1036, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C020N_STR.wav", "answer": "coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board", "subset": "str", "task_type": "understanding", "prediction": "Coniston Partners of New York said it has a 6.8% stake in Gillette and may seek to acquire the company or gain seats on its board.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1037, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C020U_STR.wav", "answer": "we had to sustain some modest operating losses", "subset": "str", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1038, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C020V_STR.wav", "answer": "we didn't like that", "subset": "str", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1039, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C020Z_STR.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "str", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1040, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C0211_STR.wav", "answer": "a print media campaign will begin the following day", "subset": "str", "task_type": "understanding", "prediction": "a print media campaign will begin the following day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1041, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C0212_STR.wav", "answer": "the real change though is in how china looks", "subset": "str", "task_type": "understanding", "prediction": "the real change though is in how china looks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1042, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C0214_STR.wav", "answer": "the numbers looked amazingly good industrial growth rates above ten percent per year year after year", "subset": "str", "task_type": "understanding", "prediction": "The numbers looked amazingly good. Industrial growth rates above 10% per year, year after year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1043, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_445C0215_STR.wav", "answer": "and after a temporary downturn in the next couple of years the numbers 'll probably go back up", "subset": "str", "task_type": "understanding", "prediction": "And after a temporary downturn in the next couple of years. The numbers will probably go back up.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1044, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C0201_STR.wav", "answer": "here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva", "subset": "str", "task_type": "understanding", "prediction": "Here are price trends on the world's major stock markets, as calculated by Morgan Stanley, Capital International Perspective, Geneva.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1045, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C0204_STR.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "str", "task_type": "understanding", "prediction": "The consensus was that a new piece of paper isn't required, said one US diplomat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1046, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C0205_STR.wav", "answer": "no one at the state department wants to let spies in", "subset": "str", "task_type": "understanding", "prediction": "no one at the state department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1047, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C0208_STR.wav", "answer": "but the investigation could make some lenders wary", "subset": "str", "task_type": "understanding", "prediction": "but the investigation could make some lenders wary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1048, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C0209_STR.wav", "answer": "mr. icahn and an investor group he heads hold seventy two point seven percent of t. w. a.'s shares", "subset": "str", "task_type": "understanding", "prediction": "Mr. Icahn and an investor group he heads hold 72.7% of T. W A shares.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1049, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020A_STR.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "str", "task_type": "understanding", "prediction": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1050, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020D_STR.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "str", "task_type": "understanding", "prediction": "The issue is rated single A by Moody S and single A minus by S and P.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1051, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020J_STR.wav", "answer": "in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars", "subset": "str", "task_type": "understanding", "prediction": "In fiscal 1987, Wang had a loss of $70.7 million on revenue of $2.84 billion.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1052, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020M_STR.wav", "answer": "net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in that period", "subset": "str", "task_type": "understanding", "prediction": "Net income rose 125% to 753 million Swiss francs in that period.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1053, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020O_STR.wav", "answer": "we're not ready to say we're in technical default a spokesman says", "subset": "str", "task_type": "understanding", "prediction": "we are not ready to say we are in technical default a spokesman said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1054, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020R_STR.wav", "answer": "among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agreed", "subset": "str", "task_type": "understanding", "prediction": "among men fifty six percent said the us was doing too little in space exploration only a quarter of women agreed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1055, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020X_STR.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "str", "task_type": "understanding", "prediction": "Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1056, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C020Z_STR.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "str", "task_type": "understanding", "prediction": "Republic, New York, rose one and one quarter to 45 and 7/8.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1057, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_446C0210_STR.wav", "answer": "the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering", "subset": "str", "task_type": "understanding", "prediction": "The company said its European Banking affiliate. Safra Republic plans to raise more than $450 million through an international offering.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1058, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C0202_STR.wav", "answer": "i have my list of changes i'd like to see", "subset": "str", "task_type": "understanding", "prediction": "i have my list of changes i d like to see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1059, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C0205_STR.wav", "answer": "he doesn't", "subset": "str", "task_type": "understanding", "prediction": "he doesn t", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1060, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C0208_STR.wav", "answer": "before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company", "subset": "str", "task_type": "understanding", "prediction": "Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1061, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020G_STR.wav", "answer": "the underwriting group has a thirty day option to acquire an additional six hundred thousand shares at eight dollars each", "subset": "str", "task_type": "understanding", "prediction": "The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1062, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020I_STR.wav", "answer": "it had fourteen point five million common shares outstanding before the issue", "subset": "str", "task_type": "understanding", "prediction": "It had 14.5 million common shares, outstanding before the issue.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1063, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020J_STR.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "str", "task_type": "understanding", "prediction": "In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1064, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020K_STR.wav", "answer": "that was certainly true last week", "subset": "str", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1065, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020N_STR.wav", "answer": "it had sales of ninety one point five million dollars in the nineteen eighty six third quarter", "subset": "str", "task_type": "understanding", "prediction": "It had sales of $91.5 million in the 1986 third quarter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1066, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020P_STR.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "str", "task_type": "understanding", "prediction": "The independent committee will recommend that holders accept the offer at a meeting expected to be held in December. Twa said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1067, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020Q_STR.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "str", "task_type": "understanding", "prediction": "The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1068, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C020Z_STR.wav", "answer": "several cities have versions of the british organization body positive", "subset": "str", "task_type": "understanding", "prediction": "Several cities have versions of the British Organisation, Body Positive.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1069, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C0212_STR.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "str", "task_type": "understanding", "prediction": "no one is making very much money on it acknowledges brian j kelly chairman of bell atlantic s investment development unit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1070, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C0213_STR.wav", "answer": "we had to sustain some modest operating losses", "subset": "str", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1071, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C0214_STR.wav", "answer": "we didn't like that", "subset": "str", "task_type": "understanding", "prediction": "we didn t like that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1072, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F05_447C0217_STR.wav", "answer": "the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight", "subset": "str", "task_type": "understanding", "prediction": "The low was 1270.19, and the high was 1273.88.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1073, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C0202_STR.wav", "answer": "the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years", "subset": "str", "task_type": "understanding", "prediction": "The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1074, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C0204_STR.wav", "answer": "r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.", "subset": "str", "task_type": "understanding", "prediction": "Rli Corporation, a Peoria, Illinois, based insurance holding company, will begin trading Friday on the big board under the symbol Rli.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1075, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C0209_STR.wav", "answer": "a p. b. g. c. spokeswoman declined comment", "subset": "str", "task_type": "understanding", "prediction": "a p b g c spokeswoman declined to comment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1076, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020E_STR.wav", "answer": "the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last year", "subset": "str", "task_type": "understanding", "prediction": "The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at previous auction last year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1077, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020F_STR.wav", "answer": "the average rate on new twenty six week bills rose to six point one six percent from six point one two percent", "subset": "str", "task_type": "understanding", "prediction": "The average rate on new 26 week bills rose to 6.16% from 6.12%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1078, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020G_STR.wav", "answer": "analysts too generally played down the effect on banks", "subset": "str", "task_type": "understanding", "prediction": "Analysts, too, generally played down the effect on banks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1079, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020H_STR.wav", "answer": "in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks", "subset": "str", "task_type": "understanding", "prediction": "In a fundamental sense, the equity markets have very little to do with what goes on in the commercial banks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1080, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020I_STR.wav", "answer": "there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company", "subset": "str", "task_type": "understanding", "prediction": "There shouldn't be any risk to the banks of this sort of stuff, said Lawrence Call, a banking analyst at Merrill Lynch and Company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1081, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020K_STR.wav", "answer": "the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn", "subset": "str", "task_type": "understanding", "prediction": "The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1082, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020O_STR.wav", "answer": "unable to agree on friday the board must meet again at least by phone to register its choice", "subset": "str", "task_type": "understanding", "prediction": "Unable to agree on Friday, the board must meet again, at least by phone, to register its choice.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1083, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020P_STR.wav", "answer": "commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models", "subset": "str", "task_type": "understanding", "prediction": "Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories with new models.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1084, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C020T_STR.wav", "answer": "rates fell on short term treasury bills", "subset": "str", "task_type": "understanding", "prediction": "rates fell on short term treasury bills", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1085, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C0210_STR.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "str", "task_type": "understanding", "prediction": "yesterday moody s investors service raised milkco s credit ratings in recognition of the improved outlook for steady financial recovery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1086, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C0211_STR.wav", "answer": "about three point five billion dollars of securities are affected", "subset": "str", "task_type": "understanding", "prediction": "About $3.5 billion of securities are affected.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1087, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_440C0212_STR.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "str", "task_type": "understanding", "prediction": "He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1088, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_441C0207_STR.wav", "answer": "in japan it's all greek so to speak", "subset": "str", "task_type": "understanding", "prediction": "in japan it is all greek so to speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1089, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_441C020K_STR.wav", "answer": "the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four", "subset": "str", "task_type": "understanding", "prediction": "The following officials, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1090, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_441C020T_STR.wav", "answer": "has exposure really been reduced", "subset": "str", "task_type": "understanding", "prediction": "has exposure really been reduced", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1091, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_441C0214_STR.wav", "answer": "he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market", "subset": "str", "task_type": "understanding", "prediction": "He also said the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1092, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_441C0215_STR.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "str", "task_type": "understanding", "prediction": "He said such products could be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1093, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_441C0216_STR.wav", "answer": "he declined to name specific products", "subset": "str", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1094, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C0201_STR.wav", "answer": "bids totaling five hundred twenty five point five million dollars were submitted", "subset": "str", "task_type": "understanding", "prediction": "Bids totalling $525.5 million, were submitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1095, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C020A_STR.wav", "answer": "under terms previously reported the italian agricultural concern assumed that one hundred ninety five million dollars in subordinated debt as part of the transaction", "subset": "str", "task_type": "understanding", "prediction": "Under terms previously reported, the Italian agricultural concern assumed the $195 million in subordinated debt as part of the transaction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1096, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C020H_STR.wav", "answer": "we just received the suit and the document is massive it's two hundred pages", "subset": "str", "task_type": "understanding", "prediction": "We just received the suit, and the document is massive. It is 200 pages.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1097, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C020I_STR.wav", "answer": "but on the first read through the case is without merit and we intend to fight it", "subset": "str", "task_type": "understanding", "prediction": "But on the first read through, the case is without merit. And we intend to fight it.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1098, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C020N_STR.wav", "answer": "we're going to be bidders said a top official of a major oil company", "subset": "str", "task_type": "understanding", "prediction": "We are going to be bidders, said a top official of a major oil company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1099, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C020P_STR.wav", "answer": "the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding", "subset": "str", "task_type": "understanding", "prediction": "The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26% of its shares outstanding.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C020T_STR.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "str", "task_type": "understanding", "prediction": "Volume was modest, as 326.7 million shares changed hands compared with 396.5 million Friday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C020W_STR.wav", "answer": "yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery", "subset": "str", "task_type": "understanding", "prediction": "Yesterday, Moody's Investors Service raised Lilco's credit ratings in recognition of the improved outlook for steady financial recovery.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_442C0216_STR.wav", "answer": "important personnel usually are locked into long term contracts with incentives aimed at reducing that problem", "subset": "str", "task_type": "understanding", "prediction": "Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C0202_STR.wav", "answer": "the department previously said jobs rose by four hundred forty eight thousand in january", "subset": "str", "task_type": "understanding", "prediction": "The Department previously said jobs rose by 448000 in January.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C0203_STR.wav", "answer": "using a measure that counts the military among the employed the rate was unchanged at six point six percent last month", "subset": "str", "task_type": "understanding", "prediction": "Using a measure that counts the military among the employed, the rate was unchanged at 6.6% last month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C0205_STR.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "str", "task_type": "understanding", "prediction": "MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C0206_STR.wav", "answer": "the toronto based company provides mortgage guarantees to the canadian real estate industry", "subset": "str", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to the Canadian real estate industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C0207_STR.wav", "answer": "it isn't clear yet whether the campaign works", "subset": "str", "task_type": "understanding", "prediction": "it isn t clear yet whether the campaign works", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C020D_STR.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty", "subset": "str", "task_type": "understanding", "prediction": "Among export LED electrical and computer makers. Japan, Victor Company of 50 to 2320.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C020I_STR.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "str", "task_type": "understanding", "prediction": "Unless otherwise noted, changes involved direct holdings of common stock took place in September and October 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C020J_STR.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "str", "task_type": "understanding", "prediction": "Companies are listed where transactions generally aggregate 10000 shares, or $100000.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_443C0210_STR.wav", "answer": "the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share", "subset": "str", "task_type": "understanding", "prediction": "Companies are followed by at least three analysts at a minimum. Five cent change in actual earnings per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C0201_STR.wav", "answer": "in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share", "subset": "str", "task_type": "understanding", "prediction": "In the 1985 quarter, the owner and operator of health maintenance organizations earned $6.9 million or 24 cents a share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C0202_STR.wav", "answer": "it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars", "subset": "str", "task_type": "understanding", "prediction": "It had forecast a 1986 fourth quarter loss of $18 million to $22 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C020B_STR.wav", "answer": "monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference", "subset": "str", "task_type": "understanding", "prediction": "Monday's crash is likely to affect at least one other piece of pending legislation, a sweeping trade bill that is now the subject of a House Senate conference.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C020C_STR.wav", "answer": "senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash", "subset": "str", "task_type": "understanding", "prediction": "Senate Finance Chairman Lloyd Bentsen, D. Texas said he would speed up work on the package because of the crash.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C020D_STR.wav", "answer": "it adds to the support for the trade bill getting through he said", "subset": "str", "task_type": "understanding", "prediction": "it adds to the support for the trade bill getting through he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C020F_STR.wav", "answer": "so far they have declined to comment publicly on their plans", "subset": "str", "task_type": "understanding", "prediction": "So far, they have declined to comment publicly on their plans.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C020G_STR.wav", "answer": "state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do", "subset": "str", "task_type": "understanding", "prediction": "State officials, however, say the airlines have indicated they will comply with most of the standards as long as competitors do.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C020H_STR.wav", "answer": "among export led electrical and computer makers japan victor company fell fifty two thousand three hundred twenty", "subset": "str", "task_type": "understanding", "prediction": "Among export LED electrical and computer makers. Japan Victor Company fell 52320.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C020Y_STR.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday", "subset": "str", "task_type": "understanding", "prediction": "Volume was 18190000 shares, compared with 10550000 Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C0210_STR.wav", "answer": "the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent", "subset": "str", "task_type": "understanding", "prediction": "The institute said earned premiums rose 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_444C0214_STR.wav", "answer": "money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say", "subset": "str", "task_type": "understanding", "prediction": "Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C0208_STR.wav", "answer": "their business isn't just a job but their investment", "subset": "str", "task_type": "understanding", "prediction": "their business isn t just a job but their investment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020I_STR.wav", "answer": "the airline imposed the contract without union bargaining", "subset": "str", "task_type": "understanding", "prediction": "The airline imposed the contract, without union bargaining.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020J_STR.wav", "answer": "yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling", "subset": "str", "task_type": "understanding", "prediction": "Yesterday session began with a sharp, quick decline in the Industrial Average of more than 45 points, which some market analysts attributed to foreign selling.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020M_STR.wav", "answer": "gillette is again a target of a major corporate raider", "subset": "str", "task_type": "understanding", "prediction": "Gillette is, again, a target of a major corporate raider.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020O_STR.wav", "answer": "a lengthy fight is likely", "subset": "str", "task_type": "understanding", "prediction": "a lengthy fight is likely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020P_STR.wav", "answer": "about all the businessman can count on is that policy will be pretty volatile", "subset": "str", "task_type": "understanding", "prediction": "But all the businessmen can count on is that policy will be pretty volatile.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020R_STR.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "str", "task_type": "understanding", "prediction": "If the Fed pushes the dollar higher. It may curb the demand for US exports.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020X_STR.wav", "answer": "continental started the appeal process but recently settled the case", "subset": "str", "task_type": "understanding", "prediction": "Continental started the appeal process, but recently settled the case.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C020Y_STR.wav", "answer": "neither side would disclose terms", "subset": "str", "task_type": "understanding", "prediction": "neither side would disclose terms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_445C0213_STR.wav", "answer": "from america china looked good", "subset": "str", "task_type": "understanding", "prediction": "america and china put together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C0206_STR.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "str", "task_type": "understanding", "prediction": "were not prepared to be advocates for the kgb", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020B_STR.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "str", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020C_STR.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "str", "task_type": "understanding", "prediction": "The unsold balance late yesterday was about $36.3 million, according to Shearson, Lehman Brothers, the lead underwriter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020E_STR.wav", "answer": "fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments", "subset": "str", "task_type": "understanding", "prediction": "Fidelity had contended that Gencor isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020I_STR.wav", "answer": "he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year", "subset": "str", "task_type": "understanding", "prediction": "He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020K_STR.wav", "answer": "in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty", "subset": "str", "task_type": "understanding", "prediction": "In many ways, that is just what UBS has done since Mr. Zeghers was named president in 1980.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020L_STR.wav", "answer": "assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven", "subset": "str", "task_type": "understanding", "prediction": "Assets more than doubled since then to 160.4 billion Swiss francs.115.6 billion dollars in 1987.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020N_STR.wav", "answer": "the real estate investment trust said it was still hoping to reach a new credit arrangement", "subset": "str", "task_type": "understanding", "prediction": "The real estate investment trust said it was still hoping to reach a new credit agreement.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020S_STR.wav", "answer": "among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women", "subset": "str", "task_type": "understanding", "prediction": "Among men,41% supported boosting the space exploration budget, compared with 90% of women.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020T_STR.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "str", "task_type": "understanding", "prediction": "According to the average estimate, a 7 economists surveyed by Dow Jones Capital Markets report new orders for US durable goods rose 2.4% last month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020V_STR.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "str", "task_type": "understanding", "prediction": "Mace Lem reported June 22. It came as a big surprise to most analysts and helped trigger a powerful bond rally that day.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_446C020W_STR.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "str", "task_type": "understanding", "prediction": "durable goods reports great to me are highly volatile from month to month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C0201_STR.wav", "answer": "i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month", "subset": "str", "task_type": "understanding", "prediction": "I don't mean there couldn't be some improvements in the Revenue Act of 1986, which took effect this month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C0206_STR.wav", "answer": "he cites the law of large numbers can you really expect it to grow at large numbers very long", "subset": "str", "task_type": "understanding", "prediction": "He cites the law of large numbers. Can you really expect it to grow at large numbers very long.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C0209_STR.wav", "answer": "washington national is a financial services concern", "subset": "str", "task_type": "understanding", "prediction": "Washington National is a financial services concern", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C020E_STR.wav", "answer": "northgate exploration limited said it sold four million common shares at eight dollars each", "subset": "str", "task_type": "understanding", "prediction": "Northgate Exploration Limited said it sold 4 million common shares at $8 each.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C020H_STR.wav", "answer": "the toronto based gold mining concern said proceeds would be used for general purposes", "subset": "str", "task_type": "understanding", "prediction": "The Toronto based gold mining concern said proceeds would be used for general purposes.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C020M_STR.wav", "answer": "envirodyne said it expects sales to be the highest for any third quarter in the company's history", "subset": "str", "task_type": "understanding", "prediction": "Envirodyne said it expects sales to be the highest for any third quarter in the company's history.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C020S_STR.wav", "answer": "but while the fed stands pat it is coming under increasing attack from both sides", "subset": "str", "task_type": "understanding", "prediction": "but while the fed stands pat it is coming under increasing attack from both sides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C020T_STR.wav", "answer": "some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year", "subset": "str", "task_type": "understanding", "prediction": "some critics including high reagan administration officials are raising the alarm that the feds policy is too tight and could cause recession next year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C020Y_STR.wav", "answer": "increasingly people who test positive join the support groups that have sprung up across the country in the past year", "subset": "str", "task_type": "understanding", "prediction": "Increasingly, people who test positive join the support groups that have sprung up across the country in the past year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C0210_STR.wav", "answer": "founded last october new york's body positive already has sixteen groups meeting every two weeks", "subset": "str", "task_type": "understanding", "prediction": "Founded last October, New Yorks body positive already has 16 groups meeting every two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/F06_447C0211_STR.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "str", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C0201_STR.wav", "answer": "at n. e. c. the need for international managers will keep rising", "subset": "str", "task_type": "understanding", "prediction": "At Nec, the need for international managers will keep rising.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C0205_STR.wav", "answer": "the company previously traded over the counter", "subset": "str", "task_type": "understanding", "prediction": "the company previously traded over the counter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C020N_STR.wav", "answer": "it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan", "subset": "str", "task_type": "understanding", "prediction": "it can sign off to the plan file a competing plan or take a completely passive role that neither endorses nor opposes the plan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C020U_STR.wav", "answer": "the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction", "subset": "str", "task_type": "understanding", "prediction": "the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday s auction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C020V_STR.wav", "answer": "the rate on six month bills fell to six point seven three percent from six point eight three percent", "subset": "str", "task_type": "understanding", "prediction": "the rate on six month bills fell to six point seven three percent from six point eight three percent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C020W_STR.wav", "answer": "durable goods reports frequently are highly volatile from month to month", "subset": "str", "task_type": "understanding", "prediction": "Durable goods orders frequently are highly volatile from month to month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C020X_STR.wav", "answer": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "subset": "str", "task_type": "understanding", "prediction": "many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C020Y_STR.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "str", "task_type": "understanding", "prediction": "estimates for the gain ranged from two percent to three percent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C0213_STR.wav", "answer": "he said such products would be marketed by other companies with experience in that business", "subset": "str", "task_type": "understanding", "prediction": "He said such products would be marketed by other companies with experience in that business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_440C0214_STR.wav", "answer": "he declined to name specific products", "subset": "str", "task_type": "understanding", "prediction": "he declined to name specific products", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C0209_STR.wav", "answer": "the earlier rise was previously reported as four point three percent", "subset": "str", "task_type": "understanding", "prediction": "The earlier rise was previously reported, as 4.3%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020A_STR.wav", "answer": "if defense is excluded march orders rose one percent after a three percent increase in february", "subset": "str", "task_type": "understanding", "prediction": "If defense is excluded March orders rose 1% after a 3% increase in February.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020B_STR.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "str", "task_type": "understanding", "prediction": "Grand auto slip 3 to 15 and 1,8 for the American slash standard.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020C_STR.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "str", "task_type": "understanding", "prediction": "The company, which runs retail automotive stores. Told Shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020D_STR.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "str", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020F_STR.wav", "answer": "also a move to base it abroad will have tax advantages", "subset": "str", "task_type": "understanding", "prediction": "also a move to base it abroad will have tax advantages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020L_STR.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "str", "task_type": "understanding", "prediction": "Those identified as beneficial owners hold at least 10% of a company's equity securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020N_STR.wav", "answer": "companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars", "subset": "str", "task_type": "understanding", "prediction": "Companies are listed where transactions generally aggregate 10000 shares, or $100000.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020O_STR.wav", "answer": "about all the businessman can count on is that policy will be pretty volatile", "subset": "str", "task_type": "understanding", "prediction": "About all the businessmen can count on is that policy will be pretty volatile", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020S_STR.wav", "answer": "analysts haven't focused on what happened to them", "subset": "str", "task_type": "understanding", "prediction": "analysts havent focused on what happened to them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C020V_STR.wav", "answer": "closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities", "subset": "str", "task_type": "understanding", "prediction": "Closed end funds are traded on exchanges like stocks, but invest in a wide portfolio of other securities", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C0210_STR.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "str", "task_type": "understanding", "prediction": "after the offering republic new york will hold about forty nine percent of the affiliate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C0212_STR.wav", "answer": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "subset": "str", "task_type": "understanding", "prediction": "volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_441C0213_STR.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "str", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C0203_STR.wav", "answer": "the bank holding company slated another fifty million dollar sale next tuesday", "subset": "str", "task_type": "understanding", "prediction": "The bank holding company is slated another $50 million sale next Tuesday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C020C_STR.wav", "answer": "shamrock has interests in television and radio stations energy services real estate and venture capital", "subset": "str", "task_type": "understanding", "prediction": "Shamrock has interests in television and radio stations. Energy services, real estate and venture capital.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C020F_STR.wav", "answer": "this morning the asking price for the stock was four thousand eight hundred fifty but there were no buyers", "subset": "str", "task_type": "understanding", "prediction": "This morning, the asking price for the stock was 4850, but there were no buyers.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C020G_STR.wav", "answer": "a monsanto spokesman said there's very little we can say", "subset": "str", "task_type": "understanding", "prediction": "a monsanto spokesman said there is very little we can say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C020J_STR.wav", "answer": "according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month", "subset": "str", "task_type": "understanding", "prediction": "according to the average estimate of seven economists surveyed by dow jones capital markets reports new orders for US durable goods rose two point four percent last month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C020K_STR.wav", "answer": "that would follow a two point two percent drop in may", "subset": "str", "task_type": "understanding", "prediction": "that would follow a two point two percent drop in may", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C020L_STR.wav", "answer": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "subset": "str", "task_type": "understanding", "prediction": "the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_442C0214_STR.wav", "answer": "a change in the firm's ownership also should turn on a bright warning light", "subset": "str", "task_type": "understanding", "prediction": "a change in the firms ownership should turn on a bright warning light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C0201_STR.wav", "answer": "the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before", "subset": "str", "task_type": "understanding", "prediction": "the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C0208_STR.wav", "answer": "local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members", "subset": "str", "task_type": "understanding", "prediction": "But the union has already lost 28% of the 73 new members.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020C_STR.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "str", "task_type": "understanding", "prediction": "Employment looked strong, inflation was low, and consumer spending and investment were both at half decent growth.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020E_STR.wav", "answer": "kyocera was up sixty at five thousand two hundred sixty", "subset": "str", "task_type": "understanding", "prediction": "Kyocera was up 60, at 5260.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020K_STR.wav", "answer": "after the third period ashland's coal operations began a process of becoming an independent company", "subset": "str", "task_type": "understanding", "prediction": "After the third period, Ashland's coal operation began a process of becoming an independent company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020L_STR.wav", "answer": "when its initial public offering is completed ashland is expected to retain a forty six percent stake", "subset": "str", "task_type": "understanding", "prediction": "When its initial public offering is completed. Ashland is expected to retain a 46% stake.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020M_STR.wav", "answer": "the new company ashland coal incorporated is listed on the new york stock exchange", "subset": "str", "task_type": "understanding", "prediction": "The new company, Ashland Coal Incorporated, is listed on the New York Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020P_STR.wav", "answer": "in addition u. s. west's data solutions business applied communications incorporated is working out well and performing better ahead of all our schedules", "subset": "str", "task_type": "understanding", "prediction": "in addition u s wests data solutions business applied communications incorporated is working out well and is working better and ahead of all of our schedules", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020Q_STR.wav", "answer": "m. c. i. plans to begin offering the service at the end of this month", "subset": "str", "task_type": "understanding", "prediction": "MCI plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020R_STR.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "str", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020S_STR.wav", "answer": "a print media campaign will begin the following day", "subset": "str", "task_type": "understanding", "prediction": "A print media campaign begins on Monday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020U_STR.wav", "answer": "fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards", "subset": "str", "task_type": "understanding", "prediction": "Fees range up to about $40 annually for basic cards and $60 a year for gold cards.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020X_STR.wav", "answer": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand on monday", "subset": "str", "task_type": "understanding", "prediction": "volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand on monday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020Y_STR.wav", "answer": "there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged", "subset": "str", "task_type": "understanding", "prediction": "There were 256 issues advancing,303 declining and 292 unchanged.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C020Z_STR.wav", "answer": "companies listed below reported quarterly profit substantially different from the average of analysts' estimates", "subset": "str", "task_type": "understanding", "prediction": "Companies listed below reported quarterly profit, substantially different from the average of analysts estimates.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C0211_STR.wav", "answer": "estimated and actual results involving losses are omitted", "subset": "str", "task_type": "understanding", "prediction": "Estimated and actual results involving losses are omitted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C0212_STR.wav", "answer": "yesterday's losers included automobiles", "subset": "str", "task_type": "understanding", "prediction": "yesterdays losers included automobiles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_443C0213_STR.wav", "answer": "honda was down ten to one thousand nine hundred thirty", "subset": "str", "task_type": "understanding", "prediction": "Honda was down 10 to 1930.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C0203_STR.wav", "answer": "revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars", "subset": "str", "task_type": "understanding", "prediction": "Revenue in the quarter more than doubled to $362.4 million from $149.2 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C0204_STR.wav", "answer": "separately new york state sold about seventy seven point one million dollars of certificates of participation", "subset": "str", "task_type": "understanding", "prediction": "Separately, New York State sold about $77.1 million of certificates of participation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C0205_STR.wav", "answer": "the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven", "subset": "str", "task_type": "understanding", "prediction": "The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C0206_STR.wav", "answer": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "subset": "str", "task_type": "understanding", "prediction": "the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C020K_STR.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "str", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C020L_STR.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "str", "task_type": "understanding", "prediction": "no one is making very much money on it acknowledges brian j kelly chairman of bell atlantic s investment development unit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C020M_STR.wav", "answer": "we had to sustain some modest operating losses", "subset": "str", "task_type": "understanding", "prediction": "we had to sustain some modest operating losses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C020O_STR.wav", "answer": "the company declined to identify the bidders but said it received offers in the high forty dollars per share", "subset": "str", "task_type": "understanding", "prediction": "The company declined to identify the bidders. But said it received offers in the high $40 per share.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C020T_STR.wav", "answer": "the market's strength may show that demand isn't all a creation of incentives", "subset": "str", "task_type": "understanding", "prediction": "The market strength may show that demand isn't all a creations, he said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_444C020V_STR.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "str", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_445C0205_STR.wav", "answer": "no one at the state department wants to let spies in", "subset": "str", "task_type": "understanding", "prediction": "no one at the state department wants to let spies in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_445C0206_STR.wav", "answer": "we're not prepared to be advocates for the k. g. b.", "subset": "str", "task_type": "understanding", "prediction": "we are not prepared to be advocates for the kgb", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_445C0207_STR.wav", "answer": "but the penalties for failure are real", "subset": "str", "task_type": "understanding", "prediction": "but the penalties for failure are real", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_445C020H_STR.wav", "answer": "the suit seeks to block the contract which would have raised pay levels and cut benefits", "subset": "str", "task_type": "understanding", "prediction": "The suit seeks to block the contract. Which would have raised pay levels, and cut benefits.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_445C020K_STR.wav", "answer": "but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close", "subset": "str", "task_type": "understanding", "prediction": "but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday s close", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_445C020L_STR.wav", "answer": "although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading", "subset": "str", "task_type": "understanding", "prediction": "although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_445C0210_STR.wav", "answer": "as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday", "subset": "str", "task_type": "understanding", "prediction": "As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_446C0202_STR.wav", "answer": "to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred", "subset": "str", "task_type": "understanding", "prediction": "To make them directly comparable, each index is based on the close of 1969, equaling 100.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_446C0203_STR.wav", "answer": "the percentage change is since year end", "subset": "str", "task_type": "understanding", "prediction": "the percentage change is since year end", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_446C0207_STR.wav", "answer": "that doesn't mean mr. icahn has committed any wrongdoing", "subset": "str", "task_type": "understanding", "prediction": "That doesn't mean Mr. Icahn has committed any wrongdoing.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_446C020P_STR.wav", "answer": "it's still unclear", "subset": "str", "task_type": "understanding", "prediction": "its still unclear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_446C020Q_STR.wav", "answer": "there was a striking split between the sexes with men more likely than women to favor space programs", "subset": "str", "task_type": "understanding", "prediction": "there was a striking split between the sexes with men more likely than women to favor space programs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_446C020U_STR.wav", "answer": "that would follow a two point two percent drop in may", "subset": "str", "task_type": "understanding", "prediction": "that would follow a two point four drop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_446C0213_STR.wav", "answer": "it also owns three state business magazines in florida georgia and arizona", "subset": "str", "task_type": "understanding", "prediction": "it also owns three state business magazines in florida georgia and arizona", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C0204_STR.wav", "answer": "mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent", "subset": "str", "task_type": "understanding", "prediction": "Mr. Roberts said he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C0207_STR.wav", "answer": "washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own", "subset": "str", "task_type": "understanding", "prediction": "Washington National paid $19 a share for the 2.6 million United presidential shares that didn't already own.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C020C_STR.wav", "answer": "sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days", "subset": "str", "task_type": "understanding", "prediction": "Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C020O_STR.wav", "answer": "the company expects to report its results in about two weeks", "subset": "str", "task_type": "understanding", "prediction": "The company expects to report its results in about two weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C020U_STR.wav", "answer": "other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation", "subset": "str", "task_type": "understanding", "prediction": "Other analysts say the Fed needs to tighten policy further to support the dollar and prevent inflation.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C020W_STR.wav", "answer": "the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape", "subset": "str", "task_type": "understanding", "prediction": "the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite table", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C020X_STR.wav", "answer": "salant shares closed unchanged on the big board at nine dollars and seventy five cents", "subset": "str", "task_type": "understanding", "prediction": "Salant shares closed unchanged on the big board at $9.75.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M05_447C0216_STR.wav", "answer": "the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight", "subset": "str", "task_type": "understanding", "prediction": "the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C0203_STR.wav", "answer": "about half these managers are in the u. s.", "subset": "str", "task_type": "understanding", "prediction": "about half these managers are in the us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C0207_STR.wav", "answer": "the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks", "subset": "str", "task_type": "understanding", "prediction": "The agency isn't likely to take any action until the unions rank and file votes on the contract in 2 to three weeks.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C020C_STR.wav", "answer": "the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture", "subset": "str", "task_type": "understanding", "prediction": "The rise in that category in July was LED by increased orders for aircraft and parts, non electrical machinery, lumber and furniture.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C020D_STR.wav", "answer": "interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction", "subset": "str", "task_type": "understanding", "prediction": "Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C020J_STR.wav", "answer": "the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said", "subset": "str", "task_type": "understanding", "prediction": "The independent committee will recommend that holders accept the offer at a meeting expected to be held in December. Twa said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C020L_STR.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "str", "task_type": "understanding", "prediction": "the investor now owns seventy three percent of the company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C020M_STR.wav", "answer": "texaco has three choices a company adviser says", "subset": "str", "task_type": "understanding", "prediction": "texaco has three choices a company adviser says", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_440C020S_STR.wav", "answer": "what we don't know is how much is price and how much is volume", "subset": "str", "task_type": "understanding", "prediction": "what we dont know is how much is price and how much is volume", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C0201_STR.wav", "answer": "first commodity appealed the expulsion and fine to the c. f. t. c.", "subset": "str", "task_type": "understanding", "prediction": "First, commodity appealed the expulsion and fine to the CFTC.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C0202_STR.wav", "answer": "a commission spokesman said a decision on the appeal is expected soon", "subset": "str", "task_type": "understanding", "prediction": "A commission spokesman said a decision on the appeal is expected soon.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C0205_STR.wav", "answer": "the language is a big problem", "subset": "str", "task_type": "understanding", "prediction": "the language is a big problem", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C0206_STR.wav", "answer": "in europe an american can at least read street signs", "subset": "str", "task_type": "understanding", "prediction": "in europe an american can at least read street signs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C0208_STR.wav", "answer": "the overall gain the fifth in the past seven months followed a revised four point one percent increase in february", "subset": "str", "task_type": "understanding", "prediction": "The overall gain, the fifth in the past seven months, followed a revised 4.1% increase in February.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020E_STR.wav", "answer": "elders brewing will be based outside australia because seventy percent of its assets are in britain and canada", "subset": "str", "task_type": "understanding", "prediction": "Elders Brewing will be based outside Australia because 70 per cent of its assets are in Britain and Canada.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020H_STR.wav", "answer": "two years ago b. a. s. f. made three separate acquisitions in the u. s.", "subset": "str", "task_type": "understanding", "prediction": "Two years ago, BASF made three separate acquisitions in the US.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020I_STR.wav", "answer": "its biggest was the one billion dollar purchase of united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry", "subset": "str", "task_type": "understanding", "prediction": "Its biggest was the $1 billion purchase of United Technologies Corporation's Inmont subsidiary, a major supplier of paint to the auto industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020J_STR.wav", "answer": "today ninety percent of the four billion dollars of b. a. s. f. sales in the u. s. is produced there", "subset": "str", "task_type": "understanding", "prediction": "today ninety percent of the four billion dollars of basf sales in the us is produced there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020M_STR.wav", "answer": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "subset": "str", "task_type": "understanding", "prediction": "unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020P_STR.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "str", "task_type": "understanding", "prediction": "if the dollar starts to plunge the fed may step up its defense of the currency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020Q_STR.wav", "answer": "if the fed pushes the dollar higher it may curb the demand for u. s. exports", "subset": "str", "task_type": "understanding", "prediction": "If the Fed pushes the dollar higher. It may curb the demand for US exports.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020W_STR.wav", "answer": "although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year", "subset": "str", "task_type": "understanding", "prediction": "although closed end funds have been around since at least the nineteen twenty s they have boomed in popularity this year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020X_STR.wav", "answer": "the bond funds in particular provide robust yields for investors and hefty fees for underwriters", "subset": "str", "task_type": "understanding", "prediction": "The bond funds, in particular, provide robust yields for investors and hefty fees for underwriters.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C020Y_STR.wav", "answer": "republic new york rose one and one quarter to forty five and seven eighths", "subset": "str", "task_type": "understanding", "prediction": "Republic, New York, rose 1 and 1 quarter to 45 and 7/8.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_441C0211_STR.wav", "answer": "at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six", "subset": "str", "task_type": "understanding", "prediction": "At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0204_STR.wav", "answer": "m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock", "subset": "str", "task_type": "understanding", "prediction": "MICC investments have three series of publicly traded preferred shares and 10 series of privately held preferred stock.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0205_STR.wav", "answer": "m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second", "subset": "str", "task_type": "understanding", "prediction": "Micc said it intends to pay the dividend arrears on July 31 to stock of record July 2.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0206_STR.wav", "answer": "the toronto based company provides mortgage guarantees to the canadian real estate industry", "subset": "str", "task_type": "understanding", "prediction": "The Toronto based company provides mortgage guarantees to the Canadian real estate industry.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0207_STR.wav", "answer": "grand auto slid three to fifteen and one eighth on the american stock exchange", "subset": "str", "task_type": "understanding", "prediction": "Grand Auto slid 3 to 15 and 1/8 on the American Stock Exchange.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0208_STR.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "str", "task_type": "understanding", "prediction": "The company, which runs a retail automotive stores, told Shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0209_STR.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "str", "task_type": "understanding", "prediction": "It received no proposal that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C020B_STR.wav", "answer": "shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said", "subset": "str", "task_type": "understanding", "prediction": "Shamrock s pretax profit for the sale was $125 million, the spokesman said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C020D_STR.wav", "answer": "sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday", "subset": "str", "task_type": "understanding", "prediction": "Sony Corporation, for example, closed at ¥4950. $34.50 a share yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C020O_STR.wav", "answer": "but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders", "subset": "str", "task_type": "understanding", "prediction": "But if the winning bids are as high as they were in some deals earlier this year, then we are not going to be winning bidders.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C020R_STR.wav", "answer": "the company then accepts the shares tendered at the lowest price needed to reach its total then pays that amount for all shares it purchases", "subset": "str", "task_type": "understanding", "prediction": "The company then accepts the shares tendered at the lowest price needed to reach its total, then pays that amount for all shares it purchases.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C020U_STR.wav", "answer": "the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine", "subset": "str", "task_type": "understanding", "prediction": "The 100 share index closed 6.8 points lower at 1759.9.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0211_STR.wav", "answer": "so normalcy has returned", "subset": "str", "task_type": "understanding", "prediction": "so normalcy has returned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_442C0215_STR.wav", "answer": "money managers who sell their firm but then continue working for them may be less dedicated under new ownership they say", "subset": "str", "task_type": "understanding", "prediction": "Money managers sell their firm, but then continue working for them. Maybe less dedicated under new ownership, they say.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C0209_STR.wav", "answer": "nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics", "subset": "str", "task_type": "understanding", "prediction": "Nonetheless, the union has moved the experiment to Richmond, Virginia, and has received inquiries from other unions about its tactics.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020A_STR.wav", "answer": "in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound", "subset": "str", "task_type": "understanding", "prediction": "In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020B_STR.wav", "answer": "that was certainly true last week", "subset": "str", "task_type": "understanding", "prediction": "that was certainly true last week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020F_STR.wav", "answer": "sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty", "subset": "str", "task_type": "understanding", "prediction": "Sony, which lost points in previous sessions this week, rebounded 80 to 5130.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020H_STR.wav", "answer": "those identified as beneficial owners hold at least ten percent of a company's equity securities", "subset": "str", "task_type": "understanding", "prediction": "Those identified as beneficial owners hold at least 10% of the company's equity securities.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020N_STR.wav", "answer": "the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains", "subset": "str", "task_type": "understanding", "prediction": "The official declined to elaborate on projections for non telephone operations. But cited several indicators of recent gains.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020O_STR.wav", "answer": "he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force", "subset": "str", "task_type": "understanding", "prediction": "He said the company has entered 16 smaller cellular markets this year and has expanded its financial services workforce.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020V_STR.wav", "answer": "in certain cases the cards are given free to subscribers", "subset": "str", "task_type": "understanding", "prediction": "in certain cases the cards are given free to subscribers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C020W_STR.wav", "answer": "the american stock exchange index lost zero point seven three to three hundred eighty point nine four", "subset": "str", "task_type": "understanding", "prediction": "The American Stock Exchange index lost 0.73 to 380.94.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_443C0214_STR.wav", "answer": "nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty", "subset": "str", "task_type": "understanding", "prediction": "Nissan lost 30 to 1520, and Toyota was down 30 to end the day at 2620.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C0207_STR.wav", "answer": "the issue is rated single a by moody's and single a minus by s. and p.", "subset": "str", "task_type": "understanding", "prediction": "The issue is rated single A by Moody S and single A minus by S and P.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C0208_STR.wav", "answer": "citicorp had twenty one point five billion dollars in capital at the end of last year", "subset": "str", "task_type": "understanding", "prediction": "Citicorp had $21.5 billion in capital at the end of last year.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C0209_STR.wav", "answer": "as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions", "subset": "str", "task_type": "understanding", "prediction": "As one of the most acquisition hungry of major banks, Citicorp is often required by regulators to raise additional capital as a condition of making acquisitions.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C020P_STR.wav", "answer": "in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday", "subset": "str", "task_type": "understanding", "prediction": "In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C020R_STR.wav", "answer": "the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year", "subset": "str", "task_type": "understanding", "prediction": "The mid July increase came even though automakers are offering incentives on fewer cars this year than they did last year or earlier this year", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C020S_STR.wav", "answer": "incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst", "subset": "str", "task_type": "understanding", "prediction": "incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C020U_STR.wav", "answer": "m. c. i. plans to begin offering the service at the end of the month", "subset": "str", "task_type": "understanding", "prediction": "Mci plans to begin offering the service at the end of this month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C020W_STR.wav", "answer": "a print media campaign will begin the following day", "subset": "str", "task_type": "understanding", "prediction": "A print media campaign will begin the following day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_444C0212_STR.wav", "answer": "realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars", "subset": "str", "task_type": "understanding", "prediction": "Realized capital gains increased 42% to $909 million from $640.9 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C0204_STR.wav", "answer": "the consensus was that a new piece of paper isn't required said one u. s. diplomat", "subset": "str", "task_type": "understanding", "prediction": "The consensus was that the new piece of paper isn't required, said one US diplomat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C0209_STR.wav", "answer": "and both mortgaged their homes to secure the loans they needed to start the business", "subset": "str", "task_type": "understanding", "prediction": "And both mortgaged their homes to secure the loans they needed to start the business.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020A_STR.wav", "answer": "a long list of other witnesses have also testified in the trial now in its fourth month", "subset": "str", "task_type": "understanding", "prediction": "A long list of other witnesses have also testified in the trial now, in its fourth month.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020E_STR.wav", "answer": "the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm", "subset": "str", "task_type": "understanding", "prediction": "The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020F_STR.wav", "answer": "it received no proposals that were in the best interest of the shareholders the company said", "subset": "str", "task_type": "understanding", "prediction": "It received no proposals that were in the best interest of the shareholders, the company said.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020G_STR.wav", "answer": "the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists", "subset": "str", "task_type": "understanding", "prediction": "the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020Q_STR.wav", "answer": "if the dollar starts to plunge the fed may step up its defense of the currency", "subset": "str", "task_type": "understanding", "prediction": "If the dollar starts to plunge, the Fed may step up its defense of the currency.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020S_STR.wav", "answer": "lately computer retailing has been tough on everybody", "subset": "str", "task_type": "understanding", "prediction": "lately computer retailing has been tough on everybody", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020T_STR.wav", "answer": "no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit", "subset": "str", "task_type": "understanding", "prediction": "No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C020W_STR.wav", "answer": "the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed", "subset": "str", "task_type": "understanding", "prediction": "The jury awarded Mr. Sharonberg $105 million, a figure based on 10 years of profits. Had his project been completed.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_445C0216_STR.wav", "answer": "where else in the third world is there so much energy and progress as in china", "subset": "str", "task_type": "understanding", "prediction": "where else in the third world is there so much energy and progress as in china", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_446C020F_STR.wav", "answer": "under the proposed transaction the los angeles based group would acquire the k. h. j. license and then sell itself to disney", "subset": "str", "task_type": "understanding", "prediction": "Under the proposed transaction, the Los Angeles based group would acquire the KHJ license and then sell itself to Disney.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_446C020G_STR.wav", "answer": "the closely held group doesn't have any significant assets according to william g. simon its president", "subset": "str", "task_type": "understanding", "prediction": "The closely held group doesn't have any significant assets, according to William G. Simon, its president.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_446C020H_STR.wav", "answer": "he said that for the full year wang's aiming for an after tax profit equal to three percent to five percent of sales", "subset": "str", "task_type": "understanding", "prediction": "He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_446C020Y_STR.wav", "answer": "estimates for the gain ranged from two percent to three percent", "subset": "str", "task_type": "understanding", "prediction": "estimates for the gain ranged from two percent to three percent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_446C0211_STR.wav", "answer": "after the offering republic new york will hold about forty nine percent of the affiliate", "subset": "str", "task_type": "understanding", "prediction": "after the offering republic new york will hold about forty nine percent of the affiliate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_446C0212_STR.wav", "answer": "closely held times publishing also owns two washington based publication congressional quarterly which covers capitol hill and governing which covers state and local governments", "subset": "str", "task_type": "understanding", "prediction": "Closely held Times Publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and Governing, which covers state and local governments.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_446C0214_STR.wav", "answer": "industry analysts value the company at about six hundred fifty million dollars", "subset": "str", "task_type": "understanding", "prediction": "Industry analysts value the company at about $650 million.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C0203_STR.wav", "answer": "and i'm sure you have your own list", "subset": "str", "task_type": "understanding", "prediction": "and i am sure you have your own list", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C020A_STR.wav", "answer": "united presidential is a life insurance company", "subset": "str", "task_type": "understanding", "prediction": "United presidential is your life insurance company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C020B_STR.wav", "answer": "these are uneducated people he says in english so the patients won't understand", "subset": "str", "task_type": "understanding", "prediction": "these are uneducated people he says in english so the patients won t understand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C020D_STR.wav", "answer": "i will tell you what i think in my office", "subset": "str", "task_type": "understanding", "prediction": "i will tell you what i think in my office", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C020F_STR.wav", "answer": "they were sold to underwriters led by prudential bache securities incorporated", "subset": "str", "task_type": "understanding", "prediction": "They were sold to underwriters, LED by Prudential Bache Securities, Incorporated.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C020L_STR.wav", "answer": "employment looked strong inflation was low and consumer spending and investment were holding up reasonably well", "subset": "str", "task_type": "understanding", "prediction": "Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C020R_STR.wav", "answer": "the investor now owns seventy three percent of the company", "subset": "str", "task_type": "understanding", "prediction": "the investor now owns seventy three percent of the company", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C020V_STR.wav", "answer": "manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid", "subset": "str", "task_type": "understanding", "prediction": "Manhattan Industries continued to trade above the offer price yesterday, indicating the market expects a higher bid.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_str_real/M06_447C0215_STR.wav", "answer": "shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level", "subset": "str", "task_type": "understanding", "prediction": "shearson lehman hutton incorporated s index of long term treasury bonds stayed in the very small range yesterday finishing very close to wednesday s closing level", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi_default_performance.json b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi_default_performance.json
new file mode 100644
index 0000000000000000000000000000000000000000..db8c44717f5aea987fd9513e1f530369799e0b2f
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi_default_performance.json
@@ -0,0 +1,25 @@
+{
+ "task": "ASR",
+ "dataset": "chime4_test-real_kimi",
+ "model": "Qwen2.5-Omni-7B-lora2",
+ "date": "2025-12-21 12:17:26.711677",
+ "performance": {
+ "bus": {
+ "wer": 8.13,
+ "total": 330
+ },
+ "caf": {
+ "wer": 5.77,
+ "total": 330
+ },
+ "ped": {
+ "wer": 6.23,
+ "total": 330
+ },
+ "str": {
+ "wer": 5.43,
+ "total": 330
+ }
+ },
+ "eval_method": "qwen2-audio-impl"
+}
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi_wer_details.jsonl b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi_wer_details.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..1dea944e6934a7eeba361d8dd0ec85ffed344b63
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi_wer_details.jsonl
@@ -0,0 +1,1320 @@
+{"index":1,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C0202_BUS.wav","answer":"the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years","subset":"bus","task_type":"understanding","prediction":"The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":2,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C0204_BUS.wav","answer":"r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.","subset":"bus","task_type":"understanding","prediction":"Rli Corporation, a Peoria, Illinois, based insurance holding company, will begin trading Friday on the big board under the symbol Rli.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":3,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C0209_BUS.wav","answer":"a p. b. g. c. spokeswoman declined comment","subset":"bus","task_type":"understanding","prediction":"a p b g c spokesman declined to comment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":4,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020E_BUS.wav","answer":"the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last week","subset":"bus","task_type":"understanding","prediction":"The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at the previous auction last week.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":5,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020F_BUS.wav","answer":"the average rate on new twenty six week bills rose to six point one six percent from six point one two percent","subset":"bus","task_type":"understanding","prediction":"The error rate on new 26 C bills rose to 6.16 from 6.12.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":6,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020G_BUS.wav","answer":"analysts too generally played down the effect on banks","subset":"bus","task_type":"understanding","prediction":"Analysts, too, generally played down the effect on banks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":7,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020H_BUS.wav","answer":"in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks","subset":"bus","task_type":"understanding","prediction":"In a fundamental sense, the equity markets have very little to do with the portfolios on in the commercial banks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":8,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020I_BUS.wav","answer":"there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company","subset":"bus","task_type":"understanding","prediction":"there shouldnt be any risk to the banks in this sort of stuff said lawrence cohen a banking analyst in maryland","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":9,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020O_BUS.wav","answer":"unable to agree on friday the board must meet again at least by phone to register its choice","subset":"bus","task_type":"understanding","prediction":"unable to agree on friday the board must meet again at least by phone to register its choice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":10,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020P_BUS.wav","answer":"commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models","subset":"bus","task_type":"understanding","prediction":"Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories of new models.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":11,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C020T_BUS.wav","answer":"rates fell on short term treasury bills","subset":"bus","task_type":"understanding","prediction":"rates fell on short term treasury notes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":12,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_440C0210_BUS.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"bus","task_type":"understanding","prediction":"Yesterday, Moody s Investors Service raised Lilco s credit ratings, indicating recognition of the improved outlook and steady financial recovery.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":13,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_441C0207_BUS.wav","answer":"in japan it's all greek so to speak","subset":"bus","task_type":"understanding","prediction":"in japan it is all greek so to speak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":14,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_441C020T_BUS.wav","answer":"has exposure really been reduced","subset":"bus","task_type":"understanding","prediction":"has exposure really been reduced","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":15,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_441C0214_BUS.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"bus","task_type":"understanding","prediction":"He also said that the company, for the first time, is developing drugs specifically for the over the counter consumer healthcare market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":16,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C0201_BUS.wav","answer":"bids totaling five hundred twenty five point five million dollars were submitted","subset":"bus","task_type":"understanding","prediction":"Its totaling $525.5 million, were submitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":17,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020A_BUS.wav","answer":"under terms previously reported the italian agricultural concern assumed about one hundred ninety five million dollars in subordinated debt as part of the transaction","subset":"bus","task_type":"understanding","prediction":"Under terms previously reported, the Italian agricultural concern assumed about $195 million in subordinated debt as part of the transaction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":18,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020H_BUS.wav","answer":"we just received the suit and the document is massive it's two hundred pages","subset":"bus","task_type":"understanding","prediction":"We just received the suit, and the document is massive. It is 200 pages.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":19,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020I_BUS.wav","answer":"but on the first read through the case is without merit and we intend to fight it","subset":"bus","task_type":"understanding","prediction":"but on the first read through the case stood without merit and we intend to fight it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":20,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020N_BUS.wav","answer":"we're going to be bidders said a top official of a major oil company","subset":"bus","task_type":"understanding","prediction":"we are going to be bidders said a top official of a major oil company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":21,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020P_BUS.wav","answer":"the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding","subset":"bus","task_type":"understanding","prediction":"The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26 per cent of its shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":22,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020T_BUS.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"bus","task_type":"understanding","prediction":"Volume was modest, as 326.7 million shares changed hands compared to 396.5 million Friday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":23,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020W_BUS.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"bus","task_type":"understanding","prediction":"Yesterday, Moody S. Investors Service raised Locus credit ratings in recognition of the improved outlook for steady financial recovery.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":24,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020X_BUS.wav","answer":"about three point five billion dollars of securities are affected","subset":"bus","task_type":"understanding","prediction":"about three point five billion dollars of securities are affected","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":25,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020Y_BUS.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"bus","task_type":"understanding","prediction":"He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":26,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C020Z_BUS.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"bus","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":27,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_442C0210_BUS.wav","answer":"he declined to name specific products","subset":"bus","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":28,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C0202_BUS.wav","answer":"the department previously said jobs rose by four hundred forty eight thousand in january","subset":"bus","task_type":"understanding","prediction":"The department previously said jobs rose by 448000 in January","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":29,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C0203_BUS.wav","answer":"using a measure that counts the military among the employed the rate was unchanged at six point six percent last month","subset":"bus","task_type":"understanding","prediction":"Using a measure that counts the military among the employed, the rate was unchanged at 6.6% last month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":30,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C0205_BUS.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"bus","task_type":"understanding","prediction":"MICC said it intends to pay the dividend to holders on July 31 to stock of record July 2.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":31,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C0206_BUS.wav","answer":"the toronto based company provides mortgage guarantees to the canadian real estate industry","subset":"bus","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to the Canadian real estate industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":32,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C0207_BUS.wav","answer":"it isn't clear yet whether the campaign works","subset":"bus","task_type":"understanding","prediction":"isn clear yet whether the campaign works","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":33,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C020D_BUS.wav","answer":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty","subset":"bus","task_type":"understanding","prediction":"Among export LED electrical and computer makers. Japan Victor Company fell 50 to 2320.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":34,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C020G_BUS.wav","answer":"the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"bus","task_type":"understanding","prediction":"The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":35,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C020I_BUS.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"bus","task_type":"understanding","prediction":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of 1987","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":36,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C020J_BUS.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"bus","task_type":"understanding","prediction":"Companies are listed where transactions generally aggregate 10000 shares or 100 or less dollars.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":37,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_443C0210_BUS.wav","answer":"the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share","subset":"bus","task_type":"understanding","prediction":"The companies are followed by at least three analysts who had a minimum 5 cent change in actual earnings per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":38,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C0201_BUS.wav","answer":"in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share","subset":"bus","task_type":"understanding","prediction":"In the 1985 quarter, the owner and operator of health maintenance organizations earned $6.9 million or 24 cents a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":39,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C0202_BUS.wav","answer":"it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars","subset":"bus","task_type":"understanding","prediction":"It had forecast a 1986 fourth quarter loss of $18 million to $22 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":40,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C020B_BUS.wav","answer":"monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference","subset":"bus","task_type":"understanding","prediction":"Monday's crash is likely to affect at least one other piece of pending legislation, the sweeping trade bill that is now the subject of a House Senate conference.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":41,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C020C_BUS.wav","answer":"senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash","subset":"bus","task_type":"understanding","prediction":"Senate Finance Chairman Lloyd Bentsen of D. Texas said he would speed up work on the package, because of the crash.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":42,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C020D_BUS.wav","answer":"it adds to the support for the trade bill getting through he said","subset":"bus","task_type":"understanding","prediction":"it adds to the support for the trade bill getting through he said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":43,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C020F_BUS.wav","answer":"so far they have declined to comment publicly on their plans","subset":"bus","task_type":"understanding","prediction":"so far they have declined to comment publicly on their plans","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":44,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C020G_BUS.wav","answer":"state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do","subset":"bus","task_type":"understanding","prediction":"State officials, however, say the airlines have indicated they will comply with most of the standards as long as competitors do.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":45,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C020H_BUS.wav","answer":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty","subset":"bus","task_type":"understanding","prediction":"Among export led computer makers Japan Victor Company sold 50 to 2320.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":46,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C020Y_BUS.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday","subset":"bus","task_type":"understanding","prediction":"Volume was 18190000 shares compared with 10550000 Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":47,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C0210_BUS.wav","answer":"the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent","subset":"bus","task_type":"understanding","prediction":"The institute said earned premiums showed 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":48,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C0214_BUS.wav","answer":"money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","subset":"bus","task_type":"understanding","prediction":"Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":49,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_444C0215_BUS.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"bus","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts with incentives aimed at reducing their output","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":50,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C0208_BUS.wav","answer":"their business isn't just a job but their investment","subset":"bus","task_type":"understanding","prediction":"their business isn t just a job it s their investment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":51,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020I_BUS.wav","answer":"the airline imposed the contract without union bargaining","subset":"bus","task_type":"understanding","prediction":"The airline imposed the contract, without union bargaining.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":52,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020J_BUS.wav","answer":"yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling","subset":"bus","task_type":"understanding","prediction":"Yesterday session began with a sharp, quick decline in the industrial average of more than 45 points, which some market analysts attributed to foreign selling.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":53,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020M_BUS.wav","answer":"gillette is again a target of a major corporate raider","subset":"bus","task_type":"understanding","prediction":"gillette is again a target of a major corporate raid","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":54,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020O_BUS.wav","answer":"a lengthy fight is likely","subset":"bus","task_type":"understanding","prediction":"a lengthy fight is likely","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":55,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020P_BUS.wav","answer":"about all the businessman can count on is that policy will be pretty volatile","subset":"bus","task_type":"understanding","prediction":"About all that businessmen can count on is that policy will be pretty volatile","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":56,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020R_BUS.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"bus","task_type":"understanding","prediction":"if the fed pushes the dollar higher it may curb the demand for u s exports","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":57,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020X_BUS.wav","answer":"continental started the appeal process but recently settled the case","subset":"bus","task_type":"understanding","prediction":"Continental started the appeal process for a recently settled case","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":58,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C020Y_BUS.wav","answer":"neither side would disclose terms","subset":"bus","task_type":"understanding","prediction":"neither side would disclose terms","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":59,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_445C0213_BUS.wav","answer":"from america china looked good","subset":"bus","task_type":"understanding","prediction":"from america china looks good","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":60,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C0206_BUS.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"bus","task_type":"understanding","prediction":"we are not prepared to be advocates for the kgb","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":61,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020B_BUS.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"bus","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":62,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020C_BUS.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"bus","task_type":"understanding","prediction":"The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":63,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020E_BUS.wav","answer":"fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments","subset":"bus","task_type":"understanding","prediction":"Fidelity had contended that Gen Corp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":64,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020I_BUS.wav","answer":"he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year","subset":"bus","task_type":"understanding","prediction":"He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":65,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020K_BUS.wav","answer":"in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty","subset":"bus","task_type":"understanding","prediction":"in many ways that is just what ubs has done since mr sanders became president in may today","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":66,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020L_BUS.wav","answer":"assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven","subset":"bus","task_type":"understanding","prediction":"Assets more than doubled since then to 160.4 million Swiss francs. $115.6 billion in 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":67,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020N_BUS.wav","answer":"the real estate investment trust said it was still hoping to reach a new credit arrangement","subset":"bus","task_type":"understanding","prediction":"The real estate investment trust said it was still hoping to reach a new credit arrangement.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":68,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020S_BUS.wav","answer":"among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women","subset":"bus","task_type":"understanding","prediction":"Among men,41% supported boosting the space exploration budget compared with 19% of women.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":69,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020T_BUS.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"bus","task_type":"understanding","prediction":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u s durable goods rose two point four percent last month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":70,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020V_BUS.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"bus","task_type":"understanding","prediction":"The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":71,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_446C020W_BUS.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"bus","task_type":"understanding","prediction":"durable goods reports frequently are highly volatile from month to month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":72,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C0201_BUS.wav","answer":"i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month","subset":"bus","task_type":"understanding","prediction":"I dont mean there couldnt be some improvements in the retroactive 1986, which took effect this month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":73,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C0206_BUS.wav","answer":"he cites the law of large numbers can you really expect it to grow at large numbers very long","subset":"bus","task_type":"understanding","prediction":"He cites the law of large numbers. Can you really expect it to grow at large numbers very long.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":74,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C0209_BUS.wav","answer":"washington national is a financial services concern","subset":"bus","task_type":"understanding","prediction":"Washington National is a financial services company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":75,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C020E_BUS.wav","answer":"northgate exploration limited said it sold four million common shares at eight dollars each","subset":"bus","task_type":"understanding","prediction":"northgate exploration limited said it sold four million common shares at eight dollars each","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":76,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C020H_BUS.wav","answer":"the toronto based gold mining concern said proceeds would be used for general purposes","subset":"bus","task_type":"understanding","prediction":"The Toronto based gold mining concern said proceeds would be used for general purposes.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":77,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C020M_BUS.wav","answer":"envirodyne said it expects sales to be the highest for any third quarter in the company's history","subset":"bus","task_type":"understanding","prediction":"Envirodyne said it expects sales to be the highest for any third quarter in the company s history","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":78,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C020Q_BUS.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"bus","task_type":"understanding","prediction":"The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":79,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C020S_BUS.wav","answer":"but while the fed stands pat it is coming under increasing attack from both sides","subset":"bus","task_type":"understanding","prediction":"but while the fed stands pat it is coming under increasing attack from both sides","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":80,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C020T_BUS.wav","answer":"some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year","subset":"bus","task_type":"understanding","prediction":"Some critics, including high Reagan administration officials. Are raising the alarm that the Fed policy is too tight and could cause a recession next year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":81,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C020Y_BUS.wav","answer":"increasingly people who test positive join the support groups that have sprung up across the country in the past year","subset":"bus","task_type":"understanding","prediction":"increasingly people who test positive join the support groups that have sprung up across the country in the past year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":82,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C0210_BUS.wav","answer":"founded last october new york's body positive already has sixteen groups meeting every two weeks","subset":"bus","task_type":"understanding","prediction":"Founded last October, New Yorks body positive already has 16 groups meeting every two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":83,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F05_447C0211_BUS.wav","answer":"lately computer retailing has been tough on everybody","subset":"bus","task_type":"understanding","prediction":"lately computer retailing has been tough on him and his","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":84,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C0206_BUS.wav","answer":"two other issues began trading recently on the big board","subset":"bus","task_type":"understanding","prediction":"Two other issues began trading recently, on the big board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":85,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C0208_BUS.wav","answer":"union officials expect ratification","subset":"bus","task_type":"understanding","prediction":"Union officials expect ratification.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":86,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C020A_BUS.wav","answer":"despite the july decline durable goods orders remained seven point seven percent above the year earlier level","subset":"bus","task_type":"understanding","prediction":"Despite the July decline, durable goods orders remain 7.7% above the year earlier level.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":87,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C020B_BUS.wav","answer":"economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment","subset":"bus","task_type":"understanding","prediction":"Economists were encouraged by a 1.6% increase in new orders for nondefense capital goods. An important indicator of future business investment.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":88,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C020K_BUS.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"bus","task_type":"understanding","prediction":"The transaction requires approval of a majority of shares of the holders, not affiliated with Mr. Icahn.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":89,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C020Q_BUS.wav","answer":"the rise in auto imports also reflects higher prices for imported cars","subset":"bus","task_type":"understanding","prediction":"The rise in auto imports also reflects higher prices for imported cars.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":90,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C020R_BUS.wav","answer":"prices are going up said george c. eads vice president and chief economist at general motors corporation","subset":"bus","task_type":"understanding","prediction":"Prices are going up, said George C. Ives, vice president and chief economist at General Motors Corporation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":91,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C020Z_BUS.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"bus","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":92,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C0211_BUS.wav","answer":"about three point five billion dollars of securities are affected","subset":"bus","task_type":"understanding","prediction":"about three point five billion dollars of securities are affected","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":93,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_440C0212_BUS.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"bus","task_type":"understanding","prediction":"He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":94,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C0203_BUS.wav","answer":"first commodity officials couldn't be reached for comment","subset":"bus","task_type":"understanding","prediction":"First commodity officials couldn't be reached for comment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":95,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C0204_BUS.wav","answer":"and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort","subset":"bus","task_type":"understanding","prediction":"And then there is the explanation why Taro Danes growth in Japan is slow, despite 15 years of effort.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":96,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C020G_BUS.wav","answer":"elders finance and elders agribusiness will remain based in australia","subset":"bus","task_type":"understanding","prediction":"Elders finance and elders agribusiness will remain based in Australia.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":97,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C020K_BUS.wav","answer":"the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"bus","task_type":"understanding","prediction":"The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":98,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C020R_BUS.wav","answer":"too much focus is placed on reduction of cross country loans mr. meyerman said","subset":"bus","task_type":"understanding","prediction":"Too much focus is placed on reductionist cross country lanes, Mr. Mayerman said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":99,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C020U_BUS.wav","answer":"our guess is no","subset":"bus","task_type":"understanding","prediction":"our guess is no","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":100,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C020Z_BUS.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"bus","task_type":"understanding","prediction":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":101,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C0215_BUS.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"bus","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in the field.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":102,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_441C0216_BUS.wav","answer":"he declined to name specific products","subset":"bus","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":103,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C0202_BUS.wav","answer":"accepted bids ranged from six point two percent to six point two two five percent","subset":"bus","task_type":"understanding","prediction":"Accepted bids ranged from 6.2 per cent to 6.225 per cent.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":104,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C020E_BUS.wav","answer":"under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents","subset":"bus","task_type":"understanding","prediction":"Under Tokyo trading rules, the maximum one day drop for Sony is 500 yen, about $3.50.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":105,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C020M_BUS.wav","answer":"even some bigger companies caution that they are leery of paying too big a premium","subset":"bus","task_type":"understanding","prediction":"Even some bigger companies are cautious. They are leery of paying too big a dividend.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":106,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C020Q_BUS.wav","answer":"in a dutch auction holders tender their shares at prices within a stated range in this case between twenty eight dollars and thirty three dollars a share","subset":"bus","task_type":"understanding","prediction":"In a Dutch auction, holders tender their shares at prices within a stated range in this case between $28 and $33 a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":107,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C020S_BUS.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"bus","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower,1418.6.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":108,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C020V_BUS.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"bus","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":109,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C0212_BUS.wav","answer":"foreigners are back and negotiating with the chinese will be as tough as ever","subset":"bus","task_type":"understanding","prediction":"Foreigners are back and negotiating with the Chinese will be as tough as ever","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":110,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C0213_BUS.wav","answer":"that's fine","subset":"bus","task_type":"understanding","prediction":"that is fine","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":111,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_442C0216_BUS.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"bus","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts with incentives aimed at reducing their costs.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":112,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_443C0204_BUS.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"bus","task_type":"understanding","prediction":"MICC Investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":113,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_443C020T_BUS.wav","answer":"visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards","subset":"bus","task_type":"understanding","prediction":"Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":114,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020A_BUS.wav","answer":"in addition banks in general are being pushed by regulators to boost their capital positions","subset":"bus","task_type":"understanding","prediction":"In addition, banks in general are being pushed by regulators to boost their capital position.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":115,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020E_BUS.wav","answer":"several airlines have also opposed the standards and may fight some aspects in court","subset":"bus","task_type":"understanding","prediction":"several airlines have also opposed the standards and may fight some aspects in court","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":116,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020I_BUS.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"bus","task_type":"understanding","prediction":"Yahoo, Sierra was up 60 at 5260.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":117,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020J_BUS.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"bus","task_type":"understanding","prediction":"70, which lost points in previous sessions, is being rebound at 80 to 5130.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":118,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020N_BUS.wav","answer":"we didn't like that","subset":"bus","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":119,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020Q_BUS.wav","answer":"the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding","subset":"bus","task_type":"understanding","prediction":"The offer is indicative of a price for the company exceeding $800 million based on 17.2 million shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":120,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020X_BUS.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"bus","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 308.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":121,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C020Z_BUS.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"bus","task_type":"understanding","prediction":"There were 256 issues advancing,303 declining and 292 unchanged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":122,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C0211_BUS.wav","answer":"however investment income which represents thirteen percent of the industry's revenues rose eleven percent in the quarter reflecting gains from the rising stock market","subset":"bus","task_type":"understanding","prediction":"However, investment income, which represents 13% of the industry's revenues, rose 11% in the quarter. Reflecting gains from the rising stock market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":123,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_444C0213_BUS.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"bus","task_type":"understanding","prediction":"A change in the firms ownership also should turn on a bright warning light.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":124,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C0201_BUS.wav","answer":"owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged","subset":"bus","task_type":"understanding","prediction":"Owens Illinois, that its share purchases will be financed by existing credit lines and new ones to be arranged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":125,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C0202_BUS.wav","answer":"if all twenty million shares were purchased the company's equity would be reduced by about one third","subset":"bus","task_type":"understanding","prediction":"If all 20 million shares were purchased. The company's equity would be reduced by about one third.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":126,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C0203_BUS.wav","answer":"a spokesman said the company has about sixty million shares outstanding","subset":"bus","task_type":"understanding","prediction":"a spokesman said the company had 60 million shares outstanding","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":127,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C020B_BUS.wav","answer":"but it is mr. west upon whom the outcome probably depends most","subset":"bus","task_type":"understanding","prediction":"But it is Mr. West upon whom the outcome probably depends most.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":128,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C020C_BUS.wav","answer":"testimony concluded this week and closing arguments are scheduled to begin monday","subset":"bus","task_type":"understanding","prediction":"Testimony continues this week. Closing arguments are scheduled to begin, Sunday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":129,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C020D_BUS.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"bus","task_type":"understanding","prediction":"Grand autos,3 to 15 and 1.8 on the American Stock Market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":130,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C020N_BUS.wav","answer":"coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board","subset":"bus","task_type":"understanding","prediction":"Coniston Partners of New York said it has a 6.8% stake in Gillette and may seek to acquire the company or gain seats on its board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":131,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C020U_BUS.wav","answer":"we had to sustain some modest operating losses","subset":"bus","task_type":"understanding","prediction":"We had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":132,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C020V_BUS.wav","answer":"we didn't like that","subset":"bus","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":133,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C020Z_BUS.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"bus","task_type":"understanding","prediction":"NCI plans to begin offering the service at the end of this month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":134,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C0211_BUS.wav","answer":"a print media campaign will begin the following day","subset":"bus","task_type":"understanding","prediction":"A print media campaign will begin the following day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":135,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C0212_BUS.wav","answer":"the real change though is in how china looks","subset":"bus","task_type":"understanding","prediction":"The real change, though, is in how China looks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":136,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C0214_BUS.wav","answer":"the numbers looked amazingly good industrial growth rates above ten percent per year year after year","subset":"bus","task_type":"understanding","prediction":"The numbers looked amazingly good. Industrial growth rate of 10% per year, year after year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":137,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_445C0215_BUS.wav","answer":"and after a temporary downturn in the next couple of years the numbers probably will go back up","subset":"bus","task_type":"understanding","prediction":"And after a temporary downturn in the next couple of years. The numbers probably will go up.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":138,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C0201_BUS.wav","answer":"here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva","subset":"bus","task_type":"understanding","prediction":"Here are price trends on the world's major stock markets, as calculated by Morgan Stanley, Capital International Perspective, Geneva.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":139,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C0204_BUS.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"bus","task_type":"understanding","prediction":"The consensus was that a new piece of paper isn't required to send one US diplomat.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":140,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C0205_BUS.wav","answer":"no one at the state department wants to let spies in","subset":"bus","task_type":"understanding","prediction":"no one at the state department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":141,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C0208_BUS.wav","answer":"but the investigation could make some lenders wary","subset":"bus","task_type":"understanding","prediction":"but the investigation could make some lenders wary","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":142,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C0209_BUS.wav","answer":"mr. icahn and an investor group he heads hold seventy two point seven percent of t. w. a.'s shares","subset":"bus","task_type":"understanding","prediction":"Mr. Icahn and an investor group he heads hold 72.7% of TWA shares.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":143,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020A_BUS.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"bus","task_type":"understanding","prediction":"Separately, New York State sold about $77.1 million of certificates of participation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":144,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020D_BUS.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"bus","task_type":"understanding","prediction":"The issue is rated single A by Moody S and single A minus by S P.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":145,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020J_BUS.wav","answer":"in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars","subset":"bus","task_type":"understanding","prediction":"In fiscal 1987, Wang had a loss of $78.7 million, or $2.84 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":146,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020M_BUS.wav","answer":"net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in the period","subset":"bus","task_type":"understanding","prediction":"Net income rose 125% to 753 million Swiss francs in the period.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":147,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020O_BUS.wav","answer":"we're not ready to say we're in technical default a spokesman said","subset":"bus","task_type":"understanding","prediction":"we are not ready to say we are in this type of default a spokesman said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":148,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020R_BUS.wav","answer":"among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agreed","subset":"bus","task_type":"understanding","prediction":"Among men,56% said the US was doing too little in space exploration. Only a quarter of women agreed.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":149,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020X_BUS.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"bus","task_type":"understanding","prediction":"Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":150,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C020Z_BUS.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"bus","task_type":"understanding","prediction":"Republic of New York, where his wife suffered a hemorrhage of 45 and 7\/8.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":151,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_446C0210_BUS.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"bus","task_type":"understanding","prediction":"The company said its European banking affiliate in the Czech Republic plans to raise more than $450 million through an international offering.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":152,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C0202_BUS.wav","answer":"i have my list of changes i'd like to see","subset":"bus","task_type":"understanding","prediction":"i have my list of changes i would like to see","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":153,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C0205_BUS.wav","answer":"he doesn't","subset":"bus","task_type":"understanding","prediction":"He doesn't.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":154,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C0208_BUS.wav","answer":"before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company","subset":"bus","task_type":"understanding","prediction":"Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":155,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C020G_BUS.wav","answer":"the underwriting group has a thirty day option to acquire an additional five hundred thousand shares at eight dollars each","subset":"bus","task_type":"understanding","prediction":"The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":156,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C020I_BUS.wav","answer":"it had fourteen point five million common shares outstanding before the issue","subset":"bus","task_type":"understanding","prediction":"It had 14 plus 5 million common shares outstanding before the issue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":157,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C020J_BUS.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"bus","task_type":"understanding","prediction":"In the efforts to restore market confidence. Administration officials have emphasized that the economy is fundamentally sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":158,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C020K_BUS.wav","answer":"that was certainly true last week","subset":"bus","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":159,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C020N_BUS.wav","answer":"it had sales of ninety one point five million dollars in the nineteen eighty six third quarter","subset":"bus","task_type":"understanding","prediction":"It had sales of 91.5 million dollars in the 1986 third quarter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":160,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C020P_BUS.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"bus","task_type":"understanding","prediction":"The independent committee will require that holders accept the offer at a meeting expected to be held in December, T D Direct said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":161,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C020Z_BUS.wav","answer":"several cities have versions of the british organization body positive","subset":"bus","task_type":"understanding","prediction":"Several cities have versions of the British Organisation, Body Positivity.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":162,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C0212_BUS.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"bus","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":163,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C0213_BUS.wav","answer":"we had to sustain some modest operating losses","subset":"bus","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":164,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C0214_BUS.wav","answer":"we didn't like that","subset":"bus","task_type":"understanding","prediction":"we did not like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":165,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/F06_447C0217_BUS.wav","answer":"the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight","subset":"bus","task_type":"understanding","prediction":"The low was 1270.19, and the high was 1273.88.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":166,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C0203_BUS.wav","answer":"about half these managers are in the u. s.","subset":"bus","task_type":"understanding","prediction":"About half these managers are in the US.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":167,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C0207_BUS.wav","answer":"the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks","subset":"bus","task_type":"understanding","prediction":"The agency isn't likely to take any action until the unions rank and file votes on the contract in 2 to three weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":168,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C020C_BUS.wav","answer":"the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture","subset":"bus","task_type":"understanding","prediction":"the rise in that category in july was led by increased orders for aircraft and parts non electrical machinery lumber and furniture","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":169,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C020D_BUS.wav","answer":"interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction","subset":"bus","task_type":"understanding","prediction":"Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":170,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C020J_BUS.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"bus","task_type":"understanding","prediction":"The independent committee will recommend that holders accept the offer at a meeting expected to be held this summer. T W A said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":171,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C020L_BUS.wav","answer":"the investor now owns seventy three percent of the company","subset":"bus","task_type":"understanding","prediction":"The investor now owns 73% of the company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":172,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C020M_BUS.wav","answer":"texaco has three choices a company adviser says","subset":"bus","task_type":"understanding","prediction":"Texaco has three choices, a company adviser says.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":173,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C020S_BUS.wav","answer":"what we don't know is how much is price and how much is volume","subset":"bus","task_type":"understanding","prediction":"We don't know how much is price and how much is volume.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":174,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_440C020Y_BUS.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"bus","task_type":"understanding","prediction":"Estimates for the gain ranged from 2% to 3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":175,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0201_BUS.wav","answer":"first commodity appealed the expulsion and fine to the c. f. t. c.","subset":"bus","task_type":"understanding","prediction":"First commodity appealed the expulsion and fine to the CFTC.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":176,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0202_BUS.wav","answer":"a commission spokesman said a decision on the appeal is expected soon","subset":"bus","task_type":"understanding","prediction":"a commission spokesman said a decision on the appeal is expected soon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":177,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0205_BUS.wav","answer":"the language is a big problem","subset":"bus","task_type":"understanding","prediction":"the language is a big problem","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":178,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0206_BUS.wav","answer":"in europe an american can at least read street signs","subset":"bus","task_type":"understanding","prediction":"in europe an american can at least read street signs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":179,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0208_BUS.wav","answer":"the overall gain the fifth in the past seven months followed a revised four point one percent increase in february","subset":"bus","task_type":"understanding","prediction":"The overall gain, the fifth in the past seven months, followed a revised 4.1% increase in February.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":180,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020B_BUS.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"bus","task_type":"understanding","prediction":"Brand Otto, slip 3 to 15 at 1,8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":181,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020C_BUS.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"bus","task_type":"understanding","prediction":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":182,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020D_BUS.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"bus","task_type":"understanding","prediction":"It received no proposals that were in the best interests of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":183,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020E_BUS.wav","answer":"elders brewing will be based outside australia because seventy percent of its assets are in britain and canada","subset":"bus","task_type":"understanding","prediction":"Elders Brewing will be based outside Australia because 70% of its assets are in Britain and Canada.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":184,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020H_BUS.wav","answer":"two years ago b. a. s. f. made three separate acquisitions in the u. s.","subset":"bus","task_type":"understanding","prediction":"Two years ago, BASF made three separate acquisitions in the US.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":185,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020I_BUS.wav","answer":"its biggest was the one billion dollar purchase of the united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry","subset":"bus","task_type":"understanding","prediction":"Its biggest was the $1 billion purchase of a United Technologies Corporation. Inmont subsidiary, a major supplier of paint to the auto industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":186,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020J_BUS.wav","answer":"today ninety percent of the four billion dollars of b. a. s. f. sales in the u. s. is produced there","subset":"bus","task_type":"understanding","prediction":"today ninety percent of the four billion dollars of basf sales in the us is produced there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":187,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020L_BUS.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"bus","task_type":"understanding","prediction":"Those identified as beneficial owners hold at least 10% of a company's equity securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":188,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020M_BUS.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"bus","task_type":"understanding","prediction":"Unless otherwise noted, the changes involved direct holdings of common stock and took place in September and October 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":189,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020P_BUS.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"bus","task_type":"understanding","prediction":"if the dollar starts to plunge the fed may step up its defense of the currency","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":190,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020Q_BUS.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"bus","task_type":"understanding","prediction":"If the Fed pushes the dollar higher. It may curb the demand for US exports.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":191,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020W_BUS.wav","answer":"although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year","subset":"bus","task_type":"understanding","prediction":"although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":192,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020X_BUS.wav","answer":"the bond funds in particular provide robust yields for investors and hefty fees for underwriters","subset":"bus","task_type":"understanding","prediction":"The bond funds, in particular, provide robust yields for investors and hefty fees for underwriters.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":193,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C020Y_BUS.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"bus","task_type":"understanding","prediction":"Republic, New York, rose one and one quarter to 45 and 7\/8.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":194,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0210_BUS.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"bus","task_type":"understanding","prediction":"After the offering, Republic New York will hold about 49% of the affiliate.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":195,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0211_BUS.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"bus","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower at 1418.7.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":196,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_441C0213_BUS.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"bus","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":197,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C0204_BUS.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"bus","task_type":"understanding","prediction":"MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":198,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C0205_BUS.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"bus","task_type":"understanding","prediction":"MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":199,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C0206_BUS.wav","answer":"the toronto based company provides mortgage guarantees to the canadian real estate industry","subset":"bus","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to the Canadian real estate industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":200,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C0208_BUS.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"bus","task_type":"understanding","prediction":"The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":201,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C0209_BUS.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"bus","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":202,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C020B_BUS.wav","answer":"shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said","subset":"bus","task_type":"understanding","prediction":"Shamrock's pretax profit from the sale was $125 million, a spokeswoman said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":203,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C020D_BUS.wav","answer":"sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday","subset":"bus","task_type":"understanding","prediction":"Sony Corporation, for example, closed at $4950.50 a share yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":204,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C020O_BUS.wav","answer":"but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders","subset":"bus","task_type":"understanding","prediction":"But if the winning bids are as high as they were in some deals earlier this year, then we are not going to be winning bidders","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":205,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C020R_BUS.wav","answer":"the company then accepts the shares tendered at the lowest price needed to reach its total then pays that amount for all shares it purchases","subset":"bus","task_type":"understanding","prediction":"The company then accepts the shares tendered at the lowest price needed to reach its total, then pays that amount for all shares in purchases.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":206,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C0211_BUS.wav","answer":"so normalcy has returned","subset":"bus","task_type":"understanding","prediction":"so normalcy has returned","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":207,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_442C0215_BUS.wav","answer":"money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","subset":"bus","task_type":"understanding","prediction":"Money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":208,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C0209_BUS.wav","answer":"nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics","subset":"bus","task_type":"understanding","prediction":"nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":209,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020A_BUS.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"bus","task_type":"understanding","prediction":"In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":210,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020B_BUS.wav","answer":"that was certainly true last week","subset":"bus","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":211,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020C_BUS.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"bus","task_type":"understanding","prediction":"Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":212,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020F_BUS.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"bus","task_type":"understanding","prediction":"Sony, which lost points in previous sessions this week, rebounded 80 to 5130.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":213,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020N_BUS.wav","answer":"the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains","subset":"bus","task_type":"understanding","prediction":"The official declined to elaborate on projections for non telephone operations. But cited several indicators of recent gains.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":214,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020O_BUS.wav","answer":"he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force","subset":"bus","task_type":"understanding","prediction":"He said the company has entered 16 smaller cellular markets this year and has expanded its financial services workforce.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":215,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020Q_BUS.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"bus","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":216,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020S_BUS.wav","answer":"a print media campaign will begin the following day","subset":"bus","task_type":"understanding","prediction":"A print media campaign will begin the following day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":217,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020V_BUS.wav","answer":"in certain cases the cards are given free to subscribers","subset":"bus","task_type":"understanding","prediction":"in certain cases the cards are given free to subscribers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":218,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C020W_BUS.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"bus","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 380.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":219,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_443C0214_BUS.wav","answer":"nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty","subset":"bus","task_type":"understanding","prediction":"Nissan lost 30 to 1520, and Toyota was down 30 to end the day at 2620.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":220,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C0207_BUS.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"bus","task_type":"understanding","prediction":"The issue is rated single A by Moody S and single A minus by F and P.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":221,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C0208_BUS.wav","answer":"citicorp had twenty one point five billion dollars in capital at the end of last year","subset":"bus","task_type":"understanding","prediction":"Citicorp had $21.5 billion in capital at the end of last year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":222,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C0209_BUS.wav","answer":"as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions","subset":"bus","task_type":"understanding","prediction":"as one of the most acquisition hungry of major banks the city corp is often required by regulators to raise additional capital as a condition of making acquisitions","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":223,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C020K_BUS.wav","answer":"lately computer retailing has been tough on everybody","subset":"bus","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":224,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C020L_BUS.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"bus","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":225,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C020P_BUS.wav","answer":"in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday","subset":"bus","task_type":"understanding","prediction":"In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":226,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C020R_BUS.wav","answer":"the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year","subset":"bus","task_type":"understanding","prediction":"The mid July increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":227,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C020S_BUS.wav","answer":"incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst","subset":"bus","task_type":"understanding","prediction":"Incentives can move around sales, but not create them, says Charles Brady, an Oppenheimer and Company auto stock analyst.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":228,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_444C0212_BUS.wav","answer":"realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars","subset":"bus","task_type":"understanding","prediction":"Realized capital gains increased 42% to $909 million from $640.9 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":229,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_445C0204_BUS.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"bus","task_type":"understanding","prediction":"the consensus was that a new piece of paper isn t required said one u s diplomat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":230,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_445C0209_BUS.wav","answer":"and both mortgaged their homes to secure the loans they needed to start the business","subset":"bus","task_type":"understanding","prediction":"And both mortgaged their homes to secure the loans they needed to start the business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":231,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_445C020A_BUS.wav","answer":"a long list of other witnesses have also testified in the trial now in its fourth month","subset":"bus","task_type":"understanding","prediction":"A long list of other witnesses have also testified in the trial now in its fourth month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":232,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_445C020G_BUS.wav","answer":"the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists","subset":"bus","task_type":"understanding","prediction":"the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":233,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_445C020Q_BUS.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"bus","task_type":"understanding","prediction":"if the dollar starts to plunge the fed may step up its defense of the currency","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":234,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_445C020W_BUS.wav","answer":"the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed","subset":"bus","task_type":"understanding","prediction":"The judge awarded Mr. Sharonberg $105 million, a figure based on 10 years of profit. Had his project been completed.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":235,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_445C0216_BUS.wav","answer":"where else in the third world is there so much energy and progress as in china","subset":"bus","task_type":"understanding","prediction":"where else in the third world is there so much energy and progress as china","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":236,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_446C020F_BUS.wav","answer":"under the proposed transaction the los angeles group would acquire the k. h. j. license and then sell itself to disney","subset":"bus","task_type":"understanding","prediction":"under the proposed transaction the los angeles group would acquire the khj license and then sell itself to disney","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":237,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_446C020G_BUS.wav","answer":"the closely held group doesn't have any significant assets according to william g. simon its president","subset":"bus","task_type":"understanding","prediction":"The closely held group doesn't have any significant assets, according to William G. Simon, its president.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":238,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_446C020H_BUS.wav","answer":"he said that for the full year wang is aiming for an after tax profit equal to three percent to five percent of sales","subset":"bus","task_type":"understanding","prediction":"He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":239,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_446C0212_BUS.wav","answer":"closely held times publishing also owns two washington based publications congressional quarterly which covers capitol hill and governing which covers state and local governments","subset":"bus","task_type":"understanding","prediction":"Closely held times publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and governing, which covers state and local governments.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":240,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_446C0214_BUS.wav","answer":"industry analysts value the company at about six hundred fifty million dollars","subset":"bus","task_type":"understanding","prediction":"Industry analysts value the company at about $650 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":241,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C0203_BUS.wav","answer":"and i'm sure you have your own list","subset":"bus","task_type":"understanding","prediction":"and i am sure you have your own playlist","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":242,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C020A_BUS.wav","answer":"united presidential is a life insurance company","subset":"bus","task_type":"understanding","prediction":"United presidential is a life insurance company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":243,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C020B_BUS.wav","answer":"these are uneducated people he says in english so the patients won't understand","subset":"bus","task_type":"understanding","prediction":"These are uneducated people, he says, in English. So the patients won't understand.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":244,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C020D_BUS.wav","answer":"i will tell you what i think in my office","subset":"bus","task_type":"understanding","prediction":"i will tell you what i think in my office","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":245,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C020F_BUS.wav","answer":"they were sold to underwriters led by prudential bache securities incorporated","subset":"bus","task_type":"understanding","prediction":"they were sold to underwriters led by prudential bache securities incorporated","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":246,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C020R_BUS.wav","answer":"the investor now owns seventy three percent of the company","subset":"bus","task_type":"understanding","prediction":"The investor now owns 73% of the company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":247,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C020V_BUS.wav","answer":"manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid","subset":"bus","task_type":"understanding","prediction":"Manhattan Industries continued to trade above the offer price yesterday, indicating the market expects a higher bid.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":248,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M05_447C0215_BUS.wav","answer":"shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level","subset":"bus","task_type":"understanding","prediction":"The Shearson Lehman Incorporateds index of long term Treasury bonds stayed in a very small range yesterday, finishing very close to Wednesday's closing level.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":249,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C0201_BUS.wav","answer":"at n. e. c. the need for international managers will keep rising","subset":"bus","task_type":"understanding","prediction":"At NEC, the need for international managers will keep rising.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":250,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C0205_BUS.wav","answer":"the company previously traded over the counter","subset":"bus","task_type":"understanding","prediction":"the company previously traded over the counter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":251,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C020N_BUS.wav","answer":"it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan","subset":"bus","task_type":"understanding","prediction":"It can sign on to the plan. File a competing plan or take a completely passive role that neither endorses nor opposes the plan.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":252,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C020U_BUS.wav","answer":"the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction","subset":"bus","task_type":"understanding","prediction":"The rate on the latest three month bill declined to 6.43%. Bid from an average of 6.53%. at a Tuesday auction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":253,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C020V_BUS.wav","answer":"the rate on six month bills fell to six point seven three percent from six point eight three percent","subset":"bus","task_type":"understanding","prediction":"The rate on six month bills fell to 6.73% from 6.8%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":254,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C020W_BUS.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"bus","task_type":"understanding","prediction":"Durable goods reports frequently are highly volatile, from month to month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":255,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C020X_BUS.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"bus","task_type":"understanding","prediction":"Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated jump increase.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":256,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C0213_BUS.wav","answer":"he said such product would be marketed by other companies with experience in that business","subset":"bus","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":257,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_440C0214_BUS.wav","answer":"he declined to name specific products","subset":"bus","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":258,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C0209_BUS.wav","answer":"the earlier rise was previously reported as four point three percent","subset":"bus","task_type":"understanding","prediction":"The earlier rise was previously reported, as 4.3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":259,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C020A_BUS.wav","answer":"if defense is excluded march orders rose one percent after a three percent increase in february","subset":"bus","task_type":"understanding","prediction":"If defenses excluded, March orders rose 1% after a 3% increase in February.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":260,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C020F_BUS.wav","answer":"also a move to base it abroad will have tax advantages","subset":"bus","task_type":"understanding","prediction":"also a move to base abroad will have tax advantages","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":261,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C020N_BUS.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"bus","task_type":"understanding","prediction":"Companies are listed where transactions generally aggregate 10000 shares, or $100000.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":262,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C020O_BUS.wav","answer":"about all businessmen can count on is that policy will be pretty volatile","subset":"bus","task_type":"understanding","prediction":"About all the business in can count on is that policy will be pretty volatile.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":263,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C020S_BUS.wav","answer":"analysts haven't focused on what happened to them","subset":"bus","task_type":"understanding","prediction":"analysts have been focused on what happened today","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":264,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C020V_BUS.wav","answer":"closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities","subset":"bus","task_type":"understanding","prediction":"Closed end funds are traded on exchanges like stocks, but invest in a wide portfolio of other securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":265,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_441C0212_BUS.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"bus","task_type":"understanding","prediction":"Volume was modest, as 326.7 million shares changed hands, compared with 396.5 million Friday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":266,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C0203_BUS.wav","answer":"the bank holding company slated another fifty million dollar sale next tuesday","subset":"bus","task_type":"understanding","prediction":"The bank holding company slated another $50 million sale next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":267,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C0207_BUS.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"bus","task_type":"understanding","prediction":"Grand Auto slid 3 to 15 and 1\/8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":268,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C020C_BUS.wav","answer":"shamrock has interests in television and radio stations energy services real estate and venture capital","subset":"bus","task_type":"understanding","prediction":"The shamrock has interests in television and radio stations, energy services. real estate and venture capital.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":269,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C020F_BUS.wav","answer":"this morning the asking price for the stock was four thousand eight hundred fifty but there are were no buyers","subset":"bus","task_type":"understanding","prediction":"this morning we asked price for this stock four thousand eight hundred and fifty but there were no buyers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":270,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C020G_BUS.wav","answer":"a monsanto spokesman said there's very little we can say","subset":"bus","task_type":"understanding","prediction":"a monsanto spokesman said there is very little weakness in the company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":271,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C020J_BUS.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"bus","task_type":"understanding","prediction":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for US durable goods rose two point four percent last month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":272,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C020K_BUS.wav","answer":"that would follow a two point two percent drop in may","subset":"bus","task_type":"understanding","prediction":"That would follow a 2.2% drop in May.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":273,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C020L_BUS.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"bus","task_type":"understanding","prediction":"The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":274,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C020U_BUS.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"bus","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":275,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_442C0214_BUS.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"bus","task_type":"understanding","prediction":"A change in the firms ownership also should turn one of the right corner.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":276,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C0201_BUS.wav","answer":"the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before","subset":"bus","task_type":"understanding","prediction":"The Labor Department said nonfarm payroll employment increased a robust 337000 last month after a revised 319000 gain the month before","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":277,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C0208_BUS.wav","answer":"local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members","subset":"bus","task_type":"understanding","prediction":"Local membership jumped 22 per cent but the union has already lost 28 of the 73 new members","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":278,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020E_BUS.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"bus","task_type":"understanding","prediction":"Kyocera was up 60 at 5. Now it is at 260.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":279,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020H_BUS.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"bus","task_type":"understanding","prediction":"Those identified as beneficial owners hold at least 10% of the company securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":280,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020K_BUS.wav","answer":"after the third period ashland's coal operations began a process of becoming an independent company","subset":"bus","task_type":"understanding","prediction":"After the third period, Ashland's coal operations began a process of becoming an independent company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":281,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020L_BUS.wav","answer":"when its initial public offering is completed ashland is expected to retain a forty six percent stake","subset":"bus","task_type":"understanding","prediction":"When its initial public offering is completed. Ashland is expected to retain a 46% stake.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":282,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020M_BUS.wav","answer":"the new company ashland coal incorporated is listed on the new york stock exchange","subset":"bus","task_type":"understanding","prediction":"The new company, Ashton, Cullum Corporation, is listed on the New York Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":283,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020P_BUS.wav","answer":"in addition u. s. west data solutions business applied communications incorporated is working out well and performing ahead of all our schedules","subset":"bus","task_type":"understanding","prediction":"In addition, US West data solutions business applied communications incorporated is working out well and performing ahead of all of our schedules.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":284,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020R_BUS.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"bus","task_type":"understanding","prediction":"As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":285,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020U_BUS.wav","answer":"fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards","subset":"bus","task_type":"understanding","prediction":"Fees range up to about $40 annually for basic cards and $60 a year for gold cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":286,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020X_BUS.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday","subset":"bus","task_type":"understanding","prediction":"Volume was 18119000 shares, compared with 10550000 today.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":287,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020Y_BUS.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"bus","task_type":"understanding","prediction":"there were two hundred and fifty six issues advancing three hundred and three declining and two hundred and ninety two unchanged","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":288,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C020Z_BUS.wav","answer":"companies listed below reported quarterly profit substantially different from the average of analysts' estimates","subset":"bus","task_type":"understanding","prediction":"Companies listed in the lab report quarterly profit substantially different from the average of analysts estimates.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":289,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C0211_BUS.wav","answer":"estimated and actual results involving losses are omitted","subset":"bus","task_type":"understanding","prediction":"Estimated and actual results in bolded boxes are omitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":290,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C0212_BUS.wav","answer":"yesterday's losers included automobiles","subset":"bus","task_type":"understanding","prediction":"yesterday s losers included automobiles","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":291,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_443C0213_BUS.wav","answer":"honda was down ten to one thousand nine hundred thirty","subset":"bus","task_type":"understanding","prediction":"Honda was down 10 to 1930.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":292,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C0203_BUS.wav","answer":"revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars","subset":"bus","task_type":"understanding","prediction":"Revenue in the quarter more than doubled to $362.4 million from $149.2 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":293,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C0204_BUS.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"bus","task_type":"understanding","prediction":"Separately, New York State sold about $77.1 million in certificates of anticipation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":294,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C0205_BUS.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"bus","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5 percent in 1997 to 5.5 percent in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":295,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C0206_BUS.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"bus","task_type":"understanding","prediction":"The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers company underwriter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":296,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C020M_BUS.wav","answer":"we had to sustain some modest operating losses","subset":"bus","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":297,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C020O_BUS.wav","answer":"the company declined to identify the bidders but said it received offers in the high forty dollars per share","subset":"bus","task_type":"understanding","prediction":"The company declined to identify the bidders. But said it received offers in the high $40 per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":298,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C020T_BUS.wav","answer":"the market's strength may show that demand isn't all a creation of incentives","subset":"bus","task_type":"understanding","prediction":"The market strength may show that demand is in all a creation of incentives.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":299,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C020U_BUS.wav","answer":"m. c. i. plans to begin offering the service at the end of the month","subset":"bus","task_type":"understanding","prediction":"NCI plans to begin offering the service at the end of this month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":300,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C020V_BUS.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"bus","task_type":"understanding","prediction":"As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":301,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_444C020W_BUS.wav","answer":"a print media campaign will begin the following day","subset":"bus","task_type":"understanding","prediction":"A print media campaign will begin the following day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":302,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C0205_BUS.wav","answer":"no one at the state department wants to let spies in","subset":"bus","task_type":"understanding","prediction":"no one at the state department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":303,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C0206_BUS.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"bus","task_type":"understanding","prediction":"were not prepared to be advocates for the kentucky bank","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":304,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C0207_BUS.wav","answer":"but the penalties for failure are real","subset":"bus","task_type":"understanding","prediction":"but the pallidus profile your heart","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":305,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C020E_BUS.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"bus","task_type":"understanding","prediction":"Company, which runs retail, one of its stores, told Shearson, Lehman Brothers, its financial adviser to terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":306,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C020F_BUS.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"bus","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":307,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C020H_BUS.wav","answer":"the suit seeks to block the contract which would have raised pay levels but cut benefits","subset":"bus","task_type":"understanding","prediction":"The suit seeks to block the contract. Which would have raised pay levels, but cut benefits.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":308,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C020K_BUS.wav","answer":"but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close","subset":"bus","task_type":"understanding","prediction":"but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday s close","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":309,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C020L_BUS.wav","answer":"although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading","subset":"bus","task_type":"understanding","prediction":"Although those gains eroded during the afternoon. Stock prices stayed within a narrow range of the past half hour of trading.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":310,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C020S_BUS.wav","answer":"lately computer retailing has been tough on everybody","subset":"bus","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":311,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C020T_BUS.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"bus","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":312,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_445C0210_BUS.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"bus","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":313,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C0202_BUS.wav","answer":"to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred","subset":"bus","task_type":"understanding","prediction":"To make them directly comparable, each index is based on the close of 1969,100.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":314,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C0203_BUS.wav","answer":"the percentage change is since year end","subset":"bus","task_type":"understanding","prediction":"the percentage change is since year end","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":315,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C0207_BUS.wav","answer":"that doesn't mean mr. icahn has committed any wrongdoing","subset":"bus","task_type":"understanding","prediction":"that does not mean mr akon has committed any wrongdoing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":316,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C020P_BUS.wav","answer":"it's still unclear","subset":"bus","task_type":"understanding","prediction":"it still unclear","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":317,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C020Q_BUS.wav","answer":"there was a striking split between the sexes with men more likely than women to favor space programs","subset":"bus","task_type":"understanding","prediction":"There was a striking split between the sexes, with men more than likely to have went to favour space programmes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":318,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C020U_BUS.wav","answer":"that would follow a two point two percent drop in may","subset":"bus","task_type":"understanding","prediction":"that would follow a two point two percent drop in may","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":319,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C020Y_BUS.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"bus","task_type":"understanding","prediction":"estimates for the gain range from two percent to three percent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":320,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C0211_BUS.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"bus","task_type":"understanding","prediction":"After the offering, Republic near will hold about 49% of the company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":321,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_446C0213_BUS.wav","answer":"it also owns three state business magazines in florida georgia and arizona","subset":"bus","task_type":"understanding","prediction":"It also owns three state business magazines in Florida, Georgia and Arizona.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":322,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C0204_BUS.wav","answer":"mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent","subset":"bus","task_type":"understanding","prediction":"Mr. Robertson says he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":323,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C0207_BUS.wav","answer":"washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own","subset":"bus","task_type":"understanding","prediction":"Washington National paid $19 a share for the 2.6 million United presidential shares it didn't already own.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":324,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C020C_BUS.wav","answer":"sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days","subset":"bus","task_type":"understanding","prediction":"Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":325,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C020L_BUS.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"bus","task_type":"understanding","prediction":"Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":326,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C020O_BUS.wav","answer":"the company expects to report its results in about two weeks","subset":"bus","task_type":"understanding","prediction":"The company expects to report its results in about two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":327,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C020U_BUS.wav","answer":"other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation","subset":"bus","task_type":"understanding","prediction":"Other analysts say the Fed needs to tighten policy further to support the dollar and prevent inflation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":328,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C020W_BUS.wav","answer":"the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape","subset":"bus","task_type":"understanding","prediction":"The shares closed at $18.25, up 25 cents on the New York Stock Exchange composite tape.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":329,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C020X_BUS.wav","answer":"salant shares closed unchanged on the big board at nine dollars and seventy five cents","subset":"bus","task_type":"understanding","prediction":"Salon shares closed unchanged on the big board at $9.75.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":330,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_bus_real\/M06_447C0216_BUS.wav","answer":"the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight","subset":"bus","task_type":"understanding","prediction":"The index ended with a decline of 0.3,5.2,1272.18.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":331,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_440C0203_CAF.wav","answer":"about half these managers are in the u. s.","subset":"caf","task_type":"understanding","prediction":"about half these managers are in the us","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":332,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_440C0207_CAF.wav","answer":"the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks","subset":"caf","task_type":"understanding","prediction":"The agency isn't likely to take any action until the unions rank and file votes on the contracts in 2 to three weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":333,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_440C020C_CAF.wav","answer":"the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture","subset":"caf","task_type":"understanding","prediction":"The rise in that category in July was LED by increased orders for aircraft and parts. Non electrical machinery, lumber and furniture.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":334,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_440C020D_CAF.wav","answer":"interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction","subset":"caf","task_type":"understanding","prediction":"Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":335,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_440C020L_CAF.wav","answer":"the investor now owns seventy three percent of the company","subset":"caf","task_type":"understanding","prediction":"the investor now owns seventy three percent of the company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":336,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_440C020M_CAF.wav","answer":"texaco has three choices a company adviser says","subset":"caf","task_type":"understanding","prediction":"Texaco has three choices a company adviser says","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":337,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_440C020S_CAF.wav","answer":"what we don't know is how much is price and how much is volume","subset":"caf","task_type":"understanding","prediction":"what we dont know is how much is price and how much is volume","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":338,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C0201_CAF.wav","answer":"first commodity appealed the expulsion and fine to the c. f. t. c.","subset":"caf","task_type":"understanding","prediction":"First, commodity appealed the expulsion and fine to the CFTC.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":339,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C0202_CAF.wav","answer":"a commission spokesman said a decision on the appeal is expected soon","subset":"caf","task_type":"understanding","prediction":"a commission spokesman said a decision on the appeal is expected soon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":340,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C0205_CAF.wav","answer":"the language is a big problem","subset":"caf","task_type":"understanding","prediction":"the language is a big problem","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":341,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C0206_CAF.wav","answer":"in europe an american can at least read street signs","subset":"caf","task_type":"understanding","prediction":"in europe an american can at least use credit cards","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":342,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C0208_CAF.wav","answer":"the overall gain the fifth in the past seven months followed a revised four point one percent increase in february","subset":"caf","task_type":"understanding","prediction":"The overall gain, the fifth in the past seven months, followed a revised 4.1% increase in February.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":343,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C020E_CAF.wav","answer":"elders brewing will be based outside australia because seventy percent of its assets are in britain and canada","subset":"caf","task_type":"understanding","prediction":"Elders Brewing will be based outside Australia because 70% of its assets are in Britain and Canada.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":344,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C020H_CAF.wav","answer":"two years ago b. a. s. f. made three separate acquisitions in the u. s.","subset":"caf","task_type":"understanding","prediction":"Two years ago, B, A S, F made three separate acquisitions in the US.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":345,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C020I_CAF.wav","answer":"its biggest was the one billion dollar purchase of united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry","subset":"caf","task_type":"understanding","prediction":"Its biggest was the $1 billion purchase of United Technologies Corporation's Inmont subsidiary, a major supplier of paint to the auto industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":346,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C020J_CAF.wav","answer":"today ninety percent of the four billion dollars of b. a. s. f. sales in the u. s. is produced there","subset":"caf","task_type":"understanding","prediction":"today ninety percent of the four billion dollars of basf sales in the us is produced there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":347,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C020P_CAF.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"caf","task_type":"understanding","prediction":"if the dollar starts to plunge the fed may step up its defense of the currency","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":348,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C020W_CAF.wav","answer":"although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year","subset":"caf","task_type":"understanding","prediction":"Although closed end funds have been around since at least the 1920s. They have boomed in popularity this year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":349,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_441C020X_CAF.wav","answer":"the bond funds in particular provide robust yields for investors and hefty fees for underwriters","subset":"caf","task_type":"understanding","prediction":"The bond funds in particular provide robust yields for investors and hefty fees for underwriters","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":350,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C0208_CAF.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"caf","task_type":"understanding","prediction":"The company, which runs retail automotive stores. Told shearson, Lehman Brothers, its financial adviser to terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":351,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C0209_CAF.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"caf","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":352,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C020B_CAF.wav","answer":"shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said","subset":"caf","task_type":"understanding","prediction":"Shamrock's pretax profit from the sale was $125 million, the spokesman said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":353,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C020D_CAF.wav","answer":"sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday","subset":"caf","task_type":"understanding","prediction":"Sony Corporation, for example, closed at ¥4950. $34.50 a share yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":354,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C020O_CAF.wav","answer":"but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders","subset":"caf","task_type":"understanding","prediction":"but if the winning bids are as high as they were in some deals earlier this year then we are not going to be winning bidders","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":355,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C020R_CAF.wav","answer":"the company then accepts the shares tendered at the lowest price needed to reach its total then pays that amount for all shares it purchases","subset":"caf","task_type":"understanding","prediction":"The company then accepts the shares tendered at the lowest price needed to reach its total, then pays that amount for all shares it purchases.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":356,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C020S_CAF.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"caf","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":357,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C020U_CAF.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"caf","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":358,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_442C0211_CAF.wav","answer":"so normalcy has returned","subset":"caf","task_type":"understanding","prediction":"so normalcy has returned","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":359,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C0204_CAF.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"caf","task_type":"understanding","prediction":"MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":360,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C0205_CAF.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"caf","task_type":"understanding","prediction":"MICC said it intends to pay the dividend arrears on July 31 to stock of record, July 7.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":361,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C0206_CAF.wav","answer":"the toronto based company provides mortgage guarantees to the canadian real estate industry","subset":"caf","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to the Canadian real estate industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":362,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C0209_CAF.wav","answer":"nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics","subset":"caf","task_type":"understanding","prediction":"Nonetheless, the union has moved the experiment to Richmond, Virginia, and has received inquiries from other unions about its tactics","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":363,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C020H_CAF.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"caf","task_type":"understanding","prediction":"Those identified as beneficial owners hold at least 10% of a company s equity securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":364,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C020I_CAF.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"caf","task_type":"understanding","prediction":"Unless otherwise noted, changes involve direct holdings of common stock and took place in September and October 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":365,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C020N_CAF.wav","answer":"the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains","subset":"caf","task_type":"understanding","prediction":"The official declined to elaborate on projections for Nontelephone operations, but cited several indicators of recent gains.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":366,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C020O_CAF.wav","answer":"he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force","subset":"caf","task_type":"understanding","prediction":"He said the company has entered 16 smaller cellular markets this year and has expanded its financial services portfolio.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":367,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C020V_CAF.wav","answer":"in certain cases the cards are given free to subscribers","subset":"caf","task_type":"understanding","prediction":"in certain cases the cards are given free to subscribers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":368,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_443C0214_CAF.wav","answer":"nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty","subset":"caf","task_type":"understanding","prediction":"Nissan lost 30 to 1520, and Toyota was down 30 to end the day at 2620.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":369,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C0208_CAF.wav","answer":"citicorp had twenty one point five billion dollars in capital at the end of last year","subset":"caf","task_type":"understanding","prediction":"Sydney Corp had $21.5 billion in capital at the end of last year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":370,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C0209_CAF.wav","answer":"as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions","subset":"caf","task_type":"understanding","prediction":"As one of the most acquisition hungry of major banks, Citicorp is often required by regulators to raise additional capital as a condition of making acquisitions.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":371,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C020J_CAF.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"caf","task_type":"understanding","prediction":"Sony, which lost points in previous sessions this week, rebounded 80 to 5103.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":372,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C020P_CAF.wav","answer":"in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday","subset":"caf","task_type":"understanding","prediction":"In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":373,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C020R_CAF.wav","answer":"the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year","subset":"caf","task_type":"understanding","prediction":"The mid july increase came even though automakers are offering incentives on fewer cars this year than they did last year or earlier this year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":374,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C020S_CAF.wav","answer":"incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst","subset":"caf","task_type":"understanding","prediction":"Incentives can move around sales, but not create them, said Charles Brady, an Oppenheimer and company auto stock analyst.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":375,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C020X_CAF.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"caf","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 380.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":376,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C0212_CAF.wav","answer":"realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars","subset":"caf","task_type":"understanding","prediction":"Realized capital gains increased 42% to $909 million from $640.9 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":377,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_444C0214_CAF.wav","answer":"money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","subset":"caf","task_type":"understanding","prediction":"Money managers who sell their firms but then continue working for them may be less dedicated to the new ownership, they said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":378,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C0209_CAF.wav","answer":"and both mortgaged their homes to secure the loans they needed to start the business","subset":"caf","task_type":"understanding","prediction":"and both mortgaged their homes to secure the loans they needed to start the business","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":379,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020A_CAF.wav","answer":"a long list of other witnesses have also testified in the trial now in its fourth month","subset":"caf","task_type":"understanding","prediction":"A long list of other witnesses have also testified in the trial, now in its fourth month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":380,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020D_CAF.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"caf","task_type":"understanding","prediction":"Grandada slid 3 to 15 and 1.8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":381,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020E_CAF.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"caf","task_type":"understanding","prediction":"The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":382,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020F_CAF.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"caf","task_type":"understanding","prediction":"They received no proposals that were in the best interest of the shareholders, the company said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":383,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020G_CAF.wav","answer":"the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists","subset":"caf","task_type":"understanding","prediction":"The order issued late Wednesday by Judge Sianna Murphy stems from a suit filed in federal court last month by the union representing the machinists.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":384,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020Q_CAF.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"caf","task_type":"understanding","prediction":"if the dollar starts to plunge the fed may step up its defense of the currency","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":385,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020R_CAF.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"caf","task_type":"understanding","prediction":"if the fed pushes the dollar higher it may curb the demand for u s exports","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":386,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020W_CAF.wav","answer":"the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed","subset":"caf","task_type":"understanding","prediction":"The jury awarded Mr. Sharonberg $105 million, a figure based on 10 years of profits had his project been completed.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":387,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C020Z_CAF.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"caf","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":388,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C0211_CAF.wav","answer":"a print media campaign will begin the following day","subset":"caf","task_type":"understanding","prediction":"a print media campaign will begin the following day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":389,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_445C0216_CAF.wav","answer":"where else in the third world is there so much energy and progress as in china","subset":"caf","task_type":"understanding","prediction":"Where else in the third world is there so much energy and progress as in China.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":390,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C0204_CAF.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"caf","task_type":"understanding","prediction":"The consensus was that a new piece of paper isn't required, said one US diplomat.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":391,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C020D_CAF.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"caf","task_type":"understanding","prediction":"The issue is rated single A by Moody s and single A minus by S and P.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":392,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C020F_CAF.wav","answer":"under the proposed transaction the los angeles group would acquire the k. h. j. license and then sell itself to disney","subset":"caf","task_type":"understanding","prediction":"Under the proposed transaction, the Los Angeles group would acquire the KH Day license and then sell itself to Disney.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":393,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C020G_CAF.wav","answer":"the closely held group doesn't have any significant assets according to william g. simon its president","subset":"caf","task_type":"understanding","prediction":"The closely held group doesn't have any significant assets, according to William G. Hyman, its president.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":394,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C020H_CAF.wav","answer":"he said that for the full year wang is aiming for an after tax profit equal to three percent to five percent of sales","subset":"caf","task_type":"understanding","prediction":"He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":395,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C020Y_CAF.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"caf","task_type":"understanding","prediction":"Estimates for the gain range from 2% to 3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":396,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C020Z_CAF.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"caf","task_type":"understanding","prediction":"Republic, New York, rose 1 and 1 quarter to 45 and 7\/8.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":397,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C0211_CAF.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"caf","task_type":"understanding","prediction":"after the offering republic new york will hold about forty nine percent of the affiliate","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":398,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C0212_CAF.wav","answer":"closely held times publishing also owns two washington based publications congressional quarterly which covers capitol hill and governing which covers state and local governments","subset":"caf","task_type":"understanding","prediction":"Closely held times publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and Governing, which covers state and local governments.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":399,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_446C0214_CAF.wav","answer":"industry analysts value the company at about six hundred fifty million dollars","subset":"caf","task_type":"understanding","prediction":"Industry analysts value the company at about $650 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":400,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C0203_CAF.wav","answer":"and i'm sure you have your own list","subset":"caf","task_type":"understanding","prediction":"and i am sure you have your own list","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":401,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020A_CAF.wav","answer":"united presidential is a life insurance company","subset":"caf","task_type":"understanding","prediction":"united presidential is a life insurance company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":402,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020B_CAF.wav","answer":"these are uneducated people he says in english so the patients won't understand","subset":"caf","task_type":"understanding","prediction":"These are uneducated people, he says, in English. So the patients won't understand.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":403,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020D_CAF.wav","answer":"i will tell you what i think in my office","subset":"caf","task_type":"understanding","prediction":"i will tell you what i think in my office","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":404,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020F_CAF.wav","answer":"they were sold to underwriters led by prudential bache securities incorporated","subset":"caf","task_type":"understanding","prediction":"they were sold to underwriters led by prudential bache securities incorporated","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":405,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020J_CAF.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"caf","task_type":"understanding","prediction":"In their efforts to restore market confidence. Administration officials have emphasized that the economy is fundamentally sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":406,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020K_CAF.wav","answer":"that was certainly true last week","subset":"caf","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":407,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020L_CAF.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"caf","task_type":"understanding","prediction":"Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":408,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020P_CAF.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"caf","task_type":"understanding","prediction":"The independent committee will recommend that holders accept the offer at a meeting expected to be held in December, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":409,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020R_CAF.wav","answer":"the investor now owns seventy three percent of the company","subset":"caf","task_type":"understanding","prediction":"the investor now owns seventy three percent of the company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":410,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C020V_CAF.wav","answer":"manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid","subset":"caf","task_type":"understanding","prediction":"Manhattan Industries continued to trade above the offer price yesterday, indicating a market expects a higher bid.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":411,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C0211_CAF.wav","answer":"lately computer retailing has been tough on everybody","subset":"caf","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":412,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C0212_CAF.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"caf","task_type":"understanding","prediction":"no one is making very much money on it acknowledges brian j kelly chairman of bell atlantic s investment development unit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":413,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F05_447C0215_CAF.wav","answer":"shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level","subset":"caf","task_type":"understanding","prediction":"Shearson, Lehman Hutton Incorporated index of long term Treasury bonds stayed in a very small range yesterday, finishing very close to Wednesdays closing level.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":414,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_440C0201_CAF.wav","answer":"at n. e. c. the need for international managers will keep rising","subset":"caf","task_type":"understanding","prediction":"At M, E, C, the need for international managers would keep rising.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":415,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_440C0205_CAF.wav","answer":"the company previously traded over the counter","subset":"caf","task_type":"understanding","prediction":"The company previously traded over the counter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":416,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_440C020N_CAF.wav","answer":"it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan","subset":"caf","task_type":"understanding","prediction":"It can sign on to the plan. File a competing plan or take a completely passive role that neither endorses nor opposes the plan.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":417,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_440C020U_CAF.wav","answer":"the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction","subset":"caf","task_type":"understanding","prediction":"The rate on the latest three month bills declined to 6.43% bid from an average of 6.53% set at the Tuesday auction","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":418,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_440C020V_CAF.wav","answer":"the rate on six month bills fell to six point seven three percent from six point eight three percent","subset":"caf","task_type":"understanding","prediction":"The rate on six month bills fell to 6.73% from 6.83%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":419,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_440C020Y_CAF.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"caf","task_type":"understanding","prediction":"Estimates for the gain range from 2% to 3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":420,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C0209_CAF.wav","answer":"the earlier rise was previously reported as four point three percent","subset":"caf","task_type":"understanding","prediction":"the earlier rise was previously reported as four point three percent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":421,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C020A_CAF.wav","answer":"if defense is excluded march orders rose one percent after a three percent increase in february","subset":"caf","task_type":"understanding","prediction":"If defence excluded March orders rose 1% after a 3% increase in February.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":422,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C020C_CAF.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"caf","task_type":"understanding","prediction":"The company, which runs retail and automotive stores, told shearson Lehman Brothers, its financial adviser, to terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":423,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C020D_CAF.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"caf","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":424,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C020F_CAF.wav","answer":"also a move to base it abroad will have tax advantages","subset":"caf","task_type":"understanding","prediction":"Also, a move to base abroad will have tax advantages.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":425,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C020L_CAF.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"caf","task_type":"understanding","prediction":"Those identified as beneficial owners of at least 10% of the company face equity securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":426,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C020S_CAF.wav","answer":"analysts haven't focused on what happened to them","subset":"caf","task_type":"understanding","prediction":"analysts have focused on what happened to them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":427,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C020V_CAF.wav","answer":"closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities","subset":"caf","task_type":"understanding","prediction":"Closed end funds are traded on exchanges like stocks that invest in a wide portfolio of other securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":428,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C0210_CAF.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"caf","task_type":"understanding","prediction":"After the offering, Republic New York will hold about 49% of the unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":429,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_441C0213_CAF.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"caf","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":430,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C0203_CAF.wav","answer":"the bank holding company slated another fifty million dollar sale next tuesday","subset":"caf","task_type":"understanding","prediction":"The bank holding company slated another $50 million sale next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":431,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C0207_CAF.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"caf","task_type":"understanding","prediction":"Grant Auto slipped 3 to 15 and 1,8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":432,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C020C_CAF.wav","answer":"shamrock has interests in television and radio stations energy services real estate and venture capital","subset":"caf","task_type":"understanding","prediction":"Shamrock has interests in television and radio stations. Energy services, real estate and venture capital.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":433,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C020F_CAF.wav","answer":"this morning the asking price for the stock was four thousand eight hundred fifty but there were no buyers","subset":"caf","task_type":"understanding","prediction":"This morning, the asking price for the stock was 4850, but there were no buyers.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":434,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C020G_CAF.wav","answer":"a monsanto spokesman said there's very little we can say","subset":"caf","task_type":"understanding","prediction":"a monsanto spokesman said there is very little we can say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":435,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C020K_CAF.wav","answer":"that would follow a two point two percent drop in may","subset":"caf","task_type":"understanding","prediction":"That would follow a 2.2 per cent drop in May.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":436,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C020T_CAF.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"caf","task_type":"understanding","prediction":"Volume was modest, as 326.7 million shares changed hands, compared with 396.5 million Friday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":437,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C020Z_CAF.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"caf","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":438,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_442C0210_CAF.wav","answer":"he declined to name specific products","subset":"caf","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":439,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C0201_CAF.wav","answer":"the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before","subset":"caf","task_type":"understanding","prediction":"The Labor Department said non farm payroll employment increased to their best 337000 last month after revised 319000 gain the month before","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":440,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C0208_CAF.wav","answer":"local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members","subset":"caf","task_type":"understanding","prediction":"Local membership jumped 22 per cent, but the union has already lost 28 of the 73 new members.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":441,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020C_CAF.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"caf","task_type":"understanding","prediction":"Employment looks strong, inflation is low, and consumer spending and investment are holding up reasonably well.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":442,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020J_CAF.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"caf","task_type":"understanding","prediction":"companies are listed where transactions generally aggregate ten thousand shares for one hundred thousand dollars","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":443,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020K_CAF.wav","answer":"after the third period ashland's coal operations began a process of becoming an independent company","subset":"caf","task_type":"understanding","prediction":"After the third period, Ashland's coal operations began a process of becoming an independent company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":444,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020L_CAF.wav","answer":"when its initial public offering is completed ashland is expected to retain a forty six percent stake","subset":"caf","task_type":"understanding","prediction":"When its initial public offering is completed. Ashland is expected to retain a 46% stake.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":445,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020M_CAF.wav","answer":"the new company ashland coal incorporated is listed on the new york stock exchange","subset":"caf","task_type":"understanding","prediction":"The new company, Ashton, Cole Incorporated, is listed on the New York Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":446,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020P_CAF.wav","answer":"in addition u. s. west's data solutions business applied communications incorporated is working out well and performed ahead of all our schedules","subset":"caf","task_type":"understanding","prediction":"In addition, US West data solutions, business applied communications incorporated is working out well and performed ahead of all our schedules.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":447,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020R_CAF.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"caf","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":448,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020U_CAF.wav","answer":"fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards","subset":"caf","task_type":"understanding","prediction":"Fees range up to about $40 annually for basic cards and $60 a year for gold cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":449,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C020Z_CAF.wav","answer":"companies listed below reported quarterly profit substantially different from the average of analysts' estimates","subset":"caf","task_type":"understanding","prediction":"Companies listed below reported quarterly profit substantially different from the average of analyst estimates.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":450,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C0211_CAF.wav","answer":"estimated and actual results involving losses are omitted","subset":"caf","task_type":"understanding","prediction":"Estimating the actual results involving losses are omitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":451,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C0212_CAF.wav","answer":"yesterday's losers included automobiles","subset":"caf","task_type":"understanding","prediction":"yesterday s losers included automakers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":452,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_443C0213_CAF.wav","answer":"honda was down ten to one thousand nine hundred thirty","subset":"caf","task_type":"understanding","prediction":"Honda was down 10 to 1930.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":453,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C0203_CAF.wav","answer":"revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars","subset":"caf","task_type":"understanding","prediction":"Revenue in the quarter more than doubled to $362.4 million from $149.2 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":454,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020I_CAF.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"caf","task_type":"understanding","prediction":"Kyocera was up 60, at 5260.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":455,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020O_CAF.wav","answer":"the company declined to identify the bidders but said it received offers in the high forty dollars per share","subset":"caf","task_type":"understanding","prediction":"The company declined to identify the bidders. But said it received offers in the high $40 per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":456,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020T_CAF.wav","answer":"the market's strength may show that demand isn't all a creation of incentives","subset":"caf","task_type":"understanding","prediction":"The market strength may show that demand isn't all a creation of incentives.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":457,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020U_CAF.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"caf","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":458,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020V_CAF.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"caf","task_type":"understanding","prediction":"As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":459,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020W_CAF.wav","answer":"a print media campaign will begin the following day","subset":"caf","task_type":"understanding","prediction":"A print media campaign will begin the following day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":460,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020Y_CAF.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday","subset":"caf","task_type":"understanding","prediction":"Volume was 18190000 shares, compared with 10550000 Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":461,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C020Z_CAF.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"caf","task_type":"understanding","prediction":"There were 256 issues advancing,303 declining and 292 unchanged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":462,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_444C0213_CAF.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"caf","task_type":"understanding","prediction":"A change in the firms ownership also should turn on the right warning light","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":463,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C0207_CAF.wav","answer":"but the penalties for failure are real","subset":"caf","task_type":"understanding","prediction":"but the penalties for failure are real","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":464,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C020H_CAF.wav","answer":"the suit seeks to block the contract which would have raised pay levels but cut benefits","subset":"caf","task_type":"understanding","prediction":"The suit seeks to block the contract. Which would have raised pay levels, but cut benefits.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":465,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C020K_CAF.wav","answer":"but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close","subset":"caf","task_type":"understanding","prediction":"But to the surprise of almost everyone. Stock prices began a steady climb that pushed the average above 160.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":466,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C020L_CAF.wav","answer":"although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading","subset":"caf","task_type":"understanding","prediction":"Although gains eroded during the afternoon, stock prices stayed within a narrow range until the last half hour of trading.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":467,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C020P_CAF.wav","answer":"about all the businessman can count on is that policy will be pretty volatile","subset":"caf","task_type":"understanding","prediction":"About all the businessman can count on is that policy will be pretty volatile.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":468,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C020S_CAF.wav","answer":"lately computer retailing has been tough on everybody","subset":"caf","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":469,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C020T_CAF.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"caf","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's Investment Development Unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":470,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_445C0210_CAF.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"caf","task_type":"understanding","prediction":"As part of the marketing plan, the company will begin airing television commercials during prime time on election night next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":471,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C0202_CAF.wav","answer":"to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred","subset":"caf","task_type":"understanding","prediction":"To make them directly comparable, each index is based on the close of 1969, equaling 100.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":472,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C0203_CAF.wav","answer":"the percentage change is since year end","subset":"caf","task_type":"understanding","prediction":"the percentage change is since year end","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":473,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C0205_CAF.wav","answer":"no one at the state department wants to let spies in","subset":"caf","task_type":"understanding","prediction":"No one at the State Department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":474,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C0206_CAF.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"caf","task_type":"understanding","prediction":"were not prepared to be advocates for the kgb","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":475,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C0207_CAF.wav","answer":"that doesn't mean mr. icahn has committed any wrongdoing","subset":"caf","task_type":"understanding","prediction":"that does not mean mr aykcin has committed any wrongdoing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":476,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020A_CAF.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"caf","task_type":"understanding","prediction":"Separately, New York State sold about $77.1 million of certificates of participation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":477,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020B_CAF.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"caf","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":478,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020C_CAF.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"caf","task_type":"understanding","prediction":"The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers lead underwriter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":479,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020P_CAF.wav","answer":"it's still unclear","subset":"caf","task_type":"understanding","prediction":"it still unclear","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":480,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020Q_CAF.wav","answer":"there was a striking split between the sexes with men more likely than women to favor space programs","subset":"caf","task_type":"understanding","prediction":"There was a striking split between the sexes, with men more likely than women to favour space programs.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":481,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020T_CAF.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"caf","task_type":"understanding","prediction":"According to the average estimate of 7 economists surveyed by Dow Jones, capital markets report new orders for US durable goods rose 2.4% last month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":482,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020U_CAF.wav","answer":"that would follow a two point two percent drop in may","subset":"caf","task_type":"understanding","prediction":"That would follow a 2.2% drop in May.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":483,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020V_CAF.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"caf","task_type":"understanding","prediction":"The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":484,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020W_CAF.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"caf","task_type":"understanding","prediction":"Durable goods reports frequently are highly volatile, from month to month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":485,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C020X_CAF.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"caf","task_type":"understanding","prediction":"Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":486,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_446C0213_CAF.wav","answer":"it also owns three state business magazines in florida georgia and arizona","subset":"caf","task_type":"understanding","prediction":"It also owns three state fairgrounds in Florida, Georgia and Arizona.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":487,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C0204_CAF.wav","answer":"mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent","subset":"caf","task_type":"understanding","prediction":"Mr. Robertson says he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":488,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C0207_CAF.wav","answer":"washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own","subset":"caf","task_type":"understanding","prediction":"Washington National paid $19 a share for the 2.6 million United Pacific shares. it didn't already own.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":489,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C020C_CAF.wav","answer":"sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days","subset":"caf","task_type":"understanding","prediction":"Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":490,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C020O_CAF.wav","answer":"the company expects to report its results in about two weeks","subset":"caf","task_type":"understanding","prediction":"The company expects to report its results in about two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":491,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C020U_CAF.wav","answer":"other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation","subset":"caf","task_type":"understanding","prediction":"Other analysts say the Fed needs to tighten policy further to support the dollar and prevent inflation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":492,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C020W_CAF.wav","answer":"the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape","subset":"caf","task_type":"understanding","prediction":"The shares closed $18.25,25 cents on the New York Stock Exchange composite tape.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":493,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C020X_CAF.wav","answer":"salant shares closed unchanged on the big board at nine dollars and seventy five cents","subset":"caf","task_type":"understanding","prediction":"Salant shares closed unchanged on the big board at $9.75.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":494,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C0213_CAF.wav","answer":"we had to sustain some modest operating losses","subset":"caf","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":495,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/F06_447C0216_CAF.wav","answer":"the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight","subset":"caf","task_type":"understanding","prediction":"The index ended with a decline of 0.35 point to 1272.18.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":496,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C0206_CAF.wav","answer":"two other issues began trading recently on the big board","subset":"caf","task_type":"understanding","prediction":"Two other issues began trading recently, on the big board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":497,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C0208_CAF.wav","answer":"union officials expect ratification","subset":"caf","task_type":"understanding","prediction":"union officials expect ratification","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":498,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020A_CAF.wav","answer":"despite the july decline durable goods orders remained seven point seven percent above the year earlier level","subset":"caf","task_type":"understanding","prediction":"Despite the July decline durable goods orders remained 7.7% above the year earlier level","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":499,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020B_CAF.wav","answer":"economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment","subset":"caf","task_type":"understanding","prediction":"economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":500,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020J_CAF.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"caf","task_type":"understanding","prediction":"The independent committee will recommend that holders accept the offer at a meeting expected to be held in December. Twa said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":501,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020K_CAF.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"caf","task_type":"understanding","prediction":"The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":502,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020Q_CAF.wav","answer":"the rise in auto imports also reflects higher prices for imported cars","subset":"caf","task_type":"understanding","prediction":"The rise in auto imports also reflects higher prices for imported cars.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":503,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020R_CAF.wav","answer":"prices are going up said george c. eads vice president and chief economist at general motors corporation","subset":"caf","task_type":"understanding","prediction":"Prices are going up, said George C. Eads, vice president and chief economist at General Motors Corporation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":504,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020X_CAF.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"caf","task_type":"understanding","prediction":"Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":505,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C020Z_CAF.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"caf","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":506,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C0211_CAF.wav","answer":"about three point five billion dollars of securities are affected","subset":"caf","task_type":"understanding","prediction":"About $3.5 billion of securities are affected.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":507,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C0212_CAF.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"caf","task_type":"understanding","prediction":"He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":508,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C0213_CAF.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"caf","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":509,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_440C0214_CAF.wav","answer":"he declined to name specific products","subset":"caf","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":510,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C0203_CAF.wav","answer":"first commodity officials couldn't be reached for comment","subset":"caf","task_type":"understanding","prediction":"First commodity officials couldn't be reached for comment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":511,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C0204_CAF.wav","answer":"and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort","subset":"caf","task_type":"understanding","prediction":"and then there is the explanation of why teradyne s growth in japan is slow despite fifteen years of effort","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":512,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C020B_CAF.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"caf","task_type":"understanding","prediction":"Grand Auto slid 3 to 15 and 1\/8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":513,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C020G_CAF.wav","answer":"elders finance and elders agribusiness will remain based in australia","subset":"caf","task_type":"understanding","prediction":"elders finance and elders agribusiness will remain based in australia","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":514,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C020K_CAF.wav","answer":"the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"caf","task_type":"understanding","prediction":"The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":515,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C020R_CAF.wav","answer":"too much focus is placed on reduction of cross country loans mr. meyerman said","subset":"caf","task_type":"understanding","prediction":"Too much focus is placed on reduction of cross country loans, Mr. Meyerman said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":516,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C020U_CAF.wav","answer":"our guess is no","subset":"caf","task_type":"understanding","prediction":"Our guess is, no.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":517,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C020Y_CAF.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"caf","task_type":"understanding","prediction":"Republic, New York, rose 1 and 1 quarter to 45, and 7\/8.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":518,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C020Z_CAF.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"caf","task_type":"understanding","prediction":"The company said its European Banking affiliate. Safra Republic plans to raise more than $450 million through an international offering.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":519,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_441C0211_CAF.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"caf","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":520,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C0202_CAF.wav","answer":"accepted bids ranged from six point two percent to six point two two five percent","subset":"caf","task_type":"understanding","prediction":"Accepted bids ranged from 6.2% to 6.225%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":521,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C0204_CAF.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"caf","task_type":"understanding","prediction":"MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":522,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C020E_CAF.wav","answer":"under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents","subset":"caf","task_type":"understanding","prediction":"Under Tokyo trading rules the maximum one day drop for Sony is ¥500 about $3.50.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":523,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C020M_CAF.wav","answer":"even some bigger companies caution that they are leery of paying too big a premium","subset":"caf","task_type":"understanding","prediction":"Even some bigger companies caution that they are leery of paying too big a premium.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":524,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C020Q_CAF.wav","answer":"in a dutch auction holders tender their shares at prices within a stated range in this case between twenty eight dollars and thirty three dollars a share","subset":"caf","task_type":"understanding","prediction":"In a Dutch auction, holders tender their shares at prices within a stated range. In this case, between $28 and $33 a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":525,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C020V_CAF.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"caf","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":526,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C0212_CAF.wav","answer":"foreigners are back and negotiating with the chinese will be as tough as ever","subset":"caf","task_type":"understanding","prediction":"Foreigners are back and negotiating with the Chinese will be as tough as ever.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":527,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C0213_CAF.wav","answer":"that's fine","subset":"caf","task_type":"understanding","prediction":"thats fine","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":528,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C0214_CAF.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"caf","task_type":"understanding","prediction":"A change in the firms ownership also should turn on a bright warning light.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":529,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_442C0216_CAF.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"caf","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts with incentives aimed at reducing that problem.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":530,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020A_CAF.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"caf","task_type":"understanding","prediction":"In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":531,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020B_CAF.wav","answer":"that was certainly true last week","subset":"caf","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":532,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020E_CAF.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"caf","task_type":"understanding","prediction":"Kyocera was up 60 at 5216.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":533,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020F_CAF.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"caf","task_type":"understanding","prediction":"Sony, which lost points in previous sessions this week, rebounded 80 to 5130.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":534,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020Q_CAF.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"caf","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":535,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020S_CAF.wav","answer":"a print media campaign will begin the following day","subset":"caf","task_type":"understanding","prediction":"A print media campaign will begin the following day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":536,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020T_CAF.wav","answer":"visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards","subset":"caf","task_type":"understanding","prediction":"Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":537,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020W_CAF.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"caf","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 380.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":538,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_443C020Y_CAF.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"caf","task_type":"understanding","prediction":"There were 256 issues advancing,303 declining and 292 unchanged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":539,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C0204_CAF.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"caf","task_type":"understanding","prediction":"separately new york state sold about seventy seven point one million dollars of certificates of participation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":540,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C0207_CAF.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"caf","task_type":"understanding","prediction":"The issue is rated single A by Moody S and single A minus by S M T.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":541,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C020A_CAF.wav","answer":"in addition banks in general are being pushed by regulators to boost their capital positions","subset":"caf","task_type":"understanding","prediction":"In addition, banks in general are being pushed by regulators to boost their capital positions.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":542,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C020E_CAF.wav","answer":"several airlines have also opposed the standards and may fight some aspects in court","subset":"caf","task_type":"understanding","prediction":"Several airlines have also opposed the standards and may fight some aspects in court","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":543,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C020L_CAF.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"caf","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":544,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C020M_CAF.wav","answer":"we had to sustain some modest operating losses","subset":"caf","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":545,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C020N_CAF.wav","answer":"we didn't like that","subset":"caf","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":546,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C020Q_CAF.wav","answer":"the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding","subset":"caf","task_type":"understanding","prediction":"The offers indicate a total price for the company exceeding $800 million based on 17.2 million shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":547,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_444C0211_CAF.wav","answer":"however investment income which represents thirteen percent of the industry's revenue rose eleven percent in the quarter reflecting gains from the rising stock market","subset":"caf","task_type":"understanding","prediction":"however investment income which represents thirteen percent of the industry s revenue rose eleven percent in the quarter reflecting gains from the rising stock market","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":548,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0201_CAF.wav","answer":"owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged","subset":"caf","task_type":"understanding","prediction":"Owens Illinois said its share purchases would be financed by existing credit lines and new ones to be arranged","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":549,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0202_CAF.wav","answer":"if all twenty million shares were purchased the company's equity would be reduced by about one third","subset":"caf","task_type":"understanding","prediction":"If all 20 million shares were purchased. The company's equity would be reduced by about one third.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":550,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0203_CAF.wav","answer":"a spokesman said the company has about sixty million shares outstanding","subset":"caf","task_type":"understanding","prediction":"A spokesman said the company has about 60 million shares outstanding","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":551,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0204_CAF.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"caf","task_type":"understanding","prediction":"The consensus was that a new piece of paper isn't required, said one US diplomat.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":552,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0205_CAF.wav","answer":"no one at the state department wants to let spies in","subset":"caf","task_type":"understanding","prediction":"no one at the state department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":553,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C020B_CAF.wav","answer":"but it is mr. west upon whom the outcome probably depends the most","subset":"caf","task_type":"understanding","prediction":"But it is Mr. West upon whom the outcome probably depends the most.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":554,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C020C_CAF.wav","answer":"testimony concluded this week and closing arguments are scheduled to begin monday","subset":"caf","task_type":"understanding","prediction":"Testimony concluded this week, and closing arguments are scheduled to begin Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":555,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C020N_CAF.wav","answer":"coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board","subset":"caf","task_type":"understanding","prediction":"Coniston Partners of New York said it has a 6.8% stake in Gillette and may seek to acquire the company or gain seats on its board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":556,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C020U_CAF.wav","answer":"we had to sustain some modest operating losses","subset":"caf","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":557,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C020V_CAF.wav","answer":"we didn't like that","subset":"caf","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":558,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0212_CAF.wav","answer":"the real change though is in how china looks","subset":"caf","task_type":"understanding","prediction":"The real change, though, is in how China looks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":559,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0214_CAF.wav","answer":"the numbers looked amazingly good industrial growth rates above ten percent per year year after year","subset":"caf","task_type":"understanding","prediction":"The numbers looked amazingly good. Industrial growth rates above 10% per year, year after year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":560,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_445C0215_CAF.wav","answer":"and after a temporary downturn in the next couple of years the numbers probably will go back up","subset":"caf","task_type":"understanding","prediction":"and after a temporary downturn in the next couple of years the numbers probably will go back down","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":561,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C0201_CAF.wav","answer":"here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva","subset":"caf","task_type":"understanding","prediction":"here are price trends on the worlds major stock markets as calculated by morgan stanley capital international perspective geneva","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":562,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C0208_CAF.wav","answer":"but the investigation could make some lenders wary","subset":"caf","task_type":"understanding","prediction":"but the investigation could make some lenders wary","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":563,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C0209_CAF.wav","answer":"mr. icahn and an investor group he heads hold seventy two point seven percent of t. w. a.'s shares","subset":"caf","task_type":"understanding","prediction":"Mr. Icahn and an investor group he heads hold 72.7% of T W A s shares.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":564,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C020J_CAF.wav","answer":"in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars","subset":"caf","task_type":"understanding","prediction":"In fiscal 1987, Wang had a loss of $78.7 million on revenue of $2.84 billion.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":565,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C020M_CAF.wav","answer":"net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in the period","subset":"caf","task_type":"understanding","prediction":"Net income rose 125% to 753 million Swiss francs in the period.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":566,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C020O_CAF.wav","answer":"we're not ready to say we're in technical default a spokesman said","subset":"caf","task_type":"understanding","prediction":"We are not ready to say we are in technical default a spokesman said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":567,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C020R_CAF.wav","answer":"among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agreed","subset":"caf","task_type":"understanding","prediction":"among men fifty six percent said the u s was doing too little in space exploration only a quarter of women agreed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":568,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_446C0210_CAF.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"caf","task_type":"understanding","prediction":"The company said its European banking affiliate. Saffra Republic plans to raise more than $450 million through an international offering.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":569,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C0202_CAF.wav","answer":"i have my list of changes i'd like to see","subset":"caf","task_type":"understanding","prediction":"i have my list of changes i d like to see","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":570,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C0205_CAF.wav","answer":"he doesn't","subset":"caf","task_type":"understanding","prediction":"he does not","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":571,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C0208_CAF.wav","answer":"before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company","subset":"caf","task_type":"understanding","prediction":"Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":572,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C020G_CAF.wav","answer":"the underwriting group has a thirty day option to acquire an additional six hundred thousand shares at eight dollars each","subset":"caf","task_type":"understanding","prediction":"The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":573,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C020I_CAF.wav","answer":"it had fourteen point five million common shares outstanding before the issue","subset":"caf","task_type":"understanding","prediction":"It had 14.5 million common shares outstanding before the issue.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":574,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C020N_CAF.wav","answer":"it had sales of ninety one point five million dollars in the nineteen eighty six third quarter","subset":"caf","task_type":"understanding","prediction":"it had sales of ninety one point five million dollars in the nineteen eighty six third quarter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":575,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C020Z_CAF.wav","answer":"several cities have versions of the british organization body positive","subset":"caf","task_type":"understanding","prediction":"several cities have versions of the british organization body positive","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":576,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C0214_CAF.wav","answer":"we didn't like that","subset":"caf","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":577,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M05_447C0217_CAF.wav","answer":"the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight","subset":"caf","task_type":"understanding","prediction":"The low was 1270.19, and the high was 1273.88.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":578,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C0202_CAF.wav","answer":"the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years","subset":"caf","task_type":"understanding","prediction":"The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":579,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C0204_CAF.wav","answer":"r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.","subset":"caf","task_type":"understanding","prediction":"Rli Corporation, a Peoria, Illinois, based insurance holding company, will begin trading Friday on the big board under the symbol Rli.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":580,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C0209_CAF.wav","answer":"a p. b. g. c. spokeswoman declined comment","subset":"caf","task_type":"understanding","prediction":"a p b g c spokesman declined comment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":581,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020E_CAF.wav","answer":"the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last week","subset":"caf","task_type":"understanding","prediction":"The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at the previous auction last week.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":582,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020F_CAF.wav","answer":"the average rate on new twenty six week bills rose to six point one six percent from six point one two percent","subset":"caf","task_type":"understanding","prediction":"The average rate on new 26 week bills rose to 6.16% from 6.12%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":583,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020G_CAF.wav","answer":"analysts too generally played down the effect on banks","subset":"caf","task_type":"understanding","prediction":"analysts too can make a point on the capital banks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":584,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020H_CAF.wav","answer":"in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks","subset":"caf","task_type":"understanding","prediction":"In a fundamental sense, the equity markets have very little to do with what goes on in the commercial banks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":585,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020I_CAF.wav","answer":"there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company","subset":"caf","task_type":"understanding","prediction":"There shouldnt be any risk to the banks in this sort of stuff said Lawrence Cohn a banking analyst at Merrill Lynch and Company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":586,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020O_CAF.wav","answer":"unable to agree on friday the board must meet again at least by phone to register its choice","subset":"caf","task_type":"understanding","prediction":"Unable to agree on Friday, the board must meet again, at least by phone, to register its choice.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":587,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020P_CAF.wav","answer":"commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models","subset":"caf","task_type":"understanding","prediction":"Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories with new models.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":588,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020T_CAF.wav","answer":"rates fell on short term treasury bills","subset":"caf","task_type":"understanding","prediction":"rates fell on short term treasury bills","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":589,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C020W_CAF.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"caf","task_type":"understanding","prediction":"Durable goods reports frequently are highly volatile, from month to month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":590,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_440C0210_CAF.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"caf","task_type":"understanding","prediction":"Yesterday, Moody S. Investor Service raised Lilco S credit rating in recognition of the improved outlook for steady financial recovery.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":591,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C0207_CAF.wav","answer":"in japan it's all greek so to speak","subset":"caf","task_type":"understanding","prediction":"in japan it is all greek so to speak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":592,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C020M_CAF.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"caf","task_type":"understanding","prediction":"Unless otherwise noted, changes involved direct holdings of common stock and took place in September and October of 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":593,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C020N_CAF.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"caf","task_type":"understanding","prediction":"Companies are listed where transactions generally aggregate 10000 shares, or $100000.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":594,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C020O_CAF.wav","answer":"about all businessmen can count on is that policy will be pretty volatile","subset":"caf","task_type":"understanding","prediction":"About all businessmen can count on is that policy will be pretty volatile","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":595,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C020Q_CAF.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"caf","task_type":"understanding","prediction":"If the Fed pushes the dollar higher. It may curb the demand for US exports.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":596,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C020T_CAF.wav","answer":"has exposure really been reduced","subset":"caf","task_type":"understanding","prediction":"has exposure really been reduced","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":597,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C0212_CAF.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"caf","task_type":"understanding","prediction":"The volume was modest, as 326.7 million shares changed hands, compared with 396.5 million Friday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":598,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C0214_CAF.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"caf","task_type":"understanding","prediction":"He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":599,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C0215_CAF.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"caf","task_type":"understanding","prediction":"It said such products would be marketed by other companies with experience in the business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":600,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_441C0216_CAF.wav","answer":"he declined to name specific products","subset":"caf","task_type":"understanding","prediction":"He declined to name specific products.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":601,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C0201_CAF.wav","answer":"bids totaling five hundred twenty five point five million dollars were submitted","subset":"caf","task_type":"understanding","prediction":"Bids totaling $525.5 million, were submitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":602,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C0205_CAF.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"caf","task_type":"understanding","prediction":"MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":603,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C0206_CAF.wav","answer":"the toronto based company provides mortgage guarantees to the canadian real estate industry","subset":"caf","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to the Canadian real estate industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":604,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020A_CAF.wav","answer":"under terms previously reported the italian agricultural concern assumed that about one hundred ninety five million dollars in subordinated debt as part of the transaction","subset":"caf","task_type":"understanding","prediction":"Under term, previously reported, the Italian agricultural concern assumed about $195 million in subordinated debt as part of the transaction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":605,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020H_CAF.wav","answer":"we just received the suit and the document is is massive it's two hundred pages","subset":"caf","task_type":"understanding","prediction":"We just received the suit and the document is massive. It is 200 pages.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":606,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020I_CAF.wav","answer":"but on the first read through the case is without merit and we intend to fight it","subset":"caf","task_type":"understanding","prediction":"But on the first read, through the case is without merit. And we intend to fight it.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":607,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020J_CAF.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"caf","task_type":"understanding","prediction":"According to the average estimate of 7 economists surveyed by Dow Jones Capital Markets Report. New orders for US durable goods rose 2.4% last month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":608,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020L_CAF.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"caf","task_type":"understanding","prediction":"The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":609,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020N_CAF.wav","answer":"we're going to be bidders said a top official of a major oil company","subset":"caf","task_type":"understanding","prediction":"We are going to be generous, said a top official of a major oil company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":610,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020P_CAF.wav","answer":"the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding","subset":"caf","task_type":"understanding","prediction":"The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26 of its shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":611,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020W_CAF.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"caf","task_type":"understanding","prediction":"Yesterday, Moody s investor service raised Lilco s credit rating in recognition of an improved outlook for steady financial recovery.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":612,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020X_CAF.wav","answer":"about three point five billion dollars of securities are affected","subset":"caf","task_type":"understanding","prediction":"About $3.5 billion in securities are affected.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":613,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C020Y_CAF.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"caf","task_type":"understanding","prediction":"He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":614,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_442C0215_CAF.wav","answer":"money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","subset":"caf","task_type":"understanding","prediction":"Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, he said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":615,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_443C0202_CAF.wav","answer":"the department previously said jobs rose by four hundred forty eight thousand in january","subset":"caf","task_type":"understanding","prediction":"The department previously said jobs rose by 448000 in January.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":616,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_443C0203_CAF.wav","answer":"using a measure that counts the military among the employed the rate was unchanged at six point six percent last month","subset":"caf","task_type":"understanding","prediction":"using a measure that counts the military among the employed the rate was unchanged at six point six percent last month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":617,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_443C0207_CAF.wav","answer":"it isn't clear yet whether the campaign works","subset":"caf","task_type":"understanding","prediction":"It isn't clear yet, whether the campaign works.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":618,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_443C020D_CAF.wav","answer":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty","subset":"caf","task_type":"understanding","prediction":"Among export LED electrical and distributor makers. Japan Victor Company fell 52 to 2320.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":619,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_443C020G_CAF.wav","answer":"the following officers directors and large stakeholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"caf","task_type":"understanding","prediction":"The following officers, directors and large stakeholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":620,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_443C020X_CAF.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday","subset":"caf","task_type":"understanding","prediction":"volume was eighteen million one hundred and ninety thousand shares compared to ten million five hundred and fifty thousand monday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":621,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_443C0210_CAF.wav","answer":"the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share","subset":"caf","task_type":"understanding","prediction":"The companies are followed by at least three analysts and had a minimum 5 cent change in actual earnings per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":622,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C0201_CAF.wav","answer":"in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share","subset":"caf","task_type":"understanding","prediction":"In the 1985 quarter, the owner and operator of health maintenance organizations spent $6.9 million or 24 cents a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":623,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C0202_CAF.wav","answer":"it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars","subset":"caf","task_type":"understanding","prediction":"it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":624,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C0205_CAF.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"caf","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":625,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C0206_CAF.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"caf","task_type":"understanding","prediction":"The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":626,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C020B_CAF.wav","answer":"monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference","subset":"caf","task_type":"understanding","prediction":"mondays crashes likely as you affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":627,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C020C_CAF.wav","answer":"senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash","subset":"caf","task_type":"understanding","prediction":"Senate Finance Chairman Boyd Benson, D. Texas said he would speed up work on the package because of the crash.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":628,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C020D_CAF.wav","answer":"it adds to the support for the trade bill getting through he said","subset":"caf","task_type":"understanding","prediction":"It adds to the support for the trade bill getting through, he said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":629,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C020F_CAF.wav","answer":"so far they have declined to comment publicly on their plans","subset":"caf","task_type":"understanding","prediction":"So far, they have declined to comment publicly on their plans.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":630,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C020G_CAF.wav","answer":"state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do","subset":"caf","task_type":"understanding","prediction":"State officials, however, say the airlines have indicated they will comply with most of the standards as long as the competitors do","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":631,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C020H_CAF.wav","answer":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty","subset":"caf","task_type":"understanding","prediction":"Among export LED electrical and computer makers. Japan Vector Company fell 15 to 2320.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":632,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C020K_CAF.wav","answer":"lately computer retailing has been tough on everybody","subset":"caf","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":633,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C0210_CAF.wav","answer":"the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent","subset":"caf","task_type":"understanding","prediction":"The institute said earned premiums rose 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":634,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_444C0215_CAF.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"caf","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts with incentives aimed at reducing that problem.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":635,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C0206_CAF.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"caf","task_type":"understanding","prediction":"whenever prepared to be advocates for the case you made","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":636,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C0208_CAF.wav","answer":"their business isn't just a job but their investment","subset":"caf","task_type":"understanding","prediction":"Their business isn't just a job, but their investment.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":637,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C020I_CAF.wav","answer":"the airline imposed the contract without union bargaining","subset":"caf","task_type":"understanding","prediction":"The airline imposed the contract, without union bargaining.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":638,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C020J_CAF.wav","answer":"yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling","subset":"caf","task_type":"understanding","prediction":"Yesterday session began with a sharp, quick decline in the industrial average of more than 45 points, which some market analysts attributed to foreign selling.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":639,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C020M_CAF.wav","answer":"gillette is again a target of a major corporate raider","subset":"caf","task_type":"understanding","prediction":"Gillette is, again, a target of a major corporate.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":640,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C020O_CAF.wav","answer":"a lengthy fight is likely","subset":"caf","task_type":"understanding","prediction":"a lengthy fight is likely","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":641,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C020X_CAF.wav","answer":"continental started the appeal process but recently settled the case","subset":"caf","task_type":"understanding","prediction":"Continental started the appeal process but recently set up the case","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":642,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C020Y_CAF.wav","answer":"neither side would disclose terms","subset":"caf","task_type":"understanding","prediction":"neither side would disclose terms","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":643,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_445C0213_CAF.wav","answer":"from america china looked good","subset":"caf","task_type":"understanding","prediction":"From America, China looks good.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":644,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_446C020E_CAF.wav","answer":"fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments","subset":"caf","task_type":"understanding","prediction":"Fidelity had contended that Gen Corp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":645,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_446C020I_CAF.wav","answer":"he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year","subset":"caf","task_type":"understanding","prediction":"He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":646,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_446C020K_CAF.wav","answer":"in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty","subset":"caf","task_type":"understanding","prediction":"In many ways, that is just what UBS has done since Mr. Sanders became president in 1980.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":647,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_446C020L_CAF.wav","answer":"assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven","subset":"caf","task_type":"understanding","prediction":"Assets more than doubled since then to 160.4 million Swiss francs. $115.6 billion in 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":648,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_446C020N_CAF.wav","answer":"the real estate investment trust said it was still hoping to reach a new credit arrangement","subset":"caf","task_type":"understanding","prediction":"The real estate investment trust said it was still hoping to reach a new credit arrangement.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":649,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_446C020S_CAF.wav","answer":"among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women","subset":"caf","task_type":"understanding","prediction":"Among men,41% supported boosting the space exploration budget, compared with 90% of women.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":650,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C0201_CAF.wav","answer":"i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month","subset":"caf","task_type":"understanding","prediction":"i do not mean there could not be some improvements in the revenue act of nineteen eighty six which took effect last month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":651,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C0206_CAF.wav","answer":"he cites the law of large numbers can you really expect it to grow at large numbers very long","subset":"caf","task_type":"understanding","prediction":"He cites the law of large numbers. Can you really expect it to grow in large numbers, very long.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":652,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C0209_CAF.wav","answer":"washington national is a financial services concern","subset":"caf","task_type":"understanding","prediction":"Washington National is a financial services concern.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":653,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C020E_CAF.wav","answer":"northgate exploration limited said it sold four million common shares at eight dollars each","subset":"caf","task_type":"understanding","prediction":"Northgate Exploration Limited said it sold 4 million common shares at $8 each.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":654,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C020H_CAF.wav","answer":"the toronto based gold mining concern said proceeds would be used for general purposes","subset":"caf","task_type":"understanding","prediction":"The Toronto based gold mining concern said proceeds would be used for general purposes.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":655,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C020M_CAF.wav","answer":"envirodyne said it expects sales to be the highest for any third quarter in the company's history","subset":"caf","task_type":"understanding","prediction":"Envirodyne said it expects sales to be the highest for any third quarter in the company s history","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":656,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C020Q_CAF.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"caf","task_type":"understanding","prediction":"The transaction requires approval by a majority of the shares of the holders, not affiliated with Mr. Akon.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":657,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C020S_CAF.wav","answer":"but while the fed stands pat it is coming under increasing attack from both sides","subset":"caf","task_type":"understanding","prediction":"But while the Fed stands pat, it is coming under increasing attack from both sides.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":658,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C020T_CAF.wav","answer":"some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year","subset":"caf","task_type":"understanding","prediction":"Some critics, including high Reagan administration officials. Are raising the alarm that the Fed policy is too tight and could cause a recession next year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":659,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C020Y_CAF.wav","answer":"increasingly people who test positive join the support groups that have sprung across the country in the past year","subset":"caf","task_type":"understanding","prediction":"Increasingly, people who test positive join the support groups that have sprung across the country in the past year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":660,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_caf_real\/M06_447C0210_CAF.wav","answer":"founded last october new york's body positive already has sixteen groups meeting every two weeks","subset":"caf","task_type":"understanding","prediction":"Nonetheless, October Newlands body positive already has 16 groups meeting every two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":661,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_440C0201_PED.wav","answer":"at n. e. c. the need for international managers will keep rising","subset":"ped","task_type":"understanding","prediction":"at nec the need for international mergers will keep rising","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":662,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_440C0205_PED.wav","answer":"the company previously traded over the counter","subset":"ped","task_type":"understanding","prediction":"the company previously traded over the counter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":663,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_440C020N_PED.wav","answer":"it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan","subset":"ped","task_type":"understanding","prediction":"It can sign on to the plan. File a competing plan or take a completely passive role that neither endorses nor opposes the plan.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":664,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_440C020U_PED.wav","answer":"the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction","subset":"ped","task_type":"understanding","prediction":"The rate on the latest three month bills declined to 6.43% bid from an average of 6.53% set at Tuesday auction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":665,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_440C020V_PED.wav","answer":"the rate on six month bills fell to six point seven three percent from six point eight three percent","subset":"ped","task_type":"understanding","prediction":"the rate on six month bills fell to six point seven three percent from six point eight three percent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":666,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_441C0209_PED.wav","answer":"the earlier rise was previously reported as four point three percent","subset":"ped","task_type":"understanding","prediction":"The earlier rise was previously reported, as 4.3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":667,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_441C020A_PED.wav","answer":"if defense is excluded march orders rose one percent after a three percent increase in february","subset":"ped","task_type":"understanding","prediction":"If defense is excluded March orders rose 1% after a 3% increase in February.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":668,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_441C020F_PED.wav","answer":"also a move to base it abroad will have tax advantages","subset":"ped","task_type":"understanding","prediction":"also a move to base of abroad will have tax advantages","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":669,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_441C020S_PED.wav","answer":"analysts haven't focused on what happened to them","subset":"ped","task_type":"understanding","prediction":"analysts haven t focused on what happened to the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":670,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_441C020V_PED.wav","answer":"closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities","subset":"ped","task_type":"understanding","prediction":"Closed end funds are traded on exchanges like stocks, but invest in a wide portfolio of other securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":671,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C0203_PED.wav","answer":"the bank holding company slated another fifty million dollar sale next tuesday","subset":"ped","task_type":"understanding","prediction":"The bank holding company slated another $50 million sale next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":672,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C020C_PED.wav","answer":"shamrock has interests in television and radio stations energy services real estate and venture capital","subset":"ped","task_type":"understanding","prediction":"Chairman Lee is interested in television and radio stations, energy services. real estate and venture capital.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":673,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C020F_PED.wav","answer":"this morning the asking price for the stock was four thousand eight hundred fifty but there were no buyers","subset":"ped","task_type":"understanding","prediction":"This morning, the asking price for the stock was 4850, but there were no buyers.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":674,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C020G_PED.wav","answer":"a monsanto spokesman said there's very little we can say","subset":"ped","task_type":"understanding","prediction":"a monsanto spokesman said there is very little we can say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":675,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C020K_PED.wav","answer":"that would follow a two point two percent drop in may","subset":"ped","task_type":"understanding","prediction":"that would follow a two point two percent drop in may","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":676,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C020T_PED.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"ped","task_type":"understanding","prediction":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":677,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C020U_PED.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"ped","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":678,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C020Z_PED.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"ped","task_type":"understanding","prediction":"He said such products would be marketed by other companies, with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":679,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_442C0210_PED.wav","answer":"he declined to name specific products","subset":"ped","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":680,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C0201_PED.wav","answer":"the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before","subset":"ped","task_type":"understanding","prediction":"The Labor Department said nonfarm payroll employment increased a robust 337000 last month after revised 319000 gain the month before.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":681,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C0208_PED.wav","answer":"local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members","subset":"ped","task_type":"understanding","prediction":"Local membership jumped 22 per cent but the union has already lost 28 of the 73 new members","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":682,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020H_PED.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"ped","task_type":"understanding","prediction":"Those identified as beneficial owners hold at least 10% of the company's equity securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":683,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020J_PED.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"ped","task_type":"understanding","prediction":"Companies are listed where transactions generally aggregate 10000 shares, or $100000.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":684,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020K_PED.wav","answer":"after the third period ashland's coal operations began a process of becoming an independent company","subset":"ped","task_type":"understanding","prediction":"After the third period, Ashland's coal operations began a process of becoming an independent company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":685,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020L_PED.wav","answer":"when its initial public offering is completed ashland is expected to retain a forty six percent stake","subset":"ped","task_type":"understanding","prediction":"When its initial public offering is completed Ashland is expected to retain a 46% stake","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":686,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020M_PED.wav","answer":"the new company ashland coal incorporated is listed on the new york stock exchange","subset":"ped","task_type":"understanding","prediction":"The new company, Ashland, Co. Incorporated is listed on the New York Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":687,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020P_PED.wav","answer":"in addition u. s. west's data solutions business applied communications incorporated is working out well and performing ahead of all our schedules","subset":"ped","task_type":"understanding","prediction":"In addition, US West data solutions, business applied communications, Incorporated, is working out well and performing ahead of all our schedules.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":688,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020R_PED.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"ped","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":689,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020U_PED.wav","answer":"fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards","subset":"ped","task_type":"understanding","prediction":"Fees range up to about $40 annually for basic cards and $60 a year for gold cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":690,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C020Z_PED.wav","answer":"companies listed below reported quarterly profit substantially different from the average of analysts' estimates","subset":"ped","task_type":"understanding","prediction":"Companies listed below reported quarterly profits substantially different from the average of analyst estimates.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":691,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C0211_PED.wav","answer":"estimated and actual results involving losses are omitted","subset":"ped","task_type":"understanding","prediction":"Estimated and actual results involving losses are omitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":692,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C0212_PED.wav","answer":"yesterday's losers included automobiles","subset":"ped","task_type":"understanding","prediction":"yesterday s losers included automobiles","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":693,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_443C0213_PED.wav","answer":"honda was down ten to one thousand nine hundred thirty","subset":"ped","task_type":"understanding","prediction":"Honda was down 10 to 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":694,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C0203_PED.wav","answer":"revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars","subset":"ped","task_type":"understanding","prediction":"Revenue in the quarter more than doubled to $362.4 million from $149.2 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":695,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C020I_PED.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"ped","task_type":"understanding","prediction":"Kyocera was up 60 at 5260.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":696,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C020O_PED.wav","answer":"the company declined to identify the bidders but said it received offers in the high forty dollars per share","subset":"ped","task_type":"understanding","prediction":"The company declined to identify the bidders. But said it received offers in the high $40 per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":697,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C020T_PED.wav","answer":"the market's strength may show that demand isn't all a creation of incentives","subset":"ped","task_type":"understanding","prediction":"The market strength may show that demand isn't all a creation of incentives.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":698,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C020V_PED.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"ped","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":699,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C020Y_PED.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday","subset":"ped","task_type":"understanding","prediction":"Volume was 18190000 shares, compared with 10550000 Wednesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":700,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C020Z_PED.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"ped","task_type":"understanding","prediction":"There were 256 issues advancing,303 declining and 292 unchanged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":701,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_444C0213_PED.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"ped","task_type":"understanding","prediction":"A change in the firms ownership also should turn on the bright warning light.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":702,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C0207_PED.wav","answer":"but the penalties for failure are real","subset":"ped","task_type":"understanding","prediction":"but the penalties for failure are real","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":703,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020D_PED.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"ped","task_type":"understanding","prediction":"Grand Auto slid 3 to 15 and 1,8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":704,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020E_PED.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"ped","task_type":"understanding","prediction":"The company, which runs retail automotive stores. Told shearson, Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":705,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020F_PED.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"ped","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":706,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020H_PED.wav","answer":"the suit seeks to block the contract which would have raised pay levels but cut benefits","subset":"ped","task_type":"understanding","prediction":"The suit seeks to block the contract. Which would have raised pay levels and cut benefits.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":707,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020K_PED.wav","answer":"but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close","subset":"ped","task_type":"understanding","prediction":"But to the surprise of almost everyone. Stock prices began a steady climb that pushed the average above Wednesday's close.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":708,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020L_PED.wav","answer":"although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading","subset":"ped","task_type":"understanding","prediction":"although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trade","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":709,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020P_PED.wav","answer":"about all the businessman can count on is that policy will be pretty volatile","subset":"ped","task_type":"understanding","prediction":"About all that businessmen can count on is that policy will be pretty volatile.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":710,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C020Z_PED.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"ped","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":711,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C0210_PED.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"ped","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":712,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_445C0211_PED.wav","answer":"a print media campaign will begin the following day","subset":"ped","task_type":"understanding","prediction":"a print media campaign will begin the following day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":713,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C0202_PED.wav","answer":"to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred","subset":"ped","task_type":"understanding","prediction":"To make them directly comparable, each index is based on the close of 1969, equaling 100.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":714,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C0203_PED.wav","answer":"the percentage change is since year end","subset":"ped","task_type":"understanding","prediction":"the percentage change is since year end","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":715,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C0205_PED.wav","answer":"no one at the state department wants to let spies in","subset":"ped","task_type":"understanding","prediction":"no one at the state department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":716,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C0206_PED.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"ped","task_type":"understanding","prediction":"we are not prepared to be advocates for the cagey","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":717,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C0207_PED.wav","answer":"that doesn't mean mr. icahn has committed any wrongdoing","subset":"ped","task_type":"understanding","prediction":"that does not mean mr icon has committed any wrongdoing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":718,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020A_PED.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"ped","task_type":"understanding","prediction":"separately new york state sold about seventy seven point one million dollars of certificates of participation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":719,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020B_PED.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"ped","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5 percent in 1987 to 5.5 percent in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":720,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020C_PED.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"ped","task_type":"understanding","prediction":"The unspent balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":721,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020P_PED.wav","answer":"it's still unclear","subset":"ped","task_type":"understanding","prediction":"it is still unclear","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":722,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020Q_PED.wav","answer":"there was a striking split between the sexes with men more likely than women to favor space programs","subset":"ped","task_type":"understanding","prediction":"There was a striking split between the sexes, with men more likely than women to favour space programs.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":723,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020T_PED.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"ped","task_type":"understanding","prediction":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u.s durable goods rose two point four percent last month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":724,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020U_PED.wav","answer":"that would follow a two point two percent drop in may","subset":"ped","task_type":"understanding","prediction":"that would follow a two point two percent drop in may","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":725,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020V_PED.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"ped","task_type":"understanding","prediction":"The May slump reported June 22 came as a big surprise to most analysts and helped trigger a powerful bond rally that day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":726,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020W_PED.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"ped","task_type":"understanding","prediction":"Durable goods reports frequently are highly volatile, from month to month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":727,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020X_PED.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"ped","task_type":"understanding","prediction":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":728,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C020Y_PED.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"ped","task_type":"understanding","prediction":"Estimates for the gain range from 2% to 3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":729,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C0211_PED.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"ped","task_type":"understanding","prediction":"after the offering republic new york will hold about forty nine percent of the affiliate","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":730,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_446C0213_PED.wav","answer":"it also owns three state business magazines in florida georgia and arizona","subset":"ped","task_type":"understanding","prediction":"It also owns three state business magazines in Florida, Georgia and Arizona.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":731,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C0204_PED.wav","answer":"mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent","subset":"ped","task_type":"understanding","prediction":"Mr. Robertson says he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":732,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C0207_PED.wav","answer":"washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own","subset":"ped","task_type":"understanding","prediction":"Washington National paid $19 a share for the 2.6 million United presidential shares it didn't already own.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":733,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C020C_PED.wav","answer":"sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days","subset":"ped","task_type":"understanding","prediction":"Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":734,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C020L_PED.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"ped","task_type":"understanding","prediction":"Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":735,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C020O_PED.wav","answer":"the company expects to report its results in about two weeks","subset":"ped","task_type":"understanding","prediction":"The company expects to report its results in about two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":736,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C020U_PED.wav","answer":"other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation","subset":"ped","task_type":"understanding","prediction":"Other analysts say the Fed needs to tighten policy further to support the dollar and spending growth.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":737,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C020W_PED.wav","answer":"the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape","subset":"ped","task_type":"understanding","prediction":"The share closed at $18.25, up 25 cents on the New York Stock Exchange composite tape.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":738,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C020X_PED.wav","answer":"salant shares closed unchanged on the big board at nine dollars and seventy five cents","subset":"ped","task_type":"understanding","prediction":"Salad shares closed unchanged on the big board at $9.75.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":739,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C0211_PED.wav","answer":"lately computer retailing has been tough on everybody","subset":"ped","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":740,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C0212_PED.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"ped","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's Investment Development Unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":741,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C0213_PED.wav","answer":"we had to sustain some modest operating losses","subset":"ped","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":742,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F05_447C0216_PED.wav","answer":"the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight","subset":"ped","task_type":"understanding","prediction":"The index ended with a decline of 0.35 point to 1272.18.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":743,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C0203_PED.wav","answer":"and half these managers are in the u. s.","subset":"ped","task_type":"understanding","prediction":"and half these managers are in the us","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":744,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C0207_PED.wav","answer":"the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks","subset":"ped","task_type":"understanding","prediction":"The agency isn't likely to take any action until the union's rank and file votes on the contract in 2 to three weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":745,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C020C_PED.wav","answer":"the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture","subset":"ped","task_type":"understanding","prediction":"The rise in that category in July was LED by increased orders for aircraft and parts, non electrical machinery, lumber and furniture.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":746,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C020D_PED.wav","answer":"interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction","subset":"ped","task_type":"understanding","prediction":"Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":747,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C020L_PED.wav","answer":"the investor now owns seventy three percent of the company","subset":"ped","task_type":"understanding","prediction":"the investor now owns seventy three percent of the company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":748,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C020M_PED.wav","answer":"texaco has three choices a company adviser says","subset":"ped","task_type":"understanding","prediction":"Texaco has three choices, economy adviser says.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":749,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C020S_PED.wav","answer":"what we don't know is how much is price and how much is volume","subset":"ped","task_type":"understanding","prediction":"What we don't know is how much is price and how much is volume.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":750,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_440C020Y_PED.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"ped","task_type":"understanding","prediction":"Estimates for the gain range from 2% to 3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":751,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C0201_PED.wav","answer":"first commodity appealed the expulsion and fine to the c. f. t. c.","subset":"ped","task_type":"understanding","prediction":"First, commodity appealed the expulsion and fine to the CFTC.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":752,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C0202_PED.wav","answer":"a commission spokesman said a decision on the appeal is expected soon","subset":"ped","task_type":"understanding","prediction":"A commission spokesman said a decision on the appeal is expected soon.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":753,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C0205_PED.wav","answer":"the language is a big problem","subset":"ped","task_type":"understanding","prediction":"the language is a big problem","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":754,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C0206_PED.wav","answer":"in europe an american can at least read street signs","subset":"ped","task_type":"understanding","prediction":"in europe an american can at least read street signs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":755,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C0208_PED.wav","answer":"the overall gain the fifth in the past seven months followed a revised four point one percent increase in february","subset":"ped","task_type":"understanding","prediction":"The overall gain this past 7 months followed a revised 4.1% increase in January.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":756,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020C_PED.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"ped","task_type":"understanding","prediction":"The company, which runs retail automotive strips. Told Shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":757,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020D_PED.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"ped","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":758,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020E_PED.wav","answer":"elders brewing will be based outside australia because seventy percent of its assets are in britain and canada","subset":"ped","task_type":"understanding","prediction":"Elders Brewing will be based outside Australia because 70 per cent of its assets are in Britain and Canada","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":759,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020H_PED.wav","answer":"two years ago b. a. f. f. made three separate acquisitions in the u. s.","subset":"ped","task_type":"understanding","prediction":"Two years ago, BASF made three separate acquisitions in the US.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":760,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020I_PED.wav","answer":"its biggest was the one billion dollar purchase of united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry","subset":"ped","task_type":"understanding","prediction":"Its biggest was the $1 billion purchase of United Technologies Corporation's Inmont subsidiary, a major supplier of paint to the auto industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":761,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020J_PED.wav","answer":"today ninety percent of the four billion dollars of b. a. f. f. sales in the u. s. is produced there","subset":"ped","task_type":"understanding","prediction":"today ninety percent of the four billion dollars of b a s f sales in the u s is produced there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":762,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020L_PED.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"ped","task_type":"understanding","prediction":"Those identified as beneficial owners hold at least 10% of the company's equity securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":763,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020P_PED.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"ped","task_type":"understanding","prediction":"If the dollar starts to plunge, the Fed may step up its defence of the currency.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":764,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020W_PED.wav","answer":"although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year","subset":"ped","task_type":"understanding","prediction":"Although closed, end funds have been around since at least the 1920s. They have boomed in popularity, this year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":765,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C020X_PED.wav","answer":"the bond funds in particular provide robust yields for investors and hefty fees for underwriters","subset":"ped","task_type":"understanding","prediction":"The bond funds, in particular, provide robust yields for the investors and hefty fees for underwriters.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":766,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C0210_PED.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"ped","task_type":"understanding","prediction":"After the offering, Republic, New York will hold about 49% of the affiliate.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":767,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_441C0213_PED.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"ped","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":768,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C0207_PED.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"ped","task_type":"understanding","prediction":"Grand Auto slid 3 to 15 and 1\/8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":769,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C0208_PED.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"ped","task_type":"understanding","prediction":"The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":770,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C0209_PED.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"ped","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":771,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C020B_PED.wav","answer":"shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said","subset":"ped","task_type":"understanding","prediction":"Shamrock's pretax profit on the sale was $125 million, a spokesman said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":772,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C020D_PED.wav","answer":"sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday","subset":"ped","task_type":"understanding","prediction":"Sony Corporation, for example, closed at ¥4950,$34.50 a share yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":773,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C020O_PED.wav","answer":"but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders","subset":"ped","task_type":"understanding","prediction":"But if the winning bids are as high as they were in some deals earlier this year, then we are not going to be winning bidders","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":774,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C020R_PED.wav","answer":"the company then accepts the shares tendered on the lowest price needed to reach its total then pays that amount for all shares it purchases","subset":"ped","task_type":"understanding","prediction":"The company then accepts the shares tendered on the lowest price needed to reach its total, then pays that amount for all shares it purchases.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":775,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C020S_PED.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"ped","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":776,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_442C0211_PED.wav","answer":"so normalcy has returned","subset":"ped","task_type":"understanding","prediction":"so normalcy has returned","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":777,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C0204_PED.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"ped","task_type":"understanding","prediction":"M, I, C, C Investments has three series of publicly traded preferred shares and three series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":778,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C0205_PED.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"ped","task_type":"understanding","prediction":"MICC said it intends to pay the dividend arrears on July 31 to stock of records, July 2.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":779,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C0206_PED.wav","answer":"the toronto based company provides mortgage guarantees to canadian real estate industries","subset":"ped","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to Canadian real estate industries.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":780,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C0209_PED.wav","answer":"nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics","subset":"ped","task_type":"understanding","prediction":"Nonetheless, the union has moved the experiment to Richmond, Virginia, and has received inquiries from other unions about its tactics.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":781,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C020C_PED.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"ped","task_type":"understanding","prediction":"Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":782,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C020I_PED.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"ped","task_type":"understanding","prediction":"Unless otherwise noted, changes involved direct holdings of common stock and took place in September and October 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":783,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C020N_PED.wav","answer":"the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains","subset":"ped","task_type":"understanding","prediction":"The official declined to elaborate on projections for Nontelephone operations, but cited several indicators of recent gains.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":784,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C020O_PED.wav","answer":"he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force","subset":"ped","task_type":"understanding","prediction":"He said the company has entered 16 smaller cellular markets this year and has expanded its financial services workforce.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":785,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C020V_PED.wav","answer":"in certain cases the cards are given free to subscribers","subset":"ped","task_type":"understanding","prediction":"in certain cases the cards are given free to subscribers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":786,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_443C0214_PED.wav","answer":"nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty","subset":"ped","task_type":"understanding","prediction":"Mitsubishi lost 30 to 1520, and Toyota was down 30 to end the day at 2620.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":787,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C0208_PED.wav","answer":"citicorp had twenty one point five billion dollars in capital at the end of last year","subset":"ped","task_type":"understanding","prediction":"Citicorp had $21.5 billion in capital at the end of last year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":788,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C0209_PED.wav","answer":"as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions","subset":"ped","task_type":"understanding","prediction":"As one of the most acquisition hungry of major banks, Citicorp is often required by regulators to raise additional capital as a condition of making acquisitions.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":789,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C020J_PED.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"ped","task_type":"understanding","prediction":"Sony, which lost points in previous sessions this week, rebounded 80 to 5130.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":790,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C020P_PED.wav","answer":"in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday","subset":"ped","task_type":"understanding","prediction":"In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":791,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C020R_PED.wav","answer":"the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year","subset":"ped","task_type":"understanding","prediction":"The mid July increase came even though automakers are offering incentives on fewer cars this year than they did last year or earlier this year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":792,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C020S_PED.wav","answer":"incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst","subset":"ped","task_type":"understanding","prediction":"Incentives can move around sales, but not create them, said Charles Brady, an Oppenheimer and Company auto stock analyst.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":793,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C020U_PED.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"ped","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":794,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C020W_PED.wav","answer":"a print media campaign will begin the following day","subset":"ped","task_type":"understanding","prediction":"A print media campaign will begin the following day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":795,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C020X_PED.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"ped","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 380.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":796,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C0212_PED.wav","answer":"realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars","subset":"ped","task_type":"understanding","prediction":"Realized capital gains increased 42% to $909 million from $640.9 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":797,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_444C0214_PED.wav","answer":"money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","subset":"ped","task_type":"understanding","prediction":"Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":798,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C0209_PED.wav","answer":"and both mortgaged their homes to secure the loans they needed to start the business","subset":"ped","task_type":"understanding","prediction":"And both mortgaged their homes to secure the loans they needed to start the business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":799,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C020A_PED.wav","answer":"a long list of other witnesses have also testified in the trial now in its fourth month","subset":"ped","task_type":"understanding","prediction":"A long list of other witnesses have also testified in the trial now in its fourth month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":800,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C020G_PED.wav","answer":"the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists","subset":"ped","task_type":"understanding","prediction":"The order issued late Wednesday by Judge Diana Murphy stems from a suit filed in federal court last month by the union representing machinists.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":801,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C020Q_PED.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"ped","task_type":"understanding","prediction":"If the dollar starts to plunge, the Fed may step up its defense of the currency.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":802,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C020R_PED.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"ped","task_type":"understanding","prediction":"If the Fed pushes the dollar higher. It may curb demand for US exports.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":803,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C020S_PED.wav","answer":"lately computer retailing has been tough on everybody","subset":"ped","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":804,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C020T_PED.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"ped","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":805,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C020W_PED.wav","answer":"the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed","subset":"ped","task_type":"understanding","prediction":"The jury awarded Mr. Sharonberg $105 million, a figure based on 10 years of profits. Had his project been completed.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":806,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_445C0216_PED.wav","answer":"where else in the third world is there so much energy and progress as in china","subset":"ped","task_type":"understanding","prediction":"Where else in the third world is there so much energy and progress as in China.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":807,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C0204_PED.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"ped","task_type":"understanding","prediction":"The consensus was the new piece of paper isn't required, said one US diplomat.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":808,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C020D_PED.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"ped","task_type":"understanding","prediction":"The issue is rated single A by Moody S and single A minus by S P.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":809,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C020F_PED.wav","answer":"under the proposed transaction the los angeles group would acquire the k. h. j. license and then sell itself to disney","subset":"ped","task_type":"understanding","prediction":"Under the proposed transaction, the Los Angeles group would acquire the KHJ licence and then sell itself to Disney.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":810,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C020G_PED.wav","answer":"the closely held group doesn't have any significant assets according to william g. simon its president","subset":"ped","task_type":"understanding","prediction":"The closely held group does not have any significant assets. According to William G. Simon, its president.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":811,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C020H_PED.wav","answer":"he said that for the full year wang is aiming for an after tax profit equal to three percent to five percent of sales","subset":"ped","task_type":"understanding","prediction":"He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":812,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C020Z_PED.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"ped","task_type":"understanding","prediction":"Republic, New York, rose one and one quarter to 4 to 5 and 78.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":813,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C0212_PED.wav","answer":"closely held times publishing also owns two washington based publications congressional quarterly which covers capitol hill and governing which covers state and local governments","subset":"ped","task_type":"understanding","prediction":"Closely held Times Publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and Governing, which covers state and local government.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":814,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_446C0214_PED.wav","answer":"industry analysts value the company at about six hundred fifty million dollars","subset":"ped","task_type":"understanding","prediction":"Industry analysts value the company at about $650 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":815,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C0203_PED.wav","answer":"i'm not sure what you have on your own list","subset":"ped","task_type":"understanding","prediction":"i am not sure what you have on your list","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":816,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020A_PED.wav","answer":"united presidential is a life insurance company","subset":"ped","task_type":"understanding","prediction":"united presidential is a life insurance company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":817,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020B_PED.wav","answer":"these are uneducated people he says in english so the patients won't understand","subset":"ped","task_type":"understanding","prediction":"These are uneducated people, he says, in English. So the patients won't understand.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":818,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020D_PED.wav","answer":"i will tell you what i think in my office","subset":"ped","task_type":"understanding","prediction":"i will tell you what i think in my office","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":819,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020F_PED.wav","answer":"they were sold to underwriters led by prudential bache securities incorporated","subset":"ped","task_type":"understanding","prediction":"They were sold to underwriters, LED by Prudential Bache Securities Incorporated.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":820,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020J_PED.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"ped","task_type":"understanding","prediction":"In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":821,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020K_PED.wav","answer":"that was certainly true last week","subset":"ped","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":822,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020P_PED.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"ped","task_type":"understanding","prediction":"The independent committee will recommend that holders accept the offer at a meeting expected to be held in December, T W Y said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":823,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020R_PED.wav","answer":"the investor now owns seventy three percent of the company","subset":"ped","task_type":"understanding","prediction":"the investor now owns seventy three percent of the company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":824,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C020V_PED.wav","answer":"manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid","subset":"ped","task_type":"understanding","prediction":"Manhattan Industries continued to trade above the offer price yesterday, indicating the market expects a higher bid.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":825,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/F06_447C0215_PED.wav","answer":"shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level","subset":"ped","task_type":"understanding","prediction":"shearson lehman huttons incorporateds index of longterm treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":826,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0202_PED.wav","answer":"the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years","subset":"ped","task_type":"understanding","prediction":"The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":827,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0204_PED.wav","answer":"r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.","subset":"ped","task_type":"understanding","prediction":"Rli Corporation, a Peoria, Illinois, based insurance holding company, will be trading Friday on the big board under the symbol RLI.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":828,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0209_PED.wav","answer":"a p. b. g. c. spokeswoman declined comment","subset":"ped","task_type":"understanding","prediction":"A P, BGC spokeswoman declined comment.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":829,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020E_PED.wav","answer":"the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last week","subset":"ped","task_type":"understanding","prediction":"The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at the previous auction last week.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":830,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020F_PED.wav","answer":"the average rate on new twenty six week bills rose to six point one six percent from six point one two percent","subset":"ped","task_type":"understanding","prediction":"The average rate on new 26 week bills rose to 6.16% from 6.12%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":831,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020G_PED.wav","answer":"analysts too generally played down the effect on banks","subset":"ped","task_type":"understanding","prediction":"analysts too generally played down the effect on banks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":832,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020H_PED.wav","answer":"in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks","subset":"ped","task_type":"understanding","prediction":"In a fundamental sense, the equity markets have very little to do with what goes on in the commercial banks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":833,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020I_PED.wav","answer":"there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company","subset":"ped","task_type":"understanding","prediction":"There shouldn't be any risk to the banks in this sort of stuff, said Lawrence Coe, a banking analyst at Merrill Lynch and Company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":834,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020K_PED.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"ped","task_type":"understanding","prediction":"The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":835,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020O_PED.wav","answer":"unable to agree on friday the board must meet again at least by phone to register its choice","subset":"ped","task_type":"understanding","prediction":"Unable to agree on Friday, the board must meet again, at least by phone, to register its choice.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":836,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020P_PED.wav","answer":"commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models","subset":"ped","task_type":"understanding","prediction":"Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories with new models.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":837,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020T_PED.wav","answer":"rates fell on short term treasury bills","subset":"ped","task_type":"understanding","prediction":"Rates fell on short term Treasury bills.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":838,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C020W_PED.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"ped","task_type":"understanding","prediction":"durable goods reports frequently are highly volatile from month to month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":839,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0210_PED.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"ped","task_type":"understanding","prediction":"Yesterday, Moody s Investors Service raised Lilco s credit rating in recognition of the improved outlook for steady financial recovery.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":840,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0211_PED.wav","answer":"about three point five billion dollars of securities are affected","subset":"ped","task_type":"understanding","prediction":"About $3.5 billion of securities are affected.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":841,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0212_PED.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"ped","task_type":"understanding","prediction":"He said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":842,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0213_PED.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"ped","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":843,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_440C0214_PED.wav","answer":"he declined to name specific products","subset":"ped","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":844,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C0207_PED.wav","answer":"in japan it's all greek so to speak","subset":"ped","task_type":"understanding","prediction":"in japan it is all greek so to speak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":845,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C020K_PED.wav","answer":"the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"ped","task_type":"understanding","prediction":"The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":846,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C020M_PED.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"ped","task_type":"understanding","prediction":"Unless otherwise noted changes involved direct holdings of common stock and took place in September and October of 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":847,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C020N_PED.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"ped","task_type":"understanding","prediction":"Companies are listed where transactions generally aggregate 10000 shares, or $100000.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":848,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C020O_PED.wav","answer":"about all the businessman can count on is that policy will be pretty volatile","subset":"ped","task_type":"understanding","prediction":"About all the businessmen can count on is that the policy will be volatile.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":849,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C020Q_PED.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"ped","task_type":"understanding","prediction":"If the Fed pushes the dollar higher. It may curb the demand for US exports.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":850,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C020T_PED.wav","answer":"has exposure really been reduced","subset":"ped","task_type":"understanding","prediction":"has exposure really been fixed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":851,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C0212_PED.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"ped","task_type":"understanding","prediction":"Volume was modest as 326.7 million shares changed hands, compared with 396.5 million Friday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":852,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_441C0214_PED.wav","answer":"he said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"ped","task_type":"understanding","prediction":"He said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":853,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C0201_PED.wav","answer":"bids totaling five hundred twenty five point five million dollars were submitted","subset":"ped","task_type":"understanding","prediction":"Bids totaling $525.5 million, were submitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":854,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C0205_PED.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"ped","task_type":"understanding","prediction":"MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":855,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C0206_PED.wav","answer":"the toronto based company provides mortgage guarantees to the canadian real estate industry","subset":"ped","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to the Canadian real estate industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":856,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020A_PED.wav","answer":"under terms previously reported the italian agricultural concern assumed about one hundred ninety five million dollars in subordinated debt as part of the transaction","subset":"ped","task_type":"understanding","prediction":"Under terms previously reported, the Italian agricultural concern assumed about $195 million in subordinated debt as part of the transaction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":857,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020H_PED.wav","answer":"we just received the suit and the document is massive it's two hundred pages","subset":"ped","task_type":"understanding","prediction":"we just received a suit and the document is massive its two hundred pages","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":858,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020I_PED.wav","answer":"but on the first read through the case is without merit and we intend to fight it","subset":"ped","task_type":"understanding","prediction":"But on first read through, the case is without merit. And we intend to fight it.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":859,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020J_PED.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"ped","task_type":"understanding","prediction":"According to the average estimate of 7 economists surveyed by Dow Jones, capital markets report new orders for US durable goods rose 2.4% last month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":860,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020L_PED.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"ped","task_type":"understanding","prediction":"The May slump reported June 22, came as a big surprise to most analysts and helped trigger a powerful bond rally that day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":861,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020N_PED.wav","answer":"we're going to be bidders said a top official of a major oil company","subset":"ped","task_type":"understanding","prediction":"We are going to be bidders, said a top official of a major oil company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":862,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020P_PED.wav","answer":"the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding","subset":"ped","task_type":"understanding","prediction":"The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26% of its shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":863,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C020W_PED.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"ped","task_type":"understanding","prediction":"Yesterday, Moody s Investors Service raised local credit rating in recognition of the improved outlook for steady financial recovery.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":864,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C0215_PED.wav","answer":"money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","subset":"ped","task_type":"understanding","prediction":"Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":865,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_442C0216_PED.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"ped","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":866,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_443C0202_PED.wav","answer":"the department previously said jobs rose by four hundred forty eight thousand in january","subset":"ped","task_type":"understanding","prediction":"The Department previously said jobs rose by 448000 in January.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":867,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_443C0203_PED.wav","answer":"using a measure that counts the military among the employed the rate was unchanged at six point six percent last month","subset":"ped","task_type":"understanding","prediction":"Using a measure that counts the military among the employed the rate was unchanged at 6.6% last month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":868,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_443C0207_PED.wav","answer":"it isn't clear yet whether the campaign works","subset":"ped","task_type":"understanding","prediction":"it isn t clear yet whether the campaign works","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":869,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_443C020D_PED.wav","answer":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty","subset":"ped","task_type":"understanding","prediction":"Among export LED electrical and computer makers. Japan Victor Company fell 50 to 2320.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":870,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_443C020X_PED.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday","subset":"ped","task_type":"understanding","prediction":"Volume was 18190000 shares, compared with 10550000 Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":871,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_443C0210_PED.wav","answer":"the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share","subset":"ped","task_type":"understanding","prediction":"The companies are followed by at least three analysts and had a minimum 5 cent change in actual earnings per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":872,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C0201_PED.wav","answer":"in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share","subset":"ped","task_type":"understanding","prediction":"In the 1985 quarter, the owner and operator of health maintenance organizations earned $6.9 million or 24 cents a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":873,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C0202_PED.wav","answer":"it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars","subset":"ped","task_type":"understanding","prediction":"It had forecast a 1986 fourth quarter loss of $18 million to $22 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":874,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C0205_PED.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"ped","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5 in 1987 to 5.5 in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":875,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C0206_PED.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"ped","task_type":"understanding","prediction":"The unsold balance late yesterday was about $36.3 million, according to Shearson Lehman Brothers, the lead underwriter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":876,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C020B_PED.wav","answer":"monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference","subset":"ped","task_type":"understanding","prediction":"mondays crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":877,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C020C_PED.wav","answer":"senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash","subset":"ped","task_type":"understanding","prediction":"senate finance chairman lloyd bentsen d texas said he would speed up work on the package because of the crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":878,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C020D_PED.wav","answer":"it adds to the support for the trade bill getting through he said","subset":"ped","task_type":"understanding","prediction":"It adds to the support for the trade bill getting through, he said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":879,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C020F_PED.wav","answer":"so far they have declined to comment publicly on their plans","subset":"ped","task_type":"understanding","prediction":"So far, they have declined to comment publicly on their plans.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":880,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C020G_PED.wav","answer":"state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do","subset":"ped","task_type":"understanding","prediction":"State officials, however, say the airlines have indicated they will comply with most of the standards as long as competitors do.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":881,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C020H_PED.wav","answer":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty","subset":"ped","task_type":"understanding","prediction":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred and twenty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":882,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C020K_PED.wav","answer":"lately computer retailing has been tough on everybody","subset":"ped","task_type":"understanding","prediction":"Lately, computer retailing has been tough on everybody.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":883,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_444C0210_PED.wav","answer":"the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent","subset":"ped","task_type":"understanding","prediction":"The institute said earned premiums rose 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":884,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C0206_PED.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"ped","task_type":"understanding","prediction":"were not prepared to be advocates for the kgb","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":885,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C0208_PED.wav","answer":"their business isn't just a job but their investment","subset":"ped","task_type":"understanding","prediction":"Their business isn't just a job, but their investment.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":886,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C020I_PED.wav","answer":"the airline imposed the contract without union bargaining","subset":"ped","task_type":"understanding","prediction":"The airline imposed the contract, without union bargaining.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":887,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C020J_PED.wav","answer":"yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling","subset":"ped","task_type":"understanding","prediction":"yesterday session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to ford and salomon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":888,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C020M_PED.wav","answer":"gillette is again a target of a major corporate raider","subset":"ped","task_type":"understanding","prediction":"Gillette is, again, a target of a major corporate raider.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":889,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C020O_PED.wav","answer":"a lengthy flight is likely","subset":"ped","task_type":"understanding","prediction":"a lengthy flight is like","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":890,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C020X_PED.wav","answer":"continental started the appeal process but recently settled the case","subset":"ped","task_type":"understanding","prediction":"continental started the appeal process but recently settled the case","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":891,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C020Y_PED.wav","answer":"neither side would disclose terms","subset":"ped","task_type":"understanding","prediction":"neither side would disclose terms","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":892,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_445C0213_PED.wav","answer":"from america china looks good","subset":"ped","task_type":"understanding","prediction":"from america china looks good","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":893,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_446C020E_PED.wav","answer":"fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments","subset":"ped","task_type":"understanding","prediction":"fidelity has contended that gencorp isn t a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and for that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":894,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_446C020I_PED.wav","answer":"he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year","subset":"ped","task_type":"understanding","prediction":"He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":895,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_446C020K_PED.wav","answer":"in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty","subset":"ped","task_type":"understanding","prediction":"In many ways, that is just what UBS has done since Mr. Santelli was named president in 1980.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":896,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_446C020L_PED.wav","answer":"assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven","subset":"ped","task_type":"understanding","prediction":"Assets more than doubled since then to 160.4 billion Swiss francs.115.6 billion dollars in 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":897,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_446C020N_PED.wav","answer":"the real estate investment trust said it was still hoping to reach a new credit arrangement","subset":"ped","task_type":"understanding","prediction":"The real estate investment trust said it was still hoping to reach a new credit arrangement.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":898,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_446C020S_PED.wav","answer":"among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women","subset":"ped","task_type":"understanding","prediction":"Among men,41% supported boosting space exploration budget compared to 19% of women.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":899,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C0201_PED.wav","answer":"i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month","subset":"ped","task_type":"understanding","prediction":"I don't mean there couldn't be some improvements in the Revenue Act of 1986, which took effect this month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":900,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C0206_PED.wav","answer":"he cites the law of large numbers can you really expect it to grow at large numbers very long","subset":"ped","task_type":"understanding","prediction":"he cites the law of large numbers can you really expect it to grow at large numbers very long","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":901,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C0209_PED.wav","answer":"washington national is a financial services concern","subset":"ped","task_type":"understanding","prediction":"Washington National is a financial services concern.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":902,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C020E_PED.wav","answer":"northgate exploration limited said it sold four million common shares at eight dollars each","subset":"ped","task_type":"understanding","prediction":"Northgate Exploration Limited said it sold 4 million common shares at $8 each.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":903,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C020H_PED.wav","answer":"the toronto based gold mining concern said proceeds would be used for general purposes","subset":"ped","task_type":"understanding","prediction":"The Toronto based gold mining concern said proceeds would be used for general purposes.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":904,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C020M_PED.wav","answer":"envirodyne said it expects sales to be the highest for any third quarter in the company's history","subset":"ped","task_type":"understanding","prediction":"Envirodime said it expects sales to be the highest for any third quarter in the company's history.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":905,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C020S_PED.wav","answer":"but while the fed stands pat it is coming under increasing attack from both sides","subset":"ped","task_type":"understanding","prediction":"but while the fed stands pat it is coming under increasing attack from both sides","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":906,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C020T_PED.wav","answer":"some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year","subset":"ped","task_type":"understanding","prediction":"Some critics including high Reagan administration officials are raising the alarm that the Feds policy is too tight and could cause a recession next year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":907,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C020Y_PED.wav","answer":"increasingly people who test positive join the support groups that have sprung up across the country in the past year","subset":"ped","task_type":"understanding","prediction":"Increasingly people who test positive join the support groups that have sprung up across the country in the past year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":908,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M05_447C0210_PED.wav","answer":"founded last october new york's body positive already has sixteen groups meeting every two weeks","subset":"ped","task_type":"understanding","prediction":"Founded last October, New Yorks body positive already has 16 groups meeting every two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":909,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C0206_PED.wav","answer":"two other issues began trading recently on the big board","subset":"ped","task_type":"understanding","prediction":"Two other issues began trading recently, on the big board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":910,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C0208_PED.wav","answer":"union officials expect ratification","subset":"ped","task_type":"understanding","prediction":"union officials expect ratification","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":911,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C020A_PED.wav","answer":"despite the july decline durable goods orders remained seven point seven percent above the year earlier level","subset":"ped","task_type":"understanding","prediction":"Despite the July decline, durable goods orders remained 7.7% above the year earlier level.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":912,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C020B_PED.wav","answer":"economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment","subset":"ped","task_type":"understanding","prediction":"Economists were encouraged by a 1.6% increase in new orders for nondefense capital goods, an important indicator of future business investing.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":913,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C020J_PED.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"ped","task_type":"understanding","prediction":"The independent committee will recommend that holders accept the offer at a meeting expected to be held in December 2007.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":914,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C020Q_PED.wav","answer":"the rise in auto imports also reflects higher prices for imported cars","subset":"ped","task_type":"understanding","prediction":"The rise in auto imports must reflect higher prices for imported cars","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":915,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C020R_PED.wav","answer":"prices are going up said george c. eads vice president and chief economist at general motors corporation","subset":"ped","task_type":"understanding","prediction":"Prices are going up, said George C. Yads, vice president and chief economist at General Motors Corporation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":916,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C020X_PED.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"ped","task_type":"understanding","prediction":"Many analysts cite an expected increase in aircraft orders as a big reason for the notes pending June increase.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":917,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_440C020Z_PED.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"ped","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":918,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C0203_PED.wav","answer":"first commodity officials couldn't be reached for comment","subset":"ped","task_type":"understanding","prediction":"First commodity officials couldn be reached for comment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":919,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C0204_PED.wav","answer":"and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort","subset":"ped","task_type":"understanding","prediction":"And then there is the explanation of why Terradyns growth in Japan is slow, despite 15 years of effort.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":920,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C020B_PED.wav","answer":"grand auto slid three to fifteen and one eighth in the american stock exchange","subset":"ped","task_type":"understanding","prediction":"Grand author, Slade 3 to 15 and 1,8 in the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":921,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C020G_PED.wav","answer":"elders finance and elders agribusiness will remain based in australia","subset":"ped","task_type":"understanding","prediction":"Elders finance and elders agribusiness will remain based in Australia.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":922,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C020R_PED.wav","answer":"too much focus is placed on reduction of cross country loans mr. meyerman said","subset":"ped","task_type":"understanding","prediction":"Too much focus is placed on reduction of cross country loans, Mr. Meyer said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":923,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C020U_PED.wav","answer":"our guess is no","subset":"ped","task_type":"understanding","prediction":"our guess is no","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":924,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C020Y_PED.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"ped","task_type":"understanding","prediction":"Republic near rose 1 and one quarter to 45, and 7\/8.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":925,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C020Z_PED.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"ped","task_type":"understanding","prediction":"The company said its European Banking affiliate. Saffron Republic plans to raise more than $450 million through an international offering.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":926,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C0211_PED.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"ped","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":927,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C0215_PED.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"ped","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":928,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_441C0216_PED.wav","answer":"he declined to name specific products","subset":"ped","task_type":"understanding","prediction":"He declined to name specific clients.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":929,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C0202_PED.wav","answer":"accepted bids ranged from six point two percent to six point two two five percent","subset":"ped","task_type":"understanding","prediction":"Accepted bids ranged from 6.2% to 6.225%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":930,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C0204_PED.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"ped","task_type":"understanding","prediction":"MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":931,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C020E_PED.wav","answer":"under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents","subset":"ped","task_type":"understanding","prediction":"Under Tokyo trading rules, the maximum one day drop for Sony is ¥500 about $3.50.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":932,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C020M_PED.wav","answer":"even some bigger companies caution that they are leery of paying too big a premium","subset":"ped","task_type":"understanding","prediction":"Even some bigger companies caution that they are leery of paying too big a premium.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":933,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C020Q_PED.wav","answer":"in a dutch auction holders tender their shares at prices within the stated range in this case between twenty eight dollars and thirty three dollars a share","subset":"ped","task_type":"understanding","prediction":"In a Dutch auction, holders tender their shares at prices within the stated range. In this case, between $28 and $33 a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":934,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C020V_PED.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"ped","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":935,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C020X_PED.wav","answer":"about three point five billion dollars of securities are affected","subset":"ped","task_type":"understanding","prediction":"About $3.5 billion in securities are affected.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":936,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C020Y_PED.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"ped","task_type":"understanding","prediction":"He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":937,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C0212_PED.wav","answer":"foreigners are back and negotiating with the chinese will be as tough as ever","subset":"ped","task_type":"understanding","prediction":"Foreigners are back and negotiating with the Chinese will be as tough as ever.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":938,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C0213_PED.wav","answer":"that's fine","subset":"ped","task_type":"understanding","prediction":"that is fine","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":939,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_442C0214_PED.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"ped","task_type":"understanding","prediction":"A change in the firms ownership also should turn on a light bulb.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":940,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020A_PED.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"ped","task_type":"understanding","prediction":"And in the effort to restore market confidence, administration officials have emphasized that the economy's fundamentals remain sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":941,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020B_PED.wav","answer":"that was certainly true last week","subset":"ped","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":942,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020E_PED.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"ped","task_type":"understanding","prediction":"Your Sarah was at 60,5260.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":943,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020F_PED.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"ped","task_type":"understanding","prediction":"Sony, which lost points in the previous session this week, rebounded 80 to 5130.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":944,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020G_PED.wav","answer":"the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"ped","task_type":"understanding","prediction":"Filing officers, directors and large stakeholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":945,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020Q_PED.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"ped","task_type":"understanding","prediction":"Mci plans to begin offering the service at the end of the month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":946,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020S_PED.wav","answer":"a print media campaign will begin the following day","subset":"ped","task_type":"understanding","prediction":"A print media campaign will begin following that.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":947,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020T_PED.wav","answer":"visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards","subset":"ped","task_type":"understanding","prediction":"Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":948,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020W_PED.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"ped","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 380.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":949,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_443C020Y_PED.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"ped","task_type":"understanding","prediction":"There were 256 issues advancing,303 declining and 292 unchanged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":950,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C0204_PED.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"ped","task_type":"understanding","prediction":"Separately, the estate sold about $77.1 million in certificates of participation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":951,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C0207_PED.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"ped","task_type":"understanding","prediction":"The issue is rated single A by Moody S and single A minus by S and P.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":952,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C020A_PED.wav","answer":"in addition banks in general are being pushed by regulators to boost their capital positions","subset":"ped","task_type":"understanding","prediction":"In addition, banks in general are being pushed by regulators to boost their capital positions","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":953,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C020E_PED.wav","answer":"several airlines have also opposed the standards and may fight some aspects in court","subset":"ped","task_type":"understanding","prediction":"several airlines have also opposed the standards and may fight some aspects in court","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":954,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C020L_PED.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"ped","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic Investment Development.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":955,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C020M_PED.wav","answer":"we had to sustain some modest operating losses","subset":"ped","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":956,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C020N_PED.wav","answer":"we didn't like that","subset":"ped","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":957,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C020Q_PED.wav","answer":"the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding","subset":"ped","task_type":"understanding","prediction":"The offers indicate a total price for the company exceeding $800 million based on 17.2 million shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":958,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C0211_PED.wav","answer":"however investment income which represents thirteen percent of the industry's revenues rose eleven percent in the quarter reflecting gains from the rising stock market","subset":"ped","task_type":"understanding","prediction":"However, investment income, which represents 13% of the industry s revenues. Grows 11% in the quarter, reflecting gains from the rise in stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":959,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_444C0215_PED.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"ped","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":960,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0201_PED.wav","answer":"owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged","subset":"ped","task_type":"understanding","prediction":"Owens and Minor said its share purchases would be financed by existing credit lines and new ones to be arranged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":961,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0202_PED.wav","answer":"if all twenty million shares were purchased the company's equity would be reduced by about one third","subset":"ped","task_type":"understanding","prediction":"If all 20 million shares are purchased the companys equity would be reduced by about one third","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":962,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0203_PED.wav","answer":"a spokesman said the company has about sixty million shares outstanding","subset":"ped","task_type":"understanding","prediction":"A spokesman said the company has about 60 million shares outstanding","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":963,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0204_PED.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"ped","task_type":"understanding","prediction":"The consensus was that a new piece of paper isn't required, said one US diplomat.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":964,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0205_PED.wav","answer":"no one at the state department wants to let spies in","subset":"ped","task_type":"understanding","prediction":"no one at the state department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":965,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C020B_PED.wav","answer":"but it is mr. west upon whom the outcome probably depends most","subset":"ped","task_type":"understanding","prediction":"But it is Mr. West, upon whom the outcome probably depends most.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":966,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C020C_PED.wav","answer":"testimony concluded this week and closing arguments are scheduled to begin monday","subset":"ped","task_type":"understanding","prediction":"Testimony concluded this week, and closing arguments are scheduled for Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":967,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C020N_PED.wav","answer":"coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board","subset":"ped","task_type":"understanding","prediction":"Coniston Partners of New York said it has a 6.8 cent stake in Gillette and may seek to acquire the company or gain seats on its board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":968,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C020U_PED.wav","answer":"we had to sustain some modest operating losses","subset":"ped","task_type":"understanding","prediction":"We had to sustain some modest operating losses.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":969,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C020V_PED.wav","answer":"we didn't like that","subset":"ped","task_type":"understanding","prediction":"we didn like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":970,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0212_PED.wav","answer":"the real change though is in how china looks","subset":"ped","task_type":"understanding","prediction":"The real change, though, is in how China looks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":971,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0214_PED.wav","answer":"the numbers looked amazingly good industrial growth rates above ten percent per year year after year","subset":"ped","task_type":"understanding","prediction":"The numbers looked amazingly good. Industrial growth rates above 10% per year, year after year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":972,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_445C0215_PED.wav","answer":"and after a temporary downturn in the next couple of years the numbers probably will go back up","subset":"ped","task_type":"understanding","prediction":"and after a temporary downturn in the next couple of years the numbers probably will go back up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":973,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C0201_PED.wav","answer":"here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva","subset":"ped","task_type":"understanding","prediction":"Here are price trends on the worlds major stock markets as calculated by Morgan Stanley Capital International in Geneva.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":974,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C0208_PED.wav","answer":"but the investigation could make some lenders wary","subset":"ped","task_type":"understanding","prediction":"But the investigation could make some lenders wary","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":975,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C0209_PED.wav","answer":"mr. icahn an investor group he heads hold seventy two point seven percent of t. w. a.'s shares","subset":"ped","task_type":"understanding","prediction":"Mr. Hekman and an investor group he heads hold 72.7 of T W A shares.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":976,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C020J_PED.wav","answer":"in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars","subset":"ped","task_type":"understanding","prediction":"In fiscal 1987, Wang had a loss of $70.7 million on revenue of 2.8 billion dollars.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":977,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C020M_PED.wav","answer":"net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in the period","subset":"ped","task_type":"understanding","prediction":"Net income rose 125% to 753 million Swiss francs in the period.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":978,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C020O_PED.wav","answer":"we're not ready to say we're in technical default a spokesman said","subset":"ped","task_type":"understanding","prediction":"We are not ready to say we are in technical default a spokesman said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":979,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C020R_PED.wav","answer":"among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agree","subset":"ped","task_type":"understanding","prediction":"among men 26 percent said the US was doing too little in space exploration only a quarter of women agreed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":980,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_446C0210_PED.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"ped","task_type":"understanding","prediction":"The company said its European Bank affiliate. Sapporo Public plans to raise more than $450 million through an international offering.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":981,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C0202_PED.wav","answer":"i have my list of changes i'd like to see","subset":"ped","task_type":"understanding","prediction":"i have my list of changes i d like to see","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":982,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C0205_PED.wav","answer":"he doesn't","subset":"ped","task_type":"understanding","prediction":"he doesn","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":983,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C0208_PED.wav","answer":"before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company","subset":"ped","task_type":"understanding","prediction":"Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":984,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C020G_PED.wav","answer":"the underwriting group has a thirty day option to acquire an additional six hundred thousand shares at eight dollars each","subset":"ped","task_type":"understanding","prediction":"The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":985,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C020I_PED.wav","answer":"it had fourteen point five million common shares outstanding before the issue","subset":"ped","task_type":"understanding","prediction":"It had 14.5 million common shares, outstanding before the issue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":986,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C020N_PED.wav","answer":"it had sales of nineteen one point five million dollars in the nineteen eighty six third quarter","subset":"ped","task_type":"understanding","prediction":"It had sales of the 19$1.5 million in the 1986 third quarter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":987,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C020Q_PED.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"ped","task_type":"understanding","prediction":"The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Kong.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":988,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C020Z_PED.wav","answer":"several cities have versions of the british organization body positive","subset":"ped","task_type":"understanding","prediction":"several cities have versions of the british organization body positive","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":989,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C0214_PED.wav","answer":"we didn't like that","subset":"ped","task_type":"understanding","prediction":"we didnt like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":990,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_ped_real\/M06_447C0217_PED.wav","answer":"the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight","subset":"ped","task_type":"understanding","prediction":"The low was 1270.19, and the high was 1273.88.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":991,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_440C0206_STR.wav","answer":"two other issues began trading recently on the big board","subset":"str","task_type":"understanding","prediction":"Two other issues began trading recently, on the big board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":992,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_440C0208_STR.wav","answer":"union officials expect ratification","subset":"str","task_type":"understanding","prediction":"union officials expect ratification","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":993,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_440C020A_STR.wav","answer":"despite the july decline durable goods orders remained seven point seven percent above the year earlier level","subset":"str","task_type":"understanding","prediction":"Despite the July decline, durable goods orders remain 7.7% above the year earlier level.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":994,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_440C020B_STR.wav","answer":"economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment","subset":"str","task_type":"understanding","prediction":"economists were encouraged by a one point six percent increase in new orders for non defense capital goods an important indicator of future business investment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":995,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_440C020Q_STR.wav","answer":"the rise in auto imports also reflects higher prices for imported cars","subset":"str","task_type":"understanding","prediction":"The rise in auto imports also reflects higher prices for imported cars.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":996,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_440C020R_STR.wav","answer":"prices are going up said george c. eads vice president and chief economist at general motors corporation","subset":"str","task_type":"understanding","prediction":"Prices are going up, said George C. Eads, vice president and chief economist at General Motors Corporation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":997,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_440C020Z_STR.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"str","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":998,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_441C0203_STR.wav","answer":"first commodity officials couldn't be reached for comment","subset":"str","task_type":"understanding","prediction":"First commodity officials couldn't be reached for comment.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":999,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_441C0204_STR.wav","answer":"and then there's the explanation of why teradyne's growth in japan is slow despite fifteen years of effort","subset":"str","task_type":"understanding","prediction":"And then there is the explanation of why Teradaya s growth in Japan is slow, despite 15 years of effort.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1000,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_441C020G_STR.wav","answer":"elders finance and elders agribusiness will remain based in australia","subset":"str","task_type":"understanding","prediction":"Elders finance and elders agribusiness will remain based in Australia.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1001,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_441C020R_STR.wav","answer":"too much focus is placed on reduction of cross country loans mr. meyerman said","subset":"str","task_type":"understanding","prediction":"Too much focus is placed on reduction of cross country loans, Mr. Meyer said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1002,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_441C020U_STR.wav","answer":"our guess is no","subset":"str","task_type":"understanding","prediction":"our guess is no","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1003,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_441C020Z_STR.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"str","task_type":"understanding","prediction":"The company said its European Banking affiliate. Safra Republic plans to raise more than $450 million through an international offering.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1004,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C0202_STR.wav","answer":"accepted bids ranged from six point two percent to six point two two five percent","subset":"str","task_type":"understanding","prediction":"Accepted bids ranged from 6.2% to 6.225%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1005,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020E_STR.wav","answer":"under tokyo trading rules the maximum one day drop for sony is five hundred yen about three dollars and fifty cents","subset":"str","task_type":"understanding","prediction":"Under Tokyo trading rules, the maximum one day drop for Sony is ¥500 about $3.50.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1006,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020M_STR.wav","answer":"even some bigger companies caution that they are leery of paying too big a premium","subset":"str","task_type":"understanding","prediction":"Even some bigger companies cautioned that they are leery of paying too big a premium.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1007,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020Q_STR.wav","answer":"in a dutch auction holders tender their shares at prices within a stated range in this case between twenty eight dollars and thirty three dollars a share","subset":"str","task_type":"understanding","prediction":"In a Dutch auction, holders tender their shares at prices within a stated range. In this case, between $28 and $33 a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1008,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020S_STR.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"str","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1009,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020V_STR.wav","answer":"utility analysts however expect the agreement to be completed without much difficulty","subset":"str","task_type":"understanding","prediction":"Utility analysts, however, expect the agreement to be completed without much difficulty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1010,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020X_STR.wav","answer":"about three point five billion dollars of securities are affected","subset":"str","task_type":"understanding","prediction":"About $3.5 billion of securities are affected.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1011,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020Y_STR.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"str","task_type":"understanding","prediction":"He also said the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1012,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C020Z_STR.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"str","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1013,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C0210_STR.wav","answer":"he declined to name specific products","subset":"str","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1014,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C0212_STR.wav","answer":"foreigners are back and negotiating with the chinese will be as tough as ever","subset":"str","task_type":"understanding","prediction":"foreigners are back and negotiating with the chinese will be as tough as ever","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1015,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_442C0213_STR.wav","answer":"that's fine","subset":"str","task_type":"understanding","prediction":"thats fine","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1016,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_443C0204_STR.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"str","task_type":"understanding","prediction":"MICC investments has three series of publicly traded preferred shares and 10 series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1017,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_443C020G_STR.wav","answer":"the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"str","task_type":"understanding","prediction":"The following officers, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1018,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_443C020T_STR.wav","answer":"visa and mastercard fees vary because they are set by the banks or other institutions that issue the cards","subset":"str","task_type":"understanding","prediction":"Visa and Mastercard fees vary because they are set by the banks or other institutions that issue the cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1019,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020A_STR.wav","answer":"in addition banks in general are being pushed by regulators to boost their capital positions","subset":"str","task_type":"understanding","prediction":"In addition, banks in general are being pushed by regulators to boost their capital positions.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1020,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020E_STR.wav","answer":"several airlines have also opposed the standards and may fight some aspects in court","subset":"str","task_type":"understanding","prediction":"several airlines have also opposed the standards and may fight some aspects in court","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1021,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020I_STR.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"str","task_type":"understanding","prediction":"Kyocera was up 60 at 5260.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1022,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020J_STR.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"str","task_type":"understanding","prediction":"Sony, which lost points in previous sessions this week, rebounded 80 to 5130.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1023,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020N_STR.wav","answer":"we didn't like that","subset":"str","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1024,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020Q_STR.wav","answer":"the offers indicate a total price for the company exceeding eight hundred million dollars based on seventeen point two million shares outstanding","subset":"str","task_type":"understanding","prediction":"The offers indicated total price for the company exceeding $800 million based on 17.2 million shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1025,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020X_STR.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"str","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 380.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1026,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C020Z_STR.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"str","task_type":"understanding","prediction":"There were 256 issues advancing,303 declining, and 292 unchanged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1027,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C0211_STR.wav","answer":"however investment income which represents thirteen percent of the industry's revenues rose eleven percent in the quarter reflecting gains from the rising stock market","subset":"str","task_type":"understanding","prediction":"however investment income which represents thirteen percent of the industry s revenues rose eleven percent in the quarter reflecting gains from the rising stock market","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1028,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C0213_STR.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"str","task_type":"understanding","prediction":"A change in the firms ownership also should turn on a bright warning light.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1029,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_444C0215_STR.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"str","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1030,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C0201_STR.wav","answer":"owens illinois said its share purchases would be financed by existing credit lines and new ones to be arranged","subset":"str","task_type":"understanding","prediction":"Owens Illinois said its share purchases would be financed by existing credit lines and new ones to be arranged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1031,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C0202_STR.wav","answer":"if all twenty million shares were purchased the company's equity would be reduced by about one third","subset":"str","task_type":"understanding","prediction":"If all 20 million shares were purchased. The company's equity would be reduced by about one third.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1032,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C0203_STR.wav","answer":"a spokesman said the company has about sixty million shares outstanding","subset":"str","task_type":"understanding","prediction":"A spokesman said the company has about 60 million shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1033,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C020B_STR.wav","answer":"but it is mr. west upon whom the outcome probably depends most","subset":"str","task_type":"understanding","prediction":"but it is mr west upon whom the outcome probably depends most","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1034,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C020C_STR.wav","answer":"testimony concluded this week and closing arguments are scheduled to begin monday","subset":"str","task_type":"understanding","prediction":"Testimony concluded this week, and closing arguments are scheduled to begin Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1035,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C020D_STR.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"str","task_type":"understanding","prediction":"Grand Auto slid 3 to 15 and 1.8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1036,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C020N_STR.wav","answer":"coniston partners of new york said it has a six point eight percent stake in gillette and may seek to acquire the company or gain seats on its board","subset":"str","task_type":"understanding","prediction":"Coniston Partners of New York said it has a 6.8% stake in Gillette and may seek to acquire the company or gain seats on its board.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1037,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C020U_STR.wav","answer":"we had to sustain some modest operating losses","subset":"str","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1038,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C020V_STR.wav","answer":"we didn't like that","subset":"str","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1039,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C020Z_STR.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"str","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1040,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C0211_STR.wav","answer":"a print media campaign will begin the following day","subset":"str","task_type":"understanding","prediction":"a print media campaign will begin the following day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1041,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C0212_STR.wav","answer":"the real change though is in how china looks","subset":"str","task_type":"understanding","prediction":"the real change though is in how china looks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1042,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C0214_STR.wav","answer":"the numbers looked amazingly good industrial growth rates above ten percent per year year after year","subset":"str","task_type":"understanding","prediction":"The numbers looked amazingly good. Industrial growth rates above 10% per year, year after year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1043,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_445C0215_STR.wav","answer":"and after a temporary downturn in the next couple of years the numbers 'll probably go back up","subset":"str","task_type":"understanding","prediction":"And after a temporary downturn in the next couple of years. The numbers will probably go back up.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1044,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C0201_STR.wav","answer":"here are price trends on the world's major stock markets as calculated by morgan stanley capital international perspective geneva","subset":"str","task_type":"understanding","prediction":"Here are price trends on the world's major stock markets, as calculated by Morgan Stanley, Capital International Perspective, Geneva.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1045,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C0204_STR.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"str","task_type":"understanding","prediction":"The consensus was that a new piece of paper isn't required, said one US diplomat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1046,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C0205_STR.wav","answer":"no one at the state department wants to let spies in","subset":"str","task_type":"understanding","prediction":"no one at the state department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1047,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C0208_STR.wav","answer":"but the investigation could make some lenders wary","subset":"str","task_type":"understanding","prediction":"but the investigation could make some lenders wary","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1048,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C0209_STR.wav","answer":"mr. icahn and an investor group he heads hold seventy two point seven percent of t. w. a.'s shares","subset":"str","task_type":"understanding","prediction":"Mr. Icahn and an investor group he heads hold 72.7% of T. W A shares.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1049,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020A_STR.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"str","task_type":"understanding","prediction":"separately new york state sold about seventy seven point one million dollars of certificates of participation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1050,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020D_STR.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"str","task_type":"understanding","prediction":"The issue is rated single A by Moody S and single A minus by S and P.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1051,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020J_STR.wav","answer":"in fiscal nineteen eighty seven wang had a loss of seventy point seven million dollars on revenue of two point eight four billion dollars","subset":"str","task_type":"understanding","prediction":"In fiscal 1987, Wang had a loss of $70.7 million on revenue of $2.84 billion.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1052,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020M_STR.wav","answer":"net income rose one hundred twenty five percent to seven hundred fifty three million swiss francs in that period","subset":"str","task_type":"understanding","prediction":"Net income rose 125% to 753 million Swiss francs in that period.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1053,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020O_STR.wav","answer":"we're not ready to say we're in technical default a spokesman says","subset":"str","task_type":"understanding","prediction":"we are not ready to say we are in technical default a spokesman said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1054,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020R_STR.wav","answer":"among men fifty six percent said the u. s. was doing too little in space exploration only a quarter of women agreed","subset":"str","task_type":"understanding","prediction":"among men fifty six percent said the us was doing too little in space exploration only a quarter of women agreed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1055,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020X_STR.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"str","task_type":"understanding","prediction":"Many analysts cite an expected increase in aircraft orders as a big reason for the anticipated June increase.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1056,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C020Z_STR.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"str","task_type":"understanding","prediction":"Republic, New York, rose one and one quarter to 45 and 7\/8.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1057,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_446C0210_STR.wav","answer":"the company said its european banking affiliate safra republic plans to raise more than four hundred fifty million dollars through an international offering","subset":"str","task_type":"understanding","prediction":"The company said its European Banking affiliate. Safra Republic plans to raise more than $450 million through an international offering.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1058,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C0202_STR.wav","answer":"i have my list of changes i'd like to see","subset":"str","task_type":"understanding","prediction":"i have my list of changes i d like to see","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1059,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C0205_STR.wav","answer":"he doesn't","subset":"str","task_type":"understanding","prediction":"he doesn t","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1060,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C0208_STR.wav","answer":"before the transaction washington national controlled one point eight million united presidential shares or forty one point five percent of the company","subset":"str","task_type":"understanding","prediction":"Before the transaction, Washington National controlled 1.8 million United presidential shares or 41.5% of the company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1061,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020G_STR.wav","answer":"the underwriting group has a thirty day option to acquire an additional six hundred thousand shares at eight dollars each","subset":"str","task_type":"understanding","prediction":"The underwriting group has a 30 day option to acquire an additional 600000 shares at $8 each.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1062,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020I_STR.wav","answer":"it had fourteen point five million common shares outstanding before the issue","subset":"str","task_type":"understanding","prediction":"It had 14.5 million common shares, outstanding before the issue.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1063,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020J_STR.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"str","task_type":"understanding","prediction":"In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1064,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020K_STR.wav","answer":"that was certainly true last week","subset":"str","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1065,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020N_STR.wav","answer":"it had sales of ninety one point five million dollars in the nineteen eighty six third quarter","subset":"str","task_type":"understanding","prediction":"It had sales of $91.5 million in the 1986 third quarter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1066,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020P_STR.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"str","task_type":"understanding","prediction":"The independent committee will recommend that holders accept the offer at a meeting expected to be held in December. Twa said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1067,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020Q_STR.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"str","task_type":"understanding","prediction":"The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1068,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C020Z_STR.wav","answer":"several cities have versions of the british organization body positive","subset":"str","task_type":"understanding","prediction":"Several cities have versions of the British Organisation, Body Positive.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1069,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C0212_STR.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"str","task_type":"understanding","prediction":"no one is making very much money on it acknowledges brian j kelly chairman of bell atlantic s investment development unit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1070,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C0213_STR.wav","answer":"we had to sustain some modest operating losses","subset":"str","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1071,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C0214_STR.wav","answer":"we didn't like that","subset":"str","task_type":"understanding","prediction":"we didn t like that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1072,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F05_447C0217_STR.wav","answer":"the low was one thousand two hundred seventy point one nine and the high was one thousand two hundred seventy three point eight eight","subset":"str","task_type":"understanding","prediction":"The low was 1270.19, and the high was 1273.88.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1073,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C0202_STR.wav","answer":"the company has five hundred japanese managers overseas most of them in key positions and expects the number to rise sixty percent in the next five years","subset":"str","task_type":"understanding","prediction":"The company has 500 Japanese managers overseas. Most of them in key positions and expects the number to rise 60% in the next five years.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1074,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C0204_STR.wav","answer":"r. l. i. corporation a peoria illinois based insurance holding company will begin trading friday on the big board under the symbol r. l. i.","subset":"str","task_type":"understanding","prediction":"Rli Corporation, a Peoria, Illinois, based insurance holding company, will begin trading Friday on the big board under the symbol Rli.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1075,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C0209_STR.wav","answer":"a p. b. g. c. spokeswoman declined comment","subset":"str","task_type":"understanding","prediction":"a p b g c spokeswoman declined to comment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1076,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020E_STR.wav","answer":"the average rate on new thirteen week treasury bills increased to six point one two percent from five point nine seven percent at the previous auction last year","subset":"str","task_type":"understanding","prediction":"The average rate on new 13 week Treasury bills increased to 6.12% from 5.97% at previous auction last year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1077,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020F_STR.wav","answer":"the average rate on new twenty six week bills rose to six point one six percent from six point one two percent","subset":"str","task_type":"understanding","prediction":"The average rate on new 26 week bills rose to 6.16% from 6.12%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1078,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020G_STR.wav","answer":"analysts too generally played down the effect on banks","subset":"str","task_type":"understanding","prediction":"Analysts, too, generally played down the effect on banks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1079,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020H_STR.wav","answer":"in a fundamental sense the equity markets have very little to do with what goes on in the commercial banks","subset":"str","task_type":"understanding","prediction":"In a fundamental sense, the equity markets have very little to do with what goes on in the commercial banks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1080,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020I_STR.wav","answer":"there shouldn't be any risk to the banks in this sort of stuff said lawrence cohn a banking analyst at merrill lynch and company","subset":"str","task_type":"understanding","prediction":"There shouldn't be any risk to the banks of this sort of stuff, said Lawrence Call, a banking analyst at Merrill Lynch and Company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1081,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020K_STR.wav","answer":"the transaction requires approval of a majority of the shares of the holders not affiliated with mr. icahn","subset":"str","task_type":"understanding","prediction":"The transaction requires approval of a majority of the shares of the holders, not affiliated with Mr. Icahn.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1082,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020O_STR.wav","answer":"unable to agree on friday the board must meet again at least by phone to register its choice","subset":"str","task_type":"understanding","prediction":"Unable to agree on Friday, the board must meet again, at least by phone, to register its choice.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1083,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020P_STR.wav","answer":"commerce department officials noted however that auto imports usually rise in october as dealers fill their inventories with new models","subset":"str","task_type":"understanding","prediction":"Commerce Department officials noted, however, that auto imports usually rise in October as dealers fill their inventories with new models.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1084,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C020T_STR.wav","answer":"rates fell on short term treasury bills","subset":"str","task_type":"understanding","prediction":"rates fell on short term treasury bills","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1085,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C0210_STR.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"str","task_type":"understanding","prediction":"yesterday moody s investors service raised milkco s credit ratings in recognition of the improved outlook for steady financial recovery","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1086,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C0211_STR.wav","answer":"about three point five billion dollars of securities are affected","subset":"str","task_type":"understanding","prediction":"About $3.5 billion of securities are affected.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1087,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_440C0212_STR.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"str","task_type":"understanding","prediction":"He also said that the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1088,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_441C0207_STR.wav","answer":"in japan it's all greek so to speak","subset":"str","task_type":"understanding","prediction":"in japan it is all greek so to speak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1089,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_441C020K_STR.wav","answer":"the following officers directors and large stockholders of companies reported changes in holdings under the securities exchange act of nineteen thirty four","subset":"str","task_type":"understanding","prediction":"The following officials, directors and large stockholders of companies reported changes in holdings under the Securities Exchange Act of 1934.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1090,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_441C020T_STR.wav","answer":"has exposure really been reduced","subset":"str","task_type":"understanding","prediction":"has exposure really been reduced","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1091,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_441C0214_STR.wav","answer":"he also said that the company for the first time was developing drugs specifically for the over the counter consumer health care market","subset":"str","task_type":"understanding","prediction":"He also said the company, for the first time, was developing drugs specifically for the over the counter consumer health care market.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1092,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_441C0215_STR.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"str","task_type":"understanding","prediction":"He said such products could be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1093,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_441C0216_STR.wav","answer":"he declined to name specific products","subset":"str","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1094,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C0201_STR.wav","answer":"bids totaling five hundred twenty five point five million dollars were submitted","subset":"str","task_type":"understanding","prediction":"Bids totalling $525.5 million, were submitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1095,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C020A_STR.wav","answer":"under terms previously reported the italian agricultural concern assumed that one hundred ninety five million dollars in subordinated debt as part of the transaction","subset":"str","task_type":"understanding","prediction":"Under terms previously reported, the Italian agricultural concern assumed the $195 million in subordinated debt as part of the transaction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1096,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C020H_STR.wav","answer":"we just received the suit and the document is massive it's two hundred pages","subset":"str","task_type":"understanding","prediction":"We just received the suit, and the document is massive. It is 200 pages.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1097,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C020I_STR.wav","answer":"but on the first read through the case is without merit and we intend to fight it","subset":"str","task_type":"understanding","prediction":"But on the first read through, the case is without merit. And we intend to fight it.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1098,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C020N_STR.wav","answer":"we're going to be bidders said a top official of a major oil company","subset":"str","task_type":"understanding","prediction":"We are going to be bidders, said a top official of a major oil company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1099,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C020P_STR.wav","answer":"the company said it would begin a dutch auction later this week for as many as forty million shares or twenty six percent of its shares outstanding","subset":"str","task_type":"understanding","prediction":"The company said it would begin a Dutch auction later this week for as many as 40 million shares or 26% of its shares outstanding.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1100,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C020T_STR.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"str","task_type":"understanding","prediction":"Volume was modest, as 326.7 million shares changed hands compared with 396.5 million Friday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1101,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C020W_STR.wav","answer":"yesterday moody's investors service raised lilco's credit ratings in recognition of the improved outlook for steady financial recovery","subset":"str","task_type":"understanding","prediction":"Yesterday, Moody's Investors Service raised Lilco's credit ratings in recognition of the improved outlook for steady financial recovery.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1102,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_442C0216_STR.wav","answer":"important personnel usually are locked into long term contracts with incentives aimed at reducing that problem","subset":"str","task_type":"understanding","prediction":"Important personnel usually are locked into long term contracts, with incentives aimed at reducing that problem.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1103,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C0202_STR.wav","answer":"the department previously said jobs rose by four hundred forty eight thousand in january","subset":"str","task_type":"understanding","prediction":"The Department previously said jobs rose by 448000 in January.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1104,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C0203_STR.wav","answer":"using a measure that counts the military among the employed the rate was unchanged at six point six percent last month","subset":"str","task_type":"understanding","prediction":"Using a measure that counts the military among the employed, the rate was unchanged at 6.6% last month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1105,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C0205_STR.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"str","task_type":"understanding","prediction":"MICC said it intends to pay the dividend arrears on July 31 to stock of record July 2.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1106,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C0206_STR.wav","answer":"the toronto based company provides mortgage guarantees to the canadian real estate industry","subset":"str","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to the Canadian real estate industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1107,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C0207_STR.wav","answer":"it isn't clear yet whether the campaign works","subset":"str","task_type":"understanding","prediction":"it isn t clear yet whether the campaign works","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1108,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C020D_STR.wav","answer":"among export led electrical and computer makers japan victor company fell fifty to two thousand three hundred twenty","subset":"str","task_type":"understanding","prediction":"Among export LED electrical and computer makers. Japan, Victor Company of 50 to 2320.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1109,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C020I_STR.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"str","task_type":"understanding","prediction":"Unless otherwise noted, changes involved direct holdings of common stock took place in September and October 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1110,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C020J_STR.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"str","task_type":"understanding","prediction":"Companies are listed where transactions generally aggregate 10000 shares, or $100000.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1111,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_443C0210_STR.wav","answer":"the companies are followed by at least three analysts and had a minimum five cent change in actual earnings per share","subset":"str","task_type":"understanding","prediction":"Companies are followed by at least three analysts at a minimum. Five cent change in actual earnings per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1112,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C0201_STR.wav","answer":"in the nineteen eighty five quarter the owner and operator of health maintenance organizations earned six point nine million dollars or twenty four cents a share","subset":"str","task_type":"understanding","prediction":"In the 1985 quarter, the owner and operator of health maintenance organizations earned $6.9 million or 24 cents a share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1113,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C0202_STR.wav","answer":"it had forecast a nineteen eighty six fourth quarter loss of eighteen million dollars to twenty two million dollars","subset":"str","task_type":"understanding","prediction":"It had forecast a 1986 fourth quarter loss of $18 million to $22 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1114,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C020B_STR.wav","answer":"monday's crash is likely to affect at least one other piece of pending legislation the sweeping trade bill that is now the subject of a house senate conference","subset":"str","task_type":"understanding","prediction":"Monday's crash is likely to affect at least one other piece of pending legislation, a sweeping trade bill that is now the subject of a House Senate conference.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1115,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C020C_STR.wav","answer":"senate finance chairman lloyd bentsen d. texas said he would speed up work on the package because of the crash","subset":"str","task_type":"understanding","prediction":"Senate Finance Chairman Lloyd Bentsen, D. Texas said he would speed up work on the package because of the crash.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1116,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C020D_STR.wav","answer":"it adds to the support for the trade bill getting through he said","subset":"str","task_type":"understanding","prediction":"it adds to the support for the trade bill getting through he said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1117,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C020F_STR.wav","answer":"so far they have declined to comment publicly on their plans","subset":"str","task_type":"understanding","prediction":"So far, they have declined to comment publicly on their plans.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1118,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C020G_STR.wav","answer":"state officials however say the airlines have indicated they will comply with most of the standards as long as competitors do","subset":"str","task_type":"understanding","prediction":"State officials, however, say the airlines have indicated they will comply with most of the standards as long as competitors do.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1119,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C020H_STR.wav","answer":"among export led electrical and computer makers japan victor company fell fifty two thousand three hundred twenty","subset":"str","task_type":"understanding","prediction":"Among export LED electrical and computer makers. Japan Victor Company fell 52320.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1120,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C020Y_STR.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand monday","subset":"str","task_type":"understanding","prediction":"Volume was 18190000 shares, compared with 10550000 Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1121,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C0210_STR.wav","answer":"the institute said earned premiums rose three point one percent in the second quarter failing to keep pace with inflation which rose four point five percent","subset":"str","task_type":"understanding","prediction":"The institute said earned premiums rose 3.1% in the second quarter. Failing to keep pace with inflation, which rose 4.5%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1122,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_444C0214_STR.wav","answer":"money managers who sell their firms but then continue working for them may be less dedicated under new ownership they say","subset":"str","task_type":"understanding","prediction":"Money managers who sell their firms but then continue working for them may be less dedicated under new ownership, they say.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1123,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C0208_STR.wav","answer":"their business isn't just a job but their investment","subset":"str","task_type":"understanding","prediction":"their business isn t just a job but their investment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1124,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020I_STR.wav","answer":"the airline imposed the contract without union bargaining","subset":"str","task_type":"understanding","prediction":"The airline imposed the contract, without union bargaining.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1125,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020J_STR.wav","answer":"yesterday's session began with a sharp quick decline in the industrial average of more than forty five points which some market analysts attributed to foreign selling","subset":"str","task_type":"understanding","prediction":"Yesterday session began with a sharp, quick decline in the Industrial Average of more than 45 points, which some market analysts attributed to foreign selling.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1126,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020M_STR.wav","answer":"gillette is again a target of a major corporate raider","subset":"str","task_type":"understanding","prediction":"Gillette is, again, a target of a major corporate raider.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1127,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020O_STR.wav","answer":"a lengthy fight is likely","subset":"str","task_type":"understanding","prediction":"a lengthy fight is likely","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1128,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020P_STR.wav","answer":"about all the businessman can count on is that policy will be pretty volatile","subset":"str","task_type":"understanding","prediction":"But all the businessmen can count on is that policy will be pretty volatile.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1129,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020R_STR.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"str","task_type":"understanding","prediction":"If the Fed pushes the dollar higher. It may curb the demand for US exports.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1130,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020X_STR.wav","answer":"continental started the appeal process but recently settled the case","subset":"str","task_type":"understanding","prediction":"Continental started the appeal process, but recently settled the case.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1131,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C020Y_STR.wav","answer":"neither side would disclose terms","subset":"str","task_type":"understanding","prediction":"neither side would disclose terms","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1132,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_445C0213_STR.wav","answer":"from america china looked good","subset":"str","task_type":"understanding","prediction":"america and china put together","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1133,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C0206_STR.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"str","task_type":"understanding","prediction":"were not prepared to be advocates for the kgb","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1134,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020B_STR.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"str","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1135,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020C_STR.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"str","task_type":"understanding","prediction":"The unsold balance late yesterday was about $36.3 million, according to Shearson, Lehman Brothers, the lead underwriter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1136,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020E_STR.wav","answer":"fidelity had contended that gencorp isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments","subset":"str","task_type":"understanding","prediction":"Fidelity had contended that Gencor isn't a qualified broadcaster because it failed to disclose allegedly improper political campaign contributions and foreign payments.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1137,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020I_STR.wav","answer":"he said the company's goal is to have fifteen percent to twenty percent revenue growth to about three point two billion dollars for the year","subset":"str","task_type":"understanding","prediction":"He said the company's goal is to have 15% to 20% revenue growth to about $3.2 billion for the year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1138,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020K_STR.wav","answer":"in many ways that's just what u. b. s. has done since mr. senn was named president in nineteen eighty","subset":"str","task_type":"understanding","prediction":"In many ways, that is just what UBS has done since Mr. Zeghers was named president in 1980.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1139,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020L_STR.wav","answer":"assets more than doubled since then to one hundred sixty point four billion swiss francs one hundred fifteen point six billion dollars in nineteen eighty seven","subset":"str","task_type":"understanding","prediction":"Assets more than doubled since then to 160.4 billion Swiss francs.115.6 billion dollars in 1987.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1140,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020N_STR.wav","answer":"the real estate investment trust said it was still hoping to reach a new credit arrangement","subset":"str","task_type":"understanding","prediction":"The real estate investment trust said it was still hoping to reach a new credit agreement.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1141,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020S_STR.wav","answer":"among men forty one percent supported boosting the space exploration budget compared with nineteen percent of women","subset":"str","task_type":"understanding","prediction":"Among men,41% supported boosting the space exploration budget, compared with 90% of women.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1142,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020T_STR.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"str","task_type":"understanding","prediction":"According to the average estimate, a 7 economists surveyed by Dow Jones Capital Markets report new orders for US durable goods rose 2.4% last month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1143,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020V_STR.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"str","task_type":"understanding","prediction":"Mace Lem reported June 22. It came as a big surprise to most analysts and helped trigger a powerful bond rally that day.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1144,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_446C020W_STR.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"str","task_type":"understanding","prediction":"durable goods reports great to me are highly volatile from month to month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1145,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C0201_STR.wav","answer":"i don't mean there couldn't be some improvements in the revenue act of nineteen eighty six which took effect this month","subset":"str","task_type":"understanding","prediction":"I don't mean there couldn't be some improvements in the Revenue Act of 1986, which took effect this month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1146,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C0206_STR.wav","answer":"he cites the law of large numbers can you really expect it to grow at large numbers very long","subset":"str","task_type":"understanding","prediction":"He cites the law of large numbers. Can you really expect it to grow at large numbers very long.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1147,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C0209_STR.wav","answer":"washington national is a financial services concern","subset":"str","task_type":"understanding","prediction":"Washington National is a financial services concern","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1148,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C020E_STR.wav","answer":"northgate exploration limited said it sold four million common shares at eight dollars each","subset":"str","task_type":"understanding","prediction":"Northgate Exploration Limited said it sold 4 million common shares at $8 each.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1149,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C020H_STR.wav","answer":"the toronto based gold mining concern said proceeds would be used for general purposes","subset":"str","task_type":"understanding","prediction":"The Toronto based gold mining concern said proceeds would be used for general purposes.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1150,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C020M_STR.wav","answer":"envirodyne said it expects sales to be the highest for any third quarter in the company's history","subset":"str","task_type":"understanding","prediction":"Envirodyne said it expects sales to be the highest for any third quarter in the company's history.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1151,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C020S_STR.wav","answer":"but while the fed stands pat it is coming under increasing attack from both sides","subset":"str","task_type":"understanding","prediction":"but while the fed stands pat it is coming under increasing attack from both sides","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1152,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C020T_STR.wav","answer":"some critics including high reagan administration officials are raising the alarm that the fed's policy is too tight and could cause a recession next year","subset":"str","task_type":"understanding","prediction":"some critics including high reagan administration officials are raising the alarm that the feds policy is too tight and could cause recession next year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1153,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C020Y_STR.wav","answer":"increasingly people who test positive join the support groups that have sprung up across the country in the past year","subset":"str","task_type":"understanding","prediction":"Increasingly, people who test positive join the support groups that have sprung up across the country in the past year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1154,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C0210_STR.wav","answer":"founded last october new york's body positive already has sixteen groups meeting every two weeks","subset":"str","task_type":"understanding","prediction":"Founded last October, New Yorks body positive already has 16 groups meeting every two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1155,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/F06_447C0211_STR.wav","answer":"lately computer retailing has been tough on everybody","subset":"str","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1156,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C0201_STR.wav","answer":"at n. e. c. the need for international managers will keep rising","subset":"str","task_type":"understanding","prediction":"At Nec, the need for international managers will keep rising.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1157,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C0205_STR.wav","answer":"the company previously traded over the counter","subset":"str","task_type":"understanding","prediction":"the company previously traded over the counter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1158,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C020N_STR.wav","answer":"it can sign onto the plan file a competing plan or take a completely passive role that neither endorses nor opposes a plan","subset":"str","task_type":"understanding","prediction":"it can sign off to the plan file a competing plan or take a completely passive role that neither endorses nor opposes the plan","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1159,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C020U_STR.wav","answer":"the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday's auction","subset":"str","task_type":"understanding","prediction":"the rate on the latest three month bills declined to six point four three percent bid from an average of six point five three percent set at tuesday s auction","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1160,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C020V_STR.wav","answer":"the rate on six month bills fell to six point seven three percent from six point eight three percent","subset":"str","task_type":"understanding","prediction":"the rate on six month bills fell to six point seven three percent from six point eight three percent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1161,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C020W_STR.wav","answer":"durable goods reports frequently are highly volatile from month to month","subset":"str","task_type":"understanding","prediction":"Durable goods orders frequently are highly volatile from month to month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1162,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C020X_STR.wav","answer":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","subset":"str","task_type":"understanding","prediction":"many analysts cite an expected increase in aircraft orders as a big reason for the anticipated june increase","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1163,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C020Y_STR.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"str","task_type":"understanding","prediction":"estimates for the gain ranged from two percent to three percent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1164,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C0213_STR.wav","answer":"he said such products would be marketed by other companies with experience in that business","subset":"str","task_type":"understanding","prediction":"He said such products would be marketed by other companies with experience in that business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1165,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_440C0214_STR.wav","answer":"he declined to name specific products","subset":"str","task_type":"understanding","prediction":"he declined to name specific products","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1166,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C0209_STR.wav","answer":"the earlier rise was previously reported as four point three percent","subset":"str","task_type":"understanding","prediction":"The earlier rise was previously reported, as 4.3%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1167,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020A_STR.wav","answer":"if defense is excluded march orders rose one percent after a three percent increase in february","subset":"str","task_type":"understanding","prediction":"If defense is excluded March orders rose 1% after a 3% increase in February.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1168,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020B_STR.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"str","task_type":"understanding","prediction":"Grand auto slip 3 to 15 and 1,8 for the American slash standard.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1169,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020C_STR.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"str","task_type":"understanding","prediction":"The company, which runs retail automotive stores. Told Shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1170,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020D_STR.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"str","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1171,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020F_STR.wav","answer":"also a move to base it abroad will have tax advantages","subset":"str","task_type":"understanding","prediction":"also a move to base it abroad will have tax advantages","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1172,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020L_STR.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"str","task_type":"understanding","prediction":"Those identified as beneficial owners hold at least 10% of a company's equity securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1173,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020N_STR.wav","answer":"companies are listed where transactions generally aggregate ten thousand shares or one hundred thousand dollars","subset":"str","task_type":"understanding","prediction":"Companies are listed where transactions generally aggregate 10000 shares, or $100000.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1174,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020O_STR.wav","answer":"about all the businessman can count on is that policy will be pretty volatile","subset":"str","task_type":"understanding","prediction":"About all the businessmen can count on is that policy will be pretty volatile","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1175,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020S_STR.wav","answer":"analysts haven't focused on what happened to them","subset":"str","task_type":"understanding","prediction":"analysts havent focused on what happened to them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1176,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C020V_STR.wav","answer":"closed end funds are traded on exchanges like stocks but invest in a wide portfolio of other securities","subset":"str","task_type":"understanding","prediction":"Closed end funds are traded on exchanges like stocks, but invest in a wide portfolio of other securities","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1177,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C0210_STR.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"str","task_type":"understanding","prediction":"after the offering republic new york will hold about forty nine percent of the affiliate","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1178,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C0212_STR.wav","answer":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","subset":"str","task_type":"understanding","prediction":"volume was modest as three hundred twenty six point seven million shares changed hands compared with three hundred ninety six point five million friday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1179,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_441C0213_STR.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"str","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1180,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C0203_STR.wav","answer":"the bank holding company slated another fifty million dollar sale next tuesday","subset":"str","task_type":"understanding","prediction":"The bank holding company is slated another $50 million sale next Tuesday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1181,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C020C_STR.wav","answer":"shamrock has interests in television and radio stations energy services real estate and venture capital","subset":"str","task_type":"understanding","prediction":"Shamrock has interests in television and radio stations. Energy services, real estate and venture capital.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1182,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C020F_STR.wav","answer":"this morning the asking price for the stock was four thousand eight hundred fifty but there were no buyers","subset":"str","task_type":"understanding","prediction":"This morning, the asking price for the stock was 4850, but there were no buyers.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1183,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C020G_STR.wav","answer":"a monsanto spokesman said there's very little we can say","subset":"str","task_type":"understanding","prediction":"a monsanto spokesman said there is very little we can say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1184,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C020J_STR.wav","answer":"according to the average estimate of seven economists surveyed by dow jones capital markets report new orders for u. s. durable goods rose two point four percent last month","subset":"str","task_type":"understanding","prediction":"according to the average estimate of seven economists surveyed by dow jones capital markets reports new orders for US durable goods rose two point four percent last month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1185,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C020K_STR.wav","answer":"that would follow a two point two percent drop in may","subset":"str","task_type":"understanding","prediction":"that would follow a two point two percent drop in may","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1186,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C020L_STR.wav","answer":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","subset":"str","task_type":"understanding","prediction":"the may slump reported june twenty second came as a big surprise to most analysts and helped trigger a powerful bond rally that day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1187,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_442C0214_STR.wav","answer":"a change in the firm's ownership also should turn on a bright warning light","subset":"str","task_type":"understanding","prediction":"a change in the firms ownership should turn on a bright warning light","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1188,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C0201_STR.wav","answer":"the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before","subset":"str","task_type":"understanding","prediction":"the labor department said non farm payroll employment increased a robust three hundred thirty seven thousand last month after a revised three hundred nineteen thousand gain the month before","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1189,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C0208_STR.wav","answer":"local membership jumped twenty two percent but the union has already lost twenty eight of the seventy three new members","subset":"str","task_type":"understanding","prediction":"But the union has already lost 28% of the 73 new members.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1190,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020C_STR.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"str","task_type":"understanding","prediction":"Employment looked strong, inflation was low, and consumer spending and investment were both at half decent growth.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1191,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020E_STR.wav","answer":"kyocera was up sixty at five thousand two hundred sixty","subset":"str","task_type":"understanding","prediction":"Kyocera was up 60, at 5260.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1192,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020K_STR.wav","answer":"after the third period ashland's coal operations began a process of becoming an independent company","subset":"str","task_type":"understanding","prediction":"After the third period, Ashland's coal operation began a process of becoming an independent company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1193,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020L_STR.wav","answer":"when its initial public offering is completed ashland is expected to retain a forty six percent stake","subset":"str","task_type":"understanding","prediction":"When its initial public offering is completed. Ashland is expected to retain a 46% stake.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1194,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020M_STR.wav","answer":"the new company ashland coal incorporated is listed on the new york stock exchange","subset":"str","task_type":"understanding","prediction":"The new company, Ashland Coal Incorporated, is listed on the New York Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1195,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020P_STR.wav","answer":"in addition u. s. west's data solutions business applied communications incorporated is working out well and performing better ahead of all our schedules","subset":"str","task_type":"understanding","prediction":"in addition u s wests data solutions business applied communications incorporated is working out well and is working better and ahead of all of our schedules","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1196,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020Q_STR.wav","answer":"m. c. i. plans to begin offering the service at the end of this month","subset":"str","task_type":"understanding","prediction":"MCI plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1197,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020R_STR.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"str","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1198,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020S_STR.wav","answer":"a print media campaign will begin the following day","subset":"str","task_type":"understanding","prediction":"A print media campaign begins on Monday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1199,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020U_STR.wav","answer":"fees range up to about forty dollars annually for basic cards and sixty dollars a year for gold cards","subset":"str","task_type":"understanding","prediction":"Fees range up to about $40 annually for basic cards and $60 a year for gold cards.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1200,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020X_STR.wav","answer":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand on monday","subset":"str","task_type":"understanding","prediction":"volume was eighteen million one hundred ninety thousand shares compared with ten million five hundred fifty thousand on monday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1201,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020Y_STR.wav","answer":"there were two hundred fifty six issues advancing three hundred three declining and two hundred ninety two unchanged","subset":"str","task_type":"understanding","prediction":"There were 256 issues advancing,303 declining and 292 unchanged.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1202,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C020Z_STR.wav","answer":"companies listed below reported quarterly profit substantially different from the average of analysts' estimates","subset":"str","task_type":"understanding","prediction":"Companies listed below reported quarterly profit, substantially different from the average of analysts estimates.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1203,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C0211_STR.wav","answer":"estimated and actual results involving losses are omitted","subset":"str","task_type":"understanding","prediction":"Estimated and actual results involving losses are omitted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1204,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C0212_STR.wav","answer":"yesterday's losers included automobiles","subset":"str","task_type":"understanding","prediction":"yesterdays losers included automobiles","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1205,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_443C0213_STR.wav","answer":"honda was down ten to one thousand nine hundred thirty","subset":"str","task_type":"understanding","prediction":"Honda was down 10 to 1930.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1206,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C0203_STR.wav","answer":"revenue in the quarter more than doubled to three hundred sixty two point four million dollars from one hundred forty nine point two million dollars","subset":"str","task_type":"understanding","prediction":"Revenue in the quarter more than doubled to $362.4 million from $149.2 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1207,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C0204_STR.wav","answer":"separately new york state sold about seventy seven point one million dollars of certificates of participation","subset":"str","task_type":"understanding","prediction":"Separately, New York State sold about $77.1 million of certificates of participation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1208,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C0205_STR.wav","answer":"the issue was priced after auction to yield from three point five percent in nineteen eighty seven to five point five percent in nineteen ninety seven","subset":"str","task_type":"understanding","prediction":"The issue was priced after auction to yield from 3.5% in 1987 to 5.5% in 1997.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1209,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C0206_STR.wav","answer":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","subset":"str","task_type":"understanding","prediction":"the unsold balance late yesterday was about thirty six point three million dollars according to shearson lehman brothers the lead underwriter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1210,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C020K_STR.wav","answer":"lately computer retailing has been tough on everybody","subset":"str","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1211,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C020L_STR.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"str","task_type":"understanding","prediction":"no one is making very much money on it acknowledges brian j kelly chairman of bell atlantic s investment development unit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1212,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C020M_STR.wav","answer":"we had to sustain some modest operating losses","subset":"str","task_type":"understanding","prediction":"we had to sustain some modest operating losses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1213,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C020O_STR.wav","answer":"the company declined to identify the bidders but said it received offers in the high forty dollars per share","subset":"str","task_type":"understanding","prediction":"The company declined to identify the bidders. But said it received offers in the high $40 per share.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1214,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C020T_STR.wav","answer":"the market's strength may show that demand isn't all a creation of incentives","subset":"str","task_type":"understanding","prediction":"The market strength may show that demand isn't all a creations, he said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1215,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_444C020V_STR.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"str","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1216,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_445C0205_STR.wav","answer":"no one at the state department wants to let spies in","subset":"str","task_type":"understanding","prediction":"no one at the state department wants to let spies in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1217,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_445C0206_STR.wav","answer":"we're not prepared to be advocates for the k. g. b.","subset":"str","task_type":"understanding","prediction":"we are not prepared to be advocates for the kgb","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1218,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_445C0207_STR.wav","answer":"but the penalties for failure are real","subset":"str","task_type":"understanding","prediction":"but the penalties for failure are real","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1219,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_445C020H_STR.wav","answer":"the suit seeks to block the contract which would have raised pay levels and cut benefits","subset":"str","task_type":"understanding","prediction":"The suit seeks to block the contract. Which would have raised pay levels, and cut benefits.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1220,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_445C020K_STR.wav","answer":"but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday's close","subset":"str","task_type":"understanding","prediction":"but to the surprise of almost everyone stock prices began a steady climb that pushed the average above wednesday s close","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1221,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_445C020L_STR.wav","answer":"although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading","subset":"str","task_type":"understanding","prediction":"although those gains eroded during the afternoon stock prices stayed within a narrow range until the last half hour of trading","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1222,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_445C0210_STR.wav","answer":"as part of the marketing plan the company will begin airing television commercials during prime time on election night next tuesday","subset":"str","task_type":"understanding","prediction":"As part of the marketing plan the company will begin airing television commercials during prime time on election night next Tuesday","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1223,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_446C0202_STR.wav","answer":"to make them directly comparable each index is based on the close of nineteen sixty nine equaling one hundred","subset":"str","task_type":"understanding","prediction":"To make them directly comparable, each index is based on the close of 1969, equaling 100.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1224,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_446C0203_STR.wav","answer":"the percentage change is since year end","subset":"str","task_type":"understanding","prediction":"the percentage change is since year end","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1225,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_446C0207_STR.wav","answer":"that doesn't mean mr. icahn has committed any wrongdoing","subset":"str","task_type":"understanding","prediction":"That doesn't mean Mr. Icahn has committed any wrongdoing.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1226,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_446C020P_STR.wav","answer":"it's still unclear","subset":"str","task_type":"understanding","prediction":"its still unclear","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1227,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_446C020Q_STR.wav","answer":"there was a striking split between the sexes with men more likely than women to favor space programs","subset":"str","task_type":"understanding","prediction":"there was a striking split between the sexes with men more likely than women to favor space programs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1228,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_446C020U_STR.wav","answer":"that would follow a two point two percent drop in may","subset":"str","task_type":"understanding","prediction":"that would follow a two point four drop","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1229,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_446C0213_STR.wav","answer":"it also owns three state business magazines in florida georgia and arizona","subset":"str","task_type":"understanding","prediction":"it also owns three state business magazines in florida georgia and arizona","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1230,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C0204_STR.wav","answer":"mr. robertson says he would only be attracted by a nineteen multiple if he thought the projected earnings growth rate was eighteen percent to twenty percent","subset":"str","task_type":"understanding","prediction":"Mr. Roberts said he would only be attracted by a 19 multiple if he thought the projected earnings growth rate was 18% to 20%.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1231,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C0207_STR.wav","answer":"washington national paid nineteen dollars a share for the two point six million united presidential shares it didn't already own","subset":"str","task_type":"understanding","prediction":"Washington National paid $19 a share for the 2.6 million United presidential shares that didn't already own.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1232,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C020C_STR.wav","answer":"sending the refugees back isn't their idea it's just what the opposition politicians are saying in our country these days","subset":"str","task_type":"understanding","prediction":"Sending the refugees back isn't their idea. It is just what the opposition politicians are saying in our country these days","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1233,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C020O_STR.wav","answer":"the company expects to report its results in about two weeks","subset":"str","task_type":"understanding","prediction":"The company expects to report its results in about two weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1234,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C020U_STR.wav","answer":"other analysts say the fed needs to tighten policy further to support the dollar and prevent inflation","subset":"str","task_type":"understanding","prediction":"Other analysts say the Fed needs to tighten policy further to support the dollar and prevent inflation.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1235,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C020W_STR.wav","answer":"the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite tape","subset":"str","task_type":"understanding","prediction":"the shares closed at eighteen dollars and twenty five cents up twenty five cents on the new york stock exchange composite table","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1236,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C020X_STR.wav","answer":"salant shares closed unchanged on the big board at nine dollars and seventy five cents","subset":"str","task_type":"understanding","prediction":"Salant shares closed unchanged on the big board at $9.75.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1237,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M05_447C0216_STR.wav","answer":"the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight","subset":"str","task_type":"understanding","prediction":"the index ended with a decline of zero point three five point to one thousand two hundred seventy two point one eight","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1238,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C0203_STR.wav","answer":"about half these managers are in the u. s.","subset":"str","task_type":"understanding","prediction":"about half these managers are in the us","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1239,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C0207_STR.wav","answer":"the agency isn't likely to take any action until the union's rank and file votes on the contract in two to three weeks","subset":"str","task_type":"understanding","prediction":"The agency isn't likely to take any action until the unions rank and file votes on the contract in 2 to three weeks.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1240,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C020C_STR.wav","answer":"the rise in that category in july was led by increased orders for aircraft and parts nonelectrical machinery lumber and furniture","subset":"str","task_type":"understanding","prediction":"The rise in that category in July was LED by increased orders for aircraft and parts, non electrical machinery, lumber and furniture.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1241,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C020D_STR.wav","answer":"interest rates rose on short term treasury bills sold by the government yesterday at its regular weekly auction","subset":"str","task_type":"understanding","prediction":"Interest rates rose on short term Treasury bills sold by the government yesterday at its regular weekly auction.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1242,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C020J_STR.wav","answer":"the independent committee will recommend that holders accept the offer at a meeting expected to be held in december t. w. a. said","subset":"str","task_type":"understanding","prediction":"The independent committee will recommend that holders accept the offer at a meeting expected to be held in December. Twa said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1243,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C020L_STR.wav","answer":"the investor now owns seventy three percent of the company","subset":"str","task_type":"understanding","prediction":"the investor now owns seventy three percent of the company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1244,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C020M_STR.wav","answer":"texaco has three choices a company adviser says","subset":"str","task_type":"understanding","prediction":"texaco has three choices a company adviser says","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1245,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_440C020S_STR.wav","answer":"what we don't know is how much is price and how much is volume","subset":"str","task_type":"understanding","prediction":"what we dont know is how much is price and how much is volume","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1246,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C0201_STR.wav","answer":"first commodity appealed the expulsion and fine to the c. f. t. c.","subset":"str","task_type":"understanding","prediction":"First, commodity appealed the expulsion and fine to the CFTC.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1247,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C0202_STR.wav","answer":"a commission spokesman said a decision on the appeal is expected soon","subset":"str","task_type":"understanding","prediction":"A commission spokesman said a decision on the appeal is expected soon.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1248,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C0205_STR.wav","answer":"the language is a big problem","subset":"str","task_type":"understanding","prediction":"the language is a big problem","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1249,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C0206_STR.wav","answer":"in europe an american can at least read street signs","subset":"str","task_type":"understanding","prediction":"in europe an american can at least read street signs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1250,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C0208_STR.wav","answer":"the overall gain the fifth in the past seven months followed a revised four point one percent increase in february","subset":"str","task_type":"understanding","prediction":"The overall gain, the fifth in the past seven months, followed a revised 4.1% increase in February.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1251,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020E_STR.wav","answer":"elders brewing will be based outside australia because seventy percent of its assets are in britain and canada","subset":"str","task_type":"understanding","prediction":"Elders Brewing will be based outside Australia because 70 per cent of its assets are in Britain and Canada.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1252,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020H_STR.wav","answer":"two years ago b. a. s. f. made three separate acquisitions in the u. s.","subset":"str","task_type":"understanding","prediction":"Two years ago, BASF made three separate acquisitions in the US.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1253,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020I_STR.wav","answer":"its biggest was the one billion dollar purchase of united technologies corporation's inmont subsidiary a major supplier of paint to the auto industry","subset":"str","task_type":"understanding","prediction":"Its biggest was the $1 billion purchase of United Technologies Corporation's Inmont subsidiary, a major supplier of paint to the auto industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1254,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020J_STR.wav","answer":"today ninety percent of the four billion dollars of b. a. s. f. sales in the u. s. is produced there","subset":"str","task_type":"understanding","prediction":"today ninety percent of the four billion dollars of basf sales in the us is produced there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1255,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020M_STR.wav","answer":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","subset":"str","task_type":"understanding","prediction":"unless otherwise noted changes involved direct holdings of common stock and took place in september and october of nineteen eighty seven","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1256,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020P_STR.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"str","task_type":"understanding","prediction":"if the dollar starts to plunge the fed may step up its defense of the currency","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1257,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020Q_STR.wav","answer":"if the fed pushes the dollar higher it may curb the demand for u. s. exports","subset":"str","task_type":"understanding","prediction":"If the Fed pushes the dollar higher. It may curb the demand for US exports.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1258,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020W_STR.wav","answer":"although closed end funds have been around since at least the nineteen twenties they have boomed in popularity this year","subset":"str","task_type":"understanding","prediction":"although closed end funds have been around since at least the nineteen twenty s they have boomed in popularity this year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1259,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020X_STR.wav","answer":"the bond funds in particular provide robust yields for investors and hefty fees for underwriters","subset":"str","task_type":"understanding","prediction":"The bond funds, in particular, provide robust yields for investors and hefty fees for underwriters.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1260,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C020Y_STR.wav","answer":"republic new york rose one and one quarter to forty five and seven eighths","subset":"str","task_type":"understanding","prediction":"Republic, New York, rose 1 and 1 quarter to 45 and 7\/8.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1261,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_441C0211_STR.wav","answer":"at the close the financial times thirty share index was three point nine points lower at one thousand four hundred eighteen point six","subset":"str","task_type":"understanding","prediction":"At the close, the Financial Times 30 share index was 3.9 points lower at 1418.6.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1262,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0204_STR.wav","answer":"m. i. c. c. investments has three series of publicly traded preferred shares and ten series of privately held preferred stock","subset":"str","task_type":"understanding","prediction":"MICC investments have three series of publicly traded preferred shares and 10 series of privately held preferred stock.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1263,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0205_STR.wav","answer":"m. i. c. c. said it intends to pay the dividend arrears on july thirty first to stock of record july second","subset":"str","task_type":"understanding","prediction":"Micc said it intends to pay the dividend arrears on July 31 to stock of record July 2.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1264,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0206_STR.wav","answer":"the toronto based company provides mortgage guarantees to the canadian real estate industry","subset":"str","task_type":"understanding","prediction":"The Toronto based company provides mortgage guarantees to the Canadian real estate industry.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1265,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0207_STR.wav","answer":"grand auto slid three to fifteen and one eighth on the american stock exchange","subset":"str","task_type":"understanding","prediction":"Grand Auto slid 3 to 15 and 1\/8 on the American Stock Exchange.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1266,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0208_STR.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"str","task_type":"understanding","prediction":"The company, which runs a retail automotive stores, told Shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1267,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0209_STR.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"str","task_type":"understanding","prediction":"It received no proposal that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1268,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C020B_STR.wav","answer":"shamrock's pretax profit from the sale was one hundred twenty five million dollars a spokeswoman said","subset":"str","task_type":"understanding","prediction":"Shamrock s pretax profit for the sale was $125 million, the spokesman said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1269,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C020D_STR.wav","answer":"sony corporation for example closed at four thousand nine hundred fifty yen thirty four dollars and fifty cents a share yesterday","subset":"str","task_type":"understanding","prediction":"Sony Corporation, for example, closed at ¥4950. $34.50 a share yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1270,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C020O_STR.wav","answer":"but if the winning bids are as high as they were in some deals earlier this year then we're not going to be winning bidders","subset":"str","task_type":"understanding","prediction":"But if the winning bids are as high as they were in some deals earlier this year, then we are not going to be winning bidders.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1271,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C020R_STR.wav","answer":"the company then accepts the shares tendered at the lowest price needed to reach its total then pays that amount for all shares it purchases","subset":"str","task_type":"understanding","prediction":"The company then accepts the shares tendered at the lowest price needed to reach its total, then pays that amount for all shares it purchases.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1272,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C020U_STR.wav","answer":"the one hundred share index closed six point eight points lower at one thousand seven hundred fifty nine point nine","subset":"str","task_type":"understanding","prediction":"The 100 share index closed 6.8 points lower at 1759.9.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1273,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0211_STR.wav","answer":"so normalcy has returned","subset":"str","task_type":"understanding","prediction":"so normalcy has returned","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1274,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_442C0215_STR.wav","answer":"money managers who sell their firm but then continue working for them may be less dedicated under new ownership they say","subset":"str","task_type":"understanding","prediction":"Money managers sell their firm, but then continue working for them. Maybe less dedicated under new ownership, they say.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1275,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C0209_STR.wav","answer":"nonetheless the union has moved the experiment to richmond virginia and has received inquiries from other unions about its tactics","subset":"str","task_type":"understanding","prediction":"Nonetheless, the union has moved the experiment to Richmond, Virginia, and has received inquiries from other unions about its tactics.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1276,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020A_STR.wav","answer":"in the efforts to restore market confidence administration officials have emphasized that the economy's fundamentals remain sound","subset":"str","task_type":"understanding","prediction":"In the efforts to restore market confidence. Administration officials have emphasized that the economy's fundamentals remain sound.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1277,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020B_STR.wav","answer":"that was certainly true last week","subset":"str","task_type":"understanding","prediction":"that was certainly true last week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1278,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020F_STR.wav","answer":"sony which lost points in previous sessions this week rebounded eighty to five thousand one hundred thirty","subset":"str","task_type":"understanding","prediction":"Sony, which lost points in previous sessions this week, rebounded 80 to 5130.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1279,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020H_STR.wav","answer":"those identified as beneficial owners hold at least ten percent of a company's equity securities","subset":"str","task_type":"understanding","prediction":"Those identified as beneficial owners hold at least 10% of the company's equity securities.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1280,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020N_STR.wav","answer":"the official declined to elaborate on projections for non telephone operations but cited several indicators of recent gains","subset":"str","task_type":"understanding","prediction":"The official declined to elaborate on projections for non telephone operations. But cited several indicators of recent gains.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1281,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020O_STR.wav","answer":"he said the company has entered sixteen smaller cellular markets this year and has expanded its financial services work force","subset":"str","task_type":"understanding","prediction":"He said the company has entered 16 smaller cellular markets this year and has expanded its financial services workforce.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1282,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020V_STR.wav","answer":"in certain cases the cards are given free to subscribers","subset":"str","task_type":"understanding","prediction":"in certain cases the cards are given free to subscribers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1283,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C020W_STR.wav","answer":"the american stock exchange index lost zero point seven three to three hundred eighty point nine four","subset":"str","task_type":"understanding","prediction":"The American Stock Exchange index lost 0.73 to 380.94.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1284,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_443C0214_STR.wav","answer":"nissan lost thirty to one thousand five hundred twenty and toyota was down thirty to end the day at two thousand six hundred twenty","subset":"str","task_type":"understanding","prediction":"Nissan lost 30 to 1520, and Toyota was down 30 to end the day at 2620.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1285,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C0207_STR.wav","answer":"the issue is rated single a by moody's and single a minus by s. and p.","subset":"str","task_type":"understanding","prediction":"The issue is rated single A by Moody S and single A minus by S and P.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1286,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C0208_STR.wav","answer":"citicorp had twenty one point five billion dollars in capital at the end of last year","subset":"str","task_type":"understanding","prediction":"Citicorp had $21.5 billion in capital at the end of last year.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1287,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C0209_STR.wav","answer":"as one of the most acquisition hungry of major banks citicorp is often required by regulators to raise additional capital as a condition of making acquisitions","subset":"str","task_type":"understanding","prediction":"As one of the most acquisition hungry of major banks, Citicorp is often required by regulators to raise additional capital as a condition of making acquisitions.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1288,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C020P_STR.wav","answer":"in response amfac shares rose one dollar to forty seven dollars and seventy five cents in new york stock exchange composite trading yesterday","subset":"str","task_type":"understanding","prediction":"In response, Amfac shares rose $1 to $47.75 in New York Stock Exchange composite trading yesterday.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1289,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C020R_STR.wav","answer":"the mid july increase came even though auto makers are offering incentives on fewer cars this year than they did last year or earlier this year","subset":"str","task_type":"understanding","prediction":"The mid July increase came even though automakers are offering incentives on fewer cars this year than they did last year or earlier this year","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1290,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C020S_STR.wav","answer":"incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst","subset":"str","task_type":"understanding","prediction":"incentives can move around sales but not create them said charles brady an oppenheimer and company auto stock analyst","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1291,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C020U_STR.wav","answer":"m. c. i. plans to begin offering the service at the end of the month","subset":"str","task_type":"understanding","prediction":"Mci plans to begin offering the service at the end of this month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1292,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C020W_STR.wav","answer":"a print media campaign will begin the following day","subset":"str","task_type":"understanding","prediction":"A print media campaign will begin the following day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1293,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_444C0212_STR.wav","answer":"realized capital gains increased forty two percent to nine hundred nine million dollars from six hundred forty point nine million dollars","subset":"str","task_type":"understanding","prediction":"Realized capital gains increased 42% to $909 million from $640.9 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1294,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C0204_STR.wav","answer":"the consensus was that a new piece of paper isn't required said one u. s. diplomat","subset":"str","task_type":"understanding","prediction":"The consensus was that the new piece of paper isn't required, said one US diplomat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1295,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C0209_STR.wav","answer":"and both mortgaged their homes to secure the loans they needed to start the business","subset":"str","task_type":"understanding","prediction":"And both mortgaged their homes to secure the loans they needed to start the business.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1296,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020A_STR.wav","answer":"a long list of other witnesses have also testified in the trial now in its fourth month","subset":"str","task_type":"understanding","prediction":"A long list of other witnesses have also testified in the trial now, in its fourth month.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1297,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020E_STR.wav","answer":"the company which runs retail automotive stores told shearson lehman brothers its financial adviser to terminate discussions to sell the firm","subset":"str","task_type":"understanding","prediction":"The company, which runs retail automotive stores. Told shearson Lehman Brothers, its financial adviser. To terminate discussions to sell the firm.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1298,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020F_STR.wav","answer":"it received no proposals that were in the best interest of the shareholders the company said","subset":"str","task_type":"understanding","prediction":"It received no proposals that were in the best interest of the shareholders, the company said.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1299,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020G_STR.wav","answer":"the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists","subset":"str","task_type":"understanding","prediction":"the order issued late wednesday by judge diana murphy stems from a suit filed in federal court last month by the union representing the machinists","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1300,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020Q_STR.wav","answer":"if the dollar starts to plunge the fed may step up its defense of the currency","subset":"str","task_type":"understanding","prediction":"If the dollar starts to plunge, the Fed may step up its defense of the currency.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1301,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020S_STR.wav","answer":"lately computer retailing has been tough on everybody","subset":"str","task_type":"understanding","prediction":"lately computer retailing has been tough on everybody","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1302,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020T_STR.wav","answer":"no one is making very much money on it acknowledges brian j. kelly chairman of bell atlantic's investment development unit","subset":"str","task_type":"understanding","prediction":"No one is making very much money on it, acknowledges Brian J. Kelly, chairman of Bell Atlantic's investment development unit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1303,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C020W_STR.wav","answer":"the jury awarded mr. scharenberg one hundred five million dollars a figure based on ten years of profits had his project been completed","subset":"str","task_type":"understanding","prediction":"The jury awarded Mr. Sharonberg $105 million, a figure based on 10 years of profits. Had his project been completed.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1304,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_445C0216_STR.wav","answer":"where else in the third world is there so much energy and progress as in china","subset":"str","task_type":"understanding","prediction":"where else in the third world is there so much energy and progress as in china","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1305,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_446C020F_STR.wav","answer":"under the proposed transaction the los angeles based group would acquire the k. h. j. license and then sell itself to disney","subset":"str","task_type":"understanding","prediction":"Under the proposed transaction, the Los Angeles based group would acquire the KHJ license and then sell itself to Disney.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1306,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_446C020G_STR.wav","answer":"the closely held group doesn't have any significant assets according to william g. simon its president","subset":"str","task_type":"understanding","prediction":"The closely held group doesn't have any significant assets, according to William G. Simon, its president.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1307,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_446C020H_STR.wav","answer":"he said that for the full year wang's aiming for an after tax profit equal to three percent to five percent of sales","subset":"str","task_type":"understanding","prediction":"He said that for the full year. Wang is aiming for an after tax profit equal to 3% to 5% of sales.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1308,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_446C020Y_STR.wav","answer":"estimates for the gain ranged from two percent to three percent","subset":"str","task_type":"understanding","prediction":"estimates for the gain ranged from two percent to three percent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1309,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_446C0211_STR.wav","answer":"after the offering republic new york will hold about forty nine percent of the affiliate","subset":"str","task_type":"understanding","prediction":"after the offering republic new york will hold about forty nine percent of the affiliate","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1310,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_446C0212_STR.wav","answer":"closely held times publishing also owns two washington based publication congressional quarterly which covers capitol hill and governing which covers state and local governments","subset":"str","task_type":"understanding","prediction":"Closely held Times Publishing also owns two Washington based publications, Congressional Quarterly, which covers Capitol Hill and Governing, which covers state and local governments.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1311,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_446C0214_STR.wav","answer":"industry analysts value the company at about six hundred fifty million dollars","subset":"str","task_type":"understanding","prediction":"Industry analysts value the company at about $650 million.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1312,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C0203_STR.wav","answer":"and i'm sure you have your own list","subset":"str","task_type":"understanding","prediction":"and i am sure you have your own list","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1313,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C020A_STR.wav","answer":"united presidential is a life insurance company","subset":"str","task_type":"understanding","prediction":"United presidential is your life insurance company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1314,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C020B_STR.wav","answer":"these are uneducated people he says in english so the patients won't understand","subset":"str","task_type":"understanding","prediction":"these are uneducated people he says in english so the patients won t understand","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1315,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C020D_STR.wav","answer":"i will tell you what i think in my office","subset":"str","task_type":"understanding","prediction":"i will tell you what i think in my office","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1316,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C020F_STR.wav","answer":"they were sold to underwriters led by prudential bache securities incorporated","subset":"str","task_type":"understanding","prediction":"They were sold to underwriters, LED by Prudential Bache Securities, Incorporated.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1317,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C020L_STR.wav","answer":"employment looked strong inflation was low and consumer spending and investment were holding up reasonably well","subset":"str","task_type":"understanding","prediction":"Employment looked strong, inflation was low, and consumer spending and investment were holding up reasonably well.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1318,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C020R_STR.wav","answer":"the investor now owns seventy three percent of the company","subset":"str","task_type":"understanding","prediction":"the investor now owns seventy three percent of the company","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1319,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C020V_STR.wav","answer":"manhattan industries continued to trade above the offer price yesterday indicating the market expects a higher bid","subset":"str","task_type":"understanding","prediction":"Manhattan Industries continued to trade above the offer price yesterday, indicating the market expects a higher bid.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1320,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/CHIME-4\/CHiME4\/data\/audio\/16kHz\/isolated_1ch_track\/et05_str_real\/M06_447C0215_STR.wav","answer":"shearson lehman hutton incorporated's index of long term treasury bonds stayed in a very small range yesterday finishing very close to wednesday's closing level","subset":"str","task_type":"understanding","prediction":"shearson lehman hutton incorporated s index of long term treasury bonds stayed in the very small range yesterday finishing very close to wednesday s closing level","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank0.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank0.log
new file mode 100644
index 0000000000000000000000000000000000000000..63d876a66087c432b89348f1ead52a769c857aea
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank0.log
@@ -0,0 +1,4 @@
+2025-12-21 07:03:54 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: chime4_test-real_kimi
+2025-12-21 07:03:54 | INFO | Msg example: {'index': 1, 'audio': ['/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C0202_BUS.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'chime4-test-real', 'dataset_name': 'chime4_test-real_kimi', 'lang': 'en', 'subset': 'bus'}}
+2025-12-21 07:05:19 | INFO | model Qwen2.5-Omni-7B-lora2, data chime4_test-real_kimi, all 8 result merged to no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/Qwen2.5-Omni-7B-lora2_chime4_test-real_kimi.jsonl.
+2025-12-21 07:05:19 | INFO | skip eval for chime4_test-real_kimi
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank1.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank1.log
new file mode 100644
index 0000000000000000000000000000000000000000..808d26f98db88ac296220cdf6c719a198eb45574
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank1.log
@@ -0,0 +1,2 @@
+2025-12-21 07:03:35 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: chime4_test-real_kimi
+2025-12-21 07:03:35 | INFO | Msg example: {'index': 2, 'audio': ['/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C0204_BUS.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'chime4-test-real', 'dataset_name': 'chime4_test-real_kimi', 'lang': 'en', 'subset': 'bus'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank2.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank2.log
new file mode 100644
index 0000000000000000000000000000000000000000..52a574de76d5290d3279bf37ebd05a7fcdb9504a
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank2.log
@@ -0,0 +1,2 @@
+2025-12-21 07:03:28 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: chime4_test-real_kimi
+2025-12-21 07:03:28 | INFO | Msg example: {'index': 3, 'audio': ['/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C0209_BUS.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'chime4-test-real', 'dataset_name': 'chime4_test-real_kimi', 'lang': 'en', 'subset': 'bus'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank3.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank3.log
new file mode 100644
index 0000000000000000000000000000000000000000..18f9694e2e7add9e07872534582dbc258ad3845f
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank3.log
@@ -0,0 +1,2 @@
+2025-12-21 07:03:53 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: chime4_test-real_kimi
+2025-12-21 07:03:53 | INFO | Msg example: {'index': 4, 'audio': ['/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020E_BUS.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'chime4-test-real', 'dataset_name': 'chime4_test-real_kimi', 'lang': 'en', 'subset': 'bus'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank5.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank5.log
new file mode 100644
index 0000000000000000000000000000000000000000..f016db9b1652f6d5fb3621a245a2a2c7a56a5492
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank5.log
@@ -0,0 +1,2 @@
+2025-12-21 07:03:27 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: chime4_test-real_kimi
+2025-12-21 07:03:27 | INFO | Msg example: {'index': 6, 'audio': ['/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020G_BUS.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'chime4-test-real', 'dataset_name': 'chime4_test-real_kimi', 'lang': 'en', 'subset': 'bus'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank6.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank6.log
new file mode 100644
index 0000000000000000000000000000000000000000..a7468c549a43ce2e6ac3613598522c56e570312a
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/chime4_test-real_kimi/logs/rank6.log
@@ -0,0 +1,2 @@
+2025-12-21 07:03:22 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: chime4_test-real_kimi
+2025-12-21 07:03:22 | INFO | Msg example: {'index': 7, 'audio': ['/workspace/intern/pangkaiyu/dg/CHIME-4/CHiME4/data/audio/16kHz/isolated_1ch_track/et05_bus_real/F05_440C020H_BUS.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'chime4-test-real', 'dataset_name': 'chime4_test-real_kimi', 'lang': 'en', 'subset': 'bus'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus.jsonl b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..c48ef39627ace95e34f215c6ead7c9d6d14d4b8b
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus.jsonl
@@ -0,0 +1,840 @@
+{"index": 0, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp01_airport_sn0.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "diverse communities live and play", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp02_airport_sn0.wav", "answer": "He knew the skill of the great young actress.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp03_airport_sn0.wav", "answer": "Her purse was full of useless trash.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "impressed his full of decent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp04_airport_sn0.wav", "answer": "Read verse out loud for pleasure.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "reverse out loud flush", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp05_airport_sn0.wav", "answer": "Wipe the grease off his dirty face.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "Wipe the grease off the bearing face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp06_airport_sn0.wav", "answer": "Men strive but seldom get rich.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "men strive but seldom win", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 6, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp07_airport_sn0.wav", "answer": "We find joy in the simplest things.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "we find joy in the simplest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 7, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp08_airport_sn0.wav", "answer": "Hedge apples may stain your hands green.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands and clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 8, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp09_airport_sn0.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "turtles of pitt with the aid of a lemming", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 9, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp10_airport_sn0.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 10, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp11_airport_sn0.wav", "answer": "He wrote down a long list of items.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "he wrote down his long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 11, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp12_airport_sn0.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 12, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp13_airport_sn0.wav", "answer": "Smoke poured out of every crack.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "must pour out of every cranny", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 13, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp14_airport_sn0.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "ask our warranty fee and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 14, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp15_airport_sn0.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 15, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp16_airport_sn0.wav", "answer": "The stray cat gave birth to kittens.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the stray cat being first hit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 16, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp17_airport_sn0.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the lazy cow laying in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 17, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp18_airport_sn0.wav", "answer": "The friendly gang left the drug store.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 18, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp19_airport_sn0.wav", "answer": "We talked of the sideshow in the circus.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "we tossed it to find snow in the park", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 19, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp20_airport_sn0.wav", "answer": "The set of china hit the floor with a crash.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a bang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 20, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp21_airport_sn0.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "plants are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 21, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp22_airport_sn0.wav", "answer": "The line where the edges join was clean.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the line where the edges join", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 22, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp23_airport_sn0.wav", "answer": "Stop whistling and watch the boys march.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys run", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 23, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp24_airport_sn0.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "A cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 24, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp25_airport_sn0.wav", "answer": "A good book informs of what we ought to know.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "a good book informs us what we want", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 25, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp26_airport_sn0.wav", "answer": "She has a smart way of wearing clothes.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "She has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 26, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp27_airport_sn0.wav", "answer": "Bring your best compass to the third class.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "bring your best compass and a third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 27, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp28_airport_sn0.wav", "answer": "The club rented the rink for the fifth night.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 28, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp29_airport_sn0.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a fine point", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 29, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp30_airport_sn0.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "airport_0dB", "task_type": "understanding", "prediction": "lets all join as we finish the last one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 30, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp01_airport_sn10.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the birch canoe slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 31, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp02_airport_sn10.wav", "answer": "He knew the skill of the great young actress.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 32, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp03_airport_sn10.wav", "answer": "Her purse was full of useless trash.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 33, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp04_airport_sn10.wav", "answer": "Read verse out loud for pleasure.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 34, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp05_airport_sn10.wav", "answer": "Wipe the grease off his dirty face.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 35, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp06_airport_sn10.wav", "answer": "Men strive but seldom get rich.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 36, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp07_airport_sn10.wav", "answer": "We find joy in the simplest things.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 37, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp08_airport_sn10.wav", "answer": "Hedge apples may stain your hands green.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 38, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp09_airport_sn10.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 39, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp10_airport_sn10.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 40, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp11_airport_sn10.wav", "answer": "He wrote down a long list of items.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 41, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp12_airport_sn10.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 42, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp13_airport_sn10.wav", "answer": "Smoke poured out of every crack.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 43, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp14_airport_sn10.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 44, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp15_airport_sn10.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 45, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp16_airport_sn10.wav", "answer": "The stray cat gave birth to kittens.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 46, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp17_airport_sn10.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 47, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp18_airport_sn10.wav", "answer": "The friendly gang left the drug store.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 48, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp19_airport_sn10.wav", "answer": "We talked of the sideshow in the circus.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 49, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp20_airport_sn10.wav", "answer": "The set of china hit the floor with a crash.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 50, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp21_airport_sn10.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 51, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp22_airport_sn10.wav", "answer": "The line where the edges join was clean.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 52, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp23_airport_sn10.wav", "answer": "Stop whistling and watch the boys march.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 53, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp24_airport_sn10.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 54, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp25_airport_sn10.wav", "answer": "A good book informs of what we ought to know.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 55, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp26_airport_sn10.wav", "answer": "She has a smart way of wearing clothes.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 56, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp27_airport_sn10.wav", "answer": "Bring your best compass to the third class.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 57, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp28_airport_sn10.wav", "answer": "The club rented the rink for the fifth night.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 58, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp29_airport_sn10.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 59, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/10dB/sp30_airport_sn10.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "airport_10dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 60, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp01_airport_sn15.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the birch canoes slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 61, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp02_airport_sn15.wav", "answer": "He knew the skill of the great young actress.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 62, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp03_airport_sn15.wav", "answer": "Her purse was full of useless trash.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 63, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp04_airport_sn15.wav", "answer": "Read verse out loud for pleasure.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 64, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp05_airport_sn15.wav", "answer": "Wipe the grease off his dirty face.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 65, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp06_airport_sn15.wav", "answer": "Men strive but seldom get rich.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 66, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp07_airport_sn15.wav", "answer": "We find joy in the simplest things.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 67, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp08_airport_sn15.wav", "answer": "Hedge apples may stain your hands green.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 68, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp09_airport_sn15.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 69, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp10_airport_sn15.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 70, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp11_airport_sn15.wav", "answer": "He wrote down a long list of items.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 71, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp12_airport_sn15.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 72, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp13_airport_sn15.wav", "answer": "Smoke poured out of every crack.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 73, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp14_airport_sn15.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 74, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp15_airport_sn15.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 75, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp16_airport_sn15.wav", "answer": "The stray cat gave birth to kittens.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 76, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp17_airport_sn15.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 77, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp18_airport_sn15.wav", "answer": "The friendly gang left the drug store.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 78, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp19_airport_sn15.wav", "answer": "We talked of the sideshow in the circus.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 79, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp20_airport_sn15.wav", "answer": "The set of china hit the floor with a crash.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 80, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp21_airport_sn15.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 81, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp22_airport_sn15.wav", "answer": "The line where the edges join was clean.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 82, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp23_airport_sn15.wav", "answer": "Stop whistling and watch the boys march.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 83, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp24_airport_sn15.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "A cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 84, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp25_airport_sn15.wav", "answer": "A good book informs of what we ought to know.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 85, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp26_airport_sn15.wav", "answer": "She has a smart way of wearing clothes.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 86, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp27_airport_sn15.wav", "answer": "Bring your best compass to the third class.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 87, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp28_airport_sn15.wav", "answer": "The club rented the rink for the fifth night.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 88, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp29_airport_sn15.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 89, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/15dB/sp30_airport_sn15.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "airport_15dB", "task_type": "understanding", "prediction": "lets all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 90, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp01_airport_sn5.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "The birch canoe slid on the smooth water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 91, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp02_airport_sn5.wav", "answer": "He knew the skill of the great young actress.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 92, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp03_airport_sn5.wav", "answer": "Her purse was full of useless trash.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "my purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 93, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp04_airport_sn5.wav", "answer": "Read verse out loud for pleasure.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 94, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp05_airport_sn5.wav", "answer": "Wipe the grease off his dirty face.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 95, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp06_airport_sn5.wav", "answer": "Men strive but seldom get rich.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 96, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp07_airport_sn5.wav", "answer": "We find joy in the simplest things.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 97, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp08_airport_sn5.wav", "answer": "Hedge apples may stain your hands green.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 98, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp09_airport_sn5.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 99, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp10_airport_sn5.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp11_airport_sn5.wav", "answer": "He wrote down a long list of items.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp12_airport_sn5.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp13_airport_sn5.wav", "answer": "Smoke poured out of every crack.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp14_airport_sn5.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "cats are born to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp15_airport_sn5.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp16_airport_sn5.wav", "answer": "The stray cat gave birth to kittens.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp17_airport_sn5.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp18_airport_sn5.wav", "answer": "The friendly gang left the drug store.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp19_airport_sn5.wav", "answer": "We talked of the sideshow in the circus.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "we talked of the side show in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp20_airport_sn5.wav", "answer": "The set of china hit the floor with a crash.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp21_airport_sn5.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp22_airport_sn5.wav", "answer": "The line where the edges join was clean.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the line where the edges join was smooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp23_airport_sn5.wav", "answer": "Stop whistling and watch the boys march.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp24_airport_sn5.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht in the sun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp25_airport_sn5.wav", "answer": "A good book informs of what we ought to know.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp26_airport_sn5.wav", "answer": "She has a smart way of wearing clothes.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp27_airport_sn5.wav", "answer": "Bring your best compass to the third class.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp28_airport_sn5.wav", "answer": "The club rented the rink for the fifth night.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp29_airport_sn5.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "the flint suttered and lit a fine coals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/5dB/sp30_airport_sn5.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "airport_5dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp01_babble_sn0.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "first can use plant to use the one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp02_babble_sn0.wav", "answer": "He knew the skill of the great young actress.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "he knew the skill of the great young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp03_babble_sn0.wav", "answer": "Her purse was full of useless trash.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the purse was full of beautiful stones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp04_babble_sn0.wav", "answer": "Read verse out loud for pleasure.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "read verse out loud and flush", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp05_babble_sn0.wav", "answer": "Wipe the grease off his dirty face.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "wipes the grease off of jared s face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp06_babble_sn0.wav", "answer": "Men strive but seldom get rich.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "themselves dry after they went selvage down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp07_babble_sn0.wav", "answer": "We find joy in the simplest things.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "we find two ways", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp08_babble_sn0.wav", "answer": "Hedge apples may stain your hands green.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "ed apple may stain your hands and tongue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp09_babble_sn0.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "hurdles of pitch with the aid of a long throw", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp10_babble_sn0.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp11_babble_sn0.wav", "answer": "He wrote down a long list of items.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "he wrote down a long list of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp12_babble_sn0.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp13_babble_sn0.wav", "answer": "Smoke poured out of every crack.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp14_babble_sn0.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "pass all four to tia and not anything", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp15_babble_sn0.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the clothes dried on the same clothesline", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp16_babble_sn0.wav", "answer": "The stray cat gave birth to kittens.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the stray cat gave first tips", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp17_babble_sn0.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the lazy cow laying the cool back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp18_babble_sn0.wav", "answer": "The friendly gang left the drug store.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the friendly game left the drunk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp19_babble_sn0.wav", "answer": "We talked of the sideshow in the circus.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "we cautioned the high school and church", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp20_babble_sn0.wav", "answer": "The set of china hit the floor with a crash.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp21_babble_sn0.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "clamper small and large size", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp22_babble_sn0.wav", "answer": "The line where the edges join was clean.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "align where the edges join", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp23_babble_sn0.wav", "answer": "Stop whistling and watch the boys march.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "stop whistling as much as the boys are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp24_babble_sn0.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "a cruise in the wild waters of the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp25_babble_sn0.wav", "answer": "A good book informs of what we ought to know.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "facebook informs us that we are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp26_babble_sn0.wav", "answer": "She has a smart way of wearing clothes.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp27_babble_sn0.wav", "answer": "Bring your best compass to the third class.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "bring your best compass to the very class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp28_babble_sn0.wav", "answer": "The club rented the rink for the fifth night.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp29_babble_sn0.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine point", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/0dB/sp30_babble_sn0.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "babble_0dB", "task_type": "understanding", "prediction": "let s not join as we clean the last part", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp01_babble_sn10.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the birch canoes slid on the smooth plank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp02_babble_sn10.wav", "answer": "He knew the skill of the great young actress.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp03_babble_sn10.wav", "answer": "Her purse was full of useless trash.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp04_babble_sn10.wav", "answer": "Read verse out loud for pleasure.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp05_babble_sn10.wav", "answer": "Wipe the grease off his dirty face.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp06_babble_sn10.wav", "answer": "Men strive but seldom get rich.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp07_babble_sn10.wav", "answer": "We find joy in the simplest things.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp08_babble_sn10.wav", "answer": "Hedge apples may stain your hands green.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp09_babble_sn10.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp10_babble_sn10.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp11_babble_sn10.wav", "answer": "He wrote down a long list of items.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp12_babble_sn10.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp13_babble_sn10.wav", "answer": "Smoke poured out of every crack.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp14_babble_sn10.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp15_babble_sn10.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp16_babble_sn10.wav", "answer": "The stray cat gave birth to kittens.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp17_babble_sn10.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp18_babble_sn10.wav", "answer": "The friendly gang left the drug store.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp19_babble_sn10.wav", "answer": "We talked of the sideshow in the circus.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp20_babble_sn10.wav", "answer": "The set of china hit the floor with a crash.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp21_babble_sn10.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp22_babble_sn10.wav", "answer": "The line where the edges join was clean.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp23_babble_sn10.wav", "answer": "Stop whistling and watch the boys march.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp24_babble_sn10.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp25_babble_sn10.wav", "answer": "A good book informs of what we ought to know.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp26_babble_sn10.wav", "answer": "She has a smart way of wearing clothes.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp27_babble_sn10.wav", "answer": "Bring your best compass to the third class.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp28_babble_sn10.wav", "answer": "The club rented the rink for the fifth night.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp29_babble_sn10.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/10dB/sp30_babble_sn10.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "babble_10dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp01_babble_sn15.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the birch canoe slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp02_babble_sn15.wav", "answer": "He knew the skill of the great young actress.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp03_babble_sn15.wav", "answer": "Her purse was full of useless trash.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp04_babble_sn15.wav", "answer": "Read verse out loud for pleasure.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp05_babble_sn15.wav", "answer": "Wipe the grease off his dirty face.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp06_babble_sn15.wav", "answer": "Men strive but seldom get rich.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp07_babble_sn15.wav", "answer": "We find joy in the simplest things.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp08_babble_sn15.wav", "answer": "Hedge apples may stain your hands green.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp09_babble_sn15.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "hurdled a pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp10_babble_sn15.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp11_babble_sn15.wav", "answer": "He wrote down a long list of items.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp12_babble_sn15.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp13_babble_sn15.wav", "answer": "Smoke poured out of every crack.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp14_babble_sn15.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp15_babble_sn15.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp16_babble_sn15.wav", "answer": "The stray cat gave birth to kittens.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp17_babble_sn15.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp18_babble_sn15.wav", "answer": "The friendly gang left the drug store.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp19_babble_sn15.wav", "answer": "We talked of the sideshow in the circus.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp20_babble_sn15.wav", "answer": "The set of china hit the floor with a crash.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp21_babble_sn15.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp22_babble_sn15.wav", "answer": "The line where the edges join was clean.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp23_babble_sn15.wav", "answer": "Stop whistling and watch the boys march.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp24_babble_sn15.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp25_babble_sn15.wav", "answer": "A good book informs of what we ought to know.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp26_babble_sn15.wav", "answer": "She has a smart way of wearing clothes.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp27_babble_sn15.wav", "answer": "Bring your best compass to the third class.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp28_babble_sn15.wav", "answer": "The club rented the rink for the fifth night.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp29_babble_sn15.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/15dB/sp30_babble_sn15.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "babble_15dB", "task_type": "understanding", "prediction": "lets all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp01_babble_sn5.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the birch canoes slid from smooth points", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp02_babble_sn5.wav", "answer": "He knew the skill of the great young actress.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp03_babble_sn5.wav", "answer": "Her purse was full of useless trash.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "The purse is full of useless crap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp04_babble_sn5.wav", "answer": "Read verse out loud for pleasure.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp05_babble_sn5.wav", "answer": "Wipe the grease off his dirty face.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp06_babble_sn5.wav", "answer": "Men strive but seldom get rich.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "men strive but seldom achieve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp07_babble_sn5.wav", "answer": "We find joy in the simplest things.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp08_babble_sn5.wav", "answer": "Hedge apples may stain your hands green.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp09_babble_sn5.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "hurdle the fence with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp10_babble_sn5.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp11_babble_sn5.wav", "answer": "He wrote down a long list of items.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "He wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp12_babble_sn5.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp13_babble_sn5.wav", "answer": "Smoke poured out of every crack.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "smoke poured out as every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp14_babble_sn5.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp15_babble_sn5.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp16_babble_sn5.wav", "answer": "The stray cat gave birth to kittens.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the stray cat you first kidnapped", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp17_babble_sn5.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp18_babble_sn5.wav", "answer": "The friendly gang left the drug store.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the friendly gang left the drug", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp19_babble_sn5.wav", "answer": "We talked of the sideshow in the circus.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "we talked of the fight show in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp20_babble_sn5.wav", "answer": "The set of china hit the floor with a crash.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp21_babble_sn5.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp22_babble_sn5.wav", "answer": "The line where the edges join was clean.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the line where the edges join with the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp23_babble_sn5.wav", "answer": "Stop whistling and watch the boys march.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "Stop whistling and watch the boys tomorrow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp24_babble_sn5.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp25_babble_sn5.wav", "answer": "A good book informs of what we ought to know.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp26_babble_sn5.wav", "answer": "She has a smart way of wearing clothes.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp27_babble_sn5.wav", "answer": "Bring your best compass to the third class.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp28_babble_sn5.wav", "answer": "The club rented the rink for the fifth night.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp29_babble_sn5.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine twig", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/babble/5dB/sp30_babble_sn5.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "babble_5dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp01_car_sn0.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "car_0dB", "task_type": "understanding", "prediction": "very few", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp02_car_sn0.wav", "answer": "He knew the skill of the great young actress.", "subset": "car_0dB", "task_type": "understanding", "prediction": "he knew the skill of the great young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp03_car_sn0.wav", "answer": "Her purse was full of useless trash.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the first school", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp04_car_sn0.wav", "answer": "Read verse out loud for pleasure.", "subset": "car_0dB", "task_type": "understanding", "prediction": "reverse out loud", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp05_car_sn0.wav", "answer": "Wipe the grease off his dirty face.", "subset": "car_0dB", "task_type": "understanding", "prediction": "wipes the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp06_car_sn0.wav", "answer": "Men strive but seldom get rich.", "subset": "car_0dB", "task_type": "understanding", "prediction": "men strive but seldom achieve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp07_car_sn0.wav", "answer": "We find joy in the simplest things.", "subset": "car_0dB", "task_type": "understanding", "prediction": "we find joy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp08_car_sn0.wav", "answer": "Hedge apples may stain your hands green.", "subset": "car_0dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp09_car_sn0.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "car_0dB", "task_type": "understanding", "prediction": "turtles of pitch with the aid of a long", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp10_car_sn0.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "car_0dB", "task_type": "understanding", "prediction": "guy that morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp11_car_sn0.wav", "answer": "He wrote down a long list of items.", "subset": "car_0dB", "task_type": "understanding", "prediction": "he wrote down his long list of ideas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp12_car_sn0.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp13_car_sn0.wav", "answer": "Smoke poured out of every crack.", "subset": "car_0dB", "task_type": "understanding", "prediction": "moss poured out of the mrs cramp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp14_car_sn0.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "car_0dB", "task_type": "understanding", "prediction": "pass on one to kate and not to kim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp15_car_sn0.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the clothes dry on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp16_car_sn0.wav", "answer": "The stray cat gave birth to kittens.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the street tattoo first hit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp17_car_sn0.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp18_car_sn0.wav", "answer": "The friendly gang left the drug store.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the friendliness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp19_car_sn0.wav", "answer": "We talked of the sideshow in the circus.", "subset": "car_0dB", "task_type": "understanding", "prediction": "he possibly hide", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp20_car_sn0.wav", "answer": "The set of china hit the floor with a crash.", "subset": "car_0dB", "task_type": "understanding", "prediction": "instead of china hit the floor with a thud", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp21_car_sn0.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "car_0dB", "task_type": "understanding", "prediction": "plants are small", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp22_car_sn0.wav", "answer": "The line where the edges join was clean.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the line where the edges join is smooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp23_car_sn0.wav", "answer": "Stop whistling and watch the boys march.", "subset": "car_0dB", "task_type": "understanding", "prediction": "stop whistling and watch the boy run", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp24_car_sn0.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "car_0dB", "task_type": "understanding", "prediction": "are frilled in warm waters and sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp25_car_sn0.wav", "answer": "A good book informs of what we ought to know.", "subset": "car_0dB", "task_type": "understanding", "prediction": "good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp26_car_sn0.wav", "answer": "She has a smart way of wearing clothes.", "subset": "car_0dB", "task_type": "understanding", "prediction": "she has a smart way in wearing things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp27_car_sn0.wav", "answer": "Bring your best compass to the third class.", "subset": "car_0dB", "task_type": "understanding", "prediction": "bring your best to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp28_car_sn0.wav", "answer": "The club rented the rink for the fifth night.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp29_car_sn0.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "car_0dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pinecone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/0dB/sp30_car_sn0.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "car_0dB", "task_type": "understanding", "prediction": "let s all join as we see in the left", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp01_car_sn10.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the birch canoes slid on smooth water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp02_car_sn10.wav", "answer": "He knew the skill of the great young actress.", "subset": "car_10dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp03_car_sn10.wav", "answer": "Her purse was full of useless trash.", "subset": "car_10dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp04_car_sn10.wav", "answer": "Read verse out loud for pleasure.", "subset": "car_10dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp05_car_sn10.wav", "answer": "Wipe the grease off his dirty face.", "subset": "car_10dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp06_car_sn10.wav", "answer": "Men strive but seldom get rich.", "subset": "car_10dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp07_car_sn10.wav", "answer": "We find joy in the simplest things.", "subset": "car_10dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp08_car_sn10.wav", "answer": "Hedge apples may stain your hands green.", "subset": "car_10dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp09_car_sn10.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "car_10dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp10_car_sn10.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp11_car_sn10.wav", "answer": "He wrote down a long list of items.", "subset": "car_10dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp12_car_sn10.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp13_car_sn10.wav", "answer": "Smoke poured out of every crack.", "subset": "car_10dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp14_car_sn10.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "car_10dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp15_car_sn10.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp16_car_sn10.wav", "answer": "The stray cat gave birth to kittens.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the stray cat seems first to hit me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp17_car_sn10.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp18_car_sn10.wav", "answer": "The friendly gang left the drug store.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp19_car_sn10.wav", "answer": "We talked of the sideshow in the circus.", "subset": "car_10dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp20_car_sn10.wav", "answer": "The set of china hit the floor with a crash.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp21_car_sn10.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "car_10dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp22_car_sn10.wav", "answer": "The line where the edges join was clean.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp23_car_sn10.wav", "answer": "Stop whistling and watch the boys march.", "subset": "car_10dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp24_car_sn10.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "car_10dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp25_car_sn10.wav", "answer": "A good book informs of what we ought to know.", "subset": "car_10dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp26_car_sn10.wav", "answer": "She has a smart way of wearing clothes.", "subset": "car_10dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp27_car_sn10.wav", "answer": "Bring your best compass to the third class.", "subset": "car_10dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp28_car_sn10.wav", "answer": "The club rented the rink for the fifth night.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp29_car_sn10.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "car_10dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/10dB/sp30_car_sn10.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "car_10dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp01_car_sn15.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the birch canoes slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp02_car_sn15.wav", "answer": "He knew the skill of the great young actress.", "subset": "car_15dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp03_car_sn15.wav", "answer": "Her purse was full of useless trash.", "subset": "car_15dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp04_car_sn15.wav", "answer": "Read verse out loud for pleasure.", "subset": "car_15dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp05_car_sn15.wav", "answer": "Wipe the grease off his dirty face.", "subset": "car_15dB", "task_type": "understanding", "prediction": "wiped the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp06_car_sn15.wav", "answer": "Men strive but seldom get rich.", "subset": "car_15dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp07_car_sn15.wav", "answer": "We find joy in the simplest things.", "subset": "car_15dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp08_car_sn15.wav", "answer": "Hedge apples may stain your hands green.", "subset": "car_15dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp09_car_sn15.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "car_15dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp10_car_sn15.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp11_car_sn15.wav", "answer": "He wrote down a long list of items.", "subset": "car_15dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp12_car_sn15.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp13_car_sn15.wav", "answer": "Smoke poured out of every crack.", "subset": "car_15dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp14_car_sn15.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "car_15dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp15_car_sn15.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp16_car_sn15.wav", "answer": "The stray cat gave birth to kittens.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp17_car_sn15.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp18_car_sn15.wav", "answer": "The friendly gang left the drug store.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp19_car_sn15.wav", "answer": "We talked of the sideshow in the circus.", "subset": "car_15dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp20_car_sn15.wav", "answer": "The set of china hit the floor with a crash.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp21_car_sn15.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "car_15dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp22_car_sn15.wav", "answer": "The line where the edges join was clean.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp23_car_sn15.wav", "answer": "Stop whistling and watch the boys march.", "subset": "car_15dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp24_car_sn15.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "car_15dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp25_car_sn15.wav", "answer": "A good book informs of what we ought to know.", "subset": "car_15dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp26_car_sn15.wav", "answer": "She has a smart way of wearing clothes.", "subset": "car_15dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp27_car_sn15.wav", "answer": "Bring your best compass to the third class.", "subset": "car_15dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp28_car_sn15.wav", "answer": "The club rented the rink for the fifth night.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp29_car_sn15.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "car_15dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/15dB/sp30_car_sn15.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "car_15dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp01_car_sn5.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the birch canoe slid on the smooth plank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp02_car_sn5.wav", "answer": "He knew the skill of the great young actress.", "subset": "car_5dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp03_car_sn5.wav", "answer": "Her purse was full of useless trash.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp04_car_sn5.wav", "answer": "Read verse out loud for pleasure.", "subset": "car_5dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp05_car_sn5.wav", "answer": "Wipe the grease off his dirty face.", "subset": "car_5dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp06_car_sn5.wav", "answer": "Men strive but seldom get rich.", "subset": "car_5dB", "task_type": "understanding", "prediction": "men strive but seldom get", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp07_car_sn5.wav", "answer": "We find joy in the simplest things.", "subset": "car_5dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp08_car_sn5.wav", "answer": "Hedge apples may stain your hands green.", "subset": "car_5dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp09_car_sn5.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "car_5dB", "task_type": "understanding", "prediction": "turtles assist with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp10_car_sn5.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "car_5dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp11_car_sn5.wav", "answer": "He wrote down a long list of items.", "subset": "car_5dB", "task_type": "understanding", "prediction": "he wrote down his long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp12_car_sn5.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp13_car_sn5.wav", "answer": "Smoke poured out of every crack.", "subset": "car_5dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp14_car_sn5.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "car_5dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp15_car_sn5.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "car_5dB", "task_type": "understanding", "prediction": "The clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp16_car_sn5.wav", "answer": "The stray cat gave birth to kittens.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp17_car_sn5.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp18_car_sn5.wav", "answer": "The friendly gang left the drug store.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the friendly game at the drugstore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp19_car_sn5.wav", "answer": "We talked of the sideshow in the circus.", "subset": "car_5dB", "task_type": "understanding", "prediction": "we fostered the side stove in the first", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp20_car_sn5.wav", "answer": "The set of china hit the floor with a crash.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp21_car_sn5.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "car_5dB", "task_type": "understanding", "prediction": "plants are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp22_car_sn5.wav", "answer": "The line where the edges join was clean.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the line where the edges join is smooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp23_car_sn5.wav", "answer": "Stop whistling and watch the boys march.", "subset": "car_5dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp24_car_sn5.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "car_5dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht in fact", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp25_car_sn5.wav", "answer": "A good book informs of what we ought to know.", "subset": "car_5dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp26_car_sn5.wav", "answer": "She has a smart way of wearing clothes.", "subset": "car_5dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp27_car_sn5.wav", "answer": "Bring your best compass to the third class.", "subset": "car_5dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp28_car_sn5.wav", "answer": "The club rented the rink for the fifth night.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth and ninth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp29_car_sn5.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "car_5dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/car/5dB/sp30_car_sn5.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "car_5dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp01_exhibition_sn0.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "diverse communities led by smooth minds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp02_exhibition_sn0.wav", "answer": "He knew the skill of the great young actress.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "he knew the skill of the great young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp03_exhibition_sn0.wav", "answer": "Her purse was full of useless trash.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the purse is full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp04_exhibition_sn0.wav", "answer": "Read verse out loud for pleasure.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp05_exhibition_sn0.wav", "answer": "Wipe the grease off his dirty face.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "Wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp06_exhibition_sn0.wav", "answer": "Men strive but seldom get rich.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "men strive but seldom get this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp07_exhibition_sn0.wav", "answer": "We find joy in the simplest things.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "we find hui english simplest form", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp08_exhibition_sn0.wav", "answer": "Hedge apples may stain your hands green.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp09_exhibition_sn0.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "turtles of pitch with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp10_exhibition_sn0.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp11_exhibition_sn0.wav", "answer": "He wrote down a long list of items.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "he wrote down his long list of crimes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp12_exhibition_sn0.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp13_exhibition_sn0.wav", "answer": "Smoke poured out of every crack.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "smoke poured out of every crevice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp14_exhibition_sn0.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "at a want to see and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp15_exhibition_sn0.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the clothes dried on a thin clothing line", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp16_exhibition_sn0.wav", "answer": "The stray cat gave birth to kittens.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the spray pack you first", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp17_exhibition_sn0.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "a lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp18_exhibition_sn0.wav", "answer": "The friendly gang left the drug store.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp19_exhibition_sn0.wav", "answer": "We talked of the sideshow in the circus.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "and foxes decide so in the future", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp20_exhibition_sn0.wav", "answer": "The set of china hit the floor with a crash.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "instead of fineness of the soil with the cast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp21_exhibition_sn0.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "clams are small and soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp22_exhibition_sn0.wav", "answer": "The line where the edges join was clean.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the line where the edges join the screen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp23_exhibition_sn0.wav", "answer": "Stop whistling and watch the boys march.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "stop whippin and watch the boys in the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp24_exhibition_sn0.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp25_exhibition_sn0.wav", "answer": "A good book informs of what we ought to know.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "a dead fuck in forms of what you want man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp26_exhibition_sn0.wav", "answer": "She has a smart way of wearing clothes.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "She has a smart way of learning things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp27_exhibition_sn0.wav", "answer": "Bring your best compass to the third class.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "bring your best compass to the third", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp28_exhibition_sn0.wav", "answer": "The club rented the rink for the fifth night.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the club run of the rink for the fifth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp29_exhibition_sn0.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine cone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/0dB/sp30_exhibition_sn0.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "exhibition_0dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp01_exhibition_sn10.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the birch canoe slid on the smooth plants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp02_exhibition_sn10.wav", "answer": "He knew the skill of the great young actress.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp03_exhibition_sn10.wav", "answer": "Her purse was full of useless trash.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "my purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp04_exhibition_sn10.wav", "answer": "Read verse out loud for pleasure.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp05_exhibition_sn10.wav", "answer": "Wipe the grease off his dirty face.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp06_exhibition_sn10.wav", "answer": "Men strive but seldom get rich.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp07_exhibition_sn10.wav", "answer": "We find joy in the simplest things.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp08_exhibition_sn10.wav", "answer": "Hedge apples may stain your hands green.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp09_exhibition_sn10.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp10_exhibition_sn10.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp11_exhibition_sn10.wav", "answer": "He wrote down a long list of items.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp12_exhibition_sn10.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp13_exhibition_sn10.wav", "answer": "Smoke poured out of every crack.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp14_exhibition_sn10.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp15_exhibition_sn10.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp16_exhibition_sn10.wav", "answer": "The stray cat gave birth to kittens.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp17_exhibition_sn10.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp18_exhibition_sn10.wav", "answer": "The friendly gang left the drug store.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp19_exhibition_sn10.wav", "answer": "We talked of the sideshow in the circus.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "we toss of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp20_exhibition_sn10.wav", "answer": "The set of china hit the floor with a crash.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp21_exhibition_sn10.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp22_exhibition_sn10.wav", "answer": "The line where the edges join was clean.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp23_exhibition_sn10.wav", "answer": "Stop whistling and watch the boys march.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp24_exhibition_sn10.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp25_exhibition_sn10.wav", "answer": "A good book informs of what we ought to know.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp26_exhibition_sn10.wav", "answer": "She has a smart way of wearing clothes.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp27_exhibition_sn10.wav", "answer": "Bring your best compass to the third class.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp28_exhibition_sn10.wav", "answer": "The club rented the rink for the fifth night.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp29_exhibition_sn10.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine cone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/10dB/sp30_exhibition_sn10.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "exhibition_10dB", "task_type": "understanding", "prediction": "lets all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp01_exhibition_sn15.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the birch canoes slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp02_exhibition_sn15.wav", "answer": "He knew the skill of the great young actress.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp03_exhibition_sn15.wav", "answer": "Her purse was full of useless trash.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp04_exhibition_sn15.wav", "answer": "Read verse out loud for pleasure.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp05_exhibition_sn15.wav", "answer": "Wipe the grease off his dirty face.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp06_exhibition_sn15.wav", "answer": "Men strive but seldom get rich.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp07_exhibition_sn15.wav", "answer": "We find joy in the simplest things.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp08_exhibition_sn15.wav", "answer": "Hedge apples may stain your hands green.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp09_exhibition_sn15.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp10_exhibition_sn15.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp11_exhibition_sn15.wav", "answer": "He wrote down a long list of items.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp12_exhibition_sn15.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp13_exhibition_sn15.wav", "answer": "Smoke poured out of every crack.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp14_exhibition_sn15.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp15_exhibition_sn15.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp16_exhibition_sn15.wav", "answer": "The stray cat gave birth to kittens.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp17_exhibition_sn15.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp18_exhibition_sn15.wav", "answer": "The friendly gang left the drug store.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp19_exhibition_sn15.wav", "answer": "We talked of the sideshow in the circus.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp20_exhibition_sn15.wav", "answer": "The set of china hit the floor with a crash.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp21_exhibition_sn15.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp22_exhibition_sn15.wav", "answer": "The line where the edges join was clean.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp23_exhibition_sn15.wav", "answer": "Stop whistling and watch the boys march.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp24_exhibition_sn15.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp25_exhibition_sn15.wav", "answer": "A good book informs of what we ought to know.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp26_exhibition_sn15.wav", "answer": "She has a smart way of wearing clothes.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp27_exhibition_sn15.wav", "answer": "Bring your best compass to the third class.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp28_exhibition_sn15.wav", "answer": "The club rented the rink for the fifth night.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp29_exhibition_sn15.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/15dB/sp30_exhibition_sn15.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "exhibition_15dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp01_exhibition_sn5.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the birch canoes slid on smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp02_exhibition_sn5.wav", "answer": "He knew the skill of the great young actress.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp03_exhibition_sn5.wav", "answer": "Her purse was full of useless trash.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "his purse was full of useless cash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp04_exhibition_sn5.wav", "answer": "Read verse out loud for pleasure.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp05_exhibition_sn5.wav", "answer": "Wipe the grease off his dirty face.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp06_exhibition_sn5.wav", "answer": "Men strive but seldom get rich.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp07_exhibition_sn5.wav", "answer": "We find joy in the simplest things.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp08_exhibition_sn5.wav", "answer": "Hedge apples may stain your hands green.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp09_exhibition_sn5.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "turtle the pitch with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp10_exhibition_sn5.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the sky that morning was clear and right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp11_exhibition_sn5.wav", "answer": "He wrote down a long list of items.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp12_exhibition_sn5.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp13_exhibition_sn5.wav", "answer": "Smoke poured out of every crack.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp14_exhibition_sn5.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "hath a warrant to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp15_exhibition_sn5.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp16_exhibition_sn5.wav", "answer": "The stray cat gave birth to kittens.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp17_exhibition_sn5.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp18_exhibition_sn5.wav", "answer": "The friendly gang left the drug store.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp19_exhibition_sn5.wav", "answer": "We talked of the sideshow in the circus.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "we possibly decide so in the future", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp20_exhibition_sn5.wav", "answer": "The set of china hit the floor with a crash.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp21_exhibition_sn5.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "crabs are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp22_exhibition_sn5.wav", "answer": "The line where the edges join was clean.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the line where the edges join was smooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp23_exhibition_sn5.wav", "answer": "Stop whistling and watch the boys march.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "stop whittling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp24_exhibition_sn5.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a swift yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp25_exhibition_sn5.wav", "answer": "A good book informs of what we ought to know.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "a good book informs us of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp26_exhibition_sn5.wav", "answer": "She has a smart way of wearing clothes.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp27_exhibition_sn5.wav", "answer": "Bring your best compass to the third class.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp28_exhibition_sn5.wav", "answer": "The club rented the rink for the fifth night.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp29_exhibition_sn5.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine cone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/exhibition/5dB/sp30_exhibition_sn5.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "exhibition_5dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp01_restaurant_sn0.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "diverse communities live in a humid climate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp02_restaurant_sn0.wav", "answer": "He knew the skill of the great young actress.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "he knew the skill of the great young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp03_restaurant_sn0.wav", "answer": "Her purse was full of useless trash.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the first is full of peoples hands", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp04_restaurant_sn0.wav", "answer": "Read verse out loud for pleasure.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp05_restaurant_sn0.wav", "answer": "Wipe the grease off his dirty face.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "wipes the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp06_restaurant_sn0.wav", "answer": "Men strive but seldom get rich.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "men strive but seldom find", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp07_restaurant_sn0.wav", "answer": "We find joy in the simplest things.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "we find joy in the simplest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp08_restaurant_sn0.wav", "answer": "Hedge apples may stain your hands green.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "Hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp09_restaurant_sn0.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "turtles of pitch with the aid of long", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp10_restaurant_sn0.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp11_restaurant_sn0.wav", "answer": "He wrote down a long list of items.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "he wrote down in his notebook", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp12_restaurant_sn0.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the drift of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp13_restaurant_sn0.wav", "answer": "Smoke poured out of every crack.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "mum poured out his every crumb", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp14_restaurant_sn0.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "at our point to see", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp15_restaurant_sn0.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "close dry and thin what is that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp16_restaurant_sn0.wav", "answer": "The stray cat gave birth to kittens.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the stray cat sees first hit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp17_restaurant_sn0.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp18_restaurant_sn0.wav", "answer": "The friendly gang left the drug store.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the friendly gang left the driveway", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp19_restaurant_sn0.wav", "answer": "We talked of the sideshow in the circus.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "you possibly could hide the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp20_restaurant_sn0.wav", "answer": "The set of china hit the floor with a crash.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the scent of pine that hit the floor when you cracked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp21_restaurant_sn0.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "small", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp22_restaurant_sn0.wav", "answer": "The line where the edges join was clean.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the line where the edges join", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp23_restaurant_sn0.wav", "answer": "Stop whistling and watch the boys march.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "stop whittling and watch a boy work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp24_restaurant_sn0.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "a cruise in warm waters on a sleek yacht", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp25_restaurant_sn0.wav", "answer": "A good book informs of what we ought to know.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp26_restaurant_sn0.wav", "answer": "She has a smart way of wearing clothes.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "She has a smart way of wearing them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp27_restaurant_sn0.wav", "answer": "Bring your best compass to the third class.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp28_restaurant_sn0.wav", "answer": "The club rented the rink for the fifth night.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp29_restaurant_sn0.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "flint sputtered and lit a fine point", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/0dB/sp30_restaurant_sn0.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "restaurant_0dB", "task_type": "understanding", "prediction": "let us all join as we sing the last part", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp01_restaurant_sn10.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the birch canoe slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp02_restaurant_sn10.wav", "answer": "He knew the skill of the great young actress.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp03_restaurant_sn10.wav", "answer": "Her purse was full of useless trash.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp04_restaurant_sn10.wav", "answer": "Read verse out loud for pleasure.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp05_restaurant_sn10.wav", "answer": "Wipe the grease off his dirty face.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp06_restaurant_sn10.wav", "answer": "Men strive but seldom get rich.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp07_restaurant_sn10.wav", "answer": "We find joy in the simplest things.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp08_restaurant_sn10.wav", "answer": "Hedge apples may stain your hands green.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp09_restaurant_sn10.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "hurdled a pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp10_restaurant_sn10.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp11_restaurant_sn10.wav", "answer": "He wrote down a long list of items.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp12_restaurant_sn10.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp13_restaurant_sn10.wav", "answer": "Smoke poured out of every crack.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp14_restaurant_sn10.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp15_restaurant_sn10.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp16_restaurant_sn10.wav", "answer": "The stray cat gave birth to kittens.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp17_restaurant_sn10.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp18_restaurant_sn10.wav", "answer": "The friendly gang left the drug store.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp19_restaurant_sn10.wav", "answer": "We talked of the sideshow in the circus.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp20_restaurant_sn10.wav", "answer": "The set of china hit the floor with a crash.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp21_restaurant_sn10.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp22_restaurant_sn10.wav", "answer": "The line where the edges join was clean.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp23_restaurant_sn10.wav", "answer": "Stop whistling and watch the boys march.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp24_restaurant_sn10.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp25_restaurant_sn10.wav", "answer": "A good book informs of what we ought to know.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp26_restaurant_sn10.wav", "answer": "She has a smart way of wearing clothes.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp27_restaurant_sn10.wav", "answer": "Bring your best compass to the third class.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp28_restaurant_sn10.wav", "answer": "The club rented the rink for the fifth night.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp29_restaurant_sn10.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/10dB/sp30_restaurant_sn10.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "restaurant_10dB", "task_type": "understanding", "prediction": "lets all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp01_restaurant_sn15.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the birch canoe slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp02_restaurant_sn15.wav", "answer": "He knew the skill of the great young actress.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp03_restaurant_sn15.wav", "answer": "Her purse was full of useless trash.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp04_restaurant_sn15.wav", "answer": "Read verse out loud for pleasure.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp05_restaurant_sn15.wav", "answer": "Wipe the grease off his dirty face.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp06_restaurant_sn15.wav", "answer": "Men strive but seldom get rich.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp07_restaurant_sn15.wav", "answer": "We find joy in the simplest things.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp08_restaurant_sn15.wav", "answer": "Hedge apples may stain your hands green.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp09_restaurant_sn15.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp10_restaurant_sn15.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp11_restaurant_sn15.wav", "answer": "He wrote down a long list of items.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "He wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp12_restaurant_sn15.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp13_restaurant_sn15.wav", "answer": "Smoke poured out of every crack.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp14_restaurant_sn15.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp15_restaurant_sn15.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp16_restaurant_sn15.wav", "answer": "The stray cat gave birth to kittens.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp17_restaurant_sn15.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp18_restaurant_sn15.wav", "answer": "The friendly gang left the drug store.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp19_restaurant_sn15.wav", "answer": "We talked of the sideshow in the circus.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp20_restaurant_sn15.wav", "answer": "The set of china hit the floor with a crash.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp21_restaurant_sn15.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp22_restaurant_sn15.wav", "answer": "The line where the edges join was clean.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the line where the edges join was green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp23_restaurant_sn15.wav", "answer": "Stop whistling and watch the boys march.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp24_restaurant_sn15.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp25_restaurant_sn15.wav", "answer": "A good book informs of what we ought to know.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp26_restaurant_sn15.wav", "answer": "She has a smart way of wearing clothes.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp27_restaurant_sn15.wav", "answer": "Bring your best compass to the third class.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp28_restaurant_sn15.wav", "answer": "The club rented the rink for the fifth night.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp29_restaurant_sn15.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/15dB/sp30_restaurant_sn15.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "restaurant_15dB", "task_type": "understanding", "prediction": "lets all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp01_restaurant_sn5.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the birch canoe slid from the smooth plank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp02_restaurant_sn5.wav", "answer": "He knew the skill of the great young actress.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp03_restaurant_sn5.wav", "answer": "Her purse was full of useless trash.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "Her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp04_restaurant_sn5.wav", "answer": "Read verse out loud for pleasure.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "read verse out loud and in pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp05_restaurant_sn5.wav", "answer": "Wipe the grease off his dirty face.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "wipes degrees soft and dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp06_restaurant_sn5.wav", "answer": "Men strive but seldom get rich.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp07_restaurant_sn5.wav", "answer": "We find joy in the simplest things.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp08_restaurant_sn5.wav", "answer": "Hedge apples may stain your hands green.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp09_restaurant_sn5.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp10_restaurant_sn5.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp11_restaurant_sn5.wav", "answer": "He wrote down a long list of items.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp12_restaurant_sn5.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp13_restaurant_sn5.wav", "answer": "Smoke poured out of every crack.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp14_restaurant_sn5.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "cats are born to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp15_restaurant_sn5.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp16_restaurant_sn5.wav", "answer": "The stray cat gave birth to kittens.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp17_restaurant_sn5.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp18_restaurant_sn5.wav", "answer": "The friendly gang left the drug store.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the friendly gang left the drugstore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp19_restaurant_sn5.wav", "answer": "We talked of the sideshow in the circus.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp20_restaurant_sn5.wav", "answer": "The set of china hit the floor with a crash.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp21_restaurant_sn5.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp22_restaurant_sn5.wav", "answer": "The line where the edges join was clean.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the line where the edges join in the future", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp23_restaurant_sn5.wav", "answer": "Stop whistling and watch the boys march.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "Stop whistling and watch the boys and girls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp24_restaurant_sn5.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "A cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp25_restaurant_sn5.wav", "answer": "A good book informs of what we ought to know.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "a good book informs us what we are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp26_restaurant_sn5.wav", "answer": "She has a smart way of wearing clothes.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp27_restaurant_sn5.wav", "answer": "Bring your best compass to the third class.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp28_restaurant_sn5.wav", "answer": "The club rented the rink for the fifth night.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the club run of the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp29_restaurant_sn5.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a fine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/restaurant/5dB/sp30_restaurant_sn5.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "restaurant_5dB", "task_type": "understanding", "prediction": "lets all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp01_station_sn0.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "station_0dB", "task_type": "understanding", "prediction": "reverse the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp02_station_sn0.wav", "answer": "He knew the skill of the great young actress.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the skill of the great young actors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp03_station_sn0.wav", "answer": "Her purse was full of useless trash.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the first is full of useless things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp04_station_sn0.wav", "answer": "Read verse out loud for pleasure.", "subset": "station_0dB", "task_type": "understanding", "prediction": "reverse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp05_station_sn0.wav", "answer": "Wipe the grease off his dirty face.", "subset": "station_0dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp06_station_sn0.wav", "answer": "Men strive but seldom get rich.", "subset": "station_0dB", "task_type": "understanding", "prediction": "many strive but seldom achieve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp07_station_sn0.wav", "answer": "We find joy in the simplest things.", "subset": "station_0dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp08_station_sn0.wav", "answer": "Hedge apples may stain your hands green.", "subset": "station_0dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp09_station_sn0.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "station_0dB", "task_type": "understanding", "prediction": "turtle the pit is the aid of unknown food", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp10_station_sn0.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "station_0dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp11_station_sn0.wav", "answer": "He wrote down a long list of items.", "subset": "station_0dB", "task_type": "understanding", "prediction": "he wrote down his long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp12_station_sn0.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the drift of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp13_station_sn0.wav", "answer": "Smoke poured out of every crack.", "subset": "station_0dB", "task_type": "understanding", "prediction": "Smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp14_station_sn0.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "station_0dB", "task_type": "understanding", "prediction": "pass our phone to kate and not to the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp15_station_sn0.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the clothes dried on a stained wooden deck", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp16_station_sn0.wav", "answer": "The stray cat gave birth to kittens.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the stray cat sees first", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp17_station_sn0.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the lazy cow made me hold back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp18_station_sn0.wav", "answer": "The friendly gang left the drug store.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp19_station_sn0.wav", "answer": "We talked of the sideshow in the circus.", "subset": "station_0dB", "task_type": "understanding", "prediction": "we talked with the sideshow in the third", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp20_station_sn0.wav", "answer": "The set of china hit the floor with a crash.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a bang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp21_station_sn0.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "station_0dB", "task_type": "understanding", "prediction": "clams are small", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp22_station_sn0.wav", "answer": "The line where the edges join was clean.", "subset": "station_0dB", "task_type": "understanding", "prediction": "a line where the edges join is smooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp23_station_sn0.wav", "answer": "Stop whistling and watch the boys march.", "subset": "station_0dB", "task_type": "understanding", "prediction": "stop whistling and watch the boy in front", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp24_station_sn0.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "station_0dB", "task_type": "understanding", "prediction": "a fridge in warm waters and a loose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp25_station_sn0.wav", "answer": "A good book informs of what we ought to know.", "subset": "station_0dB", "task_type": "understanding", "prediction": "good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp26_station_sn0.wav", "answer": "She has a smart way of wearing clothes.", "subset": "station_0dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp27_station_sn0.wav", "answer": "Bring your best compass to the third class.", "subset": "station_0dB", "task_type": "understanding", "prediction": "bring your best to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp28_station_sn0.wav", "answer": "The club rented the rink for the fifth night.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp29_station_sn0.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "station_0dB", "task_type": "understanding", "prediction": "the flint fluttered and lit a pine bough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/0dB/sp30_station_sn0.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "station_0dB", "task_type": "understanding", "prediction": "let s not go into the same old left court", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp01_station_sn10.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the birch canoes slid on smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp02_station_sn10.wav", "answer": "He knew the skill of the great young actress.", "subset": "station_10dB", "task_type": "understanding", "prediction": "knew the skill of the great young actors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp03_station_sn10.wav", "answer": "Her purse was full of useless trash.", "subset": "station_10dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp04_station_sn10.wav", "answer": "Read verse out loud for pleasure.", "subset": "station_10dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp05_station_sn10.wav", "answer": "Wipe the grease off his dirty face.", "subset": "station_10dB", "task_type": "understanding", "prediction": "wiped the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp06_station_sn10.wav", "answer": "Men strive but seldom get rich.", "subset": "station_10dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp07_station_sn10.wav", "answer": "We find joy in the simplest things.", "subset": "station_10dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp08_station_sn10.wav", "answer": "Hedge apples may stain your hands green.", "subset": "station_10dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp09_station_sn10.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "station_10dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp10_station_sn10.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp11_station_sn10.wav", "answer": "He wrote down a long list of items.", "subset": "station_10dB", "task_type": "understanding", "prediction": "He wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp12_station_sn10.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp13_station_sn10.wav", "answer": "Smoke poured out of every crack.", "subset": "station_10dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp14_station_sn10.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "station_10dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp15_station_sn10.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp16_station_sn10.wav", "answer": "The stray cat gave birth to kittens.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp17_station_sn10.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp18_station_sn10.wav", "answer": "The friendly gang left the drug store.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp19_station_sn10.wav", "answer": "We talked of the sideshow in the circus.", "subset": "station_10dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp20_station_sn10.wav", "answer": "The set of china hit the floor with a crash.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp21_station_sn10.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "station_10dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp22_station_sn10.wav", "answer": "The line where the edges join was clean.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp23_station_sn10.wav", "answer": "Stop whistling and watch the boys march.", "subset": "station_10dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp24_station_sn10.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "station_10dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp25_station_sn10.wav", "answer": "A good book informs of what we ought to know.", "subset": "station_10dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp26_station_sn10.wav", "answer": "She has a smart way of wearing clothes.", "subset": "station_10dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp27_station_sn10.wav", "answer": "Bring your best compass to the third class.", "subset": "station_10dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp28_station_sn10.wav", "answer": "The club rented the rink for the fifth night.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp29_station_sn10.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "station_10dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/10dB/sp30_station_sn10.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "station_10dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp01_station_sn15.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the birch canoes slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp02_station_sn15.wav", "answer": "He knew the skill of the great young actress.", "subset": "station_15dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp03_station_sn15.wav", "answer": "Her purse was full of useless trash.", "subset": "station_15dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp04_station_sn15.wav", "answer": "Read verse out loud for pleasure.", "subset": "station_15dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp05_station_sn15.wav", "answer": "Wipe the grease off his dirty face.", "subset": "station_15dB", "task_type": "understanding", "prediction": "wiped the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp06_station_sn15.wav", "answer": "Men strive but seldom get rich.", "subset": "station_15dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp07_station_sn15.wav", "answer": "We find joy in the simplest things.", "subset": "station_15dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp08_station_sn15.wav", "answer": "Hedge apples may stain your hands green.", "subset": "station_15dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp09_station_sn15.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "station_15dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp10_station_sn15.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp11_station_sn15.wav", "answer": "He wrote down a long list of items.", "subset": "station_15dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp12_station_sn15.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp13_station_sn15.wav", "answer": "Smoke poured out of every crack.", "subset": "station_15dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp14_station_sn15.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "station_15dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp15_station_sn15.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp16_station_sn15.wav", "answer": "The stray cat gave birth to kittens.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp17_station_sn15.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp18_station_sn15.wav", "answer": "The friendly gang left the drug store.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp19_station_sn15.wav", "answer": "We talked of the sideshow in the circus.", "subset": "station_15dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp20_station_sn15.wav", "answer": "The set of china hit the floor with a crash.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp21_station_sn15.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "station_15dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp22_station_sn15.wav", "answer": "The line where the edges join was clean.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp23_station_sn15.wav", "answer": "Stop whistling and watch the boys march.", "subset": "station_15dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp24_station_sn15.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "station_15dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp25_station_sn15.wav", "answer": "A good book informs of what we ought to know.", "subset": "station_15dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp26_station_sn15.wav", "answer": "She has a smart way of wearing clothes.", "subset": "station_15dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp27_station_sn15.wav", "answer": "Bring your best compass to the third class.", "subset": "station_15dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp28_station_sn15.wav", "answer": "The club rented the rink for the fifth night.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp29_station_sn15.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "station_15dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/15dB/sp30_station_sn15.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "station_15dB", "task_type": "understanding", "prediction": "lets all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp01_station_sn5.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the birch communists live on a cruise ship", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp02_station_sn5.wav", "answer": "He knew the skill of the great young actress.", "subset": "station_5dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp03_station_sn5.wav", "answer": "Her purse was full of useless trash.", "subset": "station_5dB", "task_type": "understanding", "prediction": "my purse is full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp04_station_sn5.wav", "answer": "Read verse out loud for pleasure.", "subset": "station_5dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp05_station_sn5.wav", "answer": "Wipe the grease off his dirty face.", "subset": "station_5dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp06_station_sn5.wav", "answer": "Men strive but seldom get rich.", "subset": "station_5dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp07_station_sn5.wav", "answer": "We find joy in the simplest things.", "subset": "station_5dB", "task_type": "understanding", "prediction": "we find joy in the simplest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp08_station_sn5.wav", "answer": "Hedge apples may stain your hands green.", "subset": "station_5dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp09_station_sn5.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "station_5dB", "task_type": "understanding", "prediction": "turtle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp10_station_sn5.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "station_5dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp11_station_sn5.wav", "answer": "He wrote down a long list of items.", "subset": "station_5dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp12_station_sn5.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp13_station_sn5.wav", "answer": "Smoke poured out of every crack.", "subset": "station_5dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp14_station_sn5.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "station_5dB", "task_type": "understanding", "prediction": "pass our warrant to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp15_station_sn5.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "station_5dB", "task_type": "understanding", "prediction": "The clothes dried on a thin, wooden rack.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp16_station_sn5.wav", "answer": "The stray cat gave birth to kittens.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the stray cat came first to kiss", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp17_station_sn5.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp18_station_sn5.wav", "answer": "The friendly gang left the drug store.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp19_station_sn5.wav", "answer": "We talked of the sideshow in the circus.", "subset": "station_5dB", "task_type": "understanding", "prediction": "we talked with the slide show in the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp20_station_sn5.wav", "answer": "The set of china hit the floor with a crash.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp21_station_sn5.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "station_5dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp22_station_sn5.wav", "answer": "The line where the edges join was clean.", "subset": "station_5dB", "task_type": "understanding", "prediction": "a line where the edges join is free", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp23_station_sn5.wav", "answer": "Stop whistling and watch the boys march.", "subset": "station_5dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp24_station_sn5.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "station_5dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp25_station_sn5.wav", "answer": "A good book informs of what we ought to know.", "subset": "station_5dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp26_station_sn5.wav", "answer": "She has a smart way of wearing clothes.", "subset": "station_5dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp27_station_sn5.wav", "answer": "Bring your best compass to the third class.", "subset": "station_5dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp28_station_sn5.wav", "answer": "The club rented the rink for the fifth night.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp29_station_sn5.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "station_5dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/station/5dB/sp30_station_sn5.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "station_5dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp01_street_sn0.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "street_0dB", "task_type": "understanding", "prediction": "virtually", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp02_street_sn0.wav", "answer": "He knew the skill of the great young actress.", "subset": "street_0dB", "task_type": "understanding", "prediction": "he knew the skill of the great young", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp03_street_sn0.wav", "answer": "Her purse was full of useless trash.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the first is full of useless crap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp04_street_sn0.wav", "answer": "Read verse out loud for pleasure.", "subset": "street_0dB", "task_type": "understanding", "prediction": "rebirth not loud but", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp05_street_sn0.wav", "answer": "Wipe the grease off his dirty face.", "subset": "street_0dB", "task_type": "understanding", "prediction": "last degree softest air to say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp06_street_sn0.wav", "answer": "Men strive but seldom get rich.", "subset": "street_0dB", "task_type": "understanding", "prediction": "and strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp07_street_sn0.wav", "answer": "We find joy in the simplest things.", "subset": "street_0dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp08_street_sn0.wav", "answer": "Hedge apples may stain your hands green.", "subset": "street_0dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp09_street_sn0.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "street_0dB", "task_type": "understanding", "prediction": "turtles of pitt with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp10_street_sn0.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "street_0dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp11_street_sn0.wav", "answer": "He wrote down a long list of items.", "subset": "street_0dB", "task_type": "understanding", "prediction": "he wrote down his long list of findings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp12_street_sn0.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the drip of the rain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp13_street_sn0.wav", "answer": "Smoke poured out of every crack.", "subset": "street_0dB", "task_type": "understanding", "prediction": "most poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp14_street_sn0.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "street_0dB", "task_type": "understanding", "prediction": "half of one to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp15_street_sn0.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden bench", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp16_street_sn0.wav", "answer": "The stray cat gave birth to kittens.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the straight path these first six", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp17_street_sn0.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the lazy cow lay in the shade", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp18_street_sn0.wav", "answer": "The friendly gang left the drug store.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the criminal gang left the drug", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp19_street_sn0.wav", "answer": "We talked of the sideshow in the circus.", "subset": "street_0dB", "task_type": "understanding", "prediction": "impossible to find a replacement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp20_street_sn0.wav", "answer": "The set of china hit the floor with a crash.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the set of pine that hit the floor with a bang", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp21_street_sn0.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "street_0dB", "task_type": "understanding", "prediction": "plants are small", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp22_street_sn0.wav", "answer": "The line where the edges join was clean.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the line where the edges join will be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp23_street_sn0.wav", "answer": "Stop whistling and watch the boys march.", "subset": "street_0dB", "task_type": "understanding", "prediction": "stop whippin and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp24_street_sn0.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "street_0dB", "task_type": "understanding", "prediction": "a cruise in warm waters and a glimpse of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp25_street_sn0.wav", "answer": "A good book informs of what we ought to know.", "subset": "street_0dB", "task_type": "understanding", "prediction": "good book in form with what we want to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp26_street_sn0.wav", "answer": "She has a smart way of wearing clothes.", "subset": "street_0dB", "task_type": "understanding", "prediction": "She has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp27_street_sn0.wav", "answer": "Bring your best compass to the third class.", "subset": "street_0dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp28_street_sn0.wav", "answer": "The club rented the rink for the fifth night.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the club runs the range for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp29_street_sn0.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "street_0dB", "task_type": "understanding", "prediction": "the splint sputtered and lit a pine cone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/0dB/sp30_street_sn0.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "street_0dB", "task_type": "understanding", "prediction": "that song joined as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp01_street_sn10.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "street_10dB", "task_type": "understanding", "prediction": "The birch canoes slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp02_street_sn10.wav", "answer": "He knew the skill of the great young actress.", "subset": "street_10dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp03_street_sn10.wav", "answer": "Her purse was full of useless trash.", "subset": "street_10dB", "task_type": "understanding", "prediction": "my purse is full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp04_street_sn10.wav", "answer": "Read verse out loud for pleasure.", "subset": "street_10dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp05_street_sn10.wav", "answer": "Wipe the grease off his dirty face.", "subset": "street_10dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp06_street_sn10.wav", "answer": "Men strive but seldom get rich.", "subset": "street_10dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp07_street_sn10.wav", "answer": "We find joy in the simplest things.", "subset": "street_10dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp08_street_sn10.wav", "answer": "Hedge apples may stain your hands green.", "subset": "street_10dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp09_street_sn10.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "street_10dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp10_street_sn10.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp11_street_sn10.wav", "answer": "He wrote down a long list of items.", "subset": "street_10dB", "task_type": "understanding", "prediction": "He wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp12_street_sn10.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp13_street_sn10.wav", "answer": "Smoke poured out of every crack.", "subset": "street_10dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp14_street_sn10.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "street_10dB", "task_type": "understanding", "prediction": "cats are born to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp15_street_sn10.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp16_street_sn10.wav", "answer": "The stray cat gave birth to kittens.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp17_street_sn10.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp18_street_sn10.wav", "answer": "The friendly gang left the drug store.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp19_street_sn10.wav", "answer": "We talked of the sideshow in the circus.", "subset": "street_10dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp20_street_sn10.wav", "answer": "The set of china hit the floor with a crash.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp21_street_sn10.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "street_10dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp22_street_sn10.wav", "answer": "The line where the edges join was clean.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the line where the edges join was smooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp23_street_sn10.wav", "answer": "Stop whistling and watch the boys march.", "subset": "street_10dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp24_street_sn10.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "street_10dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp25_street_sn10.wav", "answer": "A good book informs of what we ought to know.", "subset": "street_10dB", "task_type": "understanding", "prediction": "a good book informs us of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp26_street_sn10.wav", "answer": "She has a smart way of wearing clothes.", "subset": "street_10dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp27_street_sn10.wav", "answer": "Bring your best compass to the third class.", "subset": "street_10dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp28_street_sn10.wav", "answer": "The club rented the rink for the fifth night.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp29_street_sn10.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "street_10dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine cone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/10dB/sp30_street_sn10.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "street_10dB", "task_type": "understanding", "prediction": "let s all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp01_street_sn15.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the birch canoe slid on the smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp02_street_sn15.wav", "answer": "He knew the skill of the great young actress.", "subset": "street_15dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp03_street_sn15.wav", "answer": "Her purse was full of useless trash.", "subset": "street_15dB", "task_type": "understanding", "prediction": "her purse was full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp04_street_sn15.wav", "answer": "Read verse out loud for pleasure.", "subset": "street_15dB", "task_type": "understanding", "prediction": "read first out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp05_street_sn15.wav", "answer": "Wipe the grease off his dirty face.", "subset": "street_15dB", "task_type": "understanding", "prediction": "wipe the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp06_street_sn15.wav", "answer": "Men strive but seldom get rich.", "subset": "street_15dB", "task_type": "understanding", "prediction": "men strive but seldom get rich", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp07_street_sn15.wav", "answer": "We find joy in the simplest things.", "subset": "street_15dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp08_street_sn15.wav", "answer": "Hedge apples may stain your hands green.", "subset": "street_15dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp09_street_sn15.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "street_15dB", "task_type": "understanding", "prediction": "hurtle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp10_street_sn15.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the sky that morning was clear and bright blue", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp11_street_sn15.wav", "answer": "He wrote down a long list of items.", "subset": "street_15dB", "task_type": "understanding", "prediction": "he wrote down a long list of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp12_street_sn15.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the drip of the rain made a fuzzy sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp13_street_sn15.wav", "answer": "Smoke poured out of every crack.", "subset": "street_15dB", "task_type": "understanding", "prediction": "smoke poured out of every crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp14_street_sn15.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "street_15dB", "task_type": "understanding", "prediction": "hats are worn to tea and not to dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp15_street_sn15.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp16_street_sn15.wav", "answer": "The stray cat gave birth to kittens.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp17_street_sn15.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp18_street_sn15.wav", "answer": "The friendly gang left the drug store.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp19_street_sn15.wav", "answer": "We talked of the sideshow in the circus.", "subset": "street_15dB", "task_type": "understanding", "prediction": "we talked of the sideshow in the circus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp20_street_sn15.wav", "answer": "The set of china hit the floor with a crash.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp21_street_sn15.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "street_15dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp22_street_sn15.wav", "answer": "The line where the edges join was clean.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the line where the edges join was clean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp23_street_sn15.wav", "answer": "Stop whistling and watch the boys march.", "subset": "street_15dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp24_street_sn15.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "street_15dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht is fun", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp25_street_sn15.wav", "answer": "A good book informs of what we ought to know.", "subset": "street_15dB", "task_type": "understanding", "prediction": "a good book informs of what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp26_street_sn15.wav", "answer": "She has a smart way of wearing clothes.", "subset": "street_15dB", "task_type": "understanding", "prediction": "she has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp27_street_sn15.wav", "answer": "Bring your best compass to the third class.", "subset": "street_15dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp28_street_sn15.wav", "answer": "The club rented the rink for the fifth night.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp29_street_sn15.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "street_15dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine torch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/15dB/sp30_street_sn15.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "street_15dB", "task_type": "understanding", "prediction": "let us all join as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp01_street_sn5.wav", "answer": "The birch canoe slid on the smooth planks.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the birch canoes live on smooth planks", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp02_street_sn5.wav", "answer": "He knew the skill of the great young actress.", "subset": "street_5dB", "task_type": "understanding", "prediction": "he knew the skill of the great young actors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp03_street_sn5.wav", "answer": "Her purse was full of useless trash.", "subset": "street_5dB", "task_type": "understanding", "prediction": "my purse is full of useless trash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp04_street_sn5.wav", "answer": "Read verse out loud for pleasure.", "subset": "street_5dB", "task_type": "understanding", "prediction": "read verse out loud for pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp05_street_sn5.wav", "answer": "Wipe the grease off his dirty face.", "subset": "street_5dB", "task_type": "understanding", "prediction": "wipes the grease off his dirty face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp06_street_sn5.wav", "answer": "Men strive but seldom get rich.", "subset": "street_5dB", "task_type": "understanding", "prediction": "men strive but seldom believe", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp07_street_sn5.wav", "answer": "We find joy in the simplest things.", "subset": "street_5dB", "task_type": "understanding", "prediction": "we find joy in the simplest things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp08_street_sn5.wav", "answer": "Hedge apples may stain your hands green.", "subset": "street_5dB", "task_type": "understanding", "prediction": "hedge apples may stain your hands green", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp09_street_sn5.wav", "answer": "Hurdle the pit with the aid of a long pole.", "subset": "street_5dB", "task_type": "understanding", "prediction": "hurdle the pit with the aid of a long pole", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp10_street_sn5.wav", "answer": "The sky that morning was clear and bright blue.", "subset": "street_5dB", "task_type": "understanding", "prediction": "sky that morning was clear and bright", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp11_street_sn5.wav", "answer": "He wrote down a long list of items.", "subset": "street_5dB", "task_type": "understanding", "prediction": "He wrote down in long lists of items", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp12_street_sn5.wav", "answer": "The drip of the rain made a pleasant sound.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the drip of the rain made a pleasant sound", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp13_street_sn5.wav", "answer": "Smoke poured out of every crack.", "subset": "street_5dB", "task_type": "understanding", "prediction": "smoke poured out in eddies crack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp14_street_sn5.wav", "answer": "Hats are worn to tea and not to dinner.", "subset": "street_5dB", "task_type": "understanding", "prediction": "cats are born to pee and not to think", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp15_street_sn5.wav", "answer": "The clothes dried on a thin wooden rack.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the clothes dried on a thin wooden rack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp16_street_sn5.wav", "answer": "The stray cat gave birth to kittens.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the stray cat gave birth to kittens", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp17_street_sn5.wav", "answer": "The lazy cow lay in the cool grass.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the lazy cow lay in the cool grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp18_street_sn5.wav", "answer": "The friendly gang left the drug store.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the friendly gang left the drug store", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp19_street_sn5.wav", "answer": "We talked of the sideshow in the circus.", "subset": "street_5dB", "task_type": "understanding", "prediction": "and possibly the sideshow in the park", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp20_street_sn5.wav", "answer": "The set of china hit the floor with a crash.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the set of china hit the floor with a crash", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp21_street_sn5.wav", "answer": "Clams are small, round, soft and tasty.", "subset": "street_5dB", "task_type": "understanding", "prediction": "clams are small round soft and tasty", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp22_street_sn5.wav", "answer": "The line where the edges join was clean.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the line where the edges join with three", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp23_street_sn5.wav", "answer": "Stop whistling and watch the boys march.", "subset": "street_5dB", "task_type": "understanding", "prediction": "stop whistling and watch the boys march", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp24_street_sn5.wav", "answer": "A cruise in warm waters in a sleek yacht is fun.", "subset": "street_5dB", "task_type": "understanding", "prediction": "a cruise in warm waters in a sleek yacht", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp25_street_sn5.wav", "answer": "A good book informs of what we ought to know.", "subset": "street_5dB", "task_type": "understanding", "prediction": "a good book informs us what we ought to know", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp26_street_sn5.wav", "answer": "She has a smart way of wearing clothes.", "subset": "street_5dB", "task_type": "understanding", "prediction": "he has a smart way of wearing clothes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp27_street_sn5.wav", "answer": "Bring your best compass to the third class.", "subset": "street_5dB", "task_type": "understanding", "prediction": "bring your best compass to the third class", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp28_street_sn5.wav", "answer": "The club rented the rink for the fifth night.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the club rented the rink for the fifth night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp29_street_sn5.wav", "answer": "The flint sputtered and lit a pine torch.", "subset": "street_5dB", "task_type": "understanding", "prediction": "the flint sputtered and lit a pine cone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/street/5dB/sp30_street_sn5.wav", "answer": "Let's all join as we sing the last chorus.", "subset": "street_5dB", "task_type": "understanding", "prediction": "that god going as we sing the last chorus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus_default_performance.json b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus_default_performance.json
new file mode 100644
index 0000000000000000000000000000000000000000..3e3077325311d1269eebfd9d55be94553f6293eb
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus_default_performance.json
@@ -0,0 +1,121 @@
+{
+ "task": "ASR",
+ "dataset": "noizeus",
+ "model": "Qwen2.5-Omni-7B-lora2",
+ "date": "2025-12-21 12:17:22.272478",
+ "performance": {
+ "airport_0dB": {
+ "wer": 28.51,
+ "total": 30
+ },
+ "airport_10dB": {
+ "wer": 1.24,
+ "total": 30
+ },
+ "airport_15dB": {
+ "wer": 1.24,
+ "total": 30
+ },
+ "airport_5dB": {
+ "wer": 7.44,
+ "total": 30
+ },
+ "babble_0dB": {
+ "wer": 42.98,
+ "total": 30
+ },
+ "babble_10dB": {
+ "wer": 2.07,
+ "total": 30
+ },
+ "babble_15dB": {
+ "wer": 1.65,
+ "total": 30
+ },
+ "babble_5dB": {
+ "wer": 11.16,
+ "total": 30
+ },
+ "car_0dB": {
+ "wer": 45.45,
+ "total": 30
+ },
+ "car_10dB": {
+ "wer": 3.72,
+ "total": 30
+ },
+ "car_15dB": {
+ "wer": 1.24,
+ "total": 30
+ },
+ "car_5dB": {
+ "wer": 11.16,
+ "total": 30
+ },
+ "exhibition_0dB": {
+ "wer": 28.51,
+ "total": 30
+ },
+ "exhibition_10dB": {
+ "wer": 3.31,
+ "total": 30
+ },
+ "exhibition_15dB": {
+ "wer": 1.24,
+ "total": 30
+ },
+ "exhibition_5dB": {
+ "wer": 9.5,
+ "total": 30
+ },
+ "restaurant_0dB": {
+ "wer": 37.19,
+ "total": 30
+ },
+ "restaurant_10dB": {
+ "wer": 2.07,
+ "total": 30
+ },
+ "restaurant_15dB": {
+ "wer": 1.24,
+ "total": 30
+ },
+ "restaurant_5dB": {
+ "wer": 12.4,
+ "total": 30
+ },
+ "station_0dB": {
+ "wer": 36.36,
+ "total": 30
+ },
+ "station_10dB": {
+ "wer": 3.31,
+ "total": 30
+ },
+ "station_15dB": {
+ "wer": 1.65,
+ "total": 30
+ },
+ "station_5dB": {
+ "wer": 10.74,
+ "total": 30
+ },
+ "street_0dB": {
+ "wer": 36.78,
+ "total": 30
+ },
+ "street_10dB": {
+ "wer": 4.55,
+ "total": 30
+ },
+ "street_15dB": {
+ "wer": 1.24,
+ "total": 30
+ },
+ "street_5dB": {
+ "wer": 14.05,
+ "total": 30
+ }
+ },
+ "eval_method": "qwen2-audio-impl"
+}
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus_wer_details.jsonl b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus_wer_details.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..eae05bd283cba577b0ce96e1a9e454fa208376f7
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus_wer_details.jsonl
@@ -0,0 +1,840 @@
+{"index":0,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp01_airport_sn0.wav","answer":"The birch canoe slid on the smooth planks.","subset":"airport_0dB","task_type":"understanding","prediction":"diverse communities live and play","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":1,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp02_airport_sn0.wav","answer":"He knew the skill of the great young actress.","subset":"airport_0dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":2,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp03_airport_sn0.wav","answer":"Her purse was full of useless trash.","subset":"airport_0dB","task_type":"understanding","prediction":"impressed his full of decent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":3,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp04_airport_sn0.wav","answer":"Read verse out loud for pleasure.","subset":"airport_0dB","task_type":"understanding","prediction":"reverse out loud flush","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":4,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp05_airport_sn0.wav","answer":"Wipe the grease off his dirty face.","subset":"airport_0dB","task_type":"understanding","prediction":"Wipe the grease off the bearing face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":5,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp06_airport_sn0.wav","answer":"Men strive but seldom get rich.","subset":"airport_0dB","task_type":"understanding","prediction":"men strive but seldom win","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":6,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp07_airport_sn0.wav","answer":"We find joy in the simplest things.","subset":"airport_0dB","task_type":"understanding","prediction":"we find joy in the simplest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":7,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp08_airport_sn0.wav","answer":"Hedge apples may stain your hands green.","subset":"airport_0dB","task_type":"understanding","prediction":"hedge apples may stain your hands and clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":8,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp09_airport_sn0.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"airport_0dB","task_type":"understanding","prediction":"turtles of pitt with the aid of a lemming","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":9,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp10_airport_sn0.wav","answer":"The sky that morning was clear and bright blue.","subset":"airport_0dB","task_type":"understanding","prediction":"sky that morning was clear and bright","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":10,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp11_airport_sn0.wav","answer":"He wrote down a long list of items.","subset":"airport_0dB","task_type":"understanding","prediction":"he wrote down his long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":11,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp12_airport_sn0.wav","answer":"The drip of the rain made a pleasant sound.","subset":"airport_0dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":12,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp13_airport_sn0.wav","answer":"Smoke poured out of every crack.","subset":"airport_0dB","task_type":"understanding","prediction":"must pour out of every cranny","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":13,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp14_airport_sn0.wav","answer":"Hats are worn to tea and not to dinner.","subset":"airport_0dB","task_type":"understanding","prediction":"ask our warranty fee and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":14,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp15_airport_sn0.wav","answer":"The clothes dried on a thin wooden rack.","subset":"airport_0dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":15,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp16_airport_sn0.wav","answer":"The stray cat gave birth to kittens.","subset":"airport_0dB","task_type":"understanding","prediction":"the stray cat being first hit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":16,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp17_airport_sn0.wav","answer":"The lazy cow lay in the cool grass.","subset":"airport_0dB","task_type":"understanding","prediction":"the lazy cow laying in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":17,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp18_airport_sn0.wav","answer":"The friendly gang left the drug store.","subset":"airport_0dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":18,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp19_airport_sn0.wav","answer":"We talked of the sideshow in the circus.","subset":"airport_0dB","task_type":"understanding","prediction":"we tossed it to find snow in the park","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":19,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp20_airport_sn0.wav","answer":"The set of china hit the floor with a crash.","subset":"airport_0dB","task_type":"understanding","prediction":"the set of china hit the floor with a bang","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":20,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp21_airport_sn0.wav","answer":"Clams are small, round, soft and tasty.","subset":"airport_0dB","task_type":"understanding","prediction":"plants are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":21,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp22_airport_sn0.wav","answer":"The line where the edges join was clean.","subset":"airport_0dB","task_type":"understanding","prediction":"the line where the edges join","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":22,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp23_airport_sn0.wav","answer":"Stop whistling and watch the boys march.","subset":"airport_0dB","task_type":"understanding","prediction":"stop whistling and watch the boys run","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":23,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp24_airport_sn0.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"airport_0dB","task_type":"understanding","prediction":"A cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":24,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp25_airport_sn0.wav","answer":"A good book informs of what we ought to know.","subset":"airport_0dB","task_type":"understanding","prediction":"a good book informs us what we want","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":25,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp26_airport_sn0.wav","answer":"She has a smart way of wearing clothes.","subset":"airport_0dB","task_type":"understanding","prediction":"She has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":26,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp27_airport_sn0.wav","answer":"Bring your best compass to the third class.","subset":"airport_0dB","task_type":"understanding","prediction":"bring your best compass and a third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":27,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp28_airport_sn0.wav","answer":"The club rented the rink for the fifth night.","subset":"airport_0dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":28,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp29_airport_sn0.wav","answer":"The flint sputtered and lit a pine torch.","subset":"airport_0dB","task_type":"understanding","prediction":"the flint sputtered and lit a fine point","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":29,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/0dB\/sp30_airport_sn0.wav","answer":"Let's all join as we sing the last chorus.","subset":"airport_0dB","task_type":"understanding","prediction":"lets all join as we finish the last one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":30,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp01_airport_sn10.wav","answer":"The birch canoe slid on the smooth planks.","subset":"airport_10dB","task_type":"understanding","prediction":"the birch canoe slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":31,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp02_airport_sn10.wav","answer":"He knew the skill of the great young actress.","subset":"airport_10dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":32,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp03_airport_sn10.wav","answer":"Her purse was full of useless trash.","subset":"airport_10dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":33,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp04_airport_sn10.wav","answer":"Read verse out loud for pleasure.","subset":"airport_10dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":34,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp05_airport_sn10.wav","answer":"Wipe the grease off his dirty face.","subset":"airport_10dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":35,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp06_airport_sn10.wav","answer":"Men strive but seldom get rich.","subset":"airport_10dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":36,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp07_airport_sn10.wav","answer":"We find joy in the simplest things.","subset":"airport_10dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":37,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp08_airport_sn10.wav","answer":"Hedge apples may stain your hands green.","subset":"airport_10dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":38,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp09_airport_sn10.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"airport_10dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":39,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp10_airport_sn10.wav","answer":"The sky that morning was clear and bright blue.","subset":"airport_10dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":40,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp11_airport_sn10.wav","answer":"He wrote down a long list of items.","subset":"airport_10dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":41,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp12_airport_sn10.wav","answer":"The drip of the rain made a pleasant sound.","subset":"airport_10dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":42,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp13_airport_sn10.wav","answer":"Smoke poured out of every crack.","subset":"airport_10dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":43,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp14_airport_sn10.wav","answer":"Hats are worn to tea and not to dinner.","subset":"airport_10dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":44,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp15_airport_sn10.wav","answer":"The clothes dried on a thin wooden rack.","subset":"airport_10dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":45,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp16_airport_sn10.wav","answer":"The stray cat gave birth to kittens.","subset":"airport_10dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":46,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp17_airport_sn10.wav","answer":"The lazy cow lay in the cool grass.","subset":"airport_10dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":47,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp18_airport_sn10.wav","answer":"The friendly gang left the drug store.","subset":"airport_10dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":48,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp19_airport_sn10.wav","answer":"We talked of the sideshow in the circus.","subset":"airport_10dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":49,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp20_airport_sn10.wav","answer":"The set of china hit the floor with a crash.","subset":"airport_10dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":50,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp21_airport_sn10.wav","answer":"Clams are small, round, soft and tasty.","subset":"airport_10dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":51,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp22_airport_sn10.wav","answer":"The line where the edges join was clean.","subset":"airport_10dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":52,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp23_airport_sn10.wav","answer":"Stop whistling and watch the boys march.","subset":"airport_10dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":53,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp24_airport_sn10.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"airport_10dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":54,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp25_airport_sn10.wav","answer":"A good book informs of what we ought to know.","subset":"airport_10dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":55,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp26_airport_sn10.wav","answer":"She has a smart way of wearing clothes.","subset":"airport_10dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":56,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp27_airport_sn10.wav","answer":"Bring your best compass to the third class.","subset":"airport_10dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":57,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp28_airport_sn10.wav","answer":"The club rented the rink for the fifth night.","subset":"airport_10dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":58,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp29_airport_sn10.wav","answer":"The flint sputtered and lit a pine torch.","subset":"airport_10dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":59,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/10dB\/sp30_airport_sn10.wav","answer":"Let's all join as we sing the last chorus.","subset":"airport_10dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":60,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp01_airport_sn15.wav","answer":"The birch canoe slid on the smooth planks.","subset":"airport_15dB","task_type":"understanding","prediction":"the birch canoes slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":61,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp02_airport_sn15.wav","answer":"He knew the skill of the great young actress.","subset":"airport_15dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":62,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp03_airport_sn15.wav","answer":"Her purse was full of useless trash.","subset":"airport_15dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":63,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp04_airport_sn15.wav","answer":"Read verse out loud for pleasure.","subset":"airport_15dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":64,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp05_airport_sn15.wav","answer":"Wipe the grease off his dirty face.","subset":"airport_15dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":65,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp06_airport_sn15.wav","answer":"Men strive but seldom get rich.","subset":"airport_15dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":66,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp07_airport_sn15.wav","answer":"We find joy in the simplest things.","subset":"airport_15dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":67,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp08_airport_sn15.wav","answer":"Hedge apples may stain your hands green.","subset":"airport_15dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":68,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp09_airport_sn15.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"airport_15dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":69,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp10_airport_sn15.wav","answer":"The sky that morning was clear and bright blue.","subset":"airport_15dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":70,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp11_airport_sn15.wav","answer":"He wrote down a long list of items.","subset":"airport_15dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":71,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp12_airport_sn15.wav","answer":"The drip of the rain made a pleasant sound.","subset":"airport_15dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":72,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp13_airport_sn15.wav","answer":"Smoke poured out of every crack.","subset":"airport_15dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":73,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp14_airport_sn15.wav","answer":"Hats are worn to tea and not to dinner.","subset":"airport_15dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":74,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp15_airport_sn15.wav","answer":"The clothes dried on a thin wooden rack.","subset":"airport_15dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":75,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp16_airport_sn15.wav","answer":"The stray cat gave birth to kittens.","subset":"airport_15dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":76,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp17_airport_sn15.wav","answer":"The lazy cow lay in the cool grass.","subset":"airport_15dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":77,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp18_airport_sn15.wav","answer":"The friendly gang left the drug store.","subset":"airport_15dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":78,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp19_airport_sn15.wav","answer":"We talked of the sideshow in the circus.","subset":"airport_15dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":79,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp20_airport_sn15.wav","answer":"The set of china hit the floor with a crash.","subset":"airport_15dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":80,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp21_airport_sn15.wav","answer":"Clams are small, round, soft and tasty.","subset":"airport_15dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":81,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp22_airport_sn15.wav","answer":"The line where the edges join was clean.","subset":"airport_15dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":82,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp23_airport_sn15.wav","answer":"Stop whistling and watch the boys march.","subset":"airport_15dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":83,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp24_airport_sn15.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"airport_15dB","task_type":"understanding","prediction":"A cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":84,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp25_airport_sn15.wav","answer":"A good book informs of what we ought to know.","subset":"airport_15dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":85,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp26_airport_sn15.wav","answer":"She has a smart way of wearing clothes.","subset":"airport_15dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":86,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp27_airport_sn15.wav","answer":"Bring your best compass to the third class.","subset":"airport_15dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":87,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp28_airport_sn15.wav","answer":"The club rented the rink for the fifth night.","subset":"airport_15dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":88,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp29_airport_sn15.wav","answer":"The flint sputtered and lit a pine torch.","subset":"airport_15dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":89,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/15dB\/sp30_airport_sn15.wav","answer":"Let's all join as we sing the last chorus.","subset":"airport_15dB","task_type":"understanding","prediction":"lets all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":90,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp01_airport_sn5.wav","answer":"The birch canoe slid on the smooth planks.","subset":"airport_5dB","task_type":"understanding","prediction":"The birch canoe slid on the smooth water","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":91,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp02_airport_sn5.wav","answer":"He knew the skill of the great young actress.","subset":"airport_5dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":92,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp03_airport_sn5.wav","answer":"Her purse was full of useless trash.","subset":"airport_5dB","task_type":"understanding","prediction":"my purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":93,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp04_airport_sn5.wav","answer":"Read verse out loud for pleasure.","subset":"airport_5dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":94,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp05_airport_sn5.wav","answer":"Wipe the grease off his dirty face.","subset":"airport_5dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":95,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp06_airport_sn5.wav","answer":"Men strive but seldom get rich.","subset":"airport_5dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":96,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp07_airport_sn5.wav","answer":"We find joy in the simplest things.","subset":"airport_5dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":97,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp08_airport_sn5.wav","answer":"Hedge apples may stain your hands green.","subset":"airport_5dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":98,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp09_airport_sn5.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"airport_5dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":99,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp10_airport_sn5.wav","answer":"The sky that morning was clear and bright blue.","subset":"airport_5dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":100,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp11_airport_sn5.wav","answer":"He wrote down a long list of items.","subset":"airport_5dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":101,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp12_airport_sn5.wav","answer":"The drip of the rain made a pleasant sound.","subset":"airport_5dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":102,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp13_airport_sn5.wav","answer":"Smoke poured out of every crack.","subset":"airport_5dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":103,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp14_airport_sn5.wav","answer":"Hats are worn to tea and not to dinner.","subset":"airport_5dB","task_type":"understanding","prediction":"cats are born to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":104,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp15_airport_sn5.wav","answer":"The clothes dried on a thin wooden rack.","subset":"airport_5dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":105,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp16_airport_sn5.wav","answer":"The stray cat gave birth to kittens.","subset":"airport_5dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":106,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp17_airport_sn5.wav","answer":"The lazy cow lay in the cool grass.","subset":"airport_5dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":107,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp18_airport_sn5.wav","answer":"The friendly gang left the drug store.","subset":"airport_5dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":108,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp19_airport_sn5.wav","answer":"We talked of the sideshow in the circus.","subset":"airport_5dB","task_type":"understanding","prediction":"we talked of the side show in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":109,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp20_airport_sn5.wav","answer":"The set of china hit the floor with a crash.","subset":"airport_5dB","task_type":"understanding","prediction":"the set of china hit the floor with a crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":110,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp21_airport_sn5.wav","answer":"Clams are small, round, soft and tasty.","subset":"airport_5dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":111,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp22_airport_sn5.wav","answer":"The line where the edges join was clean.","subset":"airport_5dB","task_type":"understanding","prediction":"the line where the edges join was smooth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":112,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp23_airport_sn5.wav","answer":"Stop whistling and watch the boys march.","subset":"airport_5dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":113,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp24_airport_sn5.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"airport_5dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht in the sun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":114,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp25_airport_sn5.wav","answer":"A good book informs of what we ought to know.","subset":"airport_5dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":115,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp26_airport_sn5.wav","answer":"She has a smart way of wearing clothes.","subset":"airport_5dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":116,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp27_airport_sn5.wav","answer":"Bring your best compass to the third class.","subset":"airport_5dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":117,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp28_airport_sn5.wav","answer":"The club rented the rink for the fifth night.","subset":"airport_5dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":118,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp29_airport_sn5.wav","answer":"The flint sputtered and lit a pine torch.","subset":"airport_5dB","task_type":"understanding","prediction":"the flint suttered and lit a fine coals","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":119,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/airport\/5dB\/sp30_airport_sn5.wav","answer":"Let's all join as we sing the last chorus.","subset":"airport_5dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":120,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp01_babble_sn0.wav","answer":"The birch canoe slid on the smooth planks.","subset":"babble_0dB","task_type":"understanding","prediction":"first can use plant to use the one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":121,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp02_babble_sn0.wav","answer":"He knew the skill of the great young actress.","subset":"babble_0dB","task_type":"understanding","prediction":"he knew the skill of the great young man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":122,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp03_babble_sn0.wav","answer":"Her purse was full of useless trash.","subset":"babble_0dB","task_type":"understanding","prediction":"the purse was full of beautiful stones","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":123,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp04_babble_sn0.wav","answer":"Read verse out loud for pleasure.","subset":"babble_0dB","task_type":"understanding","prediction":"read verse out loud and flush","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":124,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp05_babble_sn0.wav","answer":"Wipe the grease off his dirty face.","subset":"babble_0dB","task_type":"understanding","prediction":"wipes the grease off of jared s face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":125,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp06_babble_sn0.wav","answer":"Men strive but seldom get rich.","subset":"babble_0dB","task_type":"understanding","prediction":"themselves dry after they went selvage down","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":126,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp07_babble_sn0.wav","answer":"We find joy in the simplest things.","subset":"babble_0dB","task_type":"understanding","prediction":"we find two ways","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":127,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp08_babble_sn0.wav","answer":"Hedge apples may stain your hands green.","subset":"babble_0dB","task_type":"understanding","prediction":"ed apple may stain your hands and tongue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":128,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp09_babble_sn0.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"babble_0dB","task_type":"understanding","prediction":"hurdles of pitch with the aid of a long throw","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":129,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp10_babble_sn0.wav","answer":"The sky that morning was clear and bright blue.","subset":"babble_0dB","task_type":"understanding","prediction":"sky that morning was clear and bright","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":130,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp11_babble_sn0.wav","answer":"He wrote down a long list of items.","subset":"babble_0dB","task_type":"understanding","prediction":"he wrote down a long list of","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":131,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp12_babble_sn0.wav","answer":"The drip of the rain made a pleasant sound.","subset":"babble_0dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":132,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp13_babble_sn0.wav","answer":"Smoke poured out of every crack.","subset":"babble_0dB","task_type":"understanding","prediction":"poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":133,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp14_babble_sn0.wav","answer":"Hats are worn to tea and not to dinner.","subset":"babble_0dB","task_type":"understanding","prediction":"pass all four to tia and not anything","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":134,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp15_babble_sn0.wav","answer":"The clothes dried on a thin wooden rack.","subset":"babble_0dB","task_type":"understanding","prediction":"the clothes dried on the same clothesline","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":135,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp16_babble_sn0.wav","answer":"The stray cat gave birth to kittens.","subset":"babble_0dB","task_type":"understanding","prediction":"the stray cat gave first tips","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":136,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp17_babble_sn0.wav","answer":"The lazy cow lay in the cool grass.","subset":"babble_0dB","task_type":"understanding","prediction":"the lazy cow laying the cool back","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":137,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp18_babble_sn0.wav","answer":"The friendly gang left the drug store.","subset":"babble_0dB","task_type":"understanding","prediction":"the friendly game left the drunk","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":138,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp19_babble_sn0.wav","answer":"We talked of the sideshow in the circus.","subset":"babble_0dB","task_type":"understanding","prediction":"we cautioned the high school and church","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":139,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp20_babble_sn0.wav","answer":"The set of china hit the floor with a crash.","subset":"babble_0dB","task_type":"understanding","prediction":"the set of china hit the floor with a crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":140,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp21_babble_sn0.wav","answer":"Clams are small, round, soft and tasty.","subset":"babble_0dB","task_type":"understanding","prediction":"clamper small and large size","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":141,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp22_babble_sn0.wav","answer":"The line where the edges join was clean.","subset":"babble_0dB","task_type":"understanding","prediction":"align where the edges join","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":142,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp23_babble_sn0.wav","answer":"Stop whistling and watch the boys march.","subset":"babble_0dB","task_type":"understanding","prediction":"stop whistling as much as the boys are","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":143,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp24_babble_sn0.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"babble_0dB","task_type":"understanding","prediction":"a cruise in the wild waters of the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":144,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp25_babble_sn0.wav","answer":"A good book informs of what we ought to know.","subset":"babble_0dB","task_type":"understanding","prediction":"facebook informs us that we are","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":145,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp26_babble_sn0.wav","answer":"She has a smart way of wearing clothes.","subset":"babble_0dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":146,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp27_babble_sn0.wav","answer":"Bring your best compass to the third class.","subset":"babble_0dB","task_type":"understanding","prediction":"bring your best compass to the very class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":147,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp28_babble_sn0.wav","answer":"The club rented the rink for the fifth night.","subset":"babble_0dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":148,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp29_babble_sn0.wav","answer":"The flint sputtered and lit a pine torch.","subset":"babble_0dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine point","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":149,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/0dB\/sp30_babble_sn0.wav","answer":"Let's all join as we sing the last chorus.","subset":"babble_0dB","task_type":"understanding","prediction":"let s not join as we clean the last part","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":150,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp01_babble_sn10.wav","answer":"The birch canoe slid on the smooth planks.","subset":"babble_10dB","task_type":"understanding","prediction":"the birch canoes slid on the smooth plank","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":151,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp02_babble_sn10.wav","answer":"He knew the skill of the great young actress.","subset":"babble_10dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":152,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp03_babble_sn10.wav","answer":"Her purse was full of useless trash.","subset":"babble_10dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":153,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp04_babble_sn10.wav","answer":"Read verse out loud for pleasure.","subset":"babble_10dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":154,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp05_babble_sn10.wav","answer":"Wipe the grease off his dirty face.","subset":"babble_10dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":155,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp06_babble_sn10.wav","answer":"Men strive but seldom get rich.","subset":"babble_10dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":156,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp07_babble_sn10.wav","answer":"We find joy in the simplest things.","subset":"babble_10dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":157,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp08_babble_sn10.wav","answer":"Hedge apples may stain your hands green.","subset":"babble_10dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":158,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp09_babble_sn10.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"babble_10dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":159,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp10_babble_sn10.wav","answer":"The sky that morning was clear and bright blue.","subset":"babble_10dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":160,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp11_babble_sn10.wav","answer":"He wrote down a long list of items.","subset":"babble_10dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":161,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp12_babble_sn10.wav","answer":"The drip of the rain made a pleasant sound.","subset":"babble_10dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":162,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp13_babble_sn10.wav","answer":"Smoke poured out of every crack.","subset":"babble_10dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":163,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp14_babble_sn10.wav","answer":"Hats are worn to tea and not to dinner.","subset":"babble_10dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":164,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp15_babble_sn10.wav","answer":"The clothes dried on a thin wooden rack.","subset":"babble_10dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":165,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp16_babble_sn10.wav","answer":"The stray cat gave birth to kittens.","subset":"babble_10dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":166,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp17_babble_sn10.wav","answer":"The lazy cow lay in the cool grass.","subset":"babble_10dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":167,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp18_babble_sn10.wav","answer":"The friendly gang left the drug store.","subset":"babble_10dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":168,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp19_babble_sn10.wav","answer":"We talked of the sideshow in the circus.","subset":"babble_10dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":169,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp20_babble_sn10.wav","answer":"The set of china hit the floor with a crash.","subset":"babble_10dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":170,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp21_babble_sn10.wav","answer":"Clams are small, round, soft and tasty.","subset":"babble_10dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":171,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp22_babble_sn10.wav","answer":"The line where the edges join was clean.","subset":"babble_10dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":172,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp23_babble_sn10.wav","answer":"Stop whistling and watch the boys march.","subset":"babble_10dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":173,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp24_babble_sn10.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"babble_10dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":174,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp25_babble_sn10.wav","answer":"A good book informs of what we ought to know.","subset":"babble_10dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":175,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp26_babble_sn10.wav","answer":"She has a smart way of wearing clothes.","subset":"babble_10dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":176,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp27_babble_sn10.wav","answer":"Bring your best compass to the third class.","subset":"babble_10dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":177,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp28_babble_sn10.wav","answer":"The club rented the rink for the fifth night.","subset":"babble_10dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":178,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp29_babble_sn10.wav","answer":"The flint sputtered and lit a pine torch.","subset":"babble_10dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":179,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/10dB\/sp30_babble_sn10.wav","answer":"Let's all join as we sing the last chorus.","subset":"babble_10dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":180,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp01_babble_sn15.wav","answer":"The birch canoe slid on the smooth planks.","subset":"babble_15dB","task_type":"understanding","prediction":"the birch canoe slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":181,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp02_babble_sn15.wav","answer":"He knew the skill of the great young actress.","subset":"babble_15dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":182,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp03_babble_sn15.wav","answer":"Her purse was full of useless trash.","subset":"babble_15dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":183,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp04_babble_sn15.wav","answer":"Read verse out loud for pleasure.","subset":"babble_15dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":184,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp05_babble_sn15.wav","answer":"Wipe the grease off his dirty face.","subset":"babble_15dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":185,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp06_babble_sn15.wav","answer":"Men strive but seldom get rich.","subset":"babble_15dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":186,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp07_babble_sn15.wav","answer":"We find joy in the simplest things.","subset":"babble_15dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":187,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp08_babble_sn15.wav","answer":"Hedge apples may stain your hands green.","subset":"babble_15dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":188,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp09_babble_sn15.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"babble_15dB","task_type":"understanding","prediction":"hurdled a pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":189,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp10_babble_sn15.wav","answer":"The sky that morning was clear and bright blue.","subset":"babble_15dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":190,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp11_babble_sn15.wav","answer":"He wrote down a long list of items.","subset":"babble_15dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":191,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp12_babble_sn15.wav","answer":"The drip of the rain made a pleasant sound.","subset":"babble_15dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":192,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp13_babble_sn15.wav","answer":"Smoke poured out of every crack.","subset":"babble_15dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":193,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp14_babble_sn15.wav","answer":"Hats are worn to tea and not to dinner.","subset":"babble_15dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":194,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp15_babble_sn15.wav","answer":"The clothes dried on a thin wooden rack.","subset":"babble_15dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":195,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp16_babble_sn15.wav","answer":"The stray cat gave birth to kittens.","subset":"babble_15dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":196,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp17_babble_sn15.wav","answer":"The lazy cow lay in the cool grass.","subset":"babble_15dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":197,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp18_babble_sn15.wav","answer":"The friendly gang left the drug store.","subset":"babble_15dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":198,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp19_babble_sn15.wav","answer":"We talked of the sideshow in the circus.","subset":"babble_15dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":199,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp20_babble_sn15.wav","answer":"The set of china hit the floor with a crash.","subset":"babble_15dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":200,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp21_babble_sn15.wav","answer":"Clams are small, round, soft and tasty.","subset":"babble_15dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":201,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp22_babble_sn15.wav","answer":"The line where the edges join was clean.","subset":"babble_15dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":202,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp23_babble_sn15.wav","answer":"Stop whistling and watch the boys march.","subset":"babble_15dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":203,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp24_babble_sn15.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"babble_15dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":204,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp25_babble_sn15.wav","answer":"A good book informs of what we ought to know.","subset":"babble_15dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":205,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp26_babble_sn15.wav","answer":"She has a smart way of wearing clothes.","subset":"babble_15dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":206,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp27_babble_sn15.wav","answer":"Bring your best compass to the third class.","subset":"babble_15dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":207,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp28_babble_sn15.wav","answer":"The club rented the rink for the fifth night.","subset":"babble_15dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":208,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp29_babble_sn15.wav","answer":"The flint sputtered and lit a pine torch.","subset":"babble_15dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":209,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/15dB\/sp30_babble_sn15.wav","answer":"Let's all join as we sing the last chorus.","subset":"babble_15dB","task_type":"understanding","prediction":"lets all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":210,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp01_babble_sn5.wav","answer":"The birch canoe slid on the smooth planks.","subset":"babble_5dB","task_type":"understanding","prediction":"the birch canoes slid from smooth points","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":211,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp02_babble_sn5.wav","answer":"He knew the skill of the great young actress.","subset":"babble_5dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":212,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp03_babble_sn5.wav","answer":"Her purse was full of useless trash.","subset":"babble_5dB","task_type":"understanding","prediction":"The purse is full of useless crap","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":213,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp04_babble_sn5.wav","answer":"Read verse out loud for pleasure.","subset":"babble_5dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":214,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp05_babble_sn5.wav","answer":"Wipe the grease off his dirty face.","subset":"babble_5dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":215,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp06_babble_sn5.wav","answer":"Men strive but seldom get rich.","subset":"babble_5dB","task_type":"understanding","prediction":"men strive but seldom achieve","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":216,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp07_babble_sn5.wav","answer":"We find joy in the simplest things.","subset":"babble_5dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":217,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp08_babble_sn5.wav","answer":"Hedge apples may stain your hands green.","subset":"babble_5dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":218,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp09_babble_sn5.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"babble_5dB","task_type":"understanding","prediction":"hurdle the fence with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":219,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp10_babble_sn5.wav","answer":"The sky that morning was clear and bright blue.","subset":"babble_5dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":220,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp11_babble_sn5.wav","answer":"He wrote down a long list of items.","subset":"babble_5dB","task_type":"understanding","prediction":"He wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":221,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp12_babble_sn5.wav","answer":"The drip of the rain made a pleasant sound.","subset":"babble_5dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":222,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp13_babble_sn5.wav","answer":"Smoke poured out of every crack.","subset":"babble_5dB","task_type":"understanding","prediction":"smoke poured out as every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":223,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp14_babble_sn5.wav","answer":"Hats are worn to tea and not to dinner.","subset":"babble_5dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":224,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp15_babble_sn5.wav","answer":"The clothes dried on a thin wooden rack.","subset":"babble_5dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":225,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp16_babble_sn5.wav","answer":"The stray cat gave birth to kittens.","subset":"babble_5dB","task_type":"understanding","prediction":"the stray cat you first kidnapped","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":226,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp17_babble_sn5.wav","answer":"The lazy cow lay in the cool grass.","subset":"babble_5dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":227,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp18_babble_sn5.wav","answer":"The friendly gang left the drug store.","subset":"babble_5dB","task_type":"understanding","prediction":"the friendly gang left the drug","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":228,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp19_babble_sn5.wav","answer":"We talked of the sideshow in the circus.","subset":"babble_5dB","task_type":"understanding","prediction":"we talked of the fight show in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":229,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp20_babble_sn5.wav","answer":"The set of china hit the floor with a crash.","subset":"babble_5dB","task_type":"understanding","prediction":"the set of china hit the floor with a crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":230,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp21_babble_sn5.wav","answer":"Clams are small, round, soft and tasty.","subset":"babble_5dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":231,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp22_babble_sn5.wav","answer":"The line where the edges join was clean.","subset":"babble_5dB","task_type":"understanding","prediction":"the line where the edges join with the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":232,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp23_babble_sn5.wav","answer":"Stop whistling and watch the boys march.","subset":"babble_5dB","task_type":"understanding","prediction":"Stop whistling and watch the boys tomorrow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":233,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp24_babble_sn5.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"babble_5dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":234,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp25_babble_sn5.wav","answer":"A good book informs of what we ought to know.","subset":"babble_5dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":235,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp26_babble_sn5.wav","answer":"She has a smart way of wearing clothes.","subset":"babble_5dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":236,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp27_babble_sn5.wav","answer":"Bring your best compass to the third class.","subset":"babble_5dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":237,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp28_babble_sn5.wav","answer":"The club rented the rink for the fifth night.","subset":"babble_5dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":238,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp29_babble_sn5.wav","answer":"The flint sputtered and lit a pine torch.","subset":"babble_5dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine twig","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":239,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/babble\/5dB\/sp30_babble_sn5.wav","answer":"Let's all join as we sing the last chorus.","subset":"babble_5dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":240,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp01_car_sn0.wav","answer":"The birch canoe slid on the smooth planks.","subset":"car_0dB","task_type":"understanding","prediction":"very few","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":241,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp02_car_sn0.wav","answer":"He knew the skill of the great young actress.","subset":"car_0dB","task_type":"understanding","prediction":"he knew the skill of the great young man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":242,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp03_car_sn0.wav","answer":"Her purse was full of useless trash.","subset":"car_0dB","task_type":"understanding","prediction":"the first school","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":243,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp04_car_sn0.wav","answer":"Read verse out loud for pleasure.","subset":"car_0dB","task_type":"understanding","prediction":"reverse out loud","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":244,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp05_car_sn0.wav","answer":"Wipe the grease off his dirty face.","subset":"car_0dB","task_type":"understanding","prediction":"wipes the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":245,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp06_car_sn0.wav","answer":"Men strive but seldom get rich.","subset":"car_0dB","task_type":"understanding","prediction":"men strive but seldom achieve","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":246,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp07_car_sn0.wav","answer":"We find joy in the simplest things.","subset":"car_0dB","task_type":"understanding","prediction":"we find joy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":247,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp08_car_sn0.wav","answer":"Hedge apples may stain your hands green.","subset":"car_0dB","task_type":"understanding","prediction":"hedge apples may stain your hands and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":248,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp09_car_sn0.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"car_0dB","task_type":"understanding","prediction":"turtles of pitch with the aid of a long","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":249,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp10_car_sn0.wav","answer":"The sky that morning was clear and bright blue.","subset":"car_0dB","task_type":"understanding","prediction":"guy that morning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":250,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp11_car_sn0.wav","answer":"He wrote down a long list of items.","subset":"car_0dB","task_type":"understanding","prediction":"he wrote down his long list of ideas","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":251,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp12_car_sn0.wav","answer":"The drip of the rain made a pleasant sound.","subset":"car_0dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":252,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp13_car_sn0.wav","answer":"Smoke poured out of every crack.","subset":"car_0dB","task_type":"understanding","prediction":"moss poured out of the mrs cramp","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":253,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp14_car_sn0.wav","answer":"Hats are worn to tea and not to dinner.","subset":"car_0dB","task_type":"understanding","prediction":"pass on one to kate and not to kim","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":254,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp15_car_sn0.wav","answer":"The clothes dried on a thin wooden rack.","subset":"car_0dB","task_type":"understanding","prediction":"the clothes dry on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":255,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp16_car_sn0.wav","answer":"The stray cat gave birth to kittens.","subset":"car_0dB","task_type":"understanding","prediction":"the street tattoo first hit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":256,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp17_car_sn0.wav","answer":"The lazy cow lay in the cool grass.","subset":"car_0dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":257,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp18_car_sn0.wav","answer":"The friendly gang left the drug store.","subset":"car_0dB","task_type":"understanding","prediction":"the friendliness","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":258,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp19_car_sn0.wav","answer":"We talked of the sideshow in the circus.","subset":"car_0dB","task_type":"understanding","prediction":"he possibly hide","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":259,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp20_car_sn0.wav","answer":"The set of china hit the floor with a crash.","subset":"car_0dB","task_type":"understanding","prediction":"instead of china hit the floor with a thud","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":260,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp21_car_sn0.wav","answer":"Clams are small, round, soft and tasty.","subset":"car_0dB","task_type":"understanding","prediction":"plants are small","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":261,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp22_car_sn0.wav","answer":"The line where the edges join was clean.","subset":"car_0dB","task_type":"understanding","prediction":"the line where the edges join is smooth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":262,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp23_car_sn0.wav","answer":"Stop whistling and watch the boys march.","subset":"car_0dB","task_type":"understanding","prediction":"stop whistling and watch the boy run","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":263,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp24_car_sn0.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"car_0dB","task_type":"understanding","prediction":"are frilled in warm waters and sleep","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":264,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp25_car_sn0.wav","answer":"A good book informs of what we ought to know.","subset":"car_0dB","task_type":"understanding","prediction":"good","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":265,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp26_car_sn0.wav","answer":"She has a smart way of wearing clothes.","subset":"car_0dB","task_type":"understanding","prediction":"she has a smart way in wearing things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":266,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp27_car_sn0.wav","answer":"Bring your best compass to the third class.","subset":"car_0dB","task_type":"understanding","prediction":"bring your best to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":267,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp28_car_sn0.wav","answer":"The club rented the rink for the fifth night.","subset":"car_0dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":268,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp29_car_sn0.wav","answer":"The flint sputtered and lit a pine torch.","subset":"car_0dB","task_type":"understanding","prediction":"the flint sputtered and lit a pinecone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":269,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/0dB\/sp30_car_sn0.wav","answer":"Let's all join as we sing the last chorus.","subset":"car_0dB","task_type":"understanding","prediction":"let s all join as we see in the left","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":270,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp01_car_sn10.wav","answer":"The birch canoe slid on the smooth planks.","subset":"car_10dB","task_type":"understanding","prediction":"the birch canoes slid on smooth water","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":271,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp02_car_sn10.wav","answer":"He knew the skill of the great young actress.","subset":"car_10dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":272,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp03_car_sn10.wav","answer":"Her purse was full of useless trash.","subset":"car_10dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":273,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp04_car_sn10.wav","answer":"Read verse out loud for pleasure.","subset":"car_10dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":274,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp05_car_sn10.wav","answer":"Wipe the grease off his dirty face.","subset":"car_10dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":275,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp06_car_sn10.wav","answer":"Men strive but seldom get rich.","subset":"car_10dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":276,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp07_car_sn10.wav","answer":"We find joy in the simplest things.","subset":"car_10dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":277,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp08_car_sn10.wav","answer":"Hedge apples may stain your hands green.","subset":"car_10dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":278,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp09_car_sn10.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"car_10dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":279,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp10_car_sn10.wav","answer":"The sky that morning was clear and bright blue.","subset":"car_10dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":280,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp11_car_sn10.wav","answer":"He wrote down a long list of items.","subset":"car_10dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":281,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp12_car_sn10.wav","answer":"The drip of the rain made a pleasant sound.","subset":"car_10dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":282,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp13_car_sn10.wav","answer":"Smoke poured out of every crack.","subset":"car_10dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":283,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp14_car_sn10.wav","answer":"Hats are worn to tea and not to dinner.","subset":"car_10dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":284,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp15_car_sn10.wav","answer":"The clothes dried on a thin wooden rack.","subset":"car_10dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":285,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp16_car_sn10.wav","answer":"The stray cat gave birth to kittens.","subset":"car_10dB","task_type":"understanding","prediction":"the stray cat seems first to hit me","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":286,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp17_car_sn10.wav","answer":"The lazy cow lay in the cool grass.","subset":"car_10dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":287,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp18_car_sn10.wav","answer":"The friendly gang left the drug store.","subset":"car_10dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":288,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp19_car_sn10.wav","answer":"We talked of the sideshow in the circus.","subset":"car_10dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":289,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp20_car_sn10.wav","answer":"The set of china hit the floor with a crash.","subset":"car_10dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":290,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp21_car_sn10.wav","answer":"Clams are small, round, soft and tasty.","subset":"car_10dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":291,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp22_car_sn10.wav","answer":"The line where the edges join was clean.","subset":"car_10dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":292,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp23_car_sn10.wav","answer":"Stop whistling and watch the boys march.","subset":"car_10dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":293,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp24_car_sn10.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"car_10dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":294,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp25_car_sn10.wav","answer":"A good book informs of what we ought to know.","subset":"car_10dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":295,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp26_car_sn10.wav","answer":"She has a smart way of wearing clothes.","subset":"car_10dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":296,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp27_car_sn10.wav","answer":"Bring your best compass to the third class.","subset":"car_10dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":297,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp28_car_sn10.wav","answer":"The club rented the rink for the fifth night.","subset":"car_10dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":298,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp29_car_sn10.wav","answer":"The flint sputtered and lit a pine torch.","subset":"car_10dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":299,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/10dB\/sp30_car_sn10.wav","answer":"Let's all join as we sing the last chorus.","subset":"car_10dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":300,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp01_car_sn15.wav","answer":"The birch canoe slid on the smooth planks.","subset":"car_15dB","task_type":"understanding","prediction":"the birch canoes slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":301,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp02_car_sn15.wav","answer":"He knew the skill of the great young actress.","subset":"car_15dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":302,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp03_car_sn15.wav","answer":"Her purse was full of useless trash.","subset":"car_15dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":303,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp04_car_sn15.wav","answer":"Read verse out loud for pleasure.","subset":"car_15dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":304,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp05_car_sn15.wav","answer":"Wipe the grease off his dirty face.","subset":"car_15dB","task_type":"understanding","prediction":"wiped the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":305,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp06_car_sn15.wav","answer":"Men strive but seldom get rich.","subset":"car_15dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":306,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp07_car_sn15.wav","answer":"We find joy in the simplest things.","subset":"car_15dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":307,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp08_car_sn15.wav","answer":"Hedge apples may stain your hands green.","subset":"car_15dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":308,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp09_car_sn15.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"car_15dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":309,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp10_car_sn15.wav","answer":"The sky that morning was clear and bright blue.","subset":"car_15dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":310,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp11_car_sn15.wav","answer":"He wrote down a long list of items.","subset":"car_15dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":311,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp12_car_sn15.wav","answer":"The drip of the rain made a pleasant sound.","subset":"car_15dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":312,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp13_car_sn15.wav","answer":"Smoke poured out of every crack.","subset":"car_15dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":313,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp14_car_sn15.wav","answer":"Hats are worn to tea and not to dinner.","subset":"car_15dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":314,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp15_car_sn15.wav","answer":"The clothes dried on a thin wooden rack.","subset":"car_15dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":315,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp16_car_sn15.wav","answer":"The stray cat gave birth to kittens.","subset":"car_15dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":316,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp17_car_sn15.wav","answer":"The lazy cow lay in the cool grass.","subset":"car_15dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":317,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp18_car_sn15.wav","answer":"The friendly gang left the drug store.","subset":"car_15dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":318,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp19_car_sn15.wav","answer":"We talked of the sideshow in the circus.","subset":"car_15dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":319,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp20_car_sn15.wav","answer":"The set of china hit the floor with a crash.","subset":"car_15dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":320,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp21_car_sn15.wav","answer":"Clams are small, round, soft and tasty.","subset":"car_15dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":321,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp22_car_sn15.wav","answer":"The line where the edges join was clean.","subset":"car_15dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":322,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp23_car_sn15.wav","answer":"Stop whistling and watch the boys march.","subset":"car_15dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":323,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp24_car_sn15.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"car_15dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":324,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp25_car_sn15.wav","answer":"A good book informs of what we ought to know.","subset":"car_15dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":325,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp26_car_sn15.wav","answer":"She has a smart way of wearing clothes.","subset":"car_15dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":326,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp27_car_sn15.wav","answer":"Bring your best compass to the third class.","subset":"car_15dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":327,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp28_car_sn15.wav","answer":"The club rented the rink for the fifth night.","subset":"car_15dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":328,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp29_car_sn15.wav","answer":"The flint sputtered and lit a pine torch.","subset":"car_15dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":329,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/15dB\/sp30_car_sn15.wav","answer":"Let's all join as we sing the last chorus.","subset":"car_15dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":330,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp01_car_sn5.wav","answer":"The birch canoe slid on the smooth planks.","subset":"car_5dB","task_type":"understanding","prediction":"the birch canoe slid on the smooth plank","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":331,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp02_car_sn5.wav","answer":"He knew the skill of the great young actress.","subset":"car_5dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":332,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp03_car_sn5.wav","answer":"Her purse was full of useless trash.","subset":"car_5dB","task_type":"understanding","prediction":"the purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":333,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp04_car_sn5.wav","answer":"Read verse out loud for pleasure.","subset":"car_5dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":334,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp05_car_sn5.wav","answer":"Wipe the grease off his dirty face.","subset":"car_5dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":335,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp06_car_sn5.wav","answer":"Men strive but seldom get rich.","subset":"car_5dB","task_type":"understanding","prediction":"men strive but seldom get","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":336,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp07_car_sn5.wav","answer":"We find joy in the simplest things.","subset":"car_5dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":337,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp08_car_sn5.wav","answer":"Hedge apples may stain your hands green.","subset":"car_5dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":338,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp09_car_sn5.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"car_5dB","task_type":"understanding","prediction":"turtles assist with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":339,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp10_car_sn5.wav","answer":"The sky that morning was clear and bright blue.","subset":"car_5dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":340,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp11_car_sn5.wav","answer":"He wrote down a long list of items.","subset":"car_5dB","task_type":"understanding","prediction":"he wrote down his long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":341,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp12_car_sn5.wav","answer":"The drip of the rain made a pleasant sound.","subset":"car_5dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":342,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp13_car_sn5.wav","answer":"Smoke poured out of every crack.","subset":"car_5dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":343,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp14_car_sn5.wav","answer":"Hats are worn to tea and not to dinner.","subset":"car_5dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":344,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp15_car_sn5.wav","answer":"The clothes dried on a thin wooden rack.","subset":"car_5dB","task_type":"understanding","prediction":"The clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":345,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp16_car_sn5.wav","answer":"The stray cat gave birth to kittens.","subset":"car_5dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":346,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp17_car_sn5.wav","answer":"The lazy cow lay in the cool grass.","subset":"car_5dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":347,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp18_car_sn5.wav","answer":"The friendly gang left the drug store.","subset":"car_5dB","task_type":"understanding","prediction":"the friendly game at the drugstore","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":348,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp19_car_sn5.wav","answer":"We talked of the sideshow in the circus.","subset":"car_5dB","task_type":"understanding","prediction":"we fostered the side stove in the first","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":349,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp20_car_sn5.wav","answer":"The set of china hit the floor with a crash.","subset":"car_5dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":350,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp21_car_sn5.wav","answer":"Clams are small, round, soft and tasty.","subset":"car_5dB","task_type":"understanding","prediction":"plants are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":351,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp22_car_sn5.wav","answer":"The line where the edges join was clean.","subset":"car_5dB","task_type":"understanding","prediction":"the line where the edges join is smooth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":352,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp23_car_sn5.wav","answer":"Stop whistling and watch the boys march.","subset":"car_5dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":353,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp24_car_sn5.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"car_5dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht in fact","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":354,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp25_car_sn5.wav","answer":"A good book informs of what we ought to know.","subset":"car_5dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":355,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp26_car_sn5.wav","answer":"She has a smart way of wearing clothes.","subset":"car_5dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":356,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp27_car_sn5.wav","answer":"Bring your best compass to the third class.","subset":"car_5dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":357,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp28_car_sn5.wav","answer":"The club rented the rink for the fifth night.","subset":"car_5dB","task_type":"understanding","prediction":"the club rented the rink for the fifth and ninth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":358,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp29_car_sn5.wav","answer":"The flint sputtered and lit a pine torch.","subset":"car_5dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":359,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/car\/5dB\/sp30_car_sn5.wav","answer":"Let's all join as we sing the last chorus.","subset":"car_5dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":360,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp01_exhibition_sn0.wav","answer":"The birch canoe slid on the smooth planks.","subset":"exhibition_0dB","task_type":"understanding","prediction":"diverse communities led by smooth minds","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":361,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp02_exhibition_sn0.wav","answer":"He knew the skill of the great young actress.","subset":"exhibition_0dB","task_type":"understanding","prediction":"he knew the skill of the great young man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":362,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp03_exhibition_sn0.wav","answer":"Her purse was full of useless trash.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the purse is full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":363,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp04_exhibition_sn0.wav","answer":"Read verse out loud for pleasure.","subset":"exhibition_0dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":364,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp05_exhibition_sn0.wav","answer":"Wipe the grease off his dirty face.","subset":"exhibition_0dB","task_type":"understanding","prediction":"Wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":365,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp06_exhibition_sn0.wav","answer":"Men strive but seldom get rich.","subset":"exhibition_0dB","task_type":"understanding","prediction":"men strive but seldom get this","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":366,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp07_exhibition_sn0.wav","answer":"We find joy in the simplest things.","subset":"exhibition_0dB","task_type":"understanding","prediction":"we find hui english simplest form","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":367,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp08_exhibition_sn0.wav","answer":"Hedge apples may stain your hands green.","subset":"exhibition_0dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":368,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp09_exhibition_sn0.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"exhibition_0dB","task_type":"understanding","prediction":"turtles of pitch with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":369,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp10_exhibition_sn0.wav","answer":"The sky that morning was clear and bright blue.","subset":"exhibition_0dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":370,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp11_exhibition_sn0.wav","answer":"He wrote down a long list of items.","subset":"exhibition_0dB","task_type":"understanding","prediction":"he wrote down his long list of crimes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":371,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp12_exhibition_sn0.wav","answer":"The drip of the rain made a pleasant sound.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":372,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp13_exhibition_sn0.wav","answer":"Smoke poured out of every crack.","subset":"exhibition_0dB","task_type":"understanding","prediction":"smoke poured out of every crevice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":373,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp14_exhibition_sn0.wav","answer":"Hats are worn to tea and not to dinner.","subset":"exhibition_0dB","task_type":"understanding","prediction":"at a want to see and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":374,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp15_exhibition_sn0.wav","answer":"The clothes dried on a thin wooden rack.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the clothes dried on a thin clothing line","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":375,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp16_exhibition_sn0.wav","answer":"The stray cat gave birth to kittens.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the spray pack you first","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":376,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp17_exhibition_sn0.wav","answer":"The lazy cow lay in the cool grass.","subset":"exhibition_0dB","task_type":"understanding","prediction":"a lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":377,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp18_exhibition_sn0.wav","answer":"The friendly gang left the drug store.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":378,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp19_exhibition_sn0.wav","answer":"We talked of the sideshow in the circus.","subset":"exhibition_0dB","task_type":"understanding","prediction":"and foxes decide so in the future","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":379,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp20_exhibition_sn0.wav","answer":"The set of china hit the floor with a crash.","subset":"exhibition_0dB","task_type":"understanding","prediction":"instead of fineness of the soil with the cast","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":380,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp21_exhibition_sn0.wav","answer":"Clams are small, round, soft and tasty.","subset":"exhibition_0dB","task_type":"understanding","prediction":"clams are small and soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":381,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp22_exhibition_sn0.wav","answer":"The line where the edges join was clean.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the line where the edges join the screen","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":382,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp23_exhibition_sn0.wav","answer":"Stop whistling and watch the boys march.","subset":"exhibition_0dB","task_type":"understanding","prediction":"stop whippin and watch the boys in the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":383,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp24_exhibition_sn0.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"exhibition_0dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":384,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp25_exhibition_sn0.wav","answer":"A good book informs of what we ought to know.","subset":"exhibition_0dB","task_type":"understanding","prediction":"a dead fuck in forms of what you want man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":385,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp26_exhibition_sn0.wav","answer":"She has a smart way of wearing clothes.","subset":"exhibition_0dB","task_type":"understanding","prediction":"She has a smart way of learning things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":386,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp27_exhibition_sn0.wav","answer":"Bring your best compass to the third class.","subset":"exhibition_0dB","task_type":"understanding","prediction":"bring your best compass to the third","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":387,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp28_exhibition_sn0.wav","answer":"The club rented the rink for the fifth night.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the club run of the rink for the fifth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":388,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp29_exhibition_sn0.wav","answer":"The flint sputtered and lit a pine torch.","subset":"exhibition_0dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine cone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":389,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/0dB\/sp30_exhibition_sn0.wav","answer":"Let's all join as we sing the last chorus.","subset":"exhibition_0dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":390,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp01_exhibition_sn10.wav","answer":"The birch canoe slid on the smooth planks.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the birch canoe slid on the smooth plants","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":391,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp02_exhibition_sn10.wav","answer":"He knew the skill of the great young actress.","subset":"exhibition_10dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":392,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp03_exhibition_sn10.wav","answer":"Her purse was full of useless trash.","subset":"exhibition_10dB","task_type":"understanding","prediction":"my purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":393,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp04_exhibition_sn10.wav","answer":"Read verse out loud for pleasure.","subset":"exhibition_10dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":394,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp05_exhibition_sn10.wav","answer":"Wipe the grease off his dirty face.","subset":"exhibition_10dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":395,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp06_exhibition_sn10.wav","answer":"Men strive but seldom get rich.","subset":"exhibition_10dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":396,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp07_exhibition_sn10.wav","answer":"We find joy in the simplest things.","subset":"exhibition_10dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":397,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp08_exhibition_sn10.wav","answer":"Hedge apples may stain your hands green.","subset":"exhibition_10dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":398,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp09_exhibition_sn10.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"exhibition_10dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":399,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp10_exhibition_sn10.wav","answer":"The sky that morning was clear and bright blue.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":400,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp11_exhibition_sn10.wav","answer":"He wrote down a long list of items.","subset":"exhibition_10dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":401,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp12_exhibition_sn10.wav","answer":"The drip of the rain made a pleasant sound.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":402,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp13_exhibition_sn10.wav","answer":"Smoke poured out of every crack.","subset":"exhibition_10dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":403,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp14_exhibition_sn10.wav","answer":"Hats are worn to tea and not to dinner.","subset":"exhibition_10dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":404,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp15_exhibition_sn10.wav","answer":"The clothes dried on a thin wooden rack.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":405,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp16_exhibition_sn10.wav","answer":"The stray cat gave birth to kittens.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":406,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp17_exhibition_sn10.wav","answer":"The lazy cow lay in the cool grass.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":407,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp18_exhibition_sn10.wav","answer":"The friendly gang left the drug store.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":408,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp19_exhibition_sn10.wav","answer":"We talked of the sideshow in the circus.","subset":"exhibition_10dB","task_type":"understanding","prediction":"we toss of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":409,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp20_exhibition_sn10.wav","answer":"The set of china hit the floor with a crash.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the set of china hit the floor with a crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":410,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp21_exhibition_sn10.wav","answer":"Clams are small, round, soft and tasty.","subset":"exhibition_10dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":411,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp22_exhibition_sn10.wav","answer":"The line where the edges join was clean.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":412,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp23_exhibition_sn10.wav","answer":"Stop whistling and watch the boys march.","subset":"exhibition_10dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":413,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp24_exhibition_sn10.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"exhibition_10dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":414,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp25_exhibition_sn10.wav","answer":"A good book informs of what we ought to know.","subset":"exhibition_10dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":415,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp26_exhibition_sn10.wav","answer":"She has a smart way of wearing clothes.","subset":"exhibition_10dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":416,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp27_exhibition_sn10.wav","answer":"Bring your best compass to the third class.","subset":"exhibition_10dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":417,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp28_exhibition_sn10.wav","answer":"The club rented the rink for the fifth night.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":418,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp29_exhibition_sn10.wav","answer":"The flint sputtered and lit a pine torch.","subset":"exhibition_10dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine cone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":419,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/10dB\/sp30_exhibition_sn10.wav","answer":"Let's all join as we sing the last chorus.","subset":"exhibition_10dB","task_type":"understanding","prediction":"lets all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":420,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp01_exhibition_sn15.wav","answer":"The birch canoe slid on the smooth planks.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the birch canoes slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":421,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp02_exhibition_sn15.wav","answer":"He knew the skill of the great young actress.","subset":"exhibition_15dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":422,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp03_exhibition_sn15.wav","answer":"Her purse was full of useless trash.","subset":"exhibition_15dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":423,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp04_exhibition_sn15.wav","answer":"Read verse out loud for pleasure.","subset":"exhibition_15dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":424,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp05_exhibition_sn15.wav","answer":"Wipe the grease off his dirty face.","subset":"exhibition_15dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":425,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp06_exhibition_sn15.wav","answer":"Men strive but seldom get rich.","subset":"exhibition_15dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":426,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp07_exhibition_sn15.wav","answer":"We find joy in the simplest things.","subset":"exhibition_15dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":427,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp08_exhibition_sn15.wav","answer":"Hedge apples may stain your hands green.","subset":"exhibition_15dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":428,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp09_exhibition_sn15.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"exhibition_15dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":429,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp10_exhibition_sn15.wav","answer":"The sky that morning was clear and bright blue.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":430,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp11_exhibition_sn15.wav","answer":"He wrote down a long list of items.","subset":"exhibition_15dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":431,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp12_exhibition_sn15.wav","answer":"The drip of the rain made a pleasant sound.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":432,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp13_exhibition_sn15.wav","answer":"Smoke poured out of every crack.","subset":"exhibition_15dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":433,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp14_exhibition_sn15.wav","answer":"Hats are worn to tea and not to dinner.","subset":"exhibition_15dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":434,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp15_exhibition_sn15.wav","answer":"The clothes dried on a thin wooden rack.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":435,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp16_exhibition_sn15.wav","answer":"The stray cat gave birth to kittens.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":436,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp17_exhibition_sn15.wav","answer":"The lazy cow lay in the cool grass.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":437,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp18_exhibition_sn15.wav","answer":"The friendly gang left the drug store.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":438,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp19_exhibition_sn15.wav","answer":"We talked of the sideshow in the circus.","subset":"exhibition_15dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":439,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp20_exhibition_sn15.wav","answer":"The set of china hit the floor with a crash.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":440,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp21_exhibition_sn15.wav","answer":"Clams are small, round, soft and tasty.","subset":"exhibition_15dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":441,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp22_exhibition_sn15.wav","answer":"The line where the edges join was clean.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":442,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp23_exhibition_sn15.wav","answer":"Stop whistling and watch the boys march.","subset":"exhibition_15dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":443,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp24_exhibition_sn15.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"exhibition_15dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":444,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp25_exhibition_sn15.wav","answer":"A good book informs of what we ought to know.","subset":"exhibition_15dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":445,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp26_exhibition_sn15.wav","answer":"She has a smart way of wearing clothes.","subset":"exhibition_15dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":446,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp27_exhibition_sn15.wav","answer":"Bring your best compass to the third class.","subset":"exhibition_15dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":447,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp28_exhibition_sn15.wav","answer":"The club rented the rink for the fifth night.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":448,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp29_exhibition_sn15.wav","answer":"The flint sputtered and lit a pine torch.","subset":"exhibition_15dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":449,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/15dB\/sp30_exhibition_sn15.wav","answer":"Let's all join as we sing the last chorus.","subset":"exhibition_15dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":450,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp01_exhibition_sn5.wav","answer":"The birch canoe slid on the smooth planks.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the birch canoes slid on smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":451,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp02_exhibition_sn5.wav","answer":"He knew the skill of the great young actress.","subset":"exhibition_5dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":452,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp03_exhibition_sn5.wav","answer":"Her purse was full of useless trash.","subset":"exhibition_5dB","task_type":"understanding","prediction":"his purse was full of useless cash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":453,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp04_exhibition_sn5.wav","answer":"Read verse out loud for pleasure.","subset":"exhibition_5dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":454,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp05_exhibition_sn5.wav","answer":"Wipe the grease off his dirty face.","subset":"exhibition_5dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":455,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp06_exhibition_sn5.wav","answer":"Men strive but seldom get rich.","subset":"exhibition_5dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":456,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp07_exhibition_sn5.wav","answer":"We find joy in the simplest things.","subset":"exhibition_5dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":457,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp08_exhibition_sn5.wav","answer":"Hedge apples may stain your hands green.","subset":"exhibition_5dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":458,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp09_exhibition_sn5.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"exhibition_5dB","task_type":"understanding","prediction":"turtle the pitch with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":459,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp10_exhibition_sn5.wav","answer":"The sky that morning was clear and bright blue.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the sky that morning was clear and right","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":460,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp11_exhibition_sn5.wav","answer":"He wrote down a long list of items.","subset":"exhibition_5dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":461,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp12_exhibition_sn5.wav","answer":"The drip of the rain made a pleasant sound.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":462,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp13_exhibition_sn5.wav","answer":"Smoke poured out of every crack.","subset":"exhibition_5dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":463,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp14_exhibition_sn5.wav","answer":"Hats are worn to tea and not to dinner.","subset":"exhibition_5dB","task_type":"understanding","prediction":"hath a warrant to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":464,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp15_exhibition_sn5.wav","answer":"The clothes dried on a thin wooden rack.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":465,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp16_exhibition_sn5.wav","answer":"The stray cat gave birth to kittens.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":466,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp17_exhibition_sn5.wav","answer":"The lazy cow lay in the cool grass.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":467,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp18_exhibition_sn5.wav","answer":"The friendly gang left the drug store.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":468,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp19_exhibition_sn5.wav","answer":"We talked of the sideshow in the circus.","subset":"exhibition_5dB","task_type":"understanding","prediction":"we possibly decide so in the future","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":469,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp20_exhibition_sn5.wav","answer":"The set of china hit the floor with a crash.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":470,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp21_exhibition_sn5.wav","answer":"Clams are small, round, soft and tasty.","subset":"exhibition_5dB","task_type":"understanding","prediction":"crabs are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":471,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp22_exhibition_sn5.wav","answer":"The line where the edges join was clean.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the line where the edges join was smooth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":472,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp23_exhibition_sn5.wav","answer":"Stop whistling and watch the boys march.","subset":"exhibition_5dB","task_type":"understanding","prediction":"stop whittling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":473,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp24_exhibition_sn5.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"exhibition_5dB","task_type":"understanding","prediction":"a cruise in warm waters in a swift yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":474,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp25_exhibition_sn5.wav","answer":"A good book informs of what we ought to know.","subset":"exhibition_5dB","task_type":"understanding","prediction":"a good book informs us of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":475,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp26_exhibition_sn5.wav","answer":"She has a smart way of wearing clothes.","subset":"exhibition_5dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":476,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp27_exhibition_sn5.wav","answer":"Bring your best compass to the third class.","subset":"exhibition_5dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":477,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp28_exhibition_sn5.wav","answer":"The club rented the rink for the fifth night.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":478,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp29_exhibition_sn5.wav","answer":"The flint sputtered and lit a pine torch.","subset":"exhibition_5dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine cone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":479,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/exhibition\/5dB\/sp30_exhibition_sn5.wav","answer":"Let's all join as we sing the last chorus.","subset":"exhibition_5dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":480,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp01_restaurant_sn0.wav","answer":"The birch canoe slid on the smooth planks.","subset":"restaurant_0dB","task_type":"understanding","prediction":"diverse communities live in a humid climate","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":481,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp02_restaurant_sn0.wav","answer":"He knew the skill of the great young actress.","subset":"restaurant_0dB","task_type":"understanding","prediction":"he knew the skill of the great young man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":482,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp03_restaurant_sn0.wav","answer":"Her purse was full of useless trash.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the first is full of peoples hands","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":483,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp04_restaurant_sn0.wav","answer":"Read verse out loud for pleasure.","subset":"restaurant_0dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":484,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp05_restaurant_sn0.wav","answer":"Wipe the grease off his dirty face.","subset":"restaurant_0dB","task_type":"understanding","prediction":"wipes the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":485,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp06_restaurant_sn0.wav","answer":"Men strive but seldom get rich.","subset":"restaurant_0dB","task_type":"understanding","prediction":"men strive but seldom find","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":486,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp07_restaurant_sn0.wav","answer":"We find joy in the simplest things.","subset":"restaurant_0dB","task_type":"understanding","prediction":"we find joy in the simplest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":487,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp08_restaurant_sn0.wav","answer":"Hedge apples may stain your hands green.","subset":"restaurant_0dB","task_type":"understanding","prediction":"Hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":488,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp09_restaurant_sn0.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"restaurant_0dB","task_type":"understanding","prediction":"turtles of pitch with the aid of long","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":489,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp10_restaurant_sn0.wav","answer":"The sky that morning was clear and bright blue.","subset":"restaurant_0dB","task_type":"understanding","prediction":"sky that morning was clear and bright","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":490,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp11_restaurant_sn0.wav","answer":"He wrote down a long list of items.","subset":"restaurant_0dB","task_type":"understanding","prediction":"he wrote down in his notebook","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":491,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp12_restaurant_sn0.wav","answer":"The drip of the rain made a pleasant sound.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the drift of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":492,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp13_restaurant_sn0.wav","answer":"Smoke poured out of every crack.","subset":"restaurant_0dB","task_type":"understanding","prediction":"mum poured out his every crumb","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":493,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp14_restaurant_sn0.wav","answer":"Hats are worn to tea and not to dinner.","subset":"restaurant_0dB","task_type":"understanding","prediction":"at our point to see","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":494,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp15_restaurant_sn0.wav","answer":"The clothes dried on a thin wooden rack.","subset":"restaurant_0dB","task_type":"understanding","prediction":"close dry and thin what is that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":495,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp16_restaurant_sn0.wav","answer":"The stray cat gave birth to kittens.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the stray cat sees first hit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":496,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp17_restaurant_sn0.wav","answer":"The lazy cow lay in the cool grass.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":497,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp18_restaurant_sn0.wav","answer":"The friendly gang left the drug store.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the friendly gang left the driveway","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":498,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp19_restaurant_sn0.wav","answer":"We talked of the sideshow in the circus.","subset":"restaurant_0dB","task_type":"understanding","prediction":"you possibly could hide the room","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":499,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp20_restaurant_sn0.wav","answer":"The set of china hit the floor with a crash.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the scent of pine that hit the floor when you cracked","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":500,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp21_restaurant_sn0.wav","answer":"Clams are small, round, soft and tasty.","subset":"restaurant_0dB","task_type":"understanding","prediction":"small","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":501,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp22_restaurant_sn0.wav","answer":"The line where the edges join was clean.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the line where the edges join","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":502,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp23_restaurant_sn0.wav","answer":"Stop whistling and watch the boys march.","subset":"restaurant_0dB","task_type":"understanding","prediction":"stop whittling and watch a boy work","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":503,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp24_restaurant_sn0.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"restaurant_0dB","task_type":"understanding","prediction":"a cruise in warm waters on a sleek yacht","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":504,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp25_restaurant_sn0.wav","answer":"A good book informs of what we ought to know.","subset":"restaurant_0dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":505,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp26_restaurant_sn0.wav","answer":"She has a smart way of wearing clothes.","subset":"restaurant_0dB","task_type":"understanding","prediction":"She has a smart way of wearing them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":506,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp27_restaurant_sn0.wav","answer":"Bring your best compass to the third class.","subset":"restaurant_0dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":507,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp28_restaurant_sn0.wav","answer":"The club rented the rink for the fifth night.","subset":"restaurant_0dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":508,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp29_restaurant_sn0.wav","answer":"The flint sputtered and lit a pine torch.","subset":"restaurant_0dB","task_type":"understanding","prediction":"flint sputtered and lit a fine point","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":509,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/0dB\/sp30_restaurant_sn0.wav","answer":"Let's all join as we sing the last chorus.","subset":"restaurant_0dB","task_type":"understanding","prediction":"let us all join as we sing the last part","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":510,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp01_restaurant_sn10.wav","answer":"The birch canoe slid on the smooth planks.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the birch canoe slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":511,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp02_restaurant_sn10.wav","answer":"He knew the skill of the great young actress.","subset":"restaurant_10dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":512,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp03_restaurant_sn10.wav","answer":"Her purse was full of useless trash.","subset":"restaurant_10dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":513,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp04_restaurant_sn10.wav","answer":"Read verse out loud for pleasure.","subset":"restaurant_10dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":514,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp05_restaurant_sn10.wav","answer":"Wipe the grease off his dirty face.","subset":"restaurant_10dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":515,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp06_restaurant_sn10.wav","answer":"Men strive but seldom get rich.","subset":"restaurant_10dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":516,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp07_restaurant_sn10.wav","answer":"We find joy in the simplest things.","subset":"restaurant_10dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":517,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp08_restaurant_sn10.wav","answer":"Hedge apples may stain your hands green.","subset":"restaurant_10dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":518,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp09_restaurant_sn10.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"restaurant_10dB","task_type":"understanding","prediction":"hurdled a pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":519,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp10_restaurant_sn10.wav","answer":"The sky that morning was clear and bright blue.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":520,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp11_restaurant_sn10.wav","answer":"He wrote down a long list of items.","subset":"restaurant_10dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":521,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp12_restaurant_sn10.wav","answer":"The drip of the rain made a pleasant sound.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":522,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp13_restaurant_sn10.wav","answer":"Smoke poured out of every crack.","subset":"restaurant_10dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":523,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp14_restaurant_sn10.wav","answer":"Hats are worn to tea and not to dinner.","subset":"restaurant_10dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":524,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp15_restaurant_sn10.wav","answer":"The clothes dried on a thin wooden rack.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":525,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp16_restaurant_sn10.wav","answer":"The stray cat gave birth to kittens.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":526,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp17_restaurant_sn10.wav","answer":"The lazy cow lay in the cool grass.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":527,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp18_restaurant_sn10.wav","answer":"The friendly gang left the drug store.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":528,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp19_restaurant_sn10.wav","answer":"We talked of the sideshow in the circus.","subset":"restaurant_10dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":529,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp20_restaurant_sn10.wav","answer":"The set of china hit the floor with a crash.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":530,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp21_restaurant_sn10.wav","answer":"Clams are small, round, soft and tasty.","subset":"restaurant_10dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":531,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp22_restaurant_sn10.wav","answer":"The line where the edges join was clean.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":532,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp23_restaurant_sn10.wav","answer":"Stop whistling and watch the boys march.","subset":"restaurant_10dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":533,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp24_restaurant_sn10.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"restaurant_10dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":534,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp25_restaurant_sn10.wav","answer":"A good book informs of what we ought to know.","subset":"restaurant_10dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":535,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp26_restaurant_sn10.wav","answer":"She has a smart way of wearing clothes.","subset":"restaurant_10dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":536,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp27_restaurant_sn10.wav","answer":"Bring your best compass to the third class.","subset":"restaurant_10dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":537,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp28_restaurant_sn10.wav","answer":"The club rented the rink for the fifth night.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":538,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp29_restaurant_sn10.wav","answer":"The flint sputtered and lit a pine torch.","subset":"restaurant_10dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":539,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/10dB\/sp30_restaurant_sn10.wav","answer":"Let's all join as we sing the last chorus.","subset":"restaurant_10dB","task_type":"understanding","prediction":"lets all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":540,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp01_restaurant_sn15.wav","answer":"The birch canoe slid on the smooth planks.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the birch canoe slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":541,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp02_restaurant_sn15.wav","answer":"He knew the skill of the great young actress.","subset":"restaurant_15dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":542,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp03_restaurant_sn15.wav","answer":"Her purse was full of useless trash.","subset":"restaurant_15dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":543,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp04_restaurant_sn15.wav","answer":"Read verse out loud for pleasure.","subset":"restaurant_15dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":544,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp05_restaurant_sn15.wav","answer":"Wipe the grease off his dirty face.","subset":"restaurant_15dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":545,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp06_restaurant_sn15.wav","answer":"Men strive but seldom get rich.","subset":"restaurant_15dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":546,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp07_restaurant_sn15.wav","answer":"We find joy in the simplest things.","subset":"restaurant_15dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":547,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp08_restaurant_sn15.wav","answer":"Hedge apples may stain your hands green.","subset":"restaurant_15dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":548,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp09_restaurant_sn15.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"restaurant_15dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":549,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp10_restaurant_sn15.wav","answer":"The sky that morning was clear and bright blue.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":550,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp11_restaurant_sn15.wav","answer":"He wrote down a long list of items.","subset":"restaurant_15dB","task_type":"understanding","prediction":"He wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":551,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp12_restaurant_sn15.wav","answer":"The drip of the rain made a pleasant sound.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":552,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp13_restaurant_sn15.wav","answer":"Smoke poured out of every crack.","subset":"restaurant_15dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":553,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp14_restaurant_sn15.wav","answer":"Hats are worn to tea and not to dinner.","subset":"restaurant_15dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":554,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp15_restaurant_sn15.wav","answer":"The clothes dried on a thin wooden rack.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":555,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp16_restaurant_sn15.wav","answer":"The stray cat gave birth to kittens.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":556,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp17_restaurant_sn15.wav","answer":"The lazy cow lay in the cool grass.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":557,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp18_restaurant_sn15.wav","answer":"The friendly gang left the drug store.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":558,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp19_restaurant_sn15.wav","answer":"We talked of the sideshow in the circus.","subset":"restaurant_15dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":559,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp20_restaurant_sn15.wav","answer":"The set of china hit the floor with a crash.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":560,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp21_restaurant_sn15.wav","answer":"Clams are small, round, soft and tasty.","subset":"restaurant_15dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":561,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp22_restaurant_sn15.wav","answer":"The line where the edges join was clean.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the line where the edges join was green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":562,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp23_restaurant_sn15.wav","answer":"Stop whistling and watch the boys march.","subset":"restaurant_15dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":563,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp24_restaurant_sn15.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"restaurant_15dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":564,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp25_restaurant_sn15.wav","answer":"A good book informs of what we ought to know.","subset":"restaurant_15dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":565,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp26_restaurant_sn15.wav","answer":"She has a smart way of wearing clothes.","subset":"restaurant_15dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":566,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp27_restaurant_sn15.wav","answer":"Bring your best compass to the third class.","subset":"restaurant_15dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":567,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp28_restaurant_sn15.wav","answer":"The club rented the rink for the fifth night.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":568,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp29_restaurant_sn15.wav","answer":"The flint sputtered and lit a pine torch.","subset":"restaurant_15dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":569,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/15dB\/sp30_restaurant_sn15.wav","answer":"Let's all join as we sing the last chorus.","subset":"restaurant_15dB","task_type":"understanding","prediction":"lets all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":570,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp01_restaurant_sn5.wav","answer":"The birch canoe slid on the smooth planks.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the birch canoe slid from the smooth plank","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":571,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp02_restaurant_sn5.wav","answer":"He knew the skill of the great young actress.","subset":"restaurant_5dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":572,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp03_restaurant_sn5.wav","answer":"Her purse was full of useless trash.","subset":"restaurant_5dB","task_type":"understanding","prediction":"Her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":573,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp04_restaurant_sn5.wav","answer":"Read verse out loud for pleasure.","subset":"restaurant_5dB","task_type":"understanding","prediction":"read verse out loud and in pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":574,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp05_restaurant_sn5.wav","answer":"Wipe the grease off his dirty face.","subset":"restaurant_5dB","task_type":"understanding","prediction":"wipes degrees soft and dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":575,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp06_restaurant_sn5.wav","answer":"Men strive but seldom get rich.","subset":"restaurant_5dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":576,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp07_restaurant_sn5.wav","answer":"We find joy in the simplest things.","subset":"restaurant_5dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":577,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp08_restaurant_sn5.wav","answer":"Hedge apples may stain your hands green.","subset":"restaurant_5dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":578,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp09_restaurant_sn5.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"restaurant_5dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":579,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp10_restaurant_sn5.wav","answer":"The sky that morning was clear and bright blue.","subset":"restaurant_5dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":580,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp11_restaurant_sn5.wav","answer":"He wrote down a long list of items.","subset":"restaurant_5dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":581,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp12_restaurant_sn5.wav","answer":"The drip of the rain made a pleasant sound.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":582,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp13_restaurant_sn5.wav","answer":"Smoke poured out of every crack.","subset":"restaurant_5dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":583,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp14_restaurant_sn5.wav","answer":"Hats are worn to tea and not to dinner.","subset":"restaurant_5dB","task_type":"understanding","prediction":"cats are born to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":584,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp15_restaurant_sn5.wav","answer":"The clothes dried on a thin wooden rack.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":585,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp16_restaurant_sn5.wav","answer":"The stray cat gave birth to kittens.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":586,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp17_restaurant_sn5.wav","answer":"The lazy cow lay in the cool grass.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":587,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp18_restaurant_sn5.wav","answer":"The friendly gang left the drug store.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the friendly gang left the drugstore","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":588,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp19_restaurant_sn5.wav","answer":"We talked of the sideshow in the circus.","subset":"restaurant_5dB","task_type":"understanding","prediction":"we talked of the sideshow in the circle","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":589,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp20_restaurant_sn5.wav","answer":"The set of china hit the floor with a crash.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":590,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp21_restaurant_sn5.wav","answer":"Clams are small, round, soft and tasty.","subset":"restaurant_5dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":591,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp22_restaurant_sn5.wav","answer":"The line where the edges join was clean.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the line where the edges join in the future","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":592,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp23_restaurant_sn5.wav","answer":"Stop whistling and watch the boys march.","subset":"restaurant_5dB","task_type":"understanding","prediction":"Stop whistling and watch the boys and girls","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":593,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp24_restaurant_sn5.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"restaurant_5dB","task_type":"understanding","prediction":"A cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":594,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp25_restaurant_sn5.wav","answer":"A good book informs of what we ought to know.","subset":"restaurant_5dB","task_type":"understanding","prediction":"a good book informs us what we are","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":595,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp26_restaurant_sn5.wav","answer":"She has a smart way of wearing clothes.","subset":"restaurant_5dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":596,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp27_restaurant_sn5.wav","answer":"Bring your best compass to the third class.","subset":"restaurant_5dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":597,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp28_restaurant_sn5.wav","answer":"The club rented the rink for the fifth night.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the club run of the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":598,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp29_restaurant_sn5.wav","answer":"The flint sputtered and lit a pine torch.","subset":"restaurant_5dB","task_type":"understanding","prediction":"the flint sputtered and lit a fine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":599,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/restaurant\/5dB\/sp30_restaurant_sn5.wav","answer":"Let's all join as we sing the last chorus.","subset":"restaurant_5dB","task_type":"understanding","prediction":"lets all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":600,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp01_station_sn0.wav","answer":"The birch canoe slid on the smooth planks.","subset":"station_0dB","task_type":"understanding","prediction":"reverse the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":601,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp02_station_sn0.wav","answer":"He knew the skill of the great young actress.","subset":"station_0dB","task_type":"understanding","prediction":"the skill of the great young actors","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":602,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp03_station_sn0.wav","answer":"Her purse was full of useless trash.","subset":"station_0dB","task_type":"understanding","prediction":"the first is full of useless things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":603,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp04_station_sn0.wav","answer":"Read verse out loud for pleasure.","subset":"station_0dB","task_type":"understanding","prediction":"reverse","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":604,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp05_station_sn0.wav","answer":"Wipe the grease off his dirty face.","subset":"station_0dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":605,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp06_station_sn0.wav","answer":"Men strive but seldom get rich.","subset":"station_0dB","task_type":"understanding","prediction":"many strive but seldom achieve","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":606,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp07_station_sn0.wav","answer":"We find joy in the simplest things.","subset":"station_0dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":607,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp08_station_sn0.wav","answer":"Hedge apples may stain your hands green.","subset":"station_0dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":608,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp09_station_sn0.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"station_0dB","task_type":"understanding","prediction":"turtle the pit is the aid of unknown food","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":609,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp10_station_sn0.wav","answer":"The sky that morning was clear and bright blue.","subset":"station_0dB","task_type":"understanding","prediction":"sky that morning was clear and bright","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":610,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp11_station_sn0.wav","answer":"He wrote down a long list of items.","subset":"station_0dB","task_type":"understanding","prediction":"he wrote down his long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":611,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp12_station_sn0.wav","answer":"The drip of the rain made a pleasant sound.","subset":"station_0dB","task_type":"understanding","prediction":"the drift of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":612,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp13_station_sn0.wav","answer":"Smoke poured out of every crack.","subset":"station_0dB","task_type":"understanding","prediction":"Smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":613,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp14_station_sn0.wav","answer":"Hats are worn to tea and not to dinner.","subset":"station_0dB","task_type":"understanding","prediction":"pass our phone to kate and not to the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":614,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp15_station_sn0.wav","answer":"The clothes dried on a thin wooden rack.","subset":"station_0dB","task_type":"understanding","prediction":"the clothes dried on a stained wooden deck","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":615,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp16_station_sn0.wav","answer":"The stray cat gave birth to kittens.","subset":"station_0dB","task_type":"understanding","prediction":"the stray cat sees first","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":616,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp17_station_sn0.wav","answer":"The lazy cow lay in the cool grass.","subset":"station_0dB","task_type":"understanding","prediction":"the lazy cow made me hold back","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":617,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp18_station_sn0.wav","answer":"The friendly gang left the drug store.","subset":"station_0dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":618,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp19_station_sn0.wav","answer":"We talked of the sideshow in the circus.","subset":"station_0dB","task_type":"understanding","prediction":"we talked with the sideshow in the third","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":619,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp20_station_sn0.wav","answer":"The set of china hit the floor with a crash.","subset":"station_0dB","task_type":"understanding","prediction":"the set of china hit the floor with a bang","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":620,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp21_station_sn0.wav","answer":"Clams are small, round, soft and tasty.","subset":"station_0dB","task_type":"understanding","prediction":"clams are small","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":621,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp22_station_sn0.wav","answer":"The line where the edges join was clean.","subset":"station_0dB","task_type":"understanding","prediction":"a line where the edges join is smooth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":622,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp23_station_sn0.wav","answer":"Stop whistling and watch the boys march.","subset":"station_0dB","task_type":"understanding","prediction":"stop whistling and watch the boy in front","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":623,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp24_station_sn0.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"station_0dB","task_type":"understanding","prediction":"a fridge in warm waters and a loose","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":624,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp25_station_sn0.wav","answer":"A good book informs of what we ought to know.","subset":"station_0dB","task_type":"understanding","prediction":"good","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":625,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp26_station_sn0.wav","answer":"She has a smart way of wearing clothes.","subset":"station_0dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":626,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp27_station_sn0.wav","answer":"Bring your best compass to the third class.","subset":"station_0dB","task_type":"understanding","prediction":"bring your best to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":627,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp28_station_sn0.wav","answer":"The club rented the rink for the fifth night.","subset":"station_0dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":628,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp29_station_sn0.wav","answer":"The flint sputtered and lit a pine torch.","subset":"station_0dB","task_type":"understanding","prediction":"the flint fluttered and lit a pine bough","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":629,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/0dB\/sp30_station_sn0.wav","answer":"Let's all join as we sing the last chorus.","subset":"station_0dB","task_type":"understanding","prediction":"let s not go into the same old left court","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":630,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp01_station_sn10.wav","answer":"The birch canoe slid on the smooth planks.","subset":"station_10dB","task_type":"understanding","prediction":"the birch canoes slid on smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":631,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp02_station_sn10.wav","answer":"He knew the skill of the great young actress.","subset":"station_10dB","task_type":"understanding","prediction":"knew the skill of the great young actors","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":632,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp03_station_sn10.wav","answer":"Her purse was full of useless trash.","subset":"station_10dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":633,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp04_station_sn10.wav","answer":"Read verse out loud for pleasure.","subset":"station_10dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":634,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp05_station_sn10.wav","answer":"Wipe the grease off his dirty face.","subset":"station_10dB","task_type":"understanding","prediction":"wiped the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":635,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp06_station_sn10.wav","answer":"Men strive but seldom get rich.","subset":"station_10dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":636,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp07_station_sn10.wav","answer":"We find joy in the simplest things.","subset":"station_10dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":637,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp08_station_sn10.wav","answer":"Hedge apples may stain your hands green.","subset":"station_10dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":638,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp09_station_sn10.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"station_10dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":639,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp10_station_sn10.wav","answer":"The sky that morning was clear and bright blue.","subset":"station_10dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":640,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp11_station_sn10.wav","answer":"He wrote down a long list of items.","subset":"station_10dB","task_type":"understanding","prediction":"He wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":641,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp12_station_sn10.wav","answer":"The drip of the rain made a pleasant sound.","subset":"station_10dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":642,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp13_station_sn10.wav","answer":"Smoke poured out of every crack.","subset":"station_10dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":643,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp14_station_sn10.wav","answer":"Hats are worn to tea and not to dinner.","subset":"station_10dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":644,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp15_station_sn10.wav","answer":"The clothes dried on a thin wooden rack.","subset":"station_10dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":645,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp16_station_sn10.wav","answer":"The stray cat gave birth to kittens.","subset":"station_10dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":646,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp17_station_sn10.wav","answer":"The lazy cow lay in the cool grass.","subset":"station_10dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":647,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp18_station_sn10.wav","answer":"The friendly gang left the drug store.","subset":"station_10dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":648,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp19_station_sn10.wav","answer":"We talked of the sideshow in the circus.","subset":"station_10dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":649,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp20_station_sn10.wav","answer":"The set of china hit the floor with a crash.","subset":"station_10dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":650,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp21_station_sn10.wav","answer":"Clams are small, round, soft and tasty.","subset":"station_10dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":651,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp22_station_sn10.wav","answer":"The line where the edges join was clean.","subset":"station_10dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":652,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp23_station_sn10.wav","answer":"Stop whistling and watch the boys march.","subset":"station_10dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":653,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp24_station_sn10.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"station_10dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fine","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":654,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp25_station_sn10.wav","answer":"A good book informs of what we ought to know.","subset":"station_10dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":655,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp26_station_sn10.wav","answer":"She has a smart way of wearing clothes.","subset":"station_10dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":656,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp27_station_sn10.wav","answer":"Bring your best compass to the third class.","subset":"station_10dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":657,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp28_station_sn10.wav","answer":"The club rented the rink for the fifth night.","subset":"station_10dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":658,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp29_station_sn10.wav","answer":"The flint sputtered and lit a pine torch.","subset":"station_10dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":659,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/10dB\/sp30_station_sn10.wav","answer":"Let's all join as we sing the last chorus.","subset":"station_10dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":660,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp01_station_sn15.wav","answer":"The birch canoe slid on the smooth planks.","subset":"station_15dB","task_type":"understanding","prediction":"the birch canoes slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":661,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp02_station_sn15.wav","answer":"He knew the skill of the great young actress.","subset":"station_15dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":662,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp03_station_sn15.wav","answer":"Her purse was full of useless trash.","subset":"station_15dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":663,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp04_station_sn15.wav","answer":"Read verse out loud for pleasure.","subset":"station_15dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":664,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp05_station_sn15.wav","answer":"Wipe the grease off his dirty face.","subset":"station_15dB","task_type":"understanding","prediction":"wiped the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":665,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp06_station_sn15.wav","answer":"Men strive but seldom get rich.","subset":"station_15dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":666,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp07_station_sn15.wav","answer":"We find joy in the simplest things.","subset":"station_15dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":667,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp08_station_sn15.wav","answer":"Hedge apples may stain your hands green.","subset":"station_15dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":668,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp09_station_sn15.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"station_15dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":669,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp10_station_sn15.wav","answer":"The sky that morning was clear and bright blue.","subset":"station_15dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":670,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp11_station_sn15.wav","answer":"He wrote down a long list of items.","subset":"station_15dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":671,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp12_station_sn15.wav","answer":"The drip of the rain made a pleasant sound.","subset":"station_15dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":672,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp13_station_sn15.wav","answer":"Smoke poured out of every crack.","subset":"station_15dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":673,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp14_station_sn15.wav","answer":"Hats are worn to tea and not to dinner.","subset":"station_15dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":674,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp15_station_sn15.wav","answer":"The clothes dried on a thin wooden rack.","subset":"station_15dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":675,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp16_station_sn15.wav","answer":"The stray cat gave birth to kittens.","subset":"station_15dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":676,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp17_station_sn15.wav","answer":"The lazy cow lay in the cool grass.","subset":"station_15dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":677,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp18_station_sn15.wav","answer":"The friendly gang left the drug store.","subset":"station_15dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":678,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp19_station_sn15.wav","answer":"We talked of the sideshow in the circus.","subset":"station_15dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":679,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp20_station_sn15.wav","answer":"The set of china hit the floor with a crash.","subset":"station_15dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":680,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp21_station_sn15.wav","answer":"Clams are small, round, soft and tasty.","subset":"station_15dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":681,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp22_station_sn15.wav","answer":"The line where the edges join was clean.","subset":"station_15dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":682,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp23_station_sn15.wav","answer":"Stop whistling and watch the boys march.","subset":"station_15dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":683,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp24_station_sn15.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"station_15dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":684,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp25_station_sn15.wav","answer":"A good book informs of what we ought to know.","subset":"station_15dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":685,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp26_station_sn15.wav","answer":"She has a smart way of wearing clothes.","subset":"station_15dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":686,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp27_station_sn15.wav","answer":"Bring your best compass to the third class.","subset":"station_15dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":687,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp28_station_sn15.wav","answer":"The club rented the rink for the fifth night.","subset":"station_15dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":688,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp29_station_sn15.wav","answer":"The flint sputtered and lit a pine torch.","subset":"station_15dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":689,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/15dB\/sp30_station_sn15.wav","answer":"Let's all join as we sing the last chorus.","subset":"station_15dB","task_type":"understanding","prediction":"lets all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":690,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp01_station_sn5.wav","answer":"The birch canoe slid on the smooth planks.","subset":"station_5dB","task_type":"understanding","prediction":"the birch communists live on a cruise ship","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":691,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp02_station_sn5.wav","answer":"He knew the skill of the great young actress.","subset":"station_5dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":692,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp03_station_sn5.wav","answer":"Her purse was full of useless trash.","subset":"station_5dB","task_type":"understanding","prediction":"my purse is full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":693,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp04_station_sn5.wav","answer":"Read verse out loud for pleasure.","subset":"station_5dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":694,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp05_station_sn5.wav","answer":"Wipe the grease off his dirty face.","subset":"station_5dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":695,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp06_station_sn5.wav","answer":"Men strive but seldom get rich.","subset":"station_5dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":696,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp07_station_sn5.wav","answer":"We find joy in the simplest things.","subset":"station_5dB","task_type":"understanding","prediction":"we find joy in the simplest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":697,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp08_station_sn5.wav","answer":"Hedge apples may stain your hands green.","subset":"station_5dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":698,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp09_station_sn5.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"station_5dB","task_type":"understanding","prediction":"turtle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":699,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp10_station_sn5.wav","answer":"The sky that morning was clear and bright blue.","subset":"station_5dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":700,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp11_station_sn5.wav","answer":"He wrote down a long list of items.","subset":"station_5dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":701,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp12_station_sn5.wav","answer":"The drip of the rain made a pleasant sound.","subset":"station_5dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":702,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp13_station_sn5.wav","answer":"Smoke poured out of every crack.","subset":"station_5dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":703,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp14_station_sn5.wav","answer":"Hats are worn to tea and not to dinner.","subset":"station_5dB","task_type":"understanding","prediction":"pass our warrant to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":704,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp15_station_sn5.wav","answer":"The clothes dried on a thin wooden rack.","subset":"station_5dB","task_type":"understanding","prediction":"The clothes dried on a thin, wooden rack.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":705,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp16_station_sn5.wav","answer":"The stray cat gave birth to kittens.","subset":"station_5dB","task_type":"understanding","prediction":"the stray cat came first to kiss","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":706,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp17_station_sn5.wav","answer":"The lazy cow lay in the cool grass.","subset":"station_5dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":707,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp18_station_sn5.wav","answer":"The friendly gang left the drug store.","subset":"station_5dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":708,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp19_station_sn5.wav","answer":"We talked of the sideshow in the circus.","subset":"station_5dB","task_type":"understanding","prediction":"we talked with the slide show in the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":709,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp20_station_sn5.wav","answer":"The set of china hit the floor with a crash.","subset":"station_5dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":710,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp21_station_sn5.wav","answer":"Clams are small, round, soft and tasty.","subset":"station_5dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":711,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp22_station_sn5.wav","answer":"The line where the edges join was clean.","subset":"station_5dB","task_type":"understanding","prediction":"a line where the edges join is free","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":712,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp23_station_sn5.wav","answer":"Stop whistling and watch the boys march.","subset":"station_5dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":713,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp24_station_sn5.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"station_5dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":714,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp25_station_sn5.wav","answer":"A good book informs of what we ought to know.","subset":"station_5dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":715,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp26_station_sn5.wav","answer":"She has a smart way of wearing clothes.","subset":"station_5dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":716,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp27_station_sn5.wav","answer":"Bring your best compass to the third class.","subset":"station_5dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":717,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp28_station_sn5.wav","answer":"The club rented the rink for the fifth night.","subset":"station_5dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":718,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp29_station_sn5.wav","answer":"The flint sputtered and lit a pine torch.","subset":"station_5dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":719,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/station\/5dB\/sp30_station_sn5.wav","answer":"Let's all join as we sing the last chorus.","subset":"station_5dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":720,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp01_street_sn0.wav","answer":"The birch canoe slid on the smooth planks.","subset":"street_0dB","task_type":"understanding","prediction":"virtually","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":721,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp02_street_sn0.wav","answer":"He knew the skill of the great young actress.","subset":"street_0dB","task_type":"understanding","prediction":"he knew the skill of the great young","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":722,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp03_street_sn0.wav","answer":"Her purse was full of useless trash.","subset":"street_0dB","task_type":"understanding","prediction":"the first is full of useless crap","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":723,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp04_street_sn0.wav","answer":"Read verse out loud for pleasure.","subset":"street_0dB","task_type":"understanding","prediction":"rebirth not loud but","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":724,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp05_street_sn0.wav","answer":"Wipe the grease off his dirty face.","subset":"street_0dB","task_type":"understanding","prediction":"last degree softest air to say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":725,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp06_street_sn0.wav","answer":"Men strive but seldom get rich.","subset":"street_0dB","task_type":"understanding","prediction":"and strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":726,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp07_street_sn0.wav","answer":"We find joy in the simplest things.","subset":"street_0dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":727,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp08_street_sn0.wav","answer":"Hedge apples may stain your hands green.","subset":"street_0dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":728,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp09_street_sn0.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"street_0dB","task_type":"understanding","prediction":"turtles of pitt with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":729,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp10_street_sn0.wav","answer":"The sky that morning was clear and bright blue.","subset":"street_0dB","task_type":"understanding","prediction":"sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":730,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp11_street_sn0.wav","answer":"He wrote down a long list of items.","subset":"street_0dB","task_type":"understanding","prediction":"he wrote down his long list of findings","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":731,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp12_street_sn0.wav","answer":"The drip of the rain made a pleasant sound.","subset":"street_0dB","task_type":"understanding","prediction":"the drip of the rain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":732,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp13_street_sn0.wav","answer":"Smoke poured out of every crack.","subset":"street_0dB","task_type":"understanding","prediction":"most poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":733,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp14_street_sn0.wav","answer":"Hats are worn to tea and not to dinner.","subset":"street_0dB","task_type":"understanding","prediction":"half of one to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":734,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp15_street_sn0.wav","answer":"The clothes dried on a thin wooden rack.","subset":"street_0dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden bench","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":735,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp16_street_sn0.wav","answer":"The stray cat gave birth to kittens.","subset":"street_0dB","task_type":"understanding","prediction":"the straight path these first six","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":736,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp17_street_sn0.wav","answer":"The lazy cow lay in the cool grass.","subset":"street_0dB","task_type":"understanding","prediction":"the lazy cow lay in the shade","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":737,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp18_street_sn0.wav","answer":"The friendly gang left the drug store.","subset":"street_0dB","task_type":"understanding","prediction":"the criminal gang left the drug","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":738,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp19_street_sn0.wav","answer":"We talked of the sideshow in the circus.","subset":"street_0dB","task_type":"understanding","prediction":"impossible to find a replacement","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":739,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp20_street_sn0.wav","answer":"The set of china hit the floor with a crash.","subset":"street_0dB","task_type":"understanding","prediction":"the set of pine that hit the floor with a bang","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":740,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp21_street_sn0.wav","answer":"Clams are small, round, soft and tasty.","subset":"street_0dB","task_type":"understanding","prediction":"plants are small","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":741,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp22_street_sn0.wav","answer":"The line where the edges join was clean.","subset":"street_0dB","task_type":"understanding","prediction":"the line where the edges join will be","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":742,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp23_street_sn0.wav","answer":"Stop whistling and watch the boys march.","subset":"street_0dB","task_type":"understanding","prediction":"stop whippin and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":743,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp24_street_sn0.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"street_0dB","task_type":"understanding","prediction":"a cruise in warm waters and a glimpse of","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":744,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp25_street_sn0.wav","answer":"A good book informs of what we ought to know.","subset":"street_0dB","task_type":"understanding","prediction":"good book in form with what we want to","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":745,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp26_street_sn0.wav","answer":"She has a smart way of wearing clothes.","subset":"street_0dB","task_type":"understanding","prediction":"She has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":746,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp27_street_sn0.wav","answer":"Bring your best compass to the third class.","subset":"street_0dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":747,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp28_street_sn0.wav","answer":"The club rented the rink for the fifth night.","subset":"street_0dB","task_type":"understanding","prediction":"the club runs the range for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":748,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp29_street_sn0.wav","answer":"The flint sputtered and lit a pine torch.","subset":"street_0dB","task_type":"understanding","prediction":"the splint sputtered and lit a pine cone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":749,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/0dB\/sp30_street_sn0.wav","answer":"Let's all join as we sing the last chorus.","subset":"street_0dB","task_type":"understanding","prediction":"that song joined as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":750,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp01_street_sn10.wav","answer":"The birch canoe slid on the smooth planks.","subset":"street_10dB","task_type":"understanding","prediction":"The birch canoes slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":751,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp02_street_sn10.wav","answer":"He knew the skill of the great young actress.","subset":"street_10dB","task_type":"understanding","prediction":"he knew the skill of the great young actor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":752,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp03_street_sn10.wav","answer":"Her purse was full of useless trash.","subset":"street_10dB","task_type":"understanding","prediction":"my purse is full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":753,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp04_street_sn10.wav","answer":"Read verse out loud for pleasure.","subset":"street_10dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":754,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp05_street_sn10.wav","answer":"Wipe the grease off his dirty face.","subset":"street_10dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":755,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp06_street_sn10.wav","answer":"Men strive but seldom get rich.","subset":"street_10dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":756,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp07_street_sn10.wav","answer":"We find joy in the simplest things.","subset":"street_10dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":757,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp08_street_sn10.wav","answer":"Hedge apples may stain your hands green.","subset":"street_10dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":758,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp09_street_sn10.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"street_10dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":759,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp10_street_sn10.wav","answer":"The sky that morning was clear and bright blue.","subset":"street_10dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":760,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp11_street_sn10.wav","answer":"He wrote down a long list of items.","subset":"street_10dB","task_type":"understanding","prediction":"He wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":761,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp12_street_sn10.wav","answer":"The drip of the rain made a pleasant sound.","subset":"street_10dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":762,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp13_street_sn10.wav","answer":"Smoke poured out of every crack.","subset":"street_10dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":763,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp14_street_sn10.wav","answer":"Hats are worn to tea and not to dinner.","subset":"street_10dB","task_type":"understanding","prediction":"cats are born to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":764,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp15_street_sn10.wav","answer":"The clothes dried on a thin wooden rack.","subset":"street_10dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":765,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp16_street_sn10.wav","answer":"The stray cat gave birth to kittens.","subset":"street_10dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":766,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp17_street_sn10.wav","answer":"The lazy cow lay in the cool grass.","subset":"street_10dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":767,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp18_street_sn10.wav","answer":"The friendly gang left the drug store.","subset":"street_10dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":768,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp19_street_sn10.wav","answer":"We talked of the sideshow in the circus.","subset":"street_10dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":769,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp20_street_sn10.wav","answer":"The set of china hit the floor with a crash.","subset":"street_10dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":770,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp21_street_sn10.wav","answer":"Clams are small, round, soft and tasty.","subset":"street_10dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":771,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp22_street_sn10.wav","answer":"The line where the edges join was clean.","subset":"street_10dB","task_type":"understanding","prediction":"the line where the edges join was smooth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":772,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp23_street_sn10.wav","answer":"Stop whistling and watch the boys march.","subset":"street_10dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":773,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp24_street_sn10.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"street_10dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":774,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp25_street_sn10.wav","answer":"A good book informs of what we ought to know.","subset":"street_10dB","task_type":"understanding","prediction":"a good book informs us of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":775,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp26_street_sn10.wav","answer":"She has a smart way of wearing clothes.","subset":"street_10dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":776,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp27_street_sn10.wav","answer":"Bring your best compass to the third class.","subset":"street_10dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":777,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp28_street_sn10.wav","answer":"The club rented the rink for the fifth night.","subset":"street_10dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":778,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp29_street_sn10.wav","answer":"The flint sputtered and lit a pine torch.","subset":"street_10dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine cone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":779,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/10dB\/sp30_street_sn10.wav","answer":"Let's all join as we sing the last chorus.","subset":"street_10dB","task_type":"understanding","prediction":"let s all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":780,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp01_street_sn15.wav","answer":"The birch canoe slid on the smooth planks.","subset":"street_15dB","task_type":"understanding","prediction":"the birch canoe slid on the smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":781,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp02_street_sn15.wav","answer":"He knew the skill of the great young actress.","subset":"street_15dB","task_type":"understanding","prediction":"he knew the skill of the great young actress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":782,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp03_street_sn15.wav","answer":"Her purse was full of useless trash.","subset":"street_15dB","task_type":"understanding","prediction":"her purse was full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":783,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp04_street_sn15.wav","answer":"Read verse out loud for pleasure.","subset":"street_15dB","task_type":"understanding","prediction":"read first out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":784,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp05_street_sn15.wav","answer":"Wipe the grease off his dirty face.","subset":"street_15dB","task_type":"understanding","prediction":"wipe the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":785,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp06_street_sn15.wav","answer":"Men strive but seldom get rich.","subset":"street_15dB","task_type":"understanding","prediction":"men strive but seldom get rich","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":786,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp07_street_sn15.wav","answer":"We find joy in the simplest things.","subset":"street_15dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":787,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp08_street_sn15.wav","answer":"Hedge apples may stain your hands green.","subset":"street_15dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":788,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp09_street_sn15.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"street_15dB","task_type":"understanding","prediction":"hurtle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":789,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp10_street_sn15.wav","answer":"The sky that morning was clear and bright blue.","subset":"street_15dB","task_type":"understanding","prediction":"the sky that morning was clear and bright blue","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":790,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp11_street_sn15.wav","answer":"He wrote down a long list of items.","subset":"street_15dB","task_type":"understanding","prediction":"he wrote down a long list of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":791,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp12_street_sn15.wav","answer":"The drip of the rain made a pleasant sound.","subset":"street_15dB","task_type":"understanding","prediction":"the drip of the rain made a fuzzy sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":792,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp13_street_sn15.wav","answer":"Smoke poured out of every crack.","subset":"street_15dB","task_type":"understanding","prediction":"smoke poured out of every crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":793,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp14_street_sn15.wav","answer":"Hats are worn to tea and not to dinner.","subset":"street_15dB","task_type":"understanding","prediction":"hats are worn to tea and not to dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":794,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp15_street_sn15.wav","answer":"The clothes dried on a thin wooden rack.","subset":"street_15dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":795,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp16_street_sn15.wav","answer":"The stray cat gave birth to kittens.","subset":"street_15dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":796,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp17_street_sn15.wav","answer":"The lazy cow lay in the cool grass.","subset":"street_15dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":797,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp18_street_sn15.wav","answer":"The friendly gang left the drug store.","subset":"street_15dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":798,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp19_street_sn15.wav","answer":"We talked of the sideshow in the circus.","subset":"street_15dB","task_type":"understanding","prediction":"we talked of the sideshow in the circus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":799,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp20_street_sn15.wav","answer":"The set of china hit the floor with a crash.","subset":"street_15dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":800,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp21_street_sn15.wav","answer":"Clams are small, round, soft and tasty.","subset":"street_15dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":801,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp22_street_sn15.wav","answer":"The line where the edges join was clean.","subset":"street_15dB","task_type":"understanding","prediction":"the line where the edges join was clean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":802,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp23_street_sn15.wav","answer":"Stop whistling and watch the boys march.","subset":"street_15dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":803,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp24_street_sn15.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"street_15dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht is fun","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":804,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp25_street_sn15.wav","answer":"A good book informs of what we ought to know.","subset":"street_15dB","task_type":"understanding","prediction":"a good book informs of what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":805,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp26_street_sn15.wav","answer":"She has a smart way of wearing clothes.","subset":"street_15dB","task_type":"understanding","prediction":"she has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":806,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp27_street_sn15.wav","answer":"Bring your best compass to the third class.","subset":"street_15dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":807,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp28_street_sn15.wav","answer":"The club rented the rink for the fifth night.","subset":"street_15dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":808,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp29_street_sn15.wav","answer":"The flint sputtered and lit a pine torch.","subset":"street_15dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine torch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":809,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/15dB\/sp30_street_sn15.wav","answer":"Let's all join as we sing the last chorus.","subset":"street_15dB","task_type":"understanding","prediction":"let us all join as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":810,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp01_street_sn5.wav","answer":"The birch canoe slid on the smooth planks.","subset":"street_5dB","task_type":"understanding","prediction":"the birch canoes live on smooth planks","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":811,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp02_street_sn5.wav","answer":"He knew the skill of the great young actress.","subset":"street_5dB","task_type":"understanding","prediction":"he knew the skill of the great young actors","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":812,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp03_street_sn5.wav","answer":"Her purse was full of useless trash.","subset":"street_5dB","task_type":"understanding","prediction":"my purse is full of useless trash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":813,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp04_street_sn5.wav","answer":"Read verse out loud for pleasure.","subset":"street_5dB","task_type":"understanding","prediction":"read verse out loud for pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":814,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp05_street_sn5.wav","answer":"Wipe the grease off his dirty face.","subset":"street_5dB","task_type":"understanding","prediction":"wipes the grease off his dirty face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":815,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp06_street_sn5.wav","answer":"Men strive but seldom get rich.","subset":"street_5dB","task_type":"understanding","prediction":"men strive but seldom believe","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":816,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp07_street_sn5.wav","answer":"We find joy in the simplest things.","subset":"street_5dB","task_type":"understanding","prediction":"we find joy in the simplest things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":817,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp08_street_sn5.wav","answer":"Hedge apples may stain your hands green.","subset":"street_5dB","task_type":"understanding","prediction":"hedge apples may stain your hands green","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":818,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp09_street_sn5.wav","answer":"Hurdle the pit with the aid of a long pole.","subset":"street_5dB","task_type":"understanding","prediction":"hurdle the pit with the aid of a long pole","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":819,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp10_street_sn5.wav","answer":"The sky that morning was clear and bright blue.","subset":"street_5dB","task_type":"understanding","prediction":"sky that morning was clear and bright","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":820,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp11_street_sn5.wav","answer":"He wrote down a long list of items.","subset":"street_5dB","task_type":"understanding","prediction":"He wrote down in long lists of items","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":821,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp12_street_sn5.wav","answer":"The drip of the rain made a pleasant sound.","subset":"street_5dB","task_type":"understanding","prediction":"the drip of the rain made a pleasant sound","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":822,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp13_street_sn5.wav","answer":"Smoke poured out of every crack.","subset":"street_5dB","task_type":"understanding","prediction":"smoke poured out in eddies crack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":823,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp14_street_sn5.wav","answer":"Hats are worn to tea and not to dinner.","subset":"street_5dB","task_type":"understanding","prediction":"cats are born to pee and not to think","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":824,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp15_street_sn5.wav","answer":"The clothes dried on a thin wooden rack.","subset":"street_5dB","task_type":"understanding","prediction":"the clothes dried on a thin wooden rack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":825,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp16_street_sn5.wav","answer":"The stray cat gave birth to kittens.","subset":"street_5dB","task_type":"understanding","prediction":"the stray cat gave birth to kittens","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":826,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp17_street_sn5.wav","answer":"The lazy cow lay in the cool grass.","subset":"street_5dB","task_type":"understanding","prediction":"the lazy cow lay in the cool grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":827,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp18_street_sn5.wav","answer":"The friendly gang left the drug store.","subset":"street_5dB","task_type":"understanding","prediction":"the friendly gang left the drug store","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":828,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp19_street_sn5.wav","answer":"We talked of the sideshow in the circus.","subset":"street_5dB","task_type":"understanding","prediction":"and possibly the sideshow in the park","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":829,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp20_street_sn5.wav","answer":"The set of china hit the floor with a crash.","subset":"street_5dB","task_type":"understanding","prediction":"the set of china hit the floor with a crash","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":830,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp21_street_sn5.wav","answer":"Clams are small, round, soft and tasty.","subset":"street_5dB","task_type":"understanding","prediction":"clams are small round soft and tasty","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":831,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp22_street_sn5.wav","answer":"The line where the edges join was clean.","subset":"street_5dB","task_type":"understanding","prediction":"the line where the edges join with three","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":832,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp23_street_sn5.wav","answer":"Stop whistling and watch the boys march.","subset":"street_5dB","task_type":"understanding","prediction":"stop whistling and watch the boys march","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":833,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp24_street_sn5.wav","answer":"A cruise in warm waters in a sleek yacht is fun.","subset":"street_5dB","task_type":"understanding","prediction":"a cruise in warm waters in a sleek yacht","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":834,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp25_street_sn5.wav","answer":"A good book informs of what we ought to know.","subset":"street_5dB","task_type":"understanding","prediction":"a good book informs us what we ought to know","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":835,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp26_street_sn5.wav","answer":"She has a smart way of wearing clothes.","subset":"street_5dB","task_type":"understanding","prediction":"he has a smart way of wearing clothes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":836,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp27_street_sn5.wav","answer":"Bring your best compass to the third class.","subset":"street_5dB","task_type":"understanding","prediction":"bring your best compass to the third class","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":837,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp28_street_sn5.wav","answer":"The club rented the rink for the fifth night.","subset":"street_5dB","task_type":"understanding","prediction":"the club rented the rink for the fifth night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":838,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp29_street_sn5.wav","answer":"The flint sputtered and lit a pine torch.","subset":"street_5dB","task_type":"understanding","prediction":"the flint sputtered and lit a pine cone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":839,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/Kimi-Audio\/Kimi-Audio-Evalkit\/data\/downloaded_datasets\/noizeus\/noizeus\/street\/5dB\/sp30_street_sn5.wav","answer":"Let's all join as we sing the last chorus.","subset":"street_5dB","task_type":"understanding","prediction":"that god going as we sing the last chorus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank0.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank0.log
new file mode 100644
index 0000000000000000000000000000000000000000..cc0c2334e2fd185a4479ecf81c44c481991da9fc
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank0.log
@@ -0,0 +1,5 @@
+2025-12-21 06:56:38 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:38 | INFO | Msg example: {'index': 0, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp01_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
+2025-12-21 06:57:23 | INFO | waiting for other ranks to finish, time elapsed: 10s
+2025-12-21 06:57:23 | INFO | model Qwen2.5-Omni-7B-lora2, data noizeus, all 8 result merged to no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/Qwen2.5-Omni-7B-lora2_noizeus.jsonl.
+2025-12-21 06:57:23 | INFO | skip eval for noizeus
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank1.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank1.log
new file mode 100644
index 0000000000000000000000000000000000000000..c330814bdb04390e1470c2377e8d90ed00f7cb8b
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank1.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:27 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:27 | INFO | Msg example: {'index': 1, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp02_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank2.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank2.log
new file mode 100644
index 0000000000000000000000000000000000000000..944cebddac63b0974981bf408d34ad0aefa53bc7
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank2.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:26 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:26 | INFO | Msg example: {'index': 2, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp03_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank3.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank3.log
new file mode 100644
index 0000000000000000000000000000000000000000..ff190cc259fefe7fca302e2e68ca21560dac2dca
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank3.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:37 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:37 | INFO | Msg example: {'index': 3, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp04_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank4.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank4.log
new file mode 100644
index 0000000000000000000000000000000000000000..fb865a8ac24b8940e7e8393ce70f300139b88c9f
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank4.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:24 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:24 | INFO | Msg example: {'index': 4, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp05_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank5.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank5.log
new file mode 100644
index 0000000000000000000000000000000000000000..efc700cf4b3167da7beba0da8ab33676741fe410
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank5.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:23 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:23 | INFO | Msg example: {'index': 5, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp06_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank6.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank6.log
new file mode 100644
index 0000000000000000000000000000000000000000..072f4d4948fd173f6a5a8a51c1bdfedb31b195ee
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank6.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:13 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:13 | INFO | Msg example: {'index': 6, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp07_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank7.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank7.log
new file mode 100644
index 0000000000000000000000000000000000000000..e45885543d06edf2e88e563caaa2bd0c1c50b5a0
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/noizeus/logs/rank7.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:25 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: noizeus
+2025-12-21 06:56:25 | INFO | Msg example: {'index': 7, 'audio': ['/workspace/intern/pangkaiyu/Kimi-Audio/Kimi-Audio-Evalkit/data/downloaded_datasets/noizeus/noizeus/airport/0dB/sp08_airport_sn0.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'noizeus', 'dataset_name': 'noizeus', 'lang': 'en', 'subset': 'airport_0dB'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo.jsonl b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..dcfe52542936a0351e6b47b0d07c4820ca318d30
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo.jsonl
@@ -0,0 +1,1466 @@
+{"index": 1, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-babb-sp0112-ch123215-sg0025-mc01-stu-clo-dg080.wav", "answer": "of tolerant wonder anne despite her affection for rusty was not especially fond of cats but missus gardner's tone annoyed her inconsequently she remembered that missus john blythe was so fond of cats that she kept as many as her husband would allow", "subset": "babb", "task_type": "understanding", "prediction": "of tolerant wonder ann despite her affection for rusty was not especially fond of cats but mrs gardiner s tone annoyed her inconsequently she remembered that mrs john blythe was so fond of cats that she kept as many as her husband would allow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 2, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-babb-sp0122-ch121729-sg0002-mc02-lav-clo-dg060.wav", "answer": "magnus great and nator to swim a great swimmer maiden lady a term applied to an old maid by those who wish to avoid hurting her feelings malt", "subset": "babb", "task_type": "understanding", "prediction": "magnus great and nator to swim a great swimmer maiden lady a term applied to an old maid by those who wish to avoid hurting her feelings malt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 3, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-babb-sp0122-ch121730-sg0014-mc01-stu-clo-dg000.wav", "answer": "one of the hardships of a minor's life pass a form of transportation issued free to those who are quite able to pay passenger one who does not travel on a pass antonym for deadhead", "subset": "babb", "task_type": "understanding", "prediction": "one of the hardships of a miner's life pass a form of transportation issued free to those who are quite able to pay passenger one who does not travel on a pass antonym for deadhead", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 4, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0159/Lab41-SRI-VOiCES-rm1-babb-sp0159-ch135897-sg0052-mc01-stu-clo-dg100.wav", "answer": "that this solitary life is extremely irksome all these expressions and particularly the last greatly increased my love for him prince said i there is no doubt but providence has brought me into your port to afford you an opportunity", "subset": "babb", "task_type": "understanding", "prediction": "that this solitary life is extremely irksome all these expressions and particularly the last greatly increased my love for him prince said i there is no doubt but providence has brought me into your port to afford you an opportunity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 5, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0174/Lab41-SRI-VOiCES-rm1-babb-sp0174-ch084280-sg0013-mc02-lav-clo-dg010.wav", "answer": "in mary it seems to me i found both womanhood and fellowship i found what many have dreamt of love and friendship freely given and i could do nothing but clutch at her to make her my possession", "subset": "babb", "task_type": "understanding", "prediction": "in mary it seems to me i found both womanhood and fellowship i found what many have travelled after love and friendship free and yet i could do nothing but clutch at her to make her my possession", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 6, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0188/Lab41-SRI-VOiCES-rm1-babb-sp0188-ch135249-sg0029-mc01-stu-clo-dg170.wav", "answer": "but were now tall ivory columns in a fairy palace of twilight and stars in their shadows anne and gilbert talked in lover fashion of their new home and their new life together i've found a nest for us anne oh where", "subset": "babb", "task_type": "understanding", "prediction": "but were now tall ivory columns in a fairy palace of twilight and stars in their shadows anne and gilbert talked in lover fashion of their new home and their new life together i ve found a nest for us anne oh where", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 7, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-babb-sp0205-ch159056-sg0032-mc01-stu-clo-dg020.wav", "answer": "could not be improvised in this hurried though disastrously slow preparation for a war the ship in which wolfe was to sail had been lying idle for years and her pestilential bilge water soon began to make the sailors and soldiers sicken and die", "subset": "babb", "task_type": "understanding", "prediction": "could not be improved at this hurried though disastrously slow preparation for a war the ship in which wolfe was to sail had been lying idle for years and her pestilential bilge water soon began to make the sailors and soldiers sicken and die", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 8, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm1-babb-sp0208-ch126851-sg0011-mc02-lav-clo-dg070.wav", "answer": "now the farmers and the old ladies are afraid to send their animals to you just as we were beginning to be well off again now we shall be ruined entirely this is the last straw i will no longer be housekeeper for you if you don't send away that alligator", "subset": "babb", "task_type": "understanding", "prediction": "now the farmers and the old ladies are afraid to send their animals feed just as we were beginning to be well off again now we shall be ruined entirely this is the last straw i will no longer be housekeeper for you if you dont send away that alligator", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 9, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm1-babb-sp0209-ch004731-sg0033-mc02-lav-clo-dg050.wav", "answer": "that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware", "subset": "babb", "task_type": "understanding", "prediction": "that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 10, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm1-babb-sp0209-ch004733-sg0009-mc01-stu-clo-dg120.wav", "answer": "you never could persuade her to read half so much as you wished you know you could not i dare say replied missus weston smiling that i thought so then but since we have parted i can never remember emma's omitting to do any thing i wished", "subset": "babb", "task_type": "understanding", "prediction": "you never could persuade her to read half so much as you wished you know you could not i dare say replied mrs weston smiling that i thought so then but since we have parted i can never remember emma s omitting to do anything i wished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 11, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm1-babb-sp0209-ch004733-sg0009-mc02-lav-clo-dg120.wav", "answer": "you never could persuade her to read half so much as you wished you know you could not i dare say replied missus weston smiling that i thought so then but since we have parted i can never remember emma's omitting to do any thing i wished", "subset": "babb", "task_type": "understanding", "prediction": "you never could persuade her to read half so much as you wished you know you could not i dare say replied mrs weston smiling that i thought so then but since we have parted i can never remember emma s omitting to do any thing i wished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 12, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0224/Lab41-SRI-VOiCES-rm1-babb-sp0224-ch128660-sg0019-mc02-lav-clo-dg060.wav", "answer": "beware of that man be he friend or brother whose hair is one color and moustache another portland me one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of one's future husband", "subset": "babb", "task_type": "understanding", "prediction": "beware of that man be he friend or brother whose hair is one color and mustache another portland may one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of ones future husband", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 13, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0240/Lab41-SRI-VOiCES-rm1-babb-sp0240-ch160593-sg0000-mc01-stu-clo-dg100.wav", "answer": "mine by the right of the white election mine by the royal seal mine by the sign in the scarlet prison bars cannot conceal mine here in vision and in veto mine by the grave's repeal titled confirmed delirious charter", "subset": "babb", "task_type": "understanding", "prediction": "mine by the right of the white election mine by the royal seal mine by the sign the scarlet prison bars cannot conceal mine here in vision and in veto mine by the grave s repeal titled confirmed delirious charter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 14, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-babb-sp0242-ch122626-sg0030-mc02-lav-clo-dg170.wav", "answer": "did she say that to me did you hear her eliza and georgiana won't i tell mama but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing", "subset": "babb", "task_type": "understanding", "prediction": "did she say that to me do you hear her eliza and georgiana won t i tell mamma but first he ran headlong at me i felt him grasp my hair and my shoulder thea closed with a desperate thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 15, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0288/Lab41-SRI-VOiCES-rm1-babb-sp0288-ch121741-sg0007-mc01-stu-clo-dg000.wav", "answer": "by their very nature be about something amiss i have occasionally wondered how she would have behaved to a girl on reflection i think a little better but the girl would have been worse off because she could not have escaped from her as we did", "subset": "babb", "task_type": "understanding", "prediction": "by their very nature he had done something amiss i have occasionally wondered how she would have behaved to a girl on reflection i think a little better but the girl would have been in worse odds because she could not escape from paris as we did", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 16, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm1-babb-sp0472-ch129979-sg0009-mc01-stu-clo-dg180.wav", "answer": "perhaps be a little soured by finding like many others of his sex that through some unaccountable bias in favour of beauty he was the husband of a very silly woman but she knew that this kind of blunder was too common for any sensible man to be lastingly hurt by it", "subset": "babb", "task_type": "understanding", "prediction": "perhaps be a little sour by finding like many others of his sex that through some unaccountable bias in favor of beauty he was the husband of a very silly woman but he knew that this kind of blunder was too common for any sensible man to be lastingly hurt by it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 17, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm1-babb-sp0472-ch129979-sg0011-mc02-lav-clo-dg010.wav", "answer": "it will be quite delightful my love applying to her husband don't you long to have the miss dashwoods come to cleveland certainly he replied with a sneer i came into devonshire with no other view", "subset": "babb", "task_type": "understanding", "prediction": "it will be quite delightful my love applied her husband don t you long to have the moustache once come to cleveland certainly he replied with a serene mien i came into debenture with no idea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 18, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm1-babb-sp0479-ch107480-sg0016-mc01-stu-clo-dg100.wav", "answer": "to twenty five hundred and i am to land a yard or two of the stuff for you in some mysterious way i demanded how is it to be by kidnapping the lady the snatch and run game or how sarcasm does not suit your complexion bunny retorted henriette", "subset": "babb", "task_type": "understanding", "prediction": "twenty five hundred and i am to land a yard or two of the stuff for you in some mysterious way i demanded how is it to be by kidnapping the lady the snatcher and robber game or how sarcasm does not suit your complexion bunny retorted henrietta", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 19, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm1-babb-sp0479-ch134717-sg0056-mc02-lav-clo-dg050.wav", "answer": "weapons and each with musing soul retire to celebrate our dear commander's death no more for him life's stormy conflicts nor victory nor defeat no more time's dark events charging like ceaseless clouds across the sky but sing poet in our name", "subset": "babb", "task_type": "understanding", "prediction": "weapons in each music soul retire to celebrate our dear commander s death no more for him life s stormy conflicts nor victory nor defeat no more time s dark events charging like ceaseless clouds across the sky but sing poet in our name", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 20, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-babb-sp0480-ch126336-sg0008-mc02-lav-clo-dg030.wav", "answer": "ah unlucky wretch that i am sighed she would that i had married king grisly beard next they came to some fine meadows whose are these beautiful green meadows said she", "subset": "babb", "task_type": "understanding", "prediction": "unlucky wretch that i am said she would that i had married king grizzly bear next they came to some fine meadows whose are these beautiful green meadows said she", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 21, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm1-babb-sp0492-ch131882-sg0007-mc02-lav-clo-dg120.wav", "answer": "insects phileas fogg was a member of the reform and that was all the way in which he got admission to this exclusive club was simple enough he was recommended by the barings with whom he had an open credit", "subset": "babb", "task_type": "understanding", "prediction": "insects joey spugg was a member of the reform and that was all the way in which he got admission to his exclusive club was simple enough he was recommended by the bearings with whom he had an open credit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 22, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0597/Lab41-SRI-VOiCES-rm1-babb-sp0597-ch134789-sg0007-mc01-stu-clo-dg000.wav", "answer": "somewhat disturbed by intrigues but still retaining on their faces something of the serenity of toil and in their souls that flower of honesty which survives the first fall in woman one of the four was called the young because she was the youngest of them", "subset": "babb", "task_type": "understanding", "prediction": "somewhat disturbed by intrigues but still retaining on their faces something of the serenity of toil and in their souls that flower of honesty which survives the first fall in woman one of the four was called the young because she was the youngest of them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 23, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm1-babb-sp0636-ch123163-sg0044-mc01-stu-clo-dg100.wav", "answer": "grated bread soaked in cream put in the omelet some think an improvement the dripping of a nice ham some persons use for omelet instead of butter to boil eggs have the water boiling and look at your watch as you put them in", "subset": "babb", "task_type": "understanding", "prediction": "grated bread soaked in cream put in the omelet some think an improvement the dripping of a nice ham some persons use for omelet instead of butter to boil eggs have the water boiling and look at your watch as you put them in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 24, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm1-babb-sp0637-ch127579-sg0004-mc02-lav-clo-dg040.wav", "answer": "i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat", "subset": "babb", "task_type": "understanding", "prediction": "i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 25, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0652/Lab41-SRI-VOiCES-rm1-babb-sp0652-ch130737-sg0000-mc02-lav-clo-dg040.wav", "answer": "never drink any hard liquors such as whisky brandy gin or cocktails with oysters or clams as it is liable to upset you for the rest of the evening", "subset": "babb", "task_type": "understanding", "prediction": "Never drink any hard liquors such as whiskey. Brandy, gin or cocktails with oysters or clams as it is liable to upset you for the rest of the evening.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 26, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0868/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0001-mc01-stu-clo-dg180.wav", "answer": "for long the instrument was treasured by the emperor of china but all in vain were the efforts of those who in turn tried to draw melody from its strings in response to their utmost strivings there came from the harp but harsh notes of disdain", "subset": "babb", "task_type": "understanding", "prediction": "For long, the instrument was treasured by the emperor of China. But all in vain were the efforts of those who, in turn, tried to draw melody from its strings in response to their utmost strivings. There came from the harp, but harsh notes of disdain.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 27, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0868/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0001-mc02-lav-clo-dg180.wav", "answer": "for long the instrument was treasured by the emperor of china but all in vain were the efforts of those who in turn tried to draw melody from its strings in response to their utmost strivings there came from the harp but harsh notes of disdain", "subset": "babb", "task_type": "understanding", "prediction": "For long, the instrument was treasured by the emperor of China. But all in vain were the efforts of those who, in turn, tried to draw melody from its strings in response to their utmost strivings. There came from the harp, but harsh notes of disdain.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 28, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0868/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0002-mc02-lav-clo-dg070.wav", "answer": "once more the sweet breath of spring played amidst its branches the young cataracts as they danced down the ravine laughed to the budding flowers anon were heard the dreamy voices of summer with its myriad insects the gentle pattering of rain", "subset": "babb", "task_type": "understanding", "prediction": "Once more, the sweet breath of spring played amidst its branches. The young cataracts, as they danced down the ravine, laughed to the budding flowers anon. Were heard the dreamy voices of summer with its myriad insects. The gentle patterning of rain.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 29, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0868/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0017-mc02-lav-clo-dg130.wav", "answer": "he sings only of himself his works may be nearer science but are further from humanity we have an old saying in japan that a woman cannot love a man who is truly vain for their is no crevice in his heart for love to enter and fill up", "subset": "babb", "task_type": "understanding", "prediction": "he sings only of himself his works may be nearer science but are further from humanity we have an old saying in japan that a woman cannot love a man who is truly vain for there is no crevice in his heart for love to enter and fill up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 30, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0882/Lab41-SRI-VOiCES-rm1-babb-sp0882-ch123266-sg0029-mc02-lav-clo-dg000.wav", "answer": "i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay", "subset": "babb", "task_type": "understanding", "prediction": "i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 31, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0948/Lab41-SRI-VOiCES-rm1-babb-sp0948-ch132705-sg0009-mc02-lav-clo-dg090.wav", "answer": "a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said", "subset": "babb", "task_type": "understanding", "prediction": "a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 32, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm1-babb-sp0949-ch162667-sg0001-mc02-lav-clo-dg030.wav", "answer": "angles give the name to england attila king of the huns in italy genseric takes rome the lombards the people who inhabit the northern parts beyond the rhine and the danube", "subset": "babb", "task_type": "understanding", "prediction": "angles give the name to england attila king of the huns in italy genseric takes rome the lombards the people who inhabit the northern parts beyond the rhine and the danube", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 33, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm1-babb-sp0949-ch162667-sg0034-mc01-stu-clo-dg020.wav", "answer": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "subset": "babb", "task_type": "understanding", "prediction": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 34, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm1-babb-sp1050-ch134119-sg0020-mc01-stu-clo-dg060.wav", "answer": "he packed up his bottles in a leather case and went back with them all first he looked at the coffee and then stirred it then he put in a little chlorate of potassium and the family tried it all round but it tasted no better", "subset": "babb", "task_type": "understanding", "prediction": "he packed up his bottles in a leather case and went back with them all first he looked at the coffee and then stirred it then he put in a little chlorate of potassium and the family tried it all round but it tasted no better", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 35, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm1-babb-sp1050-ch134121-sg0014-mc01-stu-clo-dg110.wav", "answer": "no dinner exclaimed agamemnon i am quite hungry said solomon john at last mister peterkin said i am not proud i am willing to dine in the kitchen this room was below the dining room all consented to this", "subset": "babb", "task_type": "understanding", "prediction": "no dinner exclaimed agamemnon i am quite hungry said solomon john at last mr peterkin said i am not proud i am willing to dine in the kitchen this room was below the dining room all consented to this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 36, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp1052/Lab41-SRI-VOiCES-rm1-babb-sp1052-ch132776-sg0021-mc01-stu-clo-dg020.wav", "answer": "would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped", "subset": "babb", "task_type": "understanding", "prediction": "would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 37, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm1-babb-sp1066-ch004479-sg0015-mc01-stu-clo-dg000.wav", "answer": "i should suffer more from comparison a gentleman's family is all that i should condition for i know you i know you you would take up with any thing but i shall be a little more nice and i am sure the good campbells will be quite on my side", "subset": "babb", "task_type": "understanding", "prediction": "i should suffer more from comparison a gentleman's family is all that i should condition for i know you i know you you will take up with anything but i shall be a little more nice and i am sure the good campbells will be quite on my side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 38, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm1-babb-sp1112-ch128136-sg0031-mc02-lav-clo-dg170.wav", "answer": "are two strong simple verses and indeed the spirit of the whole poem is dignified and stately the rest of the volume however is disappointing ordinary theology has long since converted its gold into lead", "subset": "babb", "task_type": "understanding", "prediction": "Are two strong, simple verses, and indeed. The spirit of the whole poem is dignified and stately. The rest of the volume, however, is disappointing. Ordinary theology has long since converted its gold into lead.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 39, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm1-babb-sp1160-ch139727-sg0014-mc01-stu-clo-dg030.wav", "answer": "and therefore i propos'd that the orders should be payable in a year and to bear an interest of five per cent with these orders i suppos'd the provisions might easily be purchas'd the assembly with very little hesitation adopted the proposal the orders were immediately printed", "subset": "babb", "task_type": "understanding", "prediction": "and therefore i proposed that the orders should be payable in a year and to bear an interest of five per cent with these orders i supposed the provisions might easily be purchased the assembly with very little hesitation adopted the proposal the orders were immediately printed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 40, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm1-babb-sp1160-ch139730-sg0019-mc02-lav-clo-dg050.wav", "answer": "undertook to repeat what he called the philadelphia experiments and after they were performed before the king and court all the curious of paris flocked to see them i will not swell this narrative with an account of that capital experiment", "subset": "babb", "task_type": "understanding", "prediction": "Undertook to repeat what he called the Philadelphia experiments. And after they were performed before the king and court, all the curious of Paris flocked to see them. I will not swell this narrative with an account of that capital experiment.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 41, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1271/Lab41-SRI-VOiCES-rm1-babb-sp1271-ch136861-sg0014-mc02-lav-clo-dg020.wav", "answer": "did not endeavour to depress me with threats of censure from the publick or with objections learned from those who had learned them from my own preface your's is the only letter of goodwill that i have received", "subset": "babb", "task_type": "understanding", "prediction": "did not endeavor to depress me with threats of censure from the public or with objections learned from those who had learned them from my own preface yours is the only letter of good will that i have received", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 42, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm1-babb-sp1335-ch163935-sg0018-mc02-lav-clo-dg150.wav", "answer": "put a little bag of mixed spices such as are used in making pickles on to cook with the fowl while the fowl is cooking take about a pound of rice and fry it with a few sliced onions and a little butter or crisco", "subset": "babb", "task_type": "understanding", "prediction": "Put a little bag of mixed spices. Such as are used in making pickles on to cook with the fowl while the fowl is cooking. Take about a pound of rice and fry it with a few sliced onions and a little butter, or Crisco.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 43, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm1-babb-sp1335-ch163935-sg0022-mc01-stu-clo-dg110.wav", "answer": "beef or mutton pullao very delicious pullao may be made from the cheapest cuts of beef and mutton get about two pounds of beef or mutton cut in bits cook until it is very tender", "subset": "babb", "task_type": "understanding", "prediction": "beef or mutton pulao very delicious pulao may be made from the cheapest cuts of beef and mutton get about two pounds of beef or mutton cut in bits cook until it is very tender", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 44, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1425/Lab41-SRI-VOiCES-rm1-babb-sp1425-ch139297-sg0036-mc01-stu-clo-dg120.wav", "answer": "for during this interval a great change had taken place in master hugh and his once kind and affectionate wife the influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both", "subset": "babb", "task_type": "understanding", "prediction": "For during this interval, a great change had taken place in Master Hugh and his once kind and affectionate wife. The influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 45, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-babb-sp1472-ch285314-sg0011-mc01-stu-clo-dg040.wav", "answer": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up", "subset": "babb", "task_type": "understanding", "prediction": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 46, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1536/Lab41-SRI-VOiCES-rm1-babb-sp1536-ch138488-sg0027-mc01-stu-clo-dg090.wav", "answer": "mary being not merely queen consort but also queen regnant was inaugurated in all things like a king was girt with the sword lifted up into the throne and presented with the bible the spurs and the orb of the temporal grandees of the realm and of their wives and daughters", "subset": "babb", "task_type": "understanding", "prediction": "Mary, being not merely queen consort, but also queen regnant, was inaugurated in all things like a king, was girt with the sword, lifted up into the throne and presented with the Bible. The spurs and the orb of the temporal grandees of the realm and of their wives and daughters.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 47, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1737/Lab41-SRI-VOiCES-rm1-babb-sp1737-ch142397-sg0008-mc01-stu-clo-dg100.wav", "answer": "to pass along busy streets of your own building for ever ringing an imaginary bell and offering airy muffins of your own make to a bustling thronging crowd of your own creation there were points about the game it cannot be denied though it seemed scarce in harmony with this radiant wind swept morning", "subset": "babb", "task_type": "understanding", "prediction": "to pass along busy streets of your own building forever ringing an imaginary bell and offering airy muffins of your own make to a bustling thronging crowd of your own creation there were points about the game it cannot be denied though it seemed scarce in harmony with this radiant wind swept morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 48, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm1-babb-sp1867-ch154071-sg0043-mc02-lav-clo-dg170.wav", "answer": "you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i'll smash every bone in his ugly head", "subset": "babb", "task_type": "understanding", "prediction": "you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i ll smash every bone in his ugly head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 49, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1926/Lab41-SRI-VOiCES-rm1-babb-sp1926-ch143879-sg0024-mc01-stu-clo-dg100.wav", "answer": "was in direct proportion to the frequency with which he occupied her thoughts as this happened very often it sometimes appeared to missus ludlow that she had lost her courage so uncanny a result of so exhilarating an incident as inheriting a fortune", "subset": "babb", "task_type": "understanding", "prediction": "was in direct proportion to the frequency with which he occupied her thoughts as this happened very often it sometimes appeared to mrs ludlow that she had lost her courage so uncanny a result of so exhilarating an incident as inheriting a fortune", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 50, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm1-babb-sp1961-ch145733-sg0000-mc01-stu-clo-dg170.wav", "answer": "there was once a poor prince he possessed a kingdom which though small was yet large enough for him to marry on and married he wished to be now it was certainly a little audacious of him to venture to say to the emperor's daughter will you marry me but he did venture to say so", "subset": "babb", "task_type": "understanding", "prediction": "there was once a poor prince he possessed a kingdom which though small was yet large enough for him to marry on and married he wished to be now it was certainly a little audacious of him to venture to say to the emperor s daughter will you marry me but he did venture to say so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 51, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1963/Lab41-SRI-VOiCES-rm1-babb-sp1963-ch142393-sg0048-mc02-lav-clo-dg100.wav", "answer": "lest he should startle her too much yet he thought she's not one to be overstartled she's always so calm and quiet as if she was prepared for anything what was she thinking of as she wound up the hill", "subset": "babb", "task_type": "understanding", "prediction": "lest he should startle her too much yet he thought she is not one to be over startled she is always so calm and quiet as if she was prepared for anything what was she thinking of as she wound up the hill", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 52, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm1-babb-sp1970-ch028415-sg0004-mc01-stu-clo-dg120.wav", "answer": "hosanna in the highest the city was crowded with travelers from all over palestine and from foreign countries too they were the pilgrims who had come for the passover feast the crowds saw the procession coming they saw the donkey", "subset": "babb", "task_type": "understanding", "prediction": "hosanna in the highest the city was crowded with travelers from all over palestine and from foreign countries too they were the pilgrims who had come for the passover feast the crowd saw the procession coming they saw the donkey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 53, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm1-babb-sp2012-ch139356-sg0000-mc01-stu-clo-dg160.wav", "answer": "the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon", "subset": "babb", "task_type": "understanding", "prediction": "the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 54, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm1-babb-sp2110-ch161101-sg0016-mc02-lav-clo-dg040.wav", "answer": "could do the same thing at once that is true art he also has a beautiful round tone not a note is missing one hears everything everything is well marked he has a fine staccato bow", "subset": "babb", "task_type": "understanding", "prediction": "could do the same thing at once that is true art he also has a beautiful round tone not a note is missing one hears everything everything is well marked he has a fine staccato bow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 55, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2149/Lab41-SRI-VOiCES-rm1-babb-sp2149-ch008912-sg0013-mc02-lav-clo-dg150.wav", "answer": "she will soon see you now i am just going up to tell her you are here what haven't you told her before said melbury oh no said the other you see you came so very early at last the bell rang missus charmond could see him", "subset": "babb", "task_type": "understanding", "prediction": "she will soon see you now i am just going up to tell her you are here what haven t you told her before said melbury oh no said the other you see you came so very early at last the bell rang mrs charmond could see him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 56, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm1-babb-sp2156-ch017942-sg0029-mc01-stu-clo-dg080.wav", "answer": "now she will despise me and forget me it is better that she should think me a brute than that i should be always haunted by those pleading eyes the door of the distant church house opened and closed", "subset": "babb", "task_type": "understanding", "prediction": "now she will despise me and forget me it is better that she should think me a brute than that i should be always haunted by those pleading eyes the door of the distant church house opened and closed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 57, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2162/Lab41-SRI-VOiCES-rm1-babb-sp2162-ch164461-sg0006-mc02-lav-clo-dg140.wav", "answer": "since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves", "subset": "babb", "task_type": "understanding", "prediction": "since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 58, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm1-babb-sp2289-ch152257-sg0026-mc02-lav-clo-dg020.wav", "answer": "justinian also did a great deal of good by establishing a number of manufactures in constantinople it was he who first brought silk worms into europe to the last year of his life justinian was strong and active", "subset": "babb", "task_type": "understanding", "prediction": "justinian also did a great deal of good by establishing a number of manufactures in constantinople it was he who first brought silkworms into europe to the last year of his life justinian was strong and active", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 59, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm1-babb-sp2289-ch152258-sg0007-mc01-stu-clo-dg160.wav", "answer": "and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work intrusted to him and", "subset": "babb", "task_type": "understanding", "prediction": "and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work entrusted to him and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 60, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2294/Lab41-SRI-VOiCES-rm1-babb-sp2294-ch169656-sg0015-mc01-stu-clo-dg070.wav", "answer": "and the pirates boarded the schooner without further opposition the vessel was at once ransacked even the clothes of the crew being taken the ship's own boat was lowered and into this the marauders put their booty and took it ashore also carrying the captain and one of the crew with them", "subset": "babb", "task_type": "understanding", "prediction": "and the pirates boarded the schooner without further opposition the vessel was at once ransacked even the clothes of the crew being taken the ship s own boat was lowered and into this the marauders put their booty and took it ashore also carrying the captain and one of the crew with them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 61, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2294/Lab41-SRI-VOiCES-rm1-babb-sp2294-ch169656-sg0022-mc02-lav-clo-dg070.wav", "answer": "an arrangement was afterwards made with the pirates to release the captains of the fiducia and the portuguese barque rosita faro a much earlier capture and some members of both crews in exchange for the riffians captured by the spanish steamer sevilla and a ransom of three thousand dollars", "subset": "babb", "task_type": "understanding", "prediction": "an arrangement was afterwards made with the pirates to release the captains of the foudia and the portuguese bark rosita de peru a much earlier capture and some members of both crews in exchange for the riffians captured by the spanish steamer sevilla and a ransom of three thousand dollars", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 62, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm1-babb-sp2412-ch153948-sg0001-mc02-lav-clo-dg130.wav", "answer": "it will be seen that i did not succeed in my design and that however much i may have met with that was new and strange i have been unable to reap any pecuniary advantage", "subset": "babb", "task_type": "understanding", "prediction": "It will be seen that I did not succeed in my design and that, however much I may have met with. That was new and strange. I have been unable to reap any pecuniary advantage.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 63, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2532/Lab41-SRI-VOiCES-rm1-babb-sp2532-ch157475-sg0013-mc02-lav-clo-dg130.wav", "answer": "the folks will never find him down there for we can not tell them where he is and they will never guess it the dolls were all very sad they stayed out upon the shiny new tin gutter until it began raining and hoped and hoped that raggedy andy could get back up to them", "subset": "babb", "task_type": "understanding", "prediction": "the folks will never find him down there for we cannot tell them where he is and they will never guess it the dolls were all very sad they stayed out upon the shiny new tin gutter until it began raining and hoped and hoped that raggedy andy could get back up to them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 64, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2573/Lab41-SRI-VOiCES-rm1-babb-sp2573-ch178449-sg0023-mc01-stu-clo-dg080.wav", "answer": "you feeding a strip of zinc into a machine nine hours a day no wonder she broke off and then after a keen glance at his face she said i should think you would have been a bad hand at it he laughed ruefully", "subset": "babb", "task_type": "understanding", "prediction": "you feeding a strip of zinc into a machine nine hours a day no wonder she broke off and then after a keen glance at his face she said i should think you would have been a bad hand at it he laughed ruefully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 65, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2673/Lab41-SRI-VOiCES-rm1-babb-sp2673-ch156474-sg0006-mc01-stu-clo-dg030.wav", "answer": "but before it could be executed circumstances intervened effectually to thwart that object while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress", "subset": "babb", "task_type": "understanding", "prediction": "but before it could be executed circumstances intervened effectually to thwart that object while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 66, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2673/Lab41-SRI-VOiCES-rm1-babb-sp2673-ch162130-sg0014-mc01-stu-clo-dg020.wav", "answer": "it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution", "subset": "babb", "task_type": "understanding", "prediction": "it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 67, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2691/Lab41-SRI-VOiCES-rm1-babb-sp2691-ch156750-sg0014-mc01-stu-clo-dg130.wav", "answer": "for she knew that we were nimbler footed when she started us off in happy mood each cow wore a bell of different tone and knew her own name yet it was not an easy task even in pleasant weather to collect the various strings and get them home on time", "subset": "babb", "task_type": "understanding", "prediction": "for she knew that we were nimbler footed when she started us off in a happy mood each cow wore a bell of different tone and knew her own name yet it was not an easy task even in pleasant weather to collect the various strings and get them home on time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 68, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm1-babb-sp2758-ch086588-sg0001-mc02-lav-clo-dg160.wav", "answer": "he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth", "subset": "babb", "task_type": "understanding", "prediction": "he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 69, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm1-babb-sp2764-ch036617-sg0028-mc02-lav-clo-dg070.wav", "answer": "the abraham lincoln reached an average speed of eighteen point three miles per hour a considerable speed but still not enough to cope with our gigantic cetacean the frigate's interior accommodations complemented its nautical virtues i was well satisfied with my cabin", "subset": "babb", "task_type": "understanding", "prediction": "the abraham lincoln reached an average speed of eighteen point three miles per hour a considerable speed but still not enough to cope with our gigantic cetacean the frigate s interior accommodations complemented its nautical virtues i was well satisfied with my cabin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 70, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm1-babb-sp2803-ch154320-sg0000-mc01-stu-clo-dg080.wav", "answer": "fortunately will halley was not a man in a hurry and did not use a press of canvas or his masts would inevitably have come down", "subset": "babb", "task_type": "understanding", "prediction": "fortunately will halley was not a man in a hurry and did not use oppressive canvas or his mass would inevitably have come down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 71, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm1-babb-sp3368-ch170950-sg0006-mc02-lav-clo-dg080.wav", "answer": "and dine off tables and they should have sauces and sweets in the modern style yes i said now i understand the question which you would have me consider is not only how a state but how a luxurious state is created and possibly there is no harm in this", "subset": "babb", "task_type": "understanding", "prediction": "and dine off tables and they should have sauces and sweets in the modern style yes i said now i understand the question which you would have me consider is not only how a state but how a luxurious state is created and possibly there is no harm in this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 72, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm1-babb-sp3483-ch119637-sg0028-mc01-stu-clo-dg040.wav", "answer": "this creature his most prized possession san lan with the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil arts had i not seen the naked horror of her soul", "subset": "babb", "task_type": "understanding", "prediction": "this creature his most prized possession san lawn with the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil art had i not seen the naked horror of her soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 73, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp3521/Lab41-SRI-VOiCES-rm1-babb-sp3521-ch007591-sg0016-mc01-stu-clo-dg020.wav", "answer": "and thus the waltzers perforce ceased their evolutions and there was a brief disconcert of the whole gay company and while the chimes of the clock yet rang it was observed that the giddiest grew pale and the more aged and sedate passed their hands over their brows as if in confused reverie or meditation", "subset": "babb", "task_type": "understanding", "prediction": "unless the waltzers perforce ceased their evolutions and there was a brief disconcert of the whole gay company and while the chimes of the clock yet rang it was observed that the giddiest grew pale and the more aged and sedate passed their hands over their brows as if in confused reverie or meditation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 74, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_1212-3521/sp3521/Lab41-SRI-VOiCES-rm1-babb-sp3521-ch175962-sg0016-mc01-stu-clo-dg020.wav", "answer": "then my brother toby cried my father clapping his two hands together shall go with us let my old tye wig quoth my uncle toby and my laced regimentals be hung to the fire all night trim page numbering skips ten pages", "subset": "babb", "task_type": "understanding", "prediction": "then my brother toby cried my father clapping his two hands together shall go with us let my old tie wig quoth my uncle toby and my laced regimentals be hung to the fire all night trim page numbering skips ten pages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 75, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm1-babb-sp3549-ch009203-sg0006-mc01-stu-clo-dg150.wav", "answer": "approaching the shuddering rabbi addressed him as follows my son rejoice your trials here below are about to end if in the presence of such obstinacy i was forced to permit with deep regret", "subset": "babb", "task_type": "understanding", "prediction": "approaching the shuddering rabbi addressed him as follows my son rejoice your trials here below are about to end if in the presence of such obstinacy i was forced to permit with deep regret", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 76, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3645/Lab41-SRI-VOiCES-rm1-babb-sp3645-ch039840-sg0010-mc01-stu-clo-dg010.wav", "answer": "opened his hands caught the moth and resumed his former attitude before beginning to speak of my business said alexey alexandrovitch following the lawyer's movements with wondering eyes i ought to observe that the business about which i have to speak to you is to be strictly private", "subset": "babb", "task_type": "understanding", "prediction": "opened his hands caught the moth and resumed his former attitude before beginning to speak of my business said alexey alexandrovitch following the lawyer s movements with wondering eyes i ought to observe that the business about which i have to speak to you is to be strictly private", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 77, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3645/Lab41-SRI-VOiCES-rm1-babb-sp3645-ch039840-sg0032-mc02-lav-clo-dg010.wav", "answer": "if one wants the result one must admit the means if it is so alexey alexandrovitch began suddenly turning white but at that moment the lawyer rose and again went to the door to speak to the intruding clerk", "subset": "babb", "task_type": "understanding", "prediction": "if one wants the result one must admit the means if it is so alexey alexandrovitch began suddenly turning white but at that moment the lawyer rose and again went to the door to speak to the intruding clerk", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 78, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm1-babb-sp3835-ch178028-sg0016-mc01-stu-clo-dg110.wav", "answer": "that it was impossible to expect anything else from a blind and depraved old man i only wonder that the fate of russia could have been entrusted to such a man as long as this news remained unofficial it was possible to doubt it but the next day the following communication was received from count rostopchin", "subset": "babb", "task_type": "understanding", "prediction": "that it was impossible to expect anything else from a blind and depraved old man i only wonder that the fate of russia could have been entrusted to such a man as long as the news remained unofficial it was possible to doubt it but the next day the following communication was received from count rostopchin", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 79, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm1-babb-sp3923-ch153309-sg0039-mc02-lav-clo-dg060.wav", "answer": "and manufactures his own concoctions in a house he has rented here on a lonely road some half mile out of town wellgood does the man named wellgood mister grey exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town", "subset": "babb", "task_type": "understanding", "prediction": "and manufactures his own concoctions in a house he has rented here on the longview road some half mile of town wellgood does many wellgood mr gregg exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 80, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm1-babb-sp3923-ch181420-sg0021-mc01-stu-clo-dg110.wav", "answer": "and his athletics served to strengthen his appeals to the london boys whom he enrolled in the brigades he founded the inter hospital rowing club at putney and rowed in the first inter hospital race he played on the varsity football team and won the throwing the hammer at the sports", "subset": "babb", "task_type": "understanding", "prediction": "and his athletics served to strengthen his appeals to the london boys whom he enrolled in the brigades he founded the inter hospital rowing club at putney and rowed in the first inter hospital race he played on the varsity football team and won the throwing the hammer at the sports", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 81, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3972/Lab41-SRI-VOiCES-rm1-babb-sp3972-ch005791-sg0010-mc01-stu-clo-dg130.wav", "answer": "when remonstrances were sent to london he neither punished nor reprimanded the delinquents but marched an armed force into our country to compel us to be trampled on it was not an alexander nor a charlemagne coming in his strength to subdue ancient enemies or to aggrandize his name", "subset": "babb", "task_type": "understanding", "prediction": "when remonstrances were sent to london he neither punished nor reprimanded the delinquents but marched an armed force into our country to compel us to be trampled on it was not an alexander nor charlemagne coming in his strength to subdue ancient enemies or to aggrandize his name", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 82, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3989/Lab41-SRI-VOiCES-rm1-babb-sp3989-ch182402-sg0004-mc01-stu-clo-dg160.wav", "answer": "hi spotty he shouted where do you live spotty slowly turned his head and looked up at peter there was a twinkle in his eyes though peter didn't see it right here in the smiling pool where else should i live he replied", "subset": "babb", "task_type": "understanding", "prediction": "hi spotty he shouted where do you live spotty slowly turned his head and looked up at peter there was a twinkle in his eyes though peter didn't see it right here on the smiling pool where else should i live he replied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 83, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp3994/Lab41-SRI-VOiCES-rm1-babb-sp3994-ch149798-sg0017-mc01-stu-clo-dg110.wav", "answer": "added the scarecrow but how asked uncle henry in a grave voice for he could not bear to think of his dear niece dorothy being out there under water how shall we do it leave that to glinda", "subset": "babb", "task_type": "understanding", "prediction": "added the scarecrow but how asked uncle henry in a grave voice for he could not bear to think of his dear niece dorothy being out there under water how shall we do it leave that to glinda", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 84, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-babb-sp4014-ch186175-sg0019-mc01-stu-clo-dg180.wav", "answer": "and he started down the passageway toward a narrow stairs leading to a still lower chamber in the vessel three turns two to the right and one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock", "subset": "babb", "task_type": "understanding", "prediction": "and he started down the passageway towards a narrow stairs leading to a still lower chamber in the vessel three turns two to the right one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 85, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-babb-sp4014-ch186183-sg0024-mc01-stu-clo-dg170.wav", "answer": "he pointed her nose downward toward the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer's place in the taube was making desperate signals", "subset": "babb", "task_type": "understanding", "prediction": "he pointed her nose downward towards the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer s place in the top was making desperate signals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 86, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4057/Lab41-SRI-VOiCES-rm1-babb-sp4057-ch183239-sg0007-mc01-stu-clo-dg130.wav", "answer": "is not devoid of sense but why this custom designed for that excellent mortal the t atkins who walked out with nurse maids and was none too busy between whiles should be forced upon a totally different if no less estimable", "subset": "babb", "task_type": "understanding", "prediction": "is not devoid of sense but why this custom designed for that excellent mortal the t atkins who walked out with nursemaids and was none too busy between whiles should be forced upon a totally different if no less estimable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 87, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm1-babb-sp4064-ch012118-sg0002-mc02-lav-clo-dg150.wav", "answer": "they had waited but a few moments when mister underwood's carriage stopped before this entrance and an instant later kate heard her father's voice directing the coachman to call for him in about an hour as the key turned in the lock she heard walcott's voice also", "subset": "babb", "task_type": "understanding", "prediction": "they had waited but a few moments when mr underwood's carriage stopped before this entrance and an instant later kate heard her father's voice directing the coachman to call for him in about an hour as the key turned in the lock she heard walcott's voice also", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 88, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4116/Lab41-SRI-VOiCES-rm1-babb-sp4116-ch013265-sg0006-mc02-lav-clo-dg090.wav", "answer": "you are always doing some queer thing or other felicia said the older girl as the carriage whirled on past the great residences already brilliantly lighted am i what have i done that is queer now rose asked the other looking up suddenly and turning her head towards her sister", "subset": "babb", "task_type": "understanding", "prediction": "you always doing some queer thing or other felicia said the older girl as the carriage whirled on past the great residences already brilliantly lighted am i what have i done that is queer now rose asked the other looking up suddenly and turning her head towards her sister", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 89, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4145/Lab41-SRI-VOiCES-rm1-babb-sp4145-ch014013-sg0001-mc01-stu-clo-dg180.wav", "answer": "her grace had issued cards for a concert and after mature deliberation it was decided that her rival should strike out something new and announce a christening for the same night the first intimation douglas had of the honour intended him by this arrangement", "subset": "babb", "task_type": "understanding", "prediction": "her grace had issued cards for a concert and after mature deliberation it was decided that her rival should strike out something new and announce a christening for the same night the first intimation douglas had of the honour intended him by this arrangement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 90, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4145/Lab41-SRI-VOiCES-rm1-babb-sp4145-ch104606-sg0005-mc02-lav-clo-dg030.wav", "answer": "this went on jack airily is a friend of mine bruce graham graham this is miss brodie madge acknowledged the introduction with an inclination of the head which was so faint as to be almost imperceptible", "subset": "babb", "task_type": "understanding", "prediction": "this went on jack airily is a friend of mine bruce graham graham this is miss prody madge acknowledged the introduction with an inclination of the head which was so faint as to be almost imperceptible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 91, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4160/Lab41-SRI-VOiCES-rm1-babb-sp4160-ch011549-sg0020-mc01-stu-clo-dg120.wav", "answer": "she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin's wishes in the matter of military balls and blue satin slippers", "subset": "babb", "task_type": "understanding", "prediction": "she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin s wishes in the matter of military balls and blue satin slippers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 92, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4160/Lab41-SRI-VOiCES-rm1-babb-sp4160-ch011550-sg0027-mc01-stu-clo-dg050.wav", "answer": "that her pronoun was almost an interjection i thought perhaps said priscilla quietly that a message from you would gratify him if you had one to send theo took up her gloves and began to draw them on a sudden feeling of pain or discomfort striking her", "subset": "babb", "task_type": "understanding", "prediction": "that her pronoun was almost an interjection i thought perhaps said priscilla quietly that a message from you would gratify him if you had one to send theo took up her gloves and began to draw them on a sudden feeling of pain or discomfort striking her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 93, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4160/Lab41-SRI-VOiCES-rm1-babb-sp4160-ch014187-sg0005-mc01-stu-clo-dg040.wav", "answer": "a queer affair jervis a very odd affair indeed i was coming up from the borough picking my way mighty carefully across the road on account of the greasy slippery mud and had just reached the foot of london bridge when i heard a heavy lorry coming down the slope a good deal too fast", "subset": "babb", "task_type": "understanding", "prediction": "a queer affair jervis a very odd affair indeed i was coming up from the borough picking my way mighty carefully across the road on account of the greasy slippery mud and had just reached the foot of london bridge when i heard a heavy lorry coming down the slope a good deal too fast", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 94, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4331/Lab41-SRI-VOiCES-rm1-babb-sp4331-ch057180-sg0021-mc02-lav-clo-dg110.wav", "answer": "an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said up stairs they could not have talked as they were then talking", "subset": "babb", "task_type": "understanding", "prediction": "an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said upstairs they could not have talked as they were then talking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 95, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm1-babb-sp4427-ch020028-sg0010-mc01-stu-clo-dg060.wav", "answer": "i ride in the omnibus and am almost choked with my bonnet strings such a furious draught meets me in the face and when with infinite pains i have secured the only tolerably warm corner my next neighbor becomes very faint and must have the window open", "subset": "babb", "task_type": "understanding", "prediction": "arrive in the omnibus and am almost choked with my bonnet strings such a furious draught meets me in the face and when with infinite pains i have secured the only tolerably warm corner my next neighbour becomes very faint and must have the window open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 96, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm1-babb-sp4438-ch048513-sg0023-mc01-stu-clo-dg110.wav", "answer": "and no man could say more but judging from what well what people had said to him it hadn't been much of a success sometimes and often and often he had been hurt deeply hurt by being misunderstood and lucy said", "subset": "babb", "task_type": "understanding", "prediction": "and no man could say more but judging from what well what people had said to him it hadn't been much of a success sometimes and often and often he had been hurt deeply hurt by being misunderstood and lucy said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 97, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm1-babb-sp4438-ch048525-sg0023-mc02-lav-clo-dg040.wav", "answer": "she sat like a beggar in patient distress waiting for him to emerge and be kind to her of course as far as the minor wishes and preferences of every day went it was all quite easy once she had grasped the right answer to the question", "subset": "babb", "task_type": "understanding", "prediction": "she sat like a beggar in patient distress waiting for him to emerge and be kind to her of course as far as the minor wishes and preferences of every day went it was all quite easy once she had grasped the right answer to the question", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 98, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm1-babb-sp4441-ch076262-sg0010-mc02-lav-clo-dg060.wav", "answer": "and he declared that many so called unbearable situations could be borne quite easily if only one did not exaggerate their importance the time passed slowly but at last it struck ten a gentle double rap at the door relieved the tension", "subset": "babb", "task_type": "understanding", "prediction": "Annie declared that many so called unbearable situations could be borne quite easily if only one did not exaggerate their importance. The time passed slowly, but at last, it struck 10. A gentle double rap at the door, relieved the tension.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 99, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4744/Lab41-SRI-VOiCES-rm1-babb-sp4744-ch004158-sg0009-mc01-stu-clo-dg110.wav", "answer": "all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims", "subset": "babb", "task_type": "understanding", "prediction": "all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4744/Lab41-SRI-VOiCES-rm1-babb-sp4744-ch083616-sg0012-mc02-lav-clo-dg130.wav", "answer": "he it was they thought who produced the thunder and the lightning by hurling stones with his sling and the thunderbolts that fall said they are his children few villages were willing to be without one or more of these they were in appearance small round smooth stones", "subset": "babb", "task_type": "understanding", "prediction": "he it was they thought who produced the thunder and the lightning by hurling stones with his sling and the thunderbolts that fall said they are his children few villages were willing to be without one or more of these they were in appearance small round smooth stones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4859/Lab41-SRI-VOiCES-rm1-babb-sp4859-ch022176-sg0005-mc01-stu-clo-dg090.wav", "answer": "that princess mary was in moscow the death sufferings and last days of prince andrew had often occupied pierre's thoughts and now recurred to him with fresh vividness having heard at dinner that princess mary was in moscow and living in her house", "subset": "babb", "task_type": "understanding", "prediction": "that princess mary was in moscow the death sufferings and last days of prince andrew had often occupied pierre s thoughts and now recurred to him with fresh vividness having heard at dinner that princess mary was in moscow and living in her house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4859/Lab41-SRI-VOiCES-rm1-babb-sp4859-ch022176-sg0016-mc02-lav-clo-dg070.wav", "answer": "she again glanced rapidly from pierre's face to that of the lady in the black dress and said do you really not recognize her pierre looked again at the companion's pale delicate face with its black eyes and peculiar mouth and something near to him long forgotten and more than sweet", "subset": "babb", "task_type": "understanding", "prediction": "she again glanced rapidly from pierre s face to that of the lady in the black dress and said do you really not recognize her pierre looked again at the companion s pale delicate face with its black eyes and peculiar mouth and something near to him long forgotten and more than sweet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp4967/Lab41-SRI-VOiCES-rm1-babb-sp4967-ch026520-sg0009-mc02-lav-clo-dg180.wav", "answer": "king nebuchadnezzar saw a wonderful dream the accomplishment of which god showed him in his sleep but when he arose out of his bed he forgot the accomplishment so he sent for the chaldeans and magicians and the prophets and told them that he had seen a dream", "subset": "babb", "task_type": "understanding", "prediction": "king nebuchadnezzar saw a wonderful dream the accomplishment of which god showed him in his sleep but when he rose out of his bed he forgot the accomplishment so he sent for the chaldeans and magicians and the prophets and told them that he had seen a dream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm1-babb-sp5154-ch026558-sg0022-mc01-stu-clo-dg150.wav", "answer": "the monkey was at last able to pull out one of his hands the sun poured down more of his hottest rays and soon the monkey was able to pull out his two hands then he could pull out one foot then another and in a little while his body too", "subset": "babb", "task_type": "understanding", "prediction": "The monkey was at last able to pull out one of his hands. The sun poured down more of his hottest rays. And soon, the monkey was able to pull out his two hands. Then he could pull out 1 ft. Then another. And in a little while, his body, too.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm1-babb-sp5154-ch026559-sg0021-mc02-lav-clo-dg080.wav", "answer": "this is not the monkey's leg it is just a dry stick he said as he made a wry face then he fished the empty cocoanut shell out of the pot that is not the monkey's head he said as he tasted it", "subset": "babb", "task_type": "understanding", "prediction": "This is not the monkey's leg. It is just a dry stick, he said, as he made a wry face. Then he fished the empty cocoanut shell out of the pot. That is not the monkey's head, he said, as he tested it.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm1-babb-sp5189-ch037999-sg0001-mc01-stu-clo-dg030.wav", "answer": "for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries to the trip east together with minute instructions as to the journey itself selecting a proper school", "subset": "babb", "task_type": "understanding", "prediction": "for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries of the trip east together with minute instructions as to the journey itself selecting a proper school", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm1-babb-sp5189-ch056574-sg0007-mc02-lav-clo-dg120.wav", "answer": "sich a magnificent chance to make it manifest try yoor self particularly on custer tho after all continyood he in a musin abstracted sort a way wich he's fallen into lately the fellow is sich a triflin bein", "subset": "babb", "task_type": "understanding", "prediction": "such a magnificent chance to make it manifest try yourself particularly on custer though after all continued he in a musing abstracted sort of way which he has fallen into lately the fellow is such a trifling being", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5319/Lab41-SRI-VOiCES-rm1-babb-sp5319-ch042637-sg0002-mc02-lav-clo-dg010.wav", "answer": "districts and counties black men would be supported and elected to office because they were black and white men would be opposed and defeated because they were white taking mississippi for purposes of illustration", "subset": "babb", "task_type": "understanding", "prediction": "districts and counties black men would be supported and elected to office because they were black and white men would be opposed and defeated because they were white taking mississippi for purposes of illustration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5319/Lab41-SRI-VOiCES-rm1-babb-sp5319-ch042637-sg0003-mc01-stu-clo-dg120.wav", "answer": "it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position", "subset": "babb", "task_type": "understanding", "prediction": "it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5338/Lab41-SRI-VOiCES-rm1-babb-sp5338-ch024640-sg0009-mc01-stu-clo-dg080.wav", "answer": "since that time their numbers have gradually diminished but a good many are still to be found in the western counties and several with a better temper than in seventeen o seven have now taken arms for government", "subset": "babb", "task_type": "understanding", "prediction": "since that time their numbers have gradually diminished but a good many are still to be found in the western counties and several with a better temper than in seventeen o seven have now taken arms for government", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5386/Lab41-SRI-VOiCES-rm1-babb-sp5386-ch008684-sg0033-mc01-stu-clo-dg140.wav", "answer": "the son had a rope ready to cast round its horns and throw it to the ground but the ox was stronger than the rope and soon tore it in pieces then it dashed away to the wood the youth following over hedges and ditches they both went till they reached the rocky pass which bordered the herdsman's land", "subset": "babb", "task_type": "understanding", "prediction": "the sun had a rope ready to cast round its horns and throw it to the ground but the ox was stronger than the rope and soon tore it in pieces then it dashed away to the wood the youth following over hedges and ditches they both went till they reached the rocky pass which bordered the herdsman s land", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm1-babb-sp5456-ch062043-sg0003-mc01-stu-clo-dg080.wav", "answer": "she must have had a time of it it was my fate to take passage in this boat the captain was a good natured easy going man careful of the comfort of his passengers and exceedingly fond of the game of brag we had been out a little more than five days", "subset": "babb", "task_type": "understanding", "prediction": "she must have had a time of it it was my fate to take passage in this boat the captain was a good natured easy going man careful of the comfort of his passengers and exceedingly fond of the game of brag we had been out a little more than five days", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5583/Lab41-SRI-VOiCES-rm1-babb-sp5583-ch041259-sg0000-mc01-stu-clo-dg100.wav", "answer": "in the perusal of the following pages your sensibility will be most severely tried ah what were the misfortunes i had before experienced and which i have already related to you to the one i am now going to inform you of", "subset": "babb", "task_type": "understanding", "prediction": "in the perusal of the following pages your sensibility will be most severely tried ah what were the misfortunes i had before experienced and which i have already related to you to the one i am now going to inform you of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5583/Lab41-SRI-VOiCES-rm1-babb-sp5583-ch041259-sg0043-mc02-lav-clo-dg180.wav", "answer": "and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain", "subset": "babb", "task_type": "understanding", "prediction": "and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm1-babb-sp5678-ch043301-sg0011-mc02-lav-clo-dg100.wav", "answer": "the murmurs of talk rose into cheering old lord pemberton came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily", "subset": "babb", "task_type": "understanding", "prediction": "the murmurs of talk rose into cheering old lord pemberdon came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5802/Lab41-SRI-VOiCES-rm1-babb-sp5802-ch066347-sg0012-mc02-lav-clo-dg010.wav", "answer": "for example said the doctor of course we don't doubt your word but when a man makes a statement based upon personal observation it is profitable to ask him what his precise experience has been merely for the purpose of adding to our own knowledge", "subset": "babb", "task_type": "understanding", "prediction": "for example said the doctor of course we do not doubt your word but when a man makes a statement based upon personal observation it is profitable to ask him what his precise experience has been merely for the purpose of adding to our own knowledge", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm1-babb-sp5868-ch055088-sg0015-mc02-lav-clo-dg050.wav", "answer": "and the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth is whirled through europe without gaining a single idea worth crossing the street for", "subset": "babb", "task_type": "understanding", "prediction": "and the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth has whirled through europe without gaining a single idea worth crossing the straits for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp6099/Lab41-SRI-VOiCES-rm1-babb-sp6099-ch069550-sg0012-mc02-lav-clo-dg160.wav", "answer": "and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful", "subset": "babb", "task_type": "understanding", "prediction": "and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm1-babb-sp6147-ch034605-sg0039-mc01-stu-clo-dg170.wav", "answer": "she wore great dresses of velvet satin or moire some composed of fifteen or sixteen yards of material with embroideries of gold and silver and round her waist many knots of pearls alternating with other precious stones she was extravagant in gold lace", "subset": "babb", "task_type": "understanding", "prediction": "she wore great dresses of velvet satin or moire some composed of fifteen or sixteen yards of material with embroideries of gold and silver and round her waist many knots of pearls alternating with other precious stones she was extravagant in gold lace", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm1-babb-sp6147-ch034607-sg0031-mc02-lav-clo-dg080.wav", "answer": "in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher wren is a very passable mansard somers is as good as lamoignon anne has a racine in dryden", "subset": "babb", "task_type": "understanding", "prediction": "in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher rand is a very passable mazarin somers is as good as lemoignon anne has a racine in dryden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm1-babb-sp6241-ch061946-sg0006-mc01-stu-clo-dg130.wav", "answer": "i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur", "subset": "babb", "task_type": "understanding", "prediction": "i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm1-babb-sp6395-ch087997-sg0045-mc02-lav-clo-dg090.wav", "answer": "but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive", "subset": "babb", "task_type": "understanding", "prediction": "but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm1-babb-sp6415-ch100596-sg0002-mc02-lav-clo-dg070.wav", "answer": "georgie stopped to examine some loose sheets of paper which were impaled upon the door what's this patty oh that's the registration list for the german club priscilla's secretary you know and every one who wants to join comes here", "subset": "babb", "task_type": "understanding", "prediction": "georgie stopped to examine some loose sheets of paper which were impaled upon the door what s this paddy oh that s the registration list for the german club priscilla s secretary you know and everybody who wants to join comes here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm1-babb-sp6415-ch111615-sg0024-mc01-stu-clo-dg120.wav", "answer": "who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible", "subset": "babb", "task_type": "understanding", "prediction": "who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm1-babb-sp6519-ch069412-sg0034-mc02-lav-clo-dg170.wav", "answer": "the proprietor's name is yardley we have nothing against him the place is highly respectable but it harbours a boarder a permanent one i believe who has occasioned no little comment no one has ever seen her face unless it is the landlord's wife", "subset": "babb", "task_type": "understanding", "prediction": "the proprietor s name is yardley we have nothing against him the place is highly respectable but it harbors a boarder an incipient one i believe who has occasioned no little comment no one has ever seen her face unless it is the landlord s wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm1-babb-sp6519-ch231834-sg0004-mc02-lav-clo-dg080.wav", "answer": "close at hand various artifices aided her to pass for thirty and it was only in the solitude of her own room that her real age was apparent never did woman wage a more resolute fight with time than did miss greeb", "subset": "babb", "task_type": "understanding", "prediction": "close at hand various artifices aided her to pass for thirty and it was only in the solitude of her own room that her real age was apparent never did woman wage a more resolute fight with time than did miss gree", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm1-babb-sp6519-ch231834-sg0020-mc01-stu-clo-dg170.wav", "answer": "but what grounds have you to believe him any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence", "subset": "babb", "task_type": "understanding", "prediction": "but what grounds have you to believe in any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6696/Lab41-SRI-VOiCES-rm1-babb-sp6696-ch068773-sg0000-mc01-stu-clo-dg020.wav", "answer": "lucy's ghost kenneth had sent word to tom gates asking the young man to come to elmhurst but it was not until two days after the lawn party that tom appeared and asked permission to see mister forbes beth and louise were with kenneth at the time", "subset": "babb", "task_type": "understanding", "prediction": "lucy s ghost kenneth had sent word to tom gates asking the young man to come to elmhurst but it was not until two days after the lawn party that tom appeared and asked permission to see mr forbes beth and louise were with kenneth at the time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-babb-sp6895-ch092805-sg0008-mc01-stu-clo-dg040.wav", "answer": "the local note of the mere globe trotter but his opinions never fluttered or drooped he was as impartial to cities countries and continents as the winds or gravitation and as e rushmore coglan prattled of this little planet i thought with glee", "subset": "babb", "task_type": "understanding", "prediction": "the local note of the mere globe trotter but his opinions never fluttered or drooped he was as impartial to cities countries and continents as the wind or gravitation and as e rushmore coburn prattled of this little planet i thought with glee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-babb-sp6895-ch092805-sg0008-mc02-lav-clo-dg040.wav", "answer": "the local note of the mere globe trotter but his opinions never fluttered or drooped he was as impartial to cities countries and continents as the winds or gravitation and as e rushmore coglan prattled of this little planet i thought with glee", "subset": "babb", "task_type": "understanding", "prediction": "the local note of the mere globe trotter but his opinions never fluttered or drew he was impartial to cities countries and continents as the wind or gravitation and as eve rushmore cokely prattled of this little planet i thought with glee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-babb-sp6895-ch092806-sg0009-mc02-lav-clo-dg180.wav", "answer": "there was something in her manner that warned mister mc caskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware pig's face is it said missus mc caskey and hurled a stewpan full of bacon and turnips at her lord", "subset": "babb", "task_type": "understanding", "prediction": "there was something in her manner that warned mr maccaskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware pig's face is it said mrs maccaskey and hurled a stew pan full of bacon and turnips at her lord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm1-babb-sp6965-ch277899-sg0013-mc02-lav-clo-dg180.wav", "answer": "brown with a darkish tail norah changed colour does it live in a tree and eat nuts she asked hoping that the use of the adjective large might be an exaggeration vladimir laughed", "subset": "babb", "task_type": "understanding", "prediction": "brown with a darkish tail norah changed colour does it live in a tree and eat nuts she asked hoping that the use of the adjective large might be an exaggeration vladimir laughed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm1-babb-sp7000-ch083696-sg0027-mc01-stu-clo-dg000.wav", "answer": "well he said it's a pity it should be wasted i'll eat it myself which he did and me standing in the rain there looking on that did put my back up mister evans i said short and sharp i wish you a good day i am going", "subset": "babb", "task_type": "understanding", "prediction": "well he said it is a pity it should be wasted i ll leave it myself which he did and me standing in the rain there looking on that did put my back up mr evans i said short and sharp i wish you a good day i am going", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm1-babb-sp7095-ch088489-sg0021-mc01-stu-clo-dg170.wav", "answer": "the great orthodox body of religiosa dementia fell back upon the remainder of the theory that the hebrew language was the first of all languages which was spoken by the almighty given by him to adam", "subset": "babb", "task_type": "understanding", "prediction": "the great orthodox body of religiosa dementia fell back upon the remainder of the theory that the hebrew language was the first of all languages which was spoken by the almighty given by him to adam", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm1-babb-sp7148-ch007763-sg0001-mc01-stu-clo-dg130.wav", "answer": "it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing", "subset": "babb", "task_type": "understanding", "prediction": "it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm1-babb-sp7148-ch082991-sg0013-mc02-lav-clo-dg170.wav", "answer": "are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king's highness said the tall man", "subset": "babb", "task_type": "understanding", "prediction": "are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king s highness said the tall man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7264/Lab41-SRI-VOiCES-rm1-babb-sp7264-ch092316-sg0028-mc02-lav-clo-dg060.wav", "answer": "no one of them is in any sense general or really national the free press gives you the truth but only in disjointed sections for it is disparate and it is particularist it is marked with isolation and it is so marked because its origin lay in various and most diverse propaganda", "subset": "babb", "task_type": "understanding", "prediction": "no one of them is in any sense general or really national the free press gives you the truth but only in disjointed sections for it is disparate and it is particularist it is marked with isolation and it is so marked because it is originally in various and most diverse propaganda", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7276/Lab41-SRI-VOiCES-rm1-babb-sp7276-ch090847-sg0006-mc01-stu-clo-dg060.wav", "answer": "alas what are we to do i can not take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing", "subset": "babb", "task_type": "understanding", "prediction": "alas what are we to do i cannot take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7276/Lab41-SRI-VOiCES-rm1-babb-sp7276-ch090847-sg0045-mc02-lav-clo-dg030.wav", "answer": "and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen", "subset": "babb", "task_type": "understanding", "prediction": "and it is thanks to him that i have returned in time with the storm at my heels you mariana are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm1-babb-sp7278-ch246956-sg0032-mc02-lav-clo-dg110.wav", "answer": "let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves", "subset": "babb", "task_type": "understanding", "prediction": "let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm1-babb-sp7445-ch094523-sg0020-mc01-stu-clo-dg180.wav", "answer": "that the parliament while it sits must first proceed upon the king's business and that this assembly cannot without his consent impeach any of his ministers and judges even according to our present strict maxims with regard to law and the royal prerogative", "subset": "babb", "task_type": "understanding", "prediction": "That the Parliament, while it sits, must first proceed upon the king's business and that this Assembly cannot, without his consent. Impeach any of his ministers and judges. Even according to our present strict maxims. With regard to the law and the royal prerogative.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099124-sg0010-mc01-stu-clo-dg040.wav", "answer": "humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former", "subset": "babb", "task_type": "understanding", "prediction": "humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099156-sg0024-mc01-stu-clo-dg050.wav", "answer": "dated twenty sixth august in which she informs him that she has a prospect of being a mother in the month of november and of thus attaining what has been her only wish ungratified for these four years she writes from hamburg where she was on a visit to her family", "subset": "babb", "task_type": "understanding", "prediction": "dated twenty sixth august in which she informs him that she has a prospect of being a mother in the month of november and of thus attaining what has been her only wish ungratified for these four years she writes from hamburg where she was on a visit to her family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099157-sg0011-mc02-lav-clo-dg000.wav", "answer": "having submitted her first drawings to sir hans sloane and doctor mead these eminent physicians encouraged her to proceed with the work she also received the kindest countenance from mister philip miller a well known writer on horticulture", "subset": "babb", "task_type": "understanding", "prediction": "having submitted her first drawings to sir hans sloane and dr mead these eminent physicians encouraged her to proceed with the work she also received the kindest countenance from mr philip miller a well known writer on horticulture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099157-sg0017-mc02-lav-clo-dg040.wav", "answer": "he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on agriculture he went there leaving his wife in england he was received with honour at the court of stockholm", "subset": "babb", "task_type": "understanding", "prediction": "he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on aquaculture he went there leaving his wife in england he was received with honour at the court of stockholm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm1-babb-sp7540-ch101262-sg0041-mc01-stu-clo-dg000.wav", "answer": "come to me o mare of the mountain witch the prince did as he was bid and as the hair touched his fingers the wolf changed back into a mare with the foal beside her and when he had mounted and ridden her home the old woman was on the steps to receive them", "subset": "babb", "task_type": "understanding", "prediction": "come to me o mare of the mountain witch prince did as he was bid and as the hair touched his fingers the wolf changed back into a mare with the foal beside her and when he had mounted and ridden her home the old woman was on the steps to receive them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7704/Lab41-SRI-VOiCES-rm1-babb-sp7704-ch106965-sg0012-mc01-stu-clo-dg120.wav", "answer": "who is she asked teddy as tired and exhausted by his recital he threw himself on the grass to rest one of the bigger boys answered him i seed her come yesterday in a cab from the town to old sol at the turnpike she and her mother i reckon", "subset": "babb", "task_type": "understanding", "prediction": "who is she asked teddy as tired and exhausted by his recital he threw himself on the grass to rest one of the bigger boys answered him i seed her come yesterday in a cab from the town to old sol at the turnpike she and her mother i reckon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm1-babb-sp7868-ch110705-sg0018-mc01-stu-clo-dg040.wav", "answer": "something like that of a kettle on the boil gluck looked out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment", "subset": "babb", "task_type": "understanding", "prediction": "something like that of a kettle on the boil luck looked out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm1-babb-sp7881-ch109662-sg0030-mc01-stu-clo-dg040.wav", "answer": "merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her", "subset": "babb", "task_type": "understanding", "prediction": "merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7910/Lab41-SRI-VOiCES-rm1-babb-sp7910-ch105673-sg0041-mc02-lav-clo-dg130.wav", "answer": "there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries", "subset": "babb", "task_type": "understanding", "prediction": "there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm1-babb-sp7932-ch093470-sg0011-mc02-lav-clo-dg120.wav", "answer": "i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruth's own wish that it should be told to others", "subset": "babb", "task_type": "understanding", "prediction": "i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruths own wish that it should be told to others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-babb-sp7976-ch110124-sg0013-mc02-lav-clo-dg020.wav", "answer": "the two eldest ate their apples but the youngest could not eat that night she threw the apple away", "subset": "babb", "task_type": "understanding", "prediction": "The two eldest ate their apples, but the youngest could not eat that night. She threw the apple away.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-babb-sp7976-ch110124-sg0018-mc02-lav-clo-dg040.wav", "answer": "the merchant's daughter at first did not answer but as he kept on calling to her she finally asked him what it was that he wanted", "subset": "babb", "task_type": "understanding", "prediction": "The merchant's daughter at first did not answer, but as he kept on calling to her, she finally asked him what it was that he wanted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-babb-sp7981-ch112058-sg0001-mc02-lav-clo-dg010.wav", "answer": "to endow a band of priests who would devote their lives to evangelizing the peasantry on her estates vincent was delighted but considering himself unfit to undertake the management of such an enterprise he proposed that it should be put into the hands of the jesuits or the oratorians", "subset": "babb", "task_type": "understanding", "prediction": "they would now a band of priests who would devote their lives to evangelizing the peasantry on her estates vincent was delighted but considering himself unfit to undertake the management of such an enterprise he proposed that it should be put into the hands of the jesuits or the oratorians", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm1-babb-sp7995-ch276908-sg0029-mc02-lav-clo-dg060.wav", "answer": "in which on the lovely tenth of june under a serene sky the amorous jacobite kissing the odoriferous zephyr's breath gathers a nosegay of white roses to deck the whiter breast of celia", "subset": "babb", "task_type": "understanding", "prediction": "in which on the lovely tenth of june under a serene sky the amorous gigolite kissing the odoriferous zephyr s breath gathers a nosegay of white roses to deck the whiter breast of celia", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8051/Lab41-SRI-VOiCES-rm1-babb-sp8051-ch119902-sg0019-mc02-lav-clo-dg000.wav", "answer": "and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits", "subset": "babb", "task_type": "understanding", "prediction": "and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm1-babb-sp8108-ch280359-sg0013-mc02-lav-clo-dg150.wav", "answer": "by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death", "subset": "babb", "task_type": "understanding", "prediction": "by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8118/Lab41-SRI-VOiCES-rm1-babb-sp8118-ch114469-sg0018-mc01-stu-clo-dg090.wav", "answer": "then the wind shifted and drove the sheets of rain sprinkled with hail directly in his face he was compelled to stop a while and take refuge behind a big oak while he shivered in the shelter of the tree the only things that he thought of spontaneously were dry clothes hot food a fire and a warm bed", "subset": "babb", "task_type": "understanding", "prediction": "then the wind shifted and drove the sheets of rain sprinkled with hail directly in his face he was compelled to stop a while and take refuge behind a big oak while he shivered in the shelter of the tree the only things that he thought of spontaneously were dry clothes hot food a fire and a warm bed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm1-babb-sp8225-ch274375-sg0023-mc01-stu-clo-dg030.wav", "answer": "the necessities of the garrison were extreme one barrel of powder was their whole stock of ammunition remaining and their other provisions were in the same proportion essex had brought with him military stores and the neighboring country abundantly supplied him with victuals of every kind", "subset": "babb", "task_type": "understanding", "prediction": "the necessities of the garrison were extreme one barrel of powder was their whole stock of ammunition remaining and their other provisions were in the same proportion essex had brought with him military stores and the neighboring country abundantly supplied him with victuals of every kind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm1-babb-sp8225-ch274376-sg0000-mc02-lav-clo-dg120.wav", "answer": "the establishment of presbyterian discipline in their own country they were not satisfied but indulged still in an ardent passion for propagating by all methods that mode of religion in the neighboring kingdoms having flattered themselves in the fervor of their zeal", "subset": "babb", "task_type": "understanding", "prediction": "the establishment of presbyterian discipline in their own country they were not satisfied but indulged still in an ardent passion for propagating by all methods that mode of religion in the neighbouring kingdoms having flattered themselves in the fervour of their zeal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm1-babb-sp8266-ch279363-sg0024-mc01-stu-clo-dg100.wav", "answer": "they are in the nearer thickets cried the colonel and now they're climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest", "subset": "babb", "task_type": "understanding", "prediction": "they are in the nearer thickets cried the colonel and now they are climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-babb-sp8425-ch291444-sg0013-mc01-stu-clo-dg150.wav", "answer": "the infant years of our city to introduce a thousand pleasing fictions but i have scrupulously discarded many a pithy tale and marvelous adventure whereby the drowsy ear of summer indolence might be enthralled", "subset": "babb", "task_type": "understanding", "prediction": "the infant years of our city to introduce a thousand pleasing fictions but i have scrupulously discarded many a pithy tale and marvellous adventure whereby the drowsy ear of summer indolence might be enthralled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-babb-sp8425-ch292520-sg0004-mc01-stu-clo-dg030.wav", "answer": "and dinning market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare's light into one sacred rhythm for the devil's spite a woman's thin raucous voice carries the tune bids men rejoice", "subset": "babb", "task_type": "understanding", "prediction": "the dinny market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare s light into one sacred rhythm for the devil s fight a woman s thin raucous voice carries the tune bids men rejoice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-babb-sp8425-ch292520-sg0013-mc02-lav-clo-dg040.wav", "answer": "light green in the deeps like your eyes in sunshine winds the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel", "subset": "babb", "task_type": "understanding", "prediction": "light green in the deeps like your eyes in sunshine why is the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8575/Lab41-SRI-VOiCES-rm1-babb-sp8575-ch290350-sg0016-mc02-lav-clo-dg080.wav", "answer": "which we apply to all parts of time whose lengths we would consider yet there may be other parts of the universe where they no more use these measures of ours than in japan they do our inches feet or miles but yet something analogous to them there must be for without some regular periodical returns", "subset": "babb", "task_type": "understanding", "prediction": "which we apply to all parts of time whose lengths we would consider yet there may be other parts of the universe where they no more use these measures of ours than in japan they do our inches feet or miles but yet something analogous to them there must be for without some regular periodical returns", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8575/Lab41-SRI-VOiCES-rm1-babb-sp8575-ch290351-sg0021-mc01-stu-clo-dg010.wav", "answer": "and thus likewise we sometimes speak of place distance or bulk in the great inane beyond the confines of the world when we consider so much of that space as is equal to or capable to receive a body of any assigned dimensions as a cubic foot or do suppose a point in it", "subset": "babb", "task_type": "understanding", "prediction": "and thus likewise we sometimes speak of place distance or bulk in the great innate beyond the confines of the world when we consider so much of that space as is equal to or capable to receive a body of any assigned dimensions as a cubic foot or do you suppose a point in it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8635/Lab41-SRI-VOiCES-rm1-babb-sp8635-ch295756-sg0013-mc02-lav-clo-dg170.wav", "answer": "they came to the house where they were to be fed and lodged the wood men went to bed with their clothes on but george took his off and as he turned in he found his bed was of loose straw with not a thing on it but the thread bare blank et he was to wrap him self in", "subset": "babb", "task_type": "understanding", "prediction": "they came to the house where they were to be fed and lodged the woodmen went to bed with their clothes on but george took his off and as he turned in he found his bed was of loose straw with not a thing on it but the threadbare blanket he was to wrap himself in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8635/Lab41-SRI-VOiCES-rm1-babb-sp8635-ch295756-sg0026-mc02-lav-clo-dg040.wav", "answer": "a doub loon is a gold coin of spain worth not quite sixteen dol lars a pis tole is a small gold coin of spain worth not quite four dol lars this rough kind of life though he did not know it was to fit him for the toils and ills of war", "subset": "babb", "task_type": "understanding", "prediction": "a doubloon is a gold coin of spain worth not quite sixteen dollars a pistole is a small gold coin of spain worth not quite four dollars this rough kind of life though he did not know it was to fit him for the toils and ills of war", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8677/Lab41-SRI-VOiCES-rm1-babb-sp8677-ch246948-sg0037-mc02-lav-clo-dg160.wav", "answer": "then will he forgive and endure and pour out his soul for the beloved who yet grope their way in doubt and passion then every man will be dear and precious to him even the worst for in him also lies an unknown yearning after the same peace wherein he rests and loves", "subset": "babb", "task_type": "understanding", "prediction": "Then will he forgive and endure and pour out his soul for the beloved. Who yet grope their way in doubt and passion. Then every man will be dear and precious to him, even the worst for in him also lies an unknown yearning after the same peace wherein he rests and loves.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8677/Lab41-SRI-VOiCES-rm1-babb-sp8677-ch291953-sg0010-mc02-lav-clo-dg060.wav", "answer": "brave urien sleeps upon his craggy bed mountains ye mourn in vain modred whose magic song made huge plinlimmon bow his cloud topt head on dreary arvon's shore they lie smear'd with gore and ghastly pale", "subset": "babb", "task_type": "understanding", "prediction": "brave urien sleeps upon his craggy bed mountain she mourning vain modred whose magic song made huge glendower bow his cloud topped head on dreary arvon shore they lie smeared with gore and ghastly pale", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8677/Lab41-SRI-VOiCES-rm1-babb-sp8677-ch296078-sg0009-mc02-lav-clo-dg160.wav", "answer": "when these things happened aunt florence was called in as a matter of course and she set the fractures and salved the burns and stopped the flow of sawdust and proved herself in every way a most skillful nursery surgeon and physician", "subset": "babb", "task_type": "understanding", "prediction": "when these things happened aunt florence was called in as a matter of course and she set the fractures and salved the burns and stopped the flow of sawdust and proved herself in every way a most skillful nursery surgeon and physician", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm1-babb-sp8713-ch296159-sg0005-mc01-stu-clo-dg010.wav", "answer": "for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling", "subset": "babb", "task_type": "understanding", "prediction": "for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0093/Lab41-SRI-VOiCES-rm1-musi-sp0093-ch123172-sg0024-mc02-lav-clo-dg020.wav", "answer": "put more on in two days keep it in a cold place in three or four days it will do to stretch on sticks hang it up in a dry cool place with as much salt as will stick to it when quite dry put it in a paper bag and hang it up", "subset": "musi", "task_type": "understanding", "prediction": "put more on in two days keep it in a cold place in three or four days will do to stretch on sticks hang it up in a dry cool place with as much salt as will stick to it when quite dry put it in a paper bag and hang it up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-musi-sp0112-ch121671-sg0019-mc01-stu-clo-dg000.wav", "answer": "asked the grandmother who was sitting upon her doorsteps engaged in mending sixteen pairs of stockings at your house the stranger replied it looks for all the world like a big shoe a shoe she said in surprise why yes", "subset": "musi", "task_type": "understanding", "prediction": "asked the grandmother who was sitting upon her doorstep engaged in mending sixteen pairs of stockings that s your house the stranger replied it looks for all the world like a big shoe a shoe she said in surprise why yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-musi-sp0112-ch123215-sg0025-mc01-stu-clo-dg080.wav", "answer": "of tolerant wonder anne despite her affection for rusty was not especially fond of cats but missus gardner's tone annoyed her inconsequently she remembered that missus john blythe was so fond of cats that she kept as many as her husband would allow", "subset": "musi", "task_type": "understanding", "prediction": "of tolerant wonder anne despite her affection for rusty was not especially fond of cats but mrs gardiner s tone annoyed her inconsequently she remembered that mrs john blythe was so fond of cats that she kept as many as her husband would allow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-musi-sp0122-ch121729-sg0022-mc02-lav-clo-dg070.wav", "answer": "and devoted to the rubber industry negro one who votes your way nigger one who doesn't neighbor one who knows more about your affairs than yourself", "subset": "musi", "task_type": "understanding", "prediction": "and devoted to the rubber industry negro one who votes your way nigger one who doesn t neighbor one who knows more about your affairs than yourself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-musi-sp0122-ch121730-sg0018-mc01-stu-clo-dg000.wav", "answer": "pawnbroker a mercenary man to whom money is the one redeeming quality peace a mythical condition of tranquillity frequently reported from the phillipines peach a popular synonym for fair woman", "subset": "musi", "task_type": "understanding", "prediction": "pawnbroker a mercenary man to whom money is the one redeeming quality peace a mythical condition of tranquility frequently reported from the philippines peach a popular synonym for fair woman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0159/Lab41-SRI-VOiCES-rm1-musi-sp0159-ch121891-sg0012-mc02-lav-clo-dg040.wav", "answer": "for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature", "subset": "musi", "task_type": "understanding", "prediction": "for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0174/Lab41-SRI-VOiCES-rm1-musi-sp0174-ch168635-sg0002-mc01-stu-clo-dg030.wav", "answer": "his sister and his sister's children had left him only a vague and far off memory which had finally almost completely vanished he had made every effort to find them and not having been able to find them he had forgotten them", "subset": "musi", "task_type": "understanding", "prediction": "his sister and his sister's children had left him only a vague and far off memory which had finally almost completely vanished he had made every effort to find them and not having been able to find them he had forgotten them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-musi-sp0205-ch123882-sg0036-mc01-stu-clo-dg020.wav", "answer": "bill and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely as the great swamp just this side of the bridge over the ossawippi", "subset": "musi", "task_type": "understanding", "prediction": "bill and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely is the great swamp just this side of the bridge over the ossolipi", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-musi-sp0205-ch157088-sg0010-mc02-lav-clo-dg150.wav", "answer": "and sat watching olaf as he mothered the half baked bannock loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range", "subset": "musi", "task_type": "understanding", "prediction": "and sat watching olaf essie mother the half baked bannock loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm1-musi-sp0208-ch126851-sg0026-mc01-stu-clo-dg070.wav", "answer": "so long as the hens lay eggs and the cow gives milk we can have omelettes and junket and there are plenty of vegetables left in the garden the winter is still a long way off don't fuss that was the trouble with sarah she would fuss", "subset": "musi", "task_type": "understanding", "prediction": "so long as the hens lay eggs and the cow gives milk we can have omelets and junket and there are plenty of vegetables left in the garden the winter is still a long way off dont fuss that was the trouble with sarah she would fuss", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0224/Lab41-SRI-VOiCES-rm1-musi-sp0224-ch129790-sg0006-mc02-lav-clo-dg040.wav", "answer": "his mind went back over the adventure of yesterday if of yesterday it was he was clear on the matter of the easily successful raid upon the island of barbados every detail stood vividly in his memory up to the moment at which", "subset": "musi", "task_type": "understanding", "prediction": "his mind went back over the adventure of yesterday if of yesterday it was he was clear of the matter of the easily successful raid upon the island of barbados every detail stood vividly in his memory up to the moment at which", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-musi-sp0242-ch122625-sg0006-mc01-stu-clo-dg070.wav", "answer": "men too often confound them they should not be confounded appearance should not be mistaken for truth narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of christ", "subset": "musi", "task_type": "understanding", "prediction": "Men too often confound them. They should not be confounded. Appearance should not be mistaken for truth. Narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of Christ.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0296/Lab41-SRI-VOiCES-rm1-musi-sp0296-ch141721-sg0027-mc02-lav-clo-dg120.wav", "answer": "and gave him an honourable military post in his army with a farther promise of promotion to the highest dignity but upon this express condition that he would act for the future as a soldier of honour but assur'd him at the same time", "subset": "musi", "task_type": "understanding", "prediction": "and give him an honourable military post in his army with a farther promise of promotion to the highest dignity but upon this express condition that he would act for the future as a soldier of honour but assured him at the same time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm1-musi-sp0459-ch127521-sg0016-mc02-lav-clo-dg150.wav", "answer": "hung over us like a thunder cloud and it was not only we of the cabin party who perceived the danger long john was hard at work going from group to group spending himself in good advice and as for example no man could have shown a better", "subset": "musi", "task_type": "understanding", "prediction": "hung over us like a thundercloud and it was not only we of the cabin party who perceived the danger long john was hard at work going from group to group spending himself in good advice and as for example no man could have shown a better", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm1-musi-sp0459-ch127521-sg0018-mc01-stu-clo-dg140.wav", "answer": "appeared the worst we held a council in the cabin sir said the captain if i risk another order the whole ship'll come about our ears by the run you see sir here it is i get a rough answer do i not", "subset": "musi", "task_type": "understanding", "prediction": "appeared the worst we held a council in the cabin sir said the captain if i risk another order the whole ship will come about our ears by the run you see sir here it ends i get a rough answer do i not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm1-musi-sp0459-ch127522-sg0016-mc01-stu-clo-dg020.wav", "answer": "the rocks of the spy glass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain", "subset": "musi", "task_type": "understanding", "prediction": "The rocks of the spyglass reechoed it a score of times. The whole troop of marsh birds rose again, darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-musi-sp0480-ch123176-sg0003-mc01-stu-clo-dg130.wav", "answer": "if the room is kept perfectly still boiled custard beat an egg with a heaped tea spoonful of sugar stir it into a tea cupful of boiling milk and stir till it is thick", "subset": "musi", "task_type": "understanding", "prediction": "if the room is kept perfectly still boiled custard beat an egg with a heaped teaspoonful of sugar stir it into a teacup full of boiling milk and stir till it is thick", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-musi-sp0480-ch126292-sg0012-mc01-stu-clo-dg020.wav", "answer": "so chanticleer built a handsome carriage with four red wheels and harnessed six mice to it and then he and partlet got into the carriage and away they drove soon afterwards a cat met them and said where are you going", "subset": "musi", "task_type": "understanding", "prediction": "so chanticleer built a handsome carriage with four red wheels and harnessed six mice to it and then he and partlick got into the carriage and away they drove soon afterwards a cat met them and said where are you going", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-musi-sp0480-ch127525-sg0009-mc01-stu-clo-dg180.wav", "answer": "returned the captain we must keep upstream you see sir he went on if once we dropped to leeward of the landing place it's hard to say where we should get ashore", "subset": "musi", "task_type": "understanding", "prediction": "returned the captain we must keep up stream you see sir he went on if once we drop to the leeward of the landing place it is hard to say where we should get ashore", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm1-musi-sp0492-ch131899-sg0008-mc01-stu-clo-dg010.wav", "answer": "he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation", "subset": "musi", "task_type": "understanding", "prediction": "he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm1-musi-sp0636-ch128310-sg0029-mc02-lav-clo-dg120.wav", "answer": "growling over it like any four footed inmate of a menagerie towards nine o'clock he smoothed his ruffled aspect and presenting as respectable and business like an exterior as he could overlay his natural self with issued forth to the occupation of the day", "subset": "musi", "task_type": "understanding", "prediction": "growling over it like any four footed inmate of a menagerie towards nine o clock he smoothed his ruffled aspect and presenting as respectable and business like an exterior as he could overlay his natural self with issued forth to the occupation of the day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm1-musi-sp0636-ch128331-sg0021-mc01-stu-clo-dg150.wav", "answer": "and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth", "subset": "musi", "task_type": "understanding", "prediction": "and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm1-musi-sp0637-ch127579-sg0010-mc02-lav-clo-dg070.wav", "answer": "induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object", "subset": "musi", "task_type": "understanding", "prediction": "induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm1-musi-sp0637-ch127595-sg0003-mc02-lav-clo-dg140.wav", "answer": "would commence a low dismal and monotonous chant accompanying the voice with the instrumental melody produced by two small half rotten sticks tapped slowly together a pair of which were held in the hands of each person present", "subset": "musi", "task_type": "understanding", "prediction": "would commence a low dismal and monotonous chant accompanying the voice with the instrumental melody produced by two small half rotten sticks tapped slowly together a pair of which were held in the hands of each person present", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0652/Lab41-SRI-VOiCES-rm1-musi-sp0652-ch129742-sg0015-mc02-lav-clo-dg170.wav", "answer": "put the pulp into a basin with two ounces of melted butter two tablespoonfuls of lemon juice half a pound of chestnuts boiled and grated and seasoning of salt and white pepper to taste", "subset": "musi", "task_type": "understanding", "prediction": "put the pulp into a basin with two ounces of melted butter two tablespoonfuls of lemon juice half a pound of chestnuts boiled and grated and seasoning of salt and white pepper to taste", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0882/Lab41-SRI-VOiCES-rm1-musi-sp0882-ch123266-sg0029-mc02-lav-clo-dg000.wav", "answer": "i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay", "subset": "musi", "task_type": "understanding", "prediction": "i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0948/Lab41-SRI-VOiCES-rm1-musi-sp0948-ch132705-sg0009-mc01-stu-clo-dg090.wav", "answer": "a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said", "subset": "musi", "task_type": "understanding", "prediction": "a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm1-musi-sp0949-ch134657-sg0022-mc02-lav-clo-dg000.wav", "answer": "who labored to disguise the truths of facts and to pervert the sense of the laws he sometimes forgot the gravity of his station asked indiscreet or unseasonable questions and betrayed by the loudness of his voice and the agitation of his body the earnest vehemence", "subset": "musi", "task_type": "understanding", "prediction": "who labored to disguise the truth of facts and to pervert the sense of the laws he sometimes forgot the grabby of a station asked indiscreet or unseasonable questions and betrayed by the loudness of his voice and the agitation of his body the earnest venoms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm1-musi-sp0949-ch138545-sg0032-mc02-lav-clo-dg120.wav", "answer": "this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown", "subset": "musi", "task_type": "understanding", "prediction": "this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm1-musi-sp0949-ch162667-sg0034-mc02-lav-clo-dg020.wav", "answer": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "subset": "musi", "task_type": "understanding", "prediction": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1052/Lab41-SRI-VOiCES-rm1-musi-sp1052-ch139307-sg0027-mc01-stu-clo-dg160.wav", "answer": "he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what council could it be that gathered there", "subset": "musi", "task_type": "understanding", "prediction": "he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what counsel could it be that gathered there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm1-musi-sp1066-ch005330-sg0006-mc02-lav-clo-dg110.wav", "answer": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune", "subset": "musi", "task_type": "understanding", "prediction": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm1-musi-sp1066-ch103481-sg0002-mc01-stu-clo-dg080.wav", "answer": "and hope looked out again from tired eyes down where the white point gardens drank the sun and rippled to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a taunt", "subset": "musi", "task_type": "understanding", "prediction": "and hope looked out again from tired eyes down where the white point gardens strike the sun and ripple to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a taunt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm1-musi-sp1112-ch001043-sg0000-mc02-lav-clo-dg010.wav", "answer": "chapter seven a sprained ankle i was panic stricken as i ran along the corridor i was confident that the mysterious intruder and probable murderer had been found and that he lay dead or dying at the foot of the chute i got down the staircase somehow and through the kitchen to the basement stairs", "subset": "musi", "task_type": "understanding", "prediction": "chapter seven a sprained ankle i was panic stricken as i ran along the corridor i was confident that the mysterious intruder and probable murderer had been found and that he lay dead or dying at the foot of the chute i got down the staircase somehow and through the kitchen to the basement stairs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm1-musi-sp1112-ch001043-sg0006-mc02-lav-clo-dg070.wav", "answer": "but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cozy", "subset": "musi", "task_type": "understanding", "prediction": "but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cosy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm1-musi-sp1112-ch128138-sg0000-mc01-stu-clo-dg120.wav", "answer": "mister ian hamilton's ballad of hadji is undeniably clever hadji is a wonderful arab horse that a reckless hunter rides to death in the pursuit of a wild boar and the moral of the poem for there is a moral", "subset": "musi", "task_type": "understanding", "prediction": "Mr. Ian Hamiltons Ballad of Hadji is undeniably clever. Hadji is a wonderful Arab horse that a reckless hunter rides to death in the pursuit of a wild boar. And the moral of the poem for there is a moral.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm1-musi-sp1116-ch132851-sg0021-mc01-stu-clo-dg020.wav", "answer": "while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her", "subset": "musi", "task_type": "understanding", "prediction": "while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm1-musi-sp1116-ch137572-sg0003-mc01-stu-clo-dg060.wav", "answer": "when one has received the promise of something greatly desired but must wait awhile before its delivery the happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight", "subset": "musi", "task_type": "understanding", "prediction": "when one has received the promise of something greatly desired but must wait a while before its delivery the happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm1-musi-sp1116-ch137572-sg0048-mc01-stu-clo-dg070.wav", "answer": "but instead a complete trust in each other one who prides himself or herself on having to be handled with gloves has a great deal of growing up to do in order to be able to be an active partner in the marriage cry babying is no more helpful in marriage than in business or social life", "subset": "musi", "task_type": "understanding", "prediction": "but instead a complete trust in each other one who prides himself or herself on having to be handled with gloves has a great deal of growing up to do in order to be able to be an active partner in the marriage pry babying is no more helpful in marriage than in business or social life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1121/Lab41-SRI-VOiCES-rm1-musi-sp1121-ch176698-sg0034-mc02-lav-clo-dg100.wav", "answer": "and tossed her head indignantly but slowly as they went they came within sight of the house at last with its quaint gables and many latticed windows and the blue smoke curling up from its twisted chimneys", "subset": "musi", "task_type": "understanding", "prediction": "and tossed her head indignantly but slowly as they wept they came within sight of the house at last with its quaint gables and many lacquered windows and the blue smoke curling up from its twisted chimneys", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm1-musi-sp1160-ch134674-sg0003-mc01-stu-clo-dg110.wav", "answer": "and dejected countenances and without daring to complain of the murder of their king they affirmed with solemn oaths that the late invasion was the crime of some irregular robbers which the public council of the nation condemned and abhorred", "subset": "musi", "task_type": "understanding", "prediction": "and dejected countenances and without daring to complain of the murder of their king they affirmed with solemn oaths that the late invasion was the crime of some irregular robbers which the public council of the nation condemned and abhorred", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm1-musi-sp1160-ch139727-sg0005-mc01-stu-clo-dg090.wav", "answer": "which would be of more use to them we parted he going to philadelphia and i to boston in returning i met at new york with the votes of the assembly by which it appear'd that notwithstanding his promise to me he and the house were already in high contention", "subset": "musi", "task_type": "understanding", "prediction": "which would be of more use to them we parted he going to philadelphia and i to boston in returning i met at new york with the votes of the assembly by which it appeared that notwithstanding his promise to me he and the house were already in high contention", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm1-musi-sp1160-ch139730-sg0007-mc02-lav-clo-dg000.wav", "answer": "should assist in comprehending the following he procur'd an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely form'd by instrument makers his lectures", "subset": "musi", "task_type": "understanding", "prediction": "should assist in comprehending the following he procured an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely formed by instrument makers his lectures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1259/Lab41-SRI-VOiCES-rm1-musi-sp1259-ch027120-sg0012-mc01-stu-clo-dg000.wav", "answer": "and indulged their mirth for some time at the expense of their dear friend's vulgar relations with a renewal of tenderness however they returned to her room on leaving the dining parlour and sat with her till summoned to coffee she was still very poorly and elizabeth would not quit her at all", "subset": "musi", "task_type": "understanding", "prediction": "and indulged their mirth for some time at the expense of their dear friend s wild dilations with a renewal of tenderness however they returned to her room on leaving the dining parlor and sat with her till summoned to coffee she was still very poorly and elizabeth would not question her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1271/Lab41-SRI-VOiCES-rm1-musi-sp1271-ch133279-sg0006-mc01-stu-clo-dg150.wav", "answer": "which things that are supremely good in their very nature are wont to excite in the mind and i approve of it more from a recollection of the evils it prevents than from a consideration of the advantages it ensures", "subset": "musi", "task_type": "understanding", "prediction": "which things that are supremely good in their very nature are wont to excite in the mind and i approve of it more from a recollection of the evils it prevents than from a consideration of the advantages it ensures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm1-musi-sp1272-ch141231-sg0012-mc01-stu-clo-dg050.wav", "answer": "i'm here because the matter is of utmost importance and brandd is the one i must see now stand aside", "subset": "musi", "task_type": "understanding", "prediction": "i am here because the matter is of utmost importance and brand is the one i must see now stand aside", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm1-musi-sp1272-ch141231-sg0023-mc02-lav-clo-dg160.wav", "answer": "the strength that enables someone in a trance to hold his body stiff and unsupported except at two points the head and heels", "subset": "musi", "task_type": "understanding", "prediction": "The strength that enables someone in a trance to hold his body stiff and unsupported. Except at two points. The head and heels.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm1-musi-sp1335-ch163935-sg0005-mc02-lav-clo-dg110.wav", "answer": "then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander", "subset": "musi", "task_type": "understanding", "prediction": "then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm1-musi-sp1383-ch130532-sg0018-mc01-stu-clo-dg020.wav", "answer": "i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions", "subset": "musi", "task_type": "understanding", "prediction": "i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm1-musi-sp1383-ch130532-sg0027-mc02-lav-clo-dg010.wav", "answer": "i speak the secret feeling of this company i speak what i know when i say i speak wholly without authority i speak with feeling upon this point", "subset": "musi", "task_type": "understanding", "prediction": "i speak the secret feeling of this company i speak what i know when i say i speak wholly without authority i speak with feeling upon this point", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm1-musi-sp1392-ch140654-sg0008-mc02-lav-clo-dg160.wav", "answer": "company with fools as with an enemy is always painful company with the wise is pleasure", "subset": "musi", "task_type": "understanding", "prediction": "company with fools as with an enemy is always painful company with the wise is pleasure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-musi-sp1472-ch142848-sg0010-mc01-stu-clo-dg160.wav", "answer": "each labourer is able to gather from four to ten or fifteen pounds a day when the trees attain to six or seven years of age the produce becomes so inferior that they are removed to make room for a fresh succession or they are cut down to allow of numerous young shoots", "subset": "musi", "task_type": "understanding", "prediction": "each labourer is able to gather from four to ten or fifteen pounds a day when the trees attain to six or seven years of age the produce becomes so inferior that they are removed to make room for a fresh succession for they are cut down to allow of numerous young shoots", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-musi-sp1472-ch285314-sg0011-mc01-stu-clo-dg040.wav", "answer": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up", "subset": "musi", "task_type": "understanding", "prediction": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-musi-sp1472-ch285314-sg0011-mc02-lav-clo-dg040.wav", "answer": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up", "subset": "musi", "task_type": "understanding", "prediction": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1607/Lab41-SRI-VOiCES-rm1-musi-sp1607-ch149245-sg0016-mc01-stu-clo-dg100.wav", "answer": "which respect for his immense power prevented them from fully expressing after repeatedly vowing fidelity to both parties and repeatedly betraying both he began to think that he should best provide for his safety", "subset": "musi", "task_type": "understanding", "prediction": "which respect for his immense power prevented them from fully expressing after repeatedly vowing fidelity to both parties and repeatedly betraying both he began to think that he should best provide for his safety", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1841/Lab41-SRI-VOiCES-rm1-musi-sp1841-ch179183-sg0017-mc01-stu-clo-dg110.wav", "answer": "now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful", "subset": "musi", "task_type": "understanding", "prediction": "now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1851/Lab41-SRI-VOiCES-rm1-musi-sp1851-ch151817-sg0017-mc01-stu-clo-dg120.wav", "answer": "was there anything so very absurd in his method of reasoning or of drawing a deduction still that exaltation did not prevent uncle phaeton from taking all essential precautions and it was only when an especially secure landing place was sighted", "subset": "musi", "task_type": "understanding", "prediction": "was there anything so very absurd in his method of reasoning or of drawing a deduction still that exultation did not prevent uncle phaeton from taking all essential precautions and it was only when an especially secure landing place was sighted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm1-musi-sp1867-ch154071-sg0011-mc01-stu-clo-dg120.wav", "answer": "peering through the slit between the drawn curtains which sheltered him from being observed at his spying when he called out softly the sound brought gregg with one long leap out of the chair where he was sleeping to the window there could be no shadow of a doubt about it", "subset": "musi", "task_type": "understanding", "prediction": "peering through the slit between the drawn curtains which sheltered him from being observed at his spying when he called out softly the sound brought gregg with one long leap out of the chair where he was sleeping to the window there could be no shadow of a doubt about it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm1-musi-sp1874-ch089898-sg0006-mc01-stu-clo-dg010.wav", "answer": "whom wilfrid as his clerk attended to the place where he was to be beheaded being very desirous though the bishop strongly opposed it to die with him but the executioners understanding that he was a stranger and of the english nation spared him and would not put him to death with his bishop", "subset": "musi", "task_type": "understanding", "prediction": "and wilfrid as his clerk attended to the place where he was to be beheaded being very desirous though the bishop strongly opposed it to die with him but the executioners understanding that he was a stranger and of the english nation spared him and would not put him to death with his bishop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm1-musi-sp1961-ch149739-sg0018-mc02-lav-clo-dg070.wav", "answer": "he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor", "subset": "musi", "task_type": "understanding", "prediction": "he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1963/Lab41-SRI-VOiCES-rm1-musi-sp1963-ch142776-sg0013-mc02-lav-clo-dg060.wav", "answer": "a little nutmeg one teaspoonful of flour one pint of cream one pint of milk forcemeat balls mace salt and pepper to taste bread crumbs one egg two quarts of water mode", "subset": "musi", "task_type": "understanding", "prediction": "a little nutmeg one teaspoonful of flour one pint of cream one pint of milk forcemeat balls mace salt and pepper to taste bread crumbs one egg two quarts of water melt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1963/Lab41-SRI-VOiCES-rm1-musi-sp1963-ch147036-sg0034-mc02-lav-clo-dg050.wav", "answer": "milburgh had gone too far tarling saw his face lengthen and the look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath the confession of odette rider", "subset": "musi", "task_type": "understanding", "prediction": "milburgh had gone too far tarling saw his face lengthen and a look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath the confession of odad rider", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm1-musi-sp1970-ch010594-sg0035-mc01-stu-clo-dg140.wav", "answer": "but i heard her voice it was a lady's voice and what she wore beautiful jewels jewels you said she was poor so she declared herself but she had on her neck under her coat", "subset": "musi", "task_type": "understanding", "prediction": "but i heard her voice it was a lady's voice and what she wore beautiful jewels jewels you said she was poor so she declared herself but she had on her neck under her coat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139355-sg0027-mc02-lav-clo-dg180.wav", "answer": "but after all why not these indians are no longer the indians of days gone by instead of being clothed in the national fashion with a frontlet of macaw feathers bow and blow tube have they not adopted the american costume of white cotton trousers", "subset": "musi", "task_type": "understanding", "prediction": "but after all why not these indians are no longer the indians of days gone by instead of being clothed in the national fashion with a frontlet of macaw feathers bow and blow tube have they not adopted the american costume of white cotton trousers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139355-sg0028-mc01-stu-clo-dg120.wav", "answer": "at present the capital of the upper amazon it began as a simple mission founded by the portuguese carmelites about sixteen ninety two and afterward acquired by the jesuit missionaries from the beginning", "subset": "musi", "task_type": "understanding", "prediction": "at present the capital of the upper amazon it began as a simple mission founded by the portuguese carmelites about sixteen ninety two and afterward acquired by the jesuit missionaries from the beginning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139356-sg0000-mc01-stu-clo-dg160.wav", "answer": "the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon", "subset": "musi", "task_type": "understanding", "prediction": "the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139358-sg0018-mc02-lav-clo-dg130.wav", "answer": "it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries", "subset": "musi", "task_type": "understanding", "prediction": "it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2060/Lab41-SRI-VOiCES-rm1-musi-sp2060-ch147963-sg0002-mc01-stu-clo-dg020.wav", "answer": "ambrosch come along by the cornfield yesterday where i was at work and showed me three prairie dogs he'd shot he asked me if they was good to eat i spit and made a face and took on to scare him but he just looked like he was smarter'n me and put em back in his sack and walked off", "subset": "musi", "task_type": "understanding", "prediction": "ambrose come on by the cornfield yesterday where i was at work he showed me three prairie dogs he d shot he asked me if they was good to eat i spit and made a face and took on to scare him but he just looked like he was smarter i mean and put em back in his sack and walked off", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2060/Lab41-SRI-VOiCES-rm1-musi-sp2060-ch150855-sg0011-mc02-lav-clo-dg130.wav", "answer": "there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie's bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy", "subset": "musi", "task_type": "understanding", "prediction": "there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie s bewilderment was now a member of dubwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2060/Lab41-SRI-VOiCES-rm1-musi-sp2060-ch150855-sg0029-mc02-lav-clo-dg010.wav", "answer": "it's just the kind of thing poor mister ansell would say well i'm brutal i believe it does varden good to have his ears pulled now and then and i don't care whether they pull them in play or not boys ought to rough it or they never grow up into men and your mother would have agreed with me", "subset": "musi", "task_type": "understanding", "prediction": "its just the kind of thing poor mr ansell would say well i am brutal i believe it does a boy good to have his ears pulled now and then and i don't care whether they pull them in play or not boys ought to rough it or they never grow up into men and your mother would have agreed with me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2093/Lab41-SRI-VOiCES-rm1-musi-sp2093-ch143271-sg0020-mc01-stu-clo-dg040.wav", "answer": "we'll go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply", "subset": "musi", "task_type": "understanding", "prediction": "we will go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm1-musi-sp2110-ch161100-sg0030-mc01-stu-clo-dg110.wav", "answer": "he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died", "subset": "musi", "task_type": "understanding", "prediction": "he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm1-musi-sp2110-ch161101-sg0013-mc02-lav-clo-dg080.wav", "answer": "no expression neither piano nor forte but goes on always the same but all that signifies nothing to me the organ is nevertheless the king of instruments augsburg october seventeenth", "subset": "musi", "task_type": "understanding", "prediction": "no expression neither piano nor forte but goes on always the same but all that signifies nothing to me the organ is nevertheless the king of instruments augsburg october seventeen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2149/Lab41-SRI-VOiCES-rm1-musi-sp2149-ch036146-sg0008-mc01-stu-clo-dg070.wav", "answer": "what life and action and heroism there was to him in the multitudinous roar of the forest and what an eternity of existence in the monologue of the river which brawled far far below him over its wide stony bed how the river sparkled and danced and went on", "subset": "musi", "task_type": "understanding", "prediction": "what life and action and heroism there was to him in the multitudinous roar of the forest and what an eternity of existence in the monologue of the river which brawled far far below him over its white stony bed how the river sparkled and danced and went on", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm1-musi-sp2156-ch082458-sg0026-mc02-lav-clo-dg000.wav", "answer": "now bell ran out of the door and received a bullet from his own pistol the body of bell tumbled down the back stairs falling on the jailer a german by the name of geiss who was sitting at the foot of the stairs", "subset": "musi", "task_type": "understanding", "prediction": "Now, Bell ran out of the door and received a bullet from his own pistol. The body of Bell tumbled down the back stairs, falling on the jailer, a German by the name of Geiss, who was sitting at the foot of the stairs.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2269/Lab41-SRI-VOiCES-rm1-musi-sp2269-ch088761-sg0004-mc01-stu-clo-dg100.wav", "answer": "and i wanted to observe him more closely and hear what he talked about but i received orders to attend evensong at the parish church and to haunt the mind of lena houghton as we passed down the high street", "subset": "musi", "task_type": "understanding", "prediction": "and i wanted to observe him more closely and hear what he talked about but i received orders to attend evensong at the parish church and to haunt the mind of lena houghton as we passed down the high street", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2269/Lab41-SRI-VOiCES-rm1-musi-sp2269-ch088761-sg0014-mc02-lav-clo-dg000.wav", "answer": "though she stood and sat and knelt and curtseyed and articulated words her thoughts were entirely absorbed in me i crowded out the magnificat with a picture of zaluski and gertrude morley", "subset": "musi", "task_type": "understanding", "prediction": "though she stood and sat and knelt and curtseyed and articulated words her thoughts were entirely absorbed in me i crowded out the magnificat with a picture of zaluski and gertrude morley", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm1-musi-sp2289-ch152254-sg0005-mc02-lav-clo-dg010.wav", "answer": "but genseric sternly refused never he said shall i go back to spain until i am master of africa then cried boniface i will drive you back soon afterwards there was a battle between the romans and vandals and the romans were defeated", "subset": "musi", "task_type": "understanding", "prediction": "but genseric sternly refused never he said shall i go back to spain until i am master of africa then cried longface i will drive you back soon after there was a battle between romans and vandals and the romans were defeated", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm1-musi-sp2289-ch152257-sg0001-mc01-stu-clo-dg130.wav", "answer": "but he was determined to go even though he should have to walk every step of the road and live on fruits that he could gather by the way he was a bright clever boy who had spent his life hitherto in a village but was now eager to go out into the world", "subset": "musi", "task_type": "understanding", "prediction": "but he was determined to go even though he should have to walk every step of the road and live on fruits that he could gather by the way he was a bright clever boy who had spent his life hitherto in a village but was now eager to go out into the world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm1-musi-sp2289-ch152258-sg0007-mc02-lav-clo-dg160.wav", "answer": "and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work intrusted to him and", "subset": "musi", "task_type": "understanding", "prediction": "and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work entrusted to him and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm1-musi-sp2412-ch153948-sg0006-mc02-lav-clo-dg100.wav", "answer": "i was to see the sheep not necessarily close at hand nor to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet", "subset": "musi", "task_type": "understanding", "prediction": "i was to see the sheep not necessarily close at hand or to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2532/Lab41-SRI-VOiCES-rm1-musi-sp2532-ch163402-sg0000-mc02-lav-clo-dg000.wav", "answer": "because tom said we got to have some light to see how to dig by and a lantern makes too much and might get us into trouble what we must have was a lot of them rotten chunks that's called fox fire and just makes a soft kind of a glow when you lay them in a dark place", "subset": "musi", "task_type": "understanding", "prediction": "because tom said we got to have some light to see how to dig by and a lantern makes too much and might get us into trouble what we must have was a lot of them rock chunks that is called fox fire and just makes a soft kind of a glow when you lay them in a dark place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm1-musi-sp2758-ch086039-sg0011-mc01-stu-clo-dg020.wav", "answer": "and after she had cleaned her house and fed her chickens and put everything in its place again she bent over the kitchen table and the sound of her big scissors might be heard snip snap as far as the garden her husband could not see anything to snip at", "subset": "musi", "task_type": "understanding", "prediction": "and after she had cleaned her house and fed her chickens and put everything in its place again she bent over the kitchen table and the sound of her big scissors might be heard snip snap as far as the garden her husband could not see anything to snip at", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm1-musi-sp2758-ch161217-sg0015-mc01-stu-clo-dg100.wav", "answer": "aged hideous and also lame which is evidently meant to indicate the slow and halting march of destiny which they controlled painters and sculptors on the other hand depicted them as beautiful maidens of a grave but kindly aspect", "subset": "musi", "task_type": "understanding", "prediction": "Aged, hideous, and also lame, which is evidently meant to indicate the slow and halting march of destiny, which they control painters and sculptors, on the other hand, depicted them as beautiful maidens of a grave but kindly aspect", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm1-musi-sp2803-ch154320-sg0003-mc01-stu-clo-dg060.wav", "answer": "their minds were so distracted at this change of route as to be quite unhinged", "subset": "musi", "task_type": "understanding", "prediction": "their minds were so distracted at this change of route as to be quite unhinged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm1-musi-sp2911-ch015045-sg0022-mc01-stu-clo-dg110.wav", "answer": "and as the voyager passed some wooded point or thicket covered island the whistling of a stone headed arrow proclaimed perhaps the presence of these fierce marauders at montreal there was no human life save during a brief space in early summer", "subset": "musi", "task_type": "understanding", "prediction": "and as the voyager passed some wooded point or thicket covered island the whistling of a stone headed arrow proclaimed perhaps the presence of these fierce marauders at montreal there was no human life saved during a brief space in early summer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm1-musi-sp3446-ch144019-sg0006-mc01-stu-clo-dg080.wav", "answer": "preceded beche de mer english beche de mer was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose beche de mer english is a splendid argument for the esperanto enthusiasts", "subset": "musi", "task_type": "understanding", "prediction": "preceded bestumair english bestumair was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose bestumair english is a splendid argument for the esperanto enthusiasts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm1-musi-sp3483-ch174132-sg0004-mc01-stu-clo-dg120.wav", "answer": "by writing down an account of them to the best of my ability though should this my diary ever be read when i am gone the readers will but shake their heads and be the more convinced that i was mad this house how ancient it is", "subset": "musi", "task_type": "understanding", "prediction": "by writing down an account of them to the best of my ability though should this my diary ever be read when i am gone the readers will but shake their heads and be the more convinced that i was mad this house how ancient it is", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm1-musi-sp3483-ch174132-sg0010-mc01-stu-clo-dg000.wav", "answer": "but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study", "subset": "musi", "task_type": "understanding", "prediction": "but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm1-musi-sp3549-ch171171-sg0024-mc02-lav-clo-dg080.wav", "answer": "and this in hopes that they should be able to proceed so far as to rise from under ground in a safe place and by that means escape but when they came to make the experiment they were disappointed of their hope for the miners could make but small progress", "subset": "musi", "task_type": "understanding", "prediction": "and this in hopes that they should be able to proceed so far as to rise from under ground in a safe place and by that means escape but when they came to make the experiment they were disappointed of their hope for the miners could make but small progress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm1-musi-sp3549-ch173591-sg0001-mc01-stu-clo-dg090.wav", "answer": "but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots", "subset": "musi", "task_type": "understanding", "prediction": "but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm1-musi-sp3835-ch178028-sg0013-mc02-lav-clo-dg120.wav", "answer": "had suddenly taken a very large dose of the drug and had died in agony before assistance could be rendered her it was said that prince vasili and the old count had turned upon the italian but the latter had produced such letters from the unfortunate deceased that they had immediately let the matter drop", "subset": "musi", "task_type": "understanding", "prediction": "had suddenly taken a very large dose of the drug and had died in agony before assistance could be rendered her it was said that prince vasili and the old count had turned upon the italian but the latter had produced such letters from the unfortunate deceased that they had immediately let the matter drop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm1-musi-sp3835-ch178029-sg0008-mc02-lav-clo-dg060.wav", "answer": "which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire", "subset": "musi", "task_type": "understanding", "prediction": "which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked gaining time colonel i always require it replied danver conceal nothing from me i wish to know absolutely how things are sire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp3989/Lab41-SRI-VOiCES-rm1-musi-sp3989-ch182389-sg0005-mc02-lav-clo-dg150.wav", "answer": "gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mister rabbit the grandfather a thousand times removed of peter rabbit was always getting into trouble yes sir old mister rabbit was always getting into trouble", "subset": "musi", "task_type": "understanding", "prediction": "gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mr rabbit the grandfather a thousand times removed of peter rabbit was always getting in the trouble yes sir old mr rabbit was always getting in the trouble", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp3994/Lab41-SRI-VOiCES-rm1-musi-sp3994-ch011512-sg0017-mc02-lav-clo-dg130.wav", "answer": "the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved", "subset": "musi", "task_type": "understanding", "prediction": "the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4010/Lab41-SRI-VOiCES-rm1-musi-sp4010-ch010801-sg0011-mc02-lav-clo-dg070.wav", "answer": "and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operations of the spiritual as of the physical world are simply a turning again to the source", "subset": "musi", "task_type": "understanding", "prediction": "and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operation of the spiritual as of the physical world are simply a turning again to the source", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-musi-sp4014-ch186176-sg0020-mc02-lav-clo-dg140.wav", "answer": "well i'll cover the battery room said slim ignoring jerry's remark let's see lieutenant mackinson then suggested joe and they went to find the young officer who was convalescing from his encounter with the spy when he had approved the plan they got the o k of the captain", "subset": "musi", "task_type": "understanding", "prediction": "well i ll come in the band room said slant ignoring jerry s remark let s see lieutenant mackinson then suggested joe and they want to find the young officer who is convalescing from his encounter with the spy when he had approved the plan they got the o k of the captain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4110/Lab41-SRI-VOiCES-rm1-musi-sp4110-ch011535-sg0002-mc01-stu-clo-dg130.wav", "answer": "as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming", "subset": "musi", "task_type": "understanding", "prediction": "as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4116/Lab41-SRI-VOiCES-rm1-musi-sp4116-ch003582-sg0023-mc01-stu-clo-dg070.wav", "answer": "how could you don't mind it polly whispered jasper twasn't her fault phronsie said missus whitney smilingly stooping over the child would you like to see a little pussy i have for you but the chubby face didn't look up brightly as usual", "subset": "musi", "task_type": "understanding", "prediction": "how could you dont mind it polly whispered jasper twasn t her fault phronsie said mrs whitney smilingly stooping over the child would you like to see a little pussy i have for you but the chubby face did n t look up brightly as usual", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4116/Lab41-SRI-VOiCES-rm1-musi-sp4116-ch013256-sg0010-mc02-lav-clo-dg020.wav", "answer": "the girls in the carriage were smitten into helpless astonishment the saloon keeper had come to the door of the saloon and was standing there looking on with his hands on his hips and the rectangle from its windows its saloon steps its filthy sidewalk gutter and roadway paused", "subset": "musi", "task_type": "understanding", "prediction": "the girls in the carriage were smitten into helpless astonishment the saloon keeper had come to the door of the saloon and was standing there looking on with his hands on his hips and the rectangle from its windows its saloon steps its filthy sidewalk gutter and roadway paused", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4160/Lab41-SRI-VOiCES-rm1-musi-sp4160-ch011549-sg0006-mc02-lav-clo-dg000.wav", "answer": "he came to the window and looked in at her are you coming to see priscilla he said lady throckmorton said i might she answered the warmth in her face chilled by his unenthusiastic though kindly tone she did not know what a struggle it cost him to face her thus carelessly all at once", "subset": "musi", "task_type": "understanding", "prediction": "he came to the window and looked in at her are you coming to see priscilla he said lady throckmorton said i might she answered the warmth in her face chilled by his unenthusiastic though kindly tone she did not know what a struggle it cost him to face her thus carelessly all at once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4331/Lab41-SRI-VOiCES-rm1-musi-sp4331-ch057180-sg0006-mc02-lav-clo-dg020.wav", "answer": "i haven't got any pastors and masters the duchess suggested lord rufford i thought all that kind of nonsense was over said arabella i believe a great deal is over you can do many things that your mother and grandmother couldn't do but absolute freedom", "subset": "musi", "task_type": "understanding", "prediction": "i haven got any pastors and masters the duchess suggested lord rufford i thought all that kind of nonsense was over said arabella i believe a great deal is over you can do many things that your mother and grandmother couldnt do but absolute freedom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm1-musi-sp4438-ch052195-sg0014-mc01-stu-clo-dg090.wav", "answer": "and whether it had filtered down from above and was all right it wouldn't do any harm to try it he decided by the time they had reached the sidewalk and he swung behind ruth and took up his station on the outside then the other problem presented itself", "subset": "musi", "task_type": "understanding", "prediction": "and whether it had filtered down from above and was all right it wouldn't do any harm to try it he decided by the time they had reached the sidewalk and he swung behind ruth and took up his station on the outside then the other problem presented itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm1-musi-sp4535-ch279852-sg0008-mc01-stu-clo-dg120.wav", "answer": "i'll let a bullet go smack into the first man that makes a move he shouldn't here was a man they couldn't talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later", "subset": "musi", "task_type": "understanding", "prediction": "i ll let a bullet go smack into the first man that makes a move he shouldn t here was a man they couldn t talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm1-musi-sp4535-ch279856-sg0032-mc02-lav-clo-dg100.wav", "answer": "through each settlement he walked star quietly but always ready to throw himself forward dig his heels into the horse's flanks and race away an hour passed two hours three hours they pressed northward steadily sometimes at a walk but usually at a comfortable steady trot", "subset": "musi", "task_type": "understanding", "prediction": "Through each settlement, he walked stark, quietly. But always ready to throw himself forward. Dig his heels into the horse's flanks and race away. An hour passed,2 hours,3 hours. They pressed northward steadily, sometimes at a walk, usually at a comfortable, steady trot.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4590/Lab41-SRI-VOiCES-rm1-musi-sp4590-ch018005-sg0052-mc02-lav-clo-dg120.wav", "answer": "at last the labourers entirely declined to go on unless they were guarded by an iron entrenchment of course it is difficult to work a railway under these conditions and until we found an enthusiastic sportsman to get rid of these lions our enterprise was seriously hindered", "subset": "musi", "task_type": "understanding", "prediction": "at last the laborers entirely declined to go on unless they were guarded by an iron entrenchment of course it is difficult to work a railway under these conditions and until we found an enthusiastic sportsman to get rid of these lions our enterprise was seriously hindered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4744/Lab41-SRI-VOiCES-rm1-musi-sp4744-ch004158-sg0009-mc02-lav-clo-dg110.wav", "answer": "all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims", "subset": "musi", "task_type": "understanding", "prediction": "all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm1-musi-sp4839-ch015307-sg0003-mc01-stu-clo-dg050.wav", "answer": "and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at treviso when emperor maximilian's commissioner presented himself in order to take possession of it", "subset": "musi", "task_type": "understanding", "prediction": "and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor vanyadello and his allies of cambrai but at trevisa when emperor maximilian s commissioner presented himself in order to take possession of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm1-musi-sp4848-ch029108-sg0034-mc02-lav-clo-dg040.wav", "answer": "a spectacle of inconceivable sublimity so don't you see we've got the rail road to fall back on and in the meantime what are we worrying about that two hundred thousand dollars appropriation for that's all right", "subset": "musi", "task_type": "understanding", "prediction": "the spectacle of inconceivable solemnity so don t see we ve got the railroad to fall back on and in the meantime what are we worrying about that two hundred thousand dollar appropriation for that s all right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm1-musi-sp4848-ch101836-sg0017-mc01-stu-clo-dg060.wav", "answer": "the kindness you showed me on a former day so mvoo laana sat down simba kongway went away but soon returned with some game he had caught and then he brought some fire and the young man cooked the game and ate it", "subset": "musi", "task_type": "understanding", "prediction": "the kindness you showed me on a former day so magoulanes sat down simba conway went away but soon returned with some game he had caught and then he brought some fire and the young man cooked the game and ate it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4859/Lab41-SRI-VOiCES-rm1-musi-sp4859-ch022176-sg0008-mc02-lav-clo-dg110.wav", "answer": "and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman", "subset": "musi", "task_type": "understanding", "prediction": "and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4957/Lab41-SRI-VOiCES-rm1-musi-sp4957-ch023295-sg0011-mc01-stu-clo-dg120.wav", "answer": "without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sandford interrupted the menace prepared for utterance saying and you still mean i suppose to make mister rushbrook your heir", "subset": "musi", "task_type": "understanding", "prediction": "without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sanford interrupted the menace prepared for utterance saying and you still mean i suppose to make mr rushbrook your heir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp4957/Lab41-SRI-VOiCES-rm1-musi-sp4957-ch023295-sg0026-mc01-stu-clo-dg130.wav", "answer": "it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you", "subset": "musi", "task_type": "understanding", "prediction": "it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5126/Lab41-SRI-VOiCES-rm1-musi-sp5126-ch034483-sg0013-mc02-lav-clo-dg130.wav", "answer": "the sensation produced by her children and her the children were not only beautiful to look at in their smart little dresses but they were charming in the way they behaved aliosha it is true did not stand quite correctly", "subset": "musi", "task_type": "understanding", "prediction": "the sensation produced by her children and her the children were not only beautiful to look at in their smart little dresses but they were charming in the way they behaved elisha it is true did not stand quite correctly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5319/Lab41-SRI-VOiCES-rm1-musi-sp5319-ch064075-sg0017-mc02-lav-clo-dg150.wav", "answer": "the next morning when we were about ready to start out on the trap line i asked pard what he intended to do with pont he said that he would tie him to a tree that stood against the shanty close to the door we were going to take different lines of traps", "subset": "musi", "task_type": "understanding", "prediction": "the next morning when we were about ready to start out on the trap line i asked pard what he intended to do with pont he said that he would tie him to a tree that stood against the shanty close to the door we were going to take different lines of traps", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5386/Lab41-SRI-VOiCES-rm1-musi-sp5386-ch028384-sg0027-mc02-lav-clo-dg060.wav", "answer": "who were free and of age the bride who had taken care to bathe herself the night before appeared in all her splendor but veiled in imitation of rebecca who veiled herself when she came in sight of isaac she was then given to the bridegroom by her parents in words to this purpose", "subset": "musi", "task_type": "understanding", "prediction": "who were free and of age the bride who had taken care to bathe herself the night before appeared in all her splendor but veiled in imitation of rebecca who veiled herself when she came in sight of isaac she was then given to the bridegroom by her parents in words to this purpose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5400/Lab41-SRI-VOiCES-rm1-musi-sp5400-ch034479-sg0026-mc01-stu-clo-dg060.wav", "answer": "the crescent shaped curve of the cut grass the grass and flower heads slowly and rhythmically falling before the blade of his scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came", "subset": "musi", "task_type": "understanding", "prediction": "the crescent shaped curve of the cut grass the grass and flower head slowly and rhythmically falling before the blade of his scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm1-musi-sp5456-ch058161-sg0009-mc01-stu-clo-dg020.wav", "answer": "his was the rental of half havana and all matanzas and santa anna rich as he was could hardly hold a candle to light the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers", "subset": "musi", "task_type": "understanding", "prediction": "his was the rental of half a van and all matanzas and santa anna rich as he was could hardly hold a candle to like the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5583/Lab41-SRI-VOiCES-rm1-musi-sp5583-ch038026-sg0017-mc01-stu-clo-dg100.wav", "answer": "and then we'll be off as fast as we can so when the lad had got on the horse off they went at such a rate he couldn't at all tell how they went but when he had ridden awhile the horse said i think i hear a noise look round can you see anything yes", "subset": "musi", "task_type": "understanding", "prediction": "and then we ll be off as fast as we can so when the lad had got on the horse off they went at such a rate he couldn t at all tell how they went but when he had ridden a while the horse said i think i hear a noise look round can you see anything yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm1-musi-sp5635-ch053458-sg0027-mc02-lav-clo-dg080.wav", "answer": "although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a black bird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion", "subset": "musi", "task_type": "understanding", "prediction": "although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a black bird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm1-musi-sp5635-ch058137-sg0021-mc01-stu-clo-dg180.wav", "answer": "or the duties more onerous than had been anticipated that a man ought to resign and try another naturally therefore mister rapid thought he would like to sit in our chair of languages or have some employment in the state college and hence he called for that purpose on doctor sylvan who", "subset": "musi", "task_type": "understanding", "prediction": "or the duties more onerous than had been anticipated that a man ought to resign and try another naturally therefore mr rapid thought that he would like to sit in our chair of languages or have some employment in the state college and hence he called for that purpose on dr sylvan who", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm1-musi-sp5678-ch043301-sg0011-mc01-stu-clo-dg100.wav", "answer": "the murmurs of talk rose into cheering old lord pemberton came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily", "subset": "musi", "task_type": "understanding", "prediction": "the murmurs of talk rose into cheering old lord pamperdon came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm1-musi-sp5678-ch043301-sg0015-mc02-lav-clo-dg000.wav", "answer": "had been composed with both skill and ardour they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ's words themselves were quoted", "subset": "musi", "task_type": "understanding", "prediction": "had been composed with both skill and ardor they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ s words themselves were quoted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm1-musi-sp5717-ch061421-sg0010-mc02-lav-clo-dg150.wav", "answer": "as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and you'll forget there was no answer billy and you'll forget bertram's voice was insistent reproachful", "subset": "musi", "task_type": "understanding", "prediction": "as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and youll forget there was no answer billy and youll forget bertram s voice was insistent reproachful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5789/Lab41-SRI-VOiCES-rm1-musi-sp5789-ch057158-sg0004-mc02-lav-clo-dg100.wav", "answer": "she wants you to go to her at cheltenham for a month oh mister morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me", "subset": "musi", "task_type": "understanding", "prediction": "she wants you to go to her at cheltenham for a month oh mr morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm1-musi-sp5868-ch055088-sg0035-mc02-lav-clo-dg100.wav", "answer": "and the best prayer i can offer for you is perhaps that you should never need to understand me but if that sore need should come and that poison should begin to spread its mist over your brains and hearts then you will be proof against it just in proportion", "subset": "musi", "task_type": "understanding", "prediction": "And the best prayer I can offer for you is perhaps that you should never need to understand me. But if that sore need should come and that poison should begin to spread its mist over your brains and hearts. Then you will be proof against it, just in proportion.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm1-musi-sp5868-ch066166-sg0005-mc01-stu-clo-dg160.wav", "answer": "and a fringe of gray hair circling his head like a crown as he took off his tarpaulin i observed that the top of his head was quite smooth and flat as if somebody had sat down on him when he was very young there was something noticeably hearty in this man's bronzed face", "subset": "musi", "task_type": "understanding", "prediction": "and a fringe of gray hair circling his head like a crown as he took off his tarpaulin i observed that the top of his head was quite smooth and flat as if somebody had sat down on him when he was very young there was something noticeably haughty in this man s bronzed face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm1-musi-sp5935-ch043322-sg0015-mc02-lav-clo-dg170.wav", "answer": "will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure", "subset": "musi", "task_type": "understanding", "prediction": "will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm1-musi-sp5935-ch043322-sg0019-mc01-stu-clo-dg020.wav", "answer": "after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not", "subset": "musi", "task_type": "understanding", "prediction": "after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061943-sg0027-mc01-stu-clo-dg070.wav", "answer": "the men appeared robust but heavy fair haired like germans but of pensive mien exiles of a higher scale in the ladder of humanity than the eskimos but i thought much more unhappy since with superior perceptions they are compelled to live within the limits of the polar circle", "subset": "musi", "task_type": "understanding", "prediction": "The men appeared robust, but heavy, fair haired like Germans, but of pensive mien exiles of a higher scale in the ladder of humanity than the Esquimos. But I thought much more unhappy since with superior perceptions, they are compelled to live within the limits of the polar circle.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061946-sg0003-mc01-stu-clo-dg120.wav", "answer": "geographers have divided it into four parts and we had to cross the southwest quarter which in the vernacular is called sudvestr fjordungr", "subset": "musi", "task_type": "understanding", "prediction": "geographers have divided it into four parts and we had to cross the southwest quarter which in the vernacular is called suedvest fjordinger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061946-sg0022-mc01-stu-clo-dg180.wav", "answer": "i thoroughly understood and appreciated the necessity for waiting before crossing the fjord for that moment when the sea at its highest point is in a state of slack water", "subset": "musi", "task_type": "understanding", "prediction": "i thoroughly understood and appreciated the necessity for waiting before crossing the fjord or that moment when the sea at its highest point is in a state of slack water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061946-sg0023-mc02-lav-clo-dg040.wav", "answer": "accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion", "subset": "musi", "task_type": "understanding", "prediction": "accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6319/Lab41-SRI-VOiCES-rm1-musi-sp6319-ch057405-sg0001-mc02-lav-clo-dg100.wav", "answer": "after jupiter had bound prometheus on mount caucasus and had sent diseases and cares into the world men became very very wicked", "subset": "musi", "task_type": "understanding", "prediction": "after jupiter had bound prometheus on mount carpathus and had sent diseases and cares into the world men became very very wicked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm1-musi-sp6385-ch034655-sg0015-mc01-stu-clo-dg040.wav", "answer": "the maze of passages and alcoves with secret and bewildering doors checked and retarded his progress he strove to run he was obliged to wander he thought that he had but one door to thrust open while he had a skein of doors to unravel", "subset": "musi", "task_type": "understanding", "prediction": "the maze of passages and alcoves with secret and bewildering doors checked and retarded his progress he strove to run he was obliged to wander he thought that he had but one door to thrust open while he had a skein of doors to unravel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm1-musi-sp6395-ch087997-sg0045-mc02-lav-clo-dg090.wav", "answer": "but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive", "subset": "musi", "task_type": "understanding", "prediction": "but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm1-musi-sp6454-ch107462-sg0036-mc01-stu-clo-dg100.wav", "answer": "let you get up and cut its throat says he and then we will be shut of the domned screechin thing then you got the knife ma'am prompted deasey it was the bread knife she answered with the ugly notches in the blade", "subset": "musi", "task_type": "understanding", "prediction": "let you get up and cut its throat says he and then we will be shut of that darned screeching thing then you got a knife maam professed b c it was a bread knife she answered with the ugly notches in the blade", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm1-musi-sp6454-ch120342-sg0005-mc02-lav-clo-dg050.wav", "answer": "and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people in the very lowest bolgie being ill natured enough to grieve", "subset": "musi", "task_type": "understanding", "prediction": "and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people in the very lowest foggy being ill natured enough to grieve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm1-musi-sp6544-ch071420-sg0002-mc02-lav-clo-dg160.wav", "answer": "you are going to hand me over to the the authorities never come i won't hurt you he led the way through the woods across a small stream and past a spot where some wild berries grew then they struck a trail leading up a hillside the place was new to her", "subset": "musi", "task_type": "understanding", "prediction": "you are going to hand me over to the the authorities never come i won t hurt you he led the way through the woods across a small stream and past a spot where some wild berries grew then they struck a trail leading up a hillside the place was new to her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm1-musi-sp6574-ch120583-sg0009-mc02-lav-clo-dg120.wav", "answer": "but we knew how to stop them our brothers we said we matter not nor our transgression it is only our brother men who matter give no thought to us for we are nothing but listen to our words", "subset": "musi", "task_type": "understanding", "prediction": "but we knew how to stop them our brothers we said we matter not nor our transgression it is only our brother men who matter give no thought to us for we are nothing but listen to our words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm1-musi-sp6574-ch120583-sg0011-mc01-stu-clo-dg100.wav", "answer": "we spoke of it and of our long quest and of our tunnel and of our escape from the palace of corrective detention not a hand moved in that hall as we spoke nor an eye then we put the wires to the box and they all bent forward and sat still watching", "subset": "musi", "task_type": "understanding", "prediction": "we spoke of it and of our long quest and of our tunnel and of our escape from the palace of corrective detention not a hand moved in that hall as we spoke nor an eye then we put the wires to the box and they all bent forward and sat still watching", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm1-musi-sp6574-ch120583-sg0041-mc01-stu-clo-dg020.wav", "answer": "there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best", "subset": "musi", "task_type": "understanding", "prediction": "there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6696/Lab41-SRI-VOiCES-rm1-musi-sp6696-ch073296-sg0020-mc02-lav-clo-dg180.wav", "answer": "turning her eyes with affectionate anxiety toward her husband middling my dear i cannot compliment you i think mister john knightley very far from looking well what is the matter sir did you speak to me cried mister john knightley hearing his own name", "subset": "musi", "task_type": "understanding", "prediction": "turning her eyes with affectionate anxiety toward her husband middling my dear i cannot compliment you i think mr john knightley very far from looking well what is the matter sir did you speak to me cried mr john knightley hearing his own name", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-musi-sp6895-ch092806-sg0025-mc02-lav-clo-dg050.wav", "answer": "oh wailed missus murphy twas yisterday or maybe four hours ago i dunno but it's lost he is me little boy mike he was playin on the sidewalk only this mornin' or was it wednesday i'm that busy with work tis hard to keep up with dates", "subset": "musi", "task_type": "understanding", "prediction": "oh wailed mrs murphy twas yesterday or maybe four hours ago i don know but it s lost he is me little boy mike he was playing on the sidewalk only this morning or was it wednesday i m that busy with work tis hard to keep up with dates", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-musi-sp6895-ch092806-sg0035-mc02-lav-clo-dg060.wav", "answer": "we never did said mister mc caskey lingering with the fact but if we had jawn think what sorrow would be in our hearts this night with our little phelan run away and stolen in the city nowheres at all ye talk foolishness said mister mc caskey tis pat he would be named", "subset": "musi", "task_type": "understanding", "prediction": "we never did said mr maccaskey lingering with the fact but if we had john think what sorrow would be in our hearts tis night with our little phelan run away and stolen in the city nowheres at all ye talk foolishness said mr maccaskey tis pat he would be named", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm1-musi-sp6965-ch277898-sg0012-mc01-stu-clo-dg100.wav", "answer": "but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart's action was the doctor's verdict", "subset": "musi", "task_type": "understanding", "prediction": "but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart s action was the doctor s verdict", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm1-musi-sp6965-ch277899-sg0035-mc02-lav-clo-dg110.wav", "answer": "and in a few seconds missus hoopington's shrill monotone had the field to itself but after the major's display her best efforts at vocal violence missed their full effect it was as though one had come straight out from a wagner opera", "subset": "musi", "task_type": "understanding", "prediction": "and in a few seconds mrs hoopingtons shrill monotone had the field to itself but after the major s display her best efforts at vocal violence missed their full effect it was as though one had come straight out from a wagner opera", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm1-musi-sp7000-ch083708-sg0021-mc01-stu-clo-dg120.wav", "answer": "i've got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy", "subset": "musi", "task_type": "understanding", "prediction": "i have got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm1-musi-sp7095-ch088484-sg0023-mc02-lav-clo-dg100.wav", "answer": "and the glory of the morning hills science does not justify by faith but by works it is the living denial of that age long acceptance which we accord to the mystery as such", "subset": "musi", "task_type": "understanding", "prediction": "and the glory of the morning hills science does not justify by faith but by works it is the living denial of that age long acceptance which we accord to the mystery as such", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm1-musi-sp7148-ch059157-sg0007-mc01-stu-clo-dg060.wav", "answer": "she was a person of unbridled temperament and that in her later years she fell into loose ways and was no credit to the family that she had other qualities besides those mentioned by the tea dealer is shown by the passionate affection", "subset": "musi", "task_type": "understanding", "prediction": "she was a person of unbridled temperament and that in her later years she fell into loose ways and was no credit to the family that she had other qualities besides those mentioned by the tea dealer is shown by the passionate affection", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm1-musi-sp7148-ch082991-sg0013-mc01-stu-clo-dg170.wav", "answer": "are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king's highness said the tall man", "subset": "musi", "task_type": "understanding", "prediction": "are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addled pate with a vengeance the knave has been speaking treason of the king s highness said the tall man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm1-musi-sp7278-ch246956-sg0029-mc01-stu-clo-dg080.wav", "answer": "occasion to the dishonest to cavil and condemn imagine saint paul having a prevision of how he would be misunderstood and heeding it what would then have become of all those his most magnificent outbursts and would any amount of", "subset": "musi", "task_type": "understanding", "prediction": "occasion to the dishonest to cavil and condemn imagine st paul having a prevision of how he would be misunderstood and heeding it what would then have become of all those his most magnificent outbursts and would any amount of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm1-musi-sp7445-ch094522-sg0037-mc02-lav-clo-dg160.wav", "answer": "the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country", "subset": "musi", "task_type": "understanding", "prediction": "the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm1-musi-sp7445-ch094526-sg0027-mc01-stu-clo-dg020.wav", "answer": "england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vicar of christ", "subset": "musi", "task_type": "understanding", "prediction": "england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vicar of christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm1-musi-sp7498-ch099157-sg0008-mc01-stu-clo-dg000.wav", "answer": "she resolved by an unexampled labour for a woman to effect the delivery of her husband she had in her girlish days practised the drawing and colouring of flowers a suitable and amiable accomplishment of her sex", "subset": "musi", "task_type": "understanding", "prediction": "she resolved by an unexampled labor for a woman to effect the delivery of her husband she had in her girlish days practiced the drawing and coloring of flowers a suitable and amiable accomplishment of her sex", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm1-musi-sp7498-ch099157-sg0017-mc01-stu-clo-dg040.wav", "answer": "he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on agriculture he went there leaving his wife in england he was received with honour at the court of stockholm", "subset": "musi", "task_type": "understanding", "prediction": "he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on agriculture he went there leaving his wife in england he was received with honour at the court of stockholm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7704/Lab41-SRI-VOiCES-rm1-musi-sp7704-ch106965-sg0028-mc01-stu-clo-dg050.wav", "answer": "mother would give me leave to fight him just once in a way don't you think that would be nice fightin ain't the only grand thing in this world peace is grander was the slow response to this appeal that's what mother says she made me learn this morning", "subset": "musi", "task_type": "understanding", "prediction": "mother would give me leave to fight him just once in a way dont you think that would be nice fightin ain't the only grand thing in this world peace is grander was the slow response to this appeal that is what mother says she made me learn this morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm1-musi-sp7850-ch281318-sg0006-mc02-lav-clo-dg050.wav", "answer": "she popped into her new house and sat there comfortably peering out through the window slits with her sharp little eyes", "subset": "musi", "task_type": "understanding", "prediction": "She popped into her new house and SAT there comfortably, peering out through the window slits with her sharp little eyes.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm1-musi-sp7850-ch286674-sg0005-mc02-lav-clo-dg140.wav", "answer": "they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies", "subset": "musi", "task_type": "understanding", "prediction": "They did not breathe it into their mouths or through gills. But took it in through some openings in the back part of their bodies.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm1-musi-sp7881-ch109662-sg0027-mc01-stu-clo-dg180.wav", "answer": "and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet", "subset": "musi", "task_type": "understanding", "prediction": "and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm1-musi-sp7881-ch109662-sg0030-mc02-lav-clo-dg040.wav", "answer": "merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her", "subset": "musi", "task_type": "understanding", "prediction": "merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm1-musi-sp7932-ch278228-sg0004-mc02-lav-clo-dg010.wav", "answer": "whose chiefs were eager to secure the well known cashier of messrs dunbar dunbar and balderby's establishment poor clement could not go into the world yet his disappointment had been too bitter and he had no heart to go out amongst hard men of business and begin life again", "subset": "musi", "task_type": "understanding", "prediction": "whose chiefs were eager to secure the well known cashier of messrs dunbar dunbar and balderby's establishment poor leman could not go into the world yet his disappointment had been too bitter and he had no heart to go out amongst hard men of business and begin life again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm1-musi-sp7932-ch278228-sg0023-mc02-lav-clo-dg050.wav", "answer": "and the decided expression of his thin lips and prominent chin the detective business happened to be rather dull just now there was nothing stirring but a bank of england forgery case and mister carter informed clement that there were more cats in scotland yard than could find mice to kill", "subset": "musi", "task_type": "understanding", "prediction": "and the decided expression of his thin lips and prominent chin the detective business happened to be rather dull just now there was nothing stirring but a bank of england forgery case and mr carter informed clement that there were more cats in scotland yard than could find mice to kill", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-musi-sp7976-ch110124-sg0018-mc01-stu-clo-dg040.wav", "answer": "the merchant's daughter at first did not answer but as he kept on calling to her she finally asked him what it was that he wanted", "subset": "musi", "task_type": "understanding", "prediction": "The merchant's daughter at first did not answer, but as he kept on calling to her, she finally asked him what it was that he wanted.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-musi-sp7976-ch110523-sg0017-mc02-lav-clo-dg020.wav", "answer": "creep in said the witch and see if it is hot enough and then we will put in the bread but she intended when grethel got in to shut up the oven and let her bake so that she might eat her as well as hansel", "subset": "musi", "task_type": "understanding", "prediction": "pre then said the witch and see if it is hot enough and then we will put in the bread which she intended but gretel got in to shut up the oven and let her bake so that she might eat her as well as hansel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-musi-sp7981-ch112056-sg0007-mc02-lav-clo-dg060.wav", "answer": "and that as he was evidently destined to do great work for god it would be to his advantage to have powerful and influential friends although the prospect of such a post filled the humble parish priest with consternation", "subset": "musi", "task_type": "understanding", "prediction": "and that as he was evidently destined to do great work for god it would be to his advantage to have powerful and influential friends although the prospect of such a post filled the humble parish priest with consternation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-musi-sp7981-ch112057-sg0035-mc01-stu-clo-dg030.wav", "answer": "this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns taking marseilles as his first station here where the conditions were perhaps even worse than in paris", "subset": "musi", "task_type": "understanding", "prediction": "this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns picking marseilles as his first station here where the conditions were perhaps even worse than in paris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-musi-sp7981-ch112058-sg0024-mc02-lav-clo-dg070.wav", "answer": "and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries", "subset": "musi", "task_type": "understanding", "prediction": "and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of st lazare alone were at the head of sixty such seminaries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm1-musi-sp7995-ch276908-sg0017-mc01-stu-clo-dg090.wav", "answer": "not of that monster man mister booth i am undone am revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech", "subset": "musi", "task_type": "understanding", "prediction": "not of that monster man mr booth i am undone and revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8051/Lab41-SRI-VOiCES-rm1-musi-sp8051-ch295385-sg0030-mc01-stu-clo-dg010.wav", "answer": "and sorely would he swell when from the ramparts of fort casimir he beheld the flag of their high mightinesses struck to the rival fortress to heighten his vexation governor printz who as has been shown was a huge trencherman", "subset": "musi", "task_type": "understanding", "prediction": "and sorely would he swell when from the ramparts of fort casimir he beheld the flag of their high mightinesses struck to the rival fortress to heighten his vexation governor printz who as has been shown was a huge trencherman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8057/Lab41-SRI-VOiCES-rm1-musi-sp8057-ch284428-sg0011-mc02-lav-clo-dg080.wav", "answer": "said the boolooroo nodding his funny head go ahead then and eat your lunch he retreated a little way to a marble seat beside the fountain but watched the strangers carefully cap'n bill feeling sure he had won the argument whispered to the boy and girl", "subset": "musi", "task_type": "understanding", "prediction": "Said the Boolooroo nodding his funny head. Go ahead then, and eat your lunch. He retreated a little way to a marble seat beside the fountain, but watched the strangers carefully. Cap'n Bill feeling sure he had won the argument, whispered to the boy and girl.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm1-musi-sp8108-ch274318-sg0029-mc01-stu-clo-dg170.wav", "answer": "and power and confidence came with them he began to breathe deeply and regularly and at the same time to absorb into himself the forces opposed to him and to turn them to his own account", "subset": "musi", "task_type": "understanding", "prediction": "And power and confidence came with them. He began to breathe deeply and regularly. And at the same time, to absorb into himself the forces opposed to him and to turn them to his own account.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm1-musi-sp8108-ch280354-sg0022-mc02-lav-clo-dg160.wav", "answer": "oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus's lyre", "subset": "musi", "task_type": "understanding", "prediction": "oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus lyre", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8118/Lab41-SRI-VOiCES-rm1-musi-sp8118-ch268287-sg0020-mc01-stu-clo-dg090.wav", "answer": "will no depth of grief no length of time no visitation from him who is over us all ever bend your adamant and implacable will i heard with some surprise his allusion to the great being whom he was not wont to recognise", "subset": "musi", "task_type": "understanding", "prediction": "will no depth of grief no length of time no visitation from him who is over us all ever bend your adamant and implacable will i heard with some surprise his allusion to the great being whom he was not wont to recognize", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8152/Lab41-SRI-VOiCES-rm1-musi-sp8152-ch258974-sg0046-mc01-stu-clo-dg050.wav", "answer": "yet the slight reflection given to the choice of an occupation by most young people gives to this statement a very practical bearing the world is filled with industrial misfits round men in square holes good carpenters spoiled to make poor doctors", "subset": "musi", "task_type": "understanding", "prediction": "yet the slight reflection given to the choice of an occupation by most young people gives to this statement a very practical bearing the world is filled with industrial misfits round men in square holes good carpenters spoiled to make poor doctors", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-musi-sp8425-ch292520-sg0004-mc02-lav-clo-dg030.wav", "answer": "and dinning market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare's light into one sacred rhythm for the devil's spite a woman's thin raucous voice carries the tune bids men rejoice", "subset": "musi", "task_type": "understanding", "prediction": "the dimmy market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare's light into one sacred rhythm for the devil's spite a woman's thin raucous voice carries the tune bids men rejoice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8575/Lab41-SRI-VOiCES-rm1-musi-sp8575-ch290351-sg0028-mc01-stu-clo-dg140.wav", "answer": "on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small", "subset": "musi", "task_type": "understanding", "prediction": "on the other side the ordinary smallest measure we have of either is looked on as a unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8575/Lab41-SRI-VOiCES-rm1-musi-sp8575-ch290351-sg0028-mc02-lav-clo-dg140.wav", "answer": "on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small", "subset": "musi", "task_type": "understanding", "prediction": "on the other side the ordinary smallest measure we have of either is looked on as a unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8605/Lab41-SRI-VOiCES-rm1-musi-sp8605-ch292138-sg0019-mc02-lav-clo-dg150.wav", "answer": "a miniature bay quite apart from the main river this is called a backwater catching hold of a tree with the hook on the end of her pole miss green brought the punt up against the bank under the overhanging willows", "subset": "musi", "task_type": "understanding", "prediction": "a miniature bay quite apart from the main river this is called a backwater catching hold of a tree with the hook on the end of her pole miss green brought the punt up against the bank under the overhanging willows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm1-musi-sp8713-ch296159-sg0045-mc02-lav-clo-dg110.wav", "answer": "and know what reaction it was capable of in a word to experimentalise in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use", "subset": "musi", "task_type": "understanding", "prediction": "and know what reaction it was capable of in a word to experimentalize in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/musi/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm1-musi-sp8713-ch302111-sg0012-mc01-stu-clo-dg010.wav", "answer": "with a knife completely pointless and an egg in knots he twisted yet no knot was seen upon it then again he asked the maiden in the sledge to sit beside him but the maid gave crafty answer i perchance at length may join you", "subset": "musi", "task_type": "understanding", "prediction": "with a knife completely pointless and an egg in knots he twisted yet no nub is seen upon it then again he asked the maiden in the sledge to sit beside him but the maid gave crafty answer i perchance at length may join you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0093/Lab41-SRI-VOiCES-rm1-none-sp0093-ch123172-sg0007-mc01-stu-clo-dg180.wav", "answer": "when the cream will be thick and rich and churns easier if the weather is very cold and the cream has been chilled have a large pot of water over the fire set in the bucket when it is near boiling heat and keep stirring till it is milk warm have the churn scalded and put it in", "subset": "none", "task_type": "understanding", "prediction": "when the cream will be thick and rich and churned easier if the weather is very cold and the cream has been chilled have a large pot of water over the fire set in the bucket when it is near boiling heat and keep stirring till it is milk warm have the churn scalded and put it in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0093/Lab41-SRI-VOiCES-rm1-none-sp0093-ch126209-sg0023-mc01-stu-clo-dg080.wav", "answer": "but capable of passing as such at a little distance despite some coarseness of skin and fibre she had a round and prominent bosom full lips perfect teeth and the rich complexion of a cochin hen's egg she was a complete and substantial female animal", "subset": "none", "task_type": "understanding", "prediction": "but capable of passing as such at a little distance despite some coarseness of skin and fibre she had a round and prominent bosom full lips perfect teeth and the rich complexion of a cochin hen s egg she was a complete and substantial female animal", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-none-sp0112-ch123215-sg0025-mc01-stu-clo-dg080.wav", "answer": "of tolerant wonder anne despite her affection for rusty was not especially fond of cats but missus gardner's tone annoyed her inconsequently she remembered that missus john blythe was so fond of cats that she kept as many as her husband would allow", "subset": "none", "task_type": "understanding", "prediction": "of tolerant wonder ann despite her affection for rusty was not especially fond of cats but mrs gardiner s tone annoyed her inconsequently she remembered that mrs john blythe was so fond of cats that she kept as many as her husband would allow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-none-sp0112-ch123216-sg0003-mc02-lav-clo-dg030.wav", "answer": "said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can't said anne sorrowfully", "subset": "none", "task_type": "understanding", "prediction": "said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can t said anne sorrowfully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0188/Lab41-SRI-VOiCES-rm1-none-sp0188-ch141613-sg0017-mc02-lav-clo-dg150.wav", "answer": "bridled the little girl aggrievedly as the man began to laugh and anyway i don't understand why some folks should have such a lot and other folks shouldn't have anything and i don't like it", "subset": "none", "task_type": "understanding", "prediction": "bridled the little girl aggrievedly as the man began to laugh and anyway i don t understand why some folks should have such a lot and other folks shouldn t have anything and i don t like it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm1-none-sp0204-ch162375-sg0020-mc01-stu-clo-dg030.wav", "answer": "that is the house of shaws she cried blood built it blood stopped the building of it blood shall bring it down see here she cried again i spit upon the ground and crack my thumb at it black be its fall", "subset": "none", "task_type": "understanding", "prediction": "that is the house of shaws she cried blood built it blood stopped the building of it blood shall bring it down see here she cried again i spit upon the ground and crack my thumb at it black be its fall", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-none-sp0205-ch123882-sg0034-mc02-lav-clo-dg180.wav", "answer": "that dull reserve that seemed to hold the passengers in the electric suburban has clean vanished and gone they are talking listen of the harvest and the late election and of how the local member is mentioned for the cabinet and all the old familiar topics of the sort", "subset": "none", "task_type": "understanding", "prediction": "that dull reserve that seemed to hold the passengers in the electric suburban has clean vanished and gone they are talking listening of the harvest and the late election and of how the local member is mentioned for the cabinet and all the old familiar topics of the sort", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-none-sp0205-ch157088-sg0010-mc02-lav-clo-dg150.wav", "answer": "and sat watching olaf as he mothered the half baked bannock loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range", "subset": "none", "task_type": "understanding", "prediction": "and sat watching olaf as he mothered the half baked bannack loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-none-sp0205-ch159056-sg0010-mc02-lav-clo-dg120.wav", "answer": "when he was a colonel and had been through the wars and at court he still believed she was a match for all the beauties he was not lucky enough to take after her in looks except in her one weak feature a cutaway chin his body indeed", "subset": "none", "task_type": "understanding", "prediction": "when he was a colonel and had been through the wars and at court he still believed she was a match for all the beauties he was not lucky enough to take after her in looks except in her one weak feature a cutaway chin his body indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm1-none-sp0209-ch157830-sg0013-mc02-lav-clo-dg180.wav", "answer": "what every comfort of life knocked off journeys london servants horses table contractions and restrictions every where to live no longer with the decencies even of a private gentleman no", "subset": "none", "task_type": "understanding", "prediction": "what every comfort of life knocked off journeys london servants horses table contractions and restrictions everywhere to live no longer with the decencies even of a private gentleman no", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0240/Lab41-SRI-VOiCES-rm1-none-sp0240-ch160593-sg0021-mc02-lav-clo-dg060.wav", "answer": "it would be life and life is over there behind the shelf the sexton keeps the key to putting up our life his porcelain like a cup discarded of the housewife quaint or broken a newer sevres pleases old ones crack i could not die with you", "subset": "none", "task_type": "understanding", "prediction": "it would be life and life is over there behind the shelf the sexton keeps the key to putting up our life his porcelain like a cup discarded of the housewife quaint or broken a newer sever's pleases old ones crack i could not die with you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-none-sp0242-ch122626-sg0001-mc02-lav-clo-dg050.wav", "answer": "and humbled by the consciousness of my physical inferiority to eliza john and georgiana reed the said eliza john and georgiana were now clustered round their mama in the drawing room she lay reclined on a sofa by the fireside", "subset": "none", "task_type": "understanding", "prediction": "and humbled by the consciousness of my physical infirmity to eliza john and georgina reed the said eliza john and georgina were now clustered round their mamma in the drawing room she lay reclined on a sofa by the fireside", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-none-sp0242-ch126842-sg0018-mc01-stu-clo-dg000.wav", "answer": "after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cecily desperately drawing lots is wickeder that fighting said dan", "subset": "none", "task_type": "understanding", "prediction": "after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cicely desperately drawing lots is wickeder than fighting said dan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0288/Lab41-SRI-VOiCES-rm1-none-sp0288-ch130994-sg0033-mc02-lav-clo-dg060.wav", "answer": "may serve as a standard the state of agriculture and the populousness of a country have been considered as nearly connected with each other and as a rule for the purpose intended numbers in the view of simplicity and certainty are entitled to a preference", "subset": "none", "task_type": "understanding", "prediction": "may serve as a standard the state of agriculture and the populousness of a country have been considered as nearly connected with each other and as a rule for the purpose intended numbers in the view of simplicity and certainty are entitled to a preference", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0296/Lab41-SRI-VOiCES-rm1-none-sp0296-ch129659-sg0002-mc01-stu-clo-dg150.wav", "answer": "to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding", "subset": "none", "task_type": "understanding", "prediction": "to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0296/Lab41-SRI-VOiCES-rm1-none-sp0296-ch141721-sg0022-mc02-lav-clo-dg030.wav", "answer": "of his pompous helmet his superb cuirass his rich bracelets his brilliant cuisses or armour for his thighs and other martial accoutrements when zadig had equipp'd himself cap a pee in his now recover'd armour", "subset": "none", "task_type": "understanding", "prediction": "of his pompous helmet his superb cuirass his rich bracelets his brilliant cuisses or armour for his thighs and other martial accoutrements when zany had equipped himself cap a pie in his now recovered armour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm1-none-sp0459-ch123443-sg0034-mc02-lav-clo-dg010.wav", "answer": "and just as i was thinking i should be free of them at last they must needs come wriggling down from the sky ugh serpent but i'm not a serpent i tell you said alice i'm a i'm a well what are you said the pigeon", "subset": "none", "task_type": "understanding", "prediction": "and just as i was thinking i should be free of them at last they must needs come wriggling down from the sky ah serpent but i am not a serpent i tell you said alice i am a i am a well what are you said the pigeon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm1-none-sp0472-ch130755-sg0009-mc02-lav-clo-dg070.wav", "answer": "would be hardly less painful than of both and so on through the whole list of lady russell's too gentle reductions how anne's more rigid requisitions might have been taken is of little consequence lady russell's had no success at all", "subset": "none", "task_type": "understanding", "prediction": "would be hardly less painful than of both and so on through the whole list of lady russell's too gentle reductions how anne's more rigid requisitions might have been taken is of little consequence lady russell's had no success at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm1-none-sp0479-ch107479-sg0004-mc02-lav-clo-dg170.wav", "answer": "and still retain the prejudice against inferior associations which an english gentleman whatever the vicissitudes of his career can never quite rid himself of i had to join their club an exclusive organization of butlers and gentlemen's gentlemen otherwise valets", "subset": "none", "task_type": "understanding", "prediction": "that still retain the prejudice against inferior associations which an english gentleman whatever the vicissitudes of his career can never quite rid himself of i had to join their club an exclusive organization of butlers and gentlemen s gentlemen otherwise valets", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm1-none-sp0479-ch126480-sg0027-mc01-stu-clo-dg030.wav", "answer": "little tin patty pan duchess drew a long breath then i must have been eating mouse no wonder i feel ill but perhaps i should feel worse if i had really swallowed a patty pan duchess reflected what a very awkward thing to have to explain to ribby", "subset": "none", "task_type": "understanding", "prediction": "little tin patty pan duchess drew a long breath then it must have been eating mouse no wonder i feel ill but perhaps i should feel worse if i had really swallowed a patty pan duchess reflected what a very awkward thing to have to explain to ribby", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-none-sp0480-ch126292-sg0014-mc02-lav-clo-dg110.wav", "answer": "with all my heart get up behind and be sure you do not fall off take care of this handsome coach of mine nor dirty my pretty red wheels so fine now mice be ready and wheels run steady for we are going a visit to pay", "subset": "none", "task_type": "understanding", "prediction": "with all my heart get up behind and be sure you do not fall off take care of this handsome coach of mine nor dirty my pretty red wheels so fine now mice be ready and wheels run steady for we are going a visit to pay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-none-sp0480-ch127525-sg0006-mc02-lav-clo-dg120.wav", "answer": "two fresh men were at the oars the tide keeps washing her down could you pull a little stronger not without swamping the boat said he you must bear up sir", "subset": "none", "task_type": "understanding", "prediction": "two fresh men were at the oars the tide keeps washing her down could you pull a little stronger not without swamping the boat said he you must bear up sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm1-none-sp0492-ch131899-sg0008-mc01-stu-clo-dg010.wav", "answer": "he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation", "subset": "none", "task_type": "understanding", "prediction": "he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0597/Lab41-SRI-VOiCES-rm1-none-sp0597-ch127694-sg0014-mc01-stu-clo-dg110.wav", "answer": "nevertheless the little douglas squirrel can open them indians climb the trees like bears and beat off the cones or recklessly cut off the more fruitful branches with hatchets while the squaws gather and roast them until the scales open sufficiently", "subset": "none", "task_type": "understanding", "prediction": "nevertheless the little douglas squirrel can open them indians climb the trees like bears and beat off the cones or recklessly cut off the more fruitful branches with hatchets while the squaws gather and roast them until the scales open sufficiently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0597/Lab41-SRI-VOiCES-rm1-none-sp0597-ch134789-sg0036-mc01-stu-clo-dg050.wav", "answer": "they are forever talking about it to us to me in particular just as the old women in naples cry to saint januarius faccia gialluta fa o miracolo yellow face perform thy miracle so our beauties say to me incessantly", "subset": "none", "task_type": "understanding", "prediction": "they are forever talking about it to us to me in particular just as the old women in naples cry to saint januarius facciocioluto fa un miracolo yellow face perform thy miracle so our beauties say to me incessantly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm1-none-sp0636-ch128331-sg0015-mc01-stu-clo-dg090.wav", "answer": "with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building", "subset": "none", "task_type": "understanding", "prediction": "with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0652/Lab41-SRI-VOiCES-rm1-none-sp0652-ch129742-sg0012-mc02-lav-clo-dg080.wav", "answer": "salad two cups of apples cut into small pieces one cup celery cut into small pieces one cup english walnuts", "subset": "none", "task_type": "understanding", "prediction": "salad two cups of apples cut into small pieces one cup celery cut into small pieces one cup english walnuts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0652/Lab41-SRI-VOiCES-rm1-none-sp0652-ch130737-sg0010-mc02-lav-clo-dg060.wav", "answer": "sauterne is a white bordeaux a strong luscious wine the best known varieties being", "subset": "none", "task_type": "understanding", "prediction": "Sauvignon is a white Bordeaux, a strong. Luscious wine, the best known varieties being.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm1-none-sp0949-ch162667-sg0034-mc01-stu-clo-dg020.wav", "answer": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "subset": "none", "task_type": "understanding", "prediction": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm1-none-sp1050-ch134121-sg0015-mc02-lav-clo-dg010.wav", "answer": "each one went down taking a napkin the cook laid the kitchen table put on it her best table cloth and the family sat down amanda went to the dumb waiter for the dinner but she could not move it down the family were all in dismay", "subset": "none", "task_type": "understanding", "prediction": "each one went down taking a napkin the cook laid the kitchen table put on it her best tablecloth and the family sat down amanda went to the dumb waiter for the dinner but she could not move it down the family were all in dismay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1052/Lab41-SRI-VOiCES-rm1-none-sp1052-ch139308-sg0001-mc02-lav-clo-dg130.wav", "answer": "and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there", "subset": "none", "task_type": "understanding", "prediction": "and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm1-none-sp1066-ch005330-sg0006-mc01-stu-clo-dg110.wav", "answer": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune", "subset": "none", "task_type": "understanding", "prediction": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm1-none-sp1112-ch128136-sg0019-mc01-stu-clo-dg090.wav", "answer": "are excessively tedious but when mister rodd leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed", "subset": "none", "task_type": "understanding", "prediction": "are excessively tedious but when mr rod leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm1-none-sp1116-ch132847-sg0029-mc01-stu-clo-dg050.wav", "answer": "the swallow is less swift than the wind the wind is less swift than the lightning but you my horse if you love me must be swifter than them all for there is a part of my heart that suffers the best part of my heart that is in danger and the horse heard her", "subset": "none", "task_type": "understanding", "prediction": "The swallow is less swift than the wind. The wind is less swift than the lightning. But you, my horse, if you love me, must be swifter than them all for there is a part of my heart that suffers the best part of my heart that is in danger. And the horse heard her.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm1-none-sp1116-ch132851-sg0015-mc01-stu-clo-dg070.wav", "answer": "and six new pieces of silver in the pocket of her apron and she believed that all this was owing to jegu and she could no longer do without him even in her thoughts when things had reached this pass the brownie told the young man that he had better ask barbaik to marry him", "subset": "none", "task_type": "understanding", "prediction": "and six new pieces of silver in the pocket of her apron and she believed that all this was owing to jegu and she could no longer do without him even in her thoughts when things had reached this pass the brownie told the young man that he had better ask barbe to marry him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm1-none-sp1160-ch134674-sg0015-mc01-stu-clo-dg000.wav", "answer": "as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps", "subset": "none", "task_type": "understanding", "prediction": "as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1182/Lab41-SRI-VOiCES-rm1-none-sp1182-ch133396-sg0014-mc02-lav-clo-dg150.wav", "answer": "he waited for a while and then knocked again rap tap tap presently with a click a little square wicket that pierced the door was opened and a woman's face peered out through the iron bars the one eyed hans whipped off his leathern cap", "subset": "none", "task_type": "understanding", "prediction": "he waited for a while and then knocked again rap tap tap presently with a click a little square wicket that pierced the door was opened and a woman s face peered out through the iron bars the one eyed hans whipped off his leather cap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_0032-1182/sp1182/Lab41-SRI-VOiCES-rm1-none-sp1182-ch134316-sg0027-mc01-stu-clo-dg040.wav", "answer": "she examined the room carefully at the farthermost end was another door and this she pushed gently at first and then vigorously without producing the slightest impression she still had her bag a small affair of black moire which hung from her belt", "subset": "none", "task_type": "understanding", "prediction": "she examined the room carefully at the farthermost end was another door and this she pushed gently at first and then vigorously without producing the slightest impression she still had her bag a small affair of black moire which hung from her belt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1235/Lab41-SRI-VOiCES-rm1-none-sp1235-ch135883-sg0020-mc02-lav-clo-dg070.wav", "answer": "he was agreeably surprised when he found the prince entered the council chamber without giving him the fatal orders he expected the sultan according to his custom spent the day in regulating his affairs and when the night had closed in retired with scheherazade", "subset": "none", "task_type": "understanding", "prediction": "he was agreeably surprised when he found the prince enter the council chamber without giving him the fatal orders he expected the sultan according to his custom spent the day in regulating his affairs and when the night closed in retired to shahrazad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1235/Lab41-SRI-VOiCES-rm1-none-sp1235-ch135887-sg0026-mc02-lav-clo-dg130.wav", "answer": "if he had had a design upon my life why did he save me then he needed only to have left me to my disease i could not have escaped it as life was fast decaying forbear then to fill me with unjust suspicions", "subset": "none", "task_type": "understanding", "prediction": "if he had had a design upon my life why did he save me then he needed only to have left me to my disease i could not have escaped it as life was fast decaying forbear then to fill me with unjust suspicions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm1-none-sp1246-ch135815-sg0012-mc02-lav-clo-dg000.wav", "answer": "peter was delighted to air his knowledge the last one i was in said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it", "subset": "none", "task_type": "understanding", "prediction": "peter was delighted to air his knowledge the last one i was in he said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm1-none-sp1272-ch135031-sg0000-mc01-stu-clo-dg090.wav", "answer": "because you were sleeping instead of conquering the lovely rose princess has become a fiddle without a bow while poor shaggy sits there a cooing dove", "subset": "none", "task_type": "understanding", "prediction": "because you are sleeping instead of conquering the lovely rose princess has become a fiddle without a bow while poor shaggy sits there a cooing dove", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm1-none-sp1383-ch130489-sg0016-mc02-lav-clo-dg150.wav", "answer": "her heart fluttered with a vague terror her heart pounded in her throat her heart was full of speechless sorrow her hurrying thoughts clamored for utterance her imagination recoiled her interest flagged", "subset": "none", "task_type": "understanding", "prediction": "her heart fluttered with a vague terror her heart pounded in her throat her heart was full of speechless sorrow her hurrying thoughts clamored for utterance her imagination recoiled her interest flagged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm1-none-sp1383-ch130489-sg0018-mc02-lav-clo-dg130.wav", "answer": "her mood was unaccountably chilled her musings took a sudden and arbitrary twist her scarlet lip curled cruelly her smile was faintly depreciatory her smile was linked with a sigh", "subset": "none", "task_type": "understanding", "prediction": "her mood was unaccountably chilled her musings took a sudden and arbitrary twist her scarlet lip curled cruelly her smile was faintly depreciatory her smile was linked with a sigh", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-none-sp1472-ch142848-sg0009-mc01-stu-clo-dg160.wav", "answer": "the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves one selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation", "subset": "none", "task_type": "understanding", "prediction": "the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves when selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-none-sp1472-ch285314-sg0037-mc02-lav-clo-dg170.wav", "answer": "mister skeelty stared at him a moment then he laughed they're mostly foreigners mister merrick who haven't yet fully mastered the english language but he added thoughtfully a few among them might subscribe if your country sheet contains any news of interest at all", "subset": "none", "task_type": "understanding", "prediction": "mr skeelty stared at him a moment then he laughed they are mostly foreigners mr merrick who haven t yet fully mastered the english language but he added thoughtfully a few among them might subscribe if your country sheet contains any news of interest at all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1851/Lab41-SRI-VOiCES-rm1-none-sp1851-ch148312-sg0008-mc02-lav-clo-dg100.wav", "answer": "he said quietly and still protested with many compliments that he would marry none but her when baptista came back he asked at once how speed you with my daughter how should i speed but well replied petruchio how but well", "subset": "none", "task_type": "understanding", "prediction": "he said quietly and still protested with many compliments that he would marry none but her when baptista came back he asked at once how speed you with my daughter how should i speed but well replied petruchio how but well", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1851/Lab41-SRI-VOiCES-rm1-none-sp1851-ch151817-sg0036-mc02-lav-clo-dg150.wav", "answer": "or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course they must be totally ignorant of all such things as flying machines and the like", "subset": "none", "task_type": "understanding", "prediction": "or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course it must be totally ignorant of all such things as flying machines and the like", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm1-none-sp1867-ch154075-sg0008-mc01-stu-clo-dg140.wav", "answer": "had the clever devil guessed at the truth so easily had he sent his follower away merely to avoid having it known that a man had taken shelter in the room of the girl he loved go on the leader was repeating let me hear the whole truth", "subset": "none", "task_type": "understanding", "prediction": "had the clever devil guessed at the truth so easily had he sent his follower away merely to avoid having it known that a man had taken shelter in the room of the girl he loved go on the leader was repeating let me hear the whole truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm1-none-sp1867-ch154075-sg0018-mc02-lav-clo-dg130.wav", "answer": "as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance", "subset": "none", "task_type": "understanding", "prediction": "as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm1-none-sp1874-ch165702-sg0018-mc01-stu-clo-dg100.wav", "answer": "emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four", "subset": "none", "task_type": "understanding", "prediction": "emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm1-none-sp1874-ch165702-sg0020-mc02-lav-clo-dg150.wav", "answer": "april fourteenth assassinated in ford's theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett", "subset": "none", "task_type": "understanding", "prediction": "april fourteenth assassinated in ford s theatre washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1926/Lab41-SRI-VOiCES-rm1-none-sp1926-ch147987-sg0012-mc02-lav-clo-dg030.wav", "answer": "when i got home i climbed in at the kitchen window i was covered with blood from my nose and lip but i was too sick to do anything about it i found a shawl and an overcoat on the hatrack lay down on the parlor sofa and in spite of my hurts went to sleep", "subset": "none", "task_type": "understanding", "prediction": "when i got home i climbed in at the kitchen window i was covered with blood from my nose and lip but i was too sick to do anything about it i found a shawl and an overcoat on the hat rack lay down on the parlor sofa and in spite of my hurts went to sleep", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm1-none-sp1970-ch026100-sg0035-mc01-stu-clo-dg110.wav", "answer": "oh his alibi is good of course because he was around the club all that evening i guess he was here and i don't remember it i shook hands with him and left far out on the golf links the coroner was bending over examining something on the ground", "subset": "none", "task_type": "understanding", "prediction": "oh his alibi is good of course because he was around the club all that evening i guess he was here and i don t remember it i shook hands with him and left far out on the golf links the coroner was bending over examining something on the ground", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm1-none-sp2012-ch139358-sg0018-mc01-stu-clo-dg130.wav", "answer": "it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries", "subset": "none", "task_type": "understanding", "prediction": "it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2074/Lab41-SRI-VOiCES-rm1-none-sp2074-ch147193-sg0032-mc01-stu-clo-dg000.wav", "answer": "king of athens who lives on pallas hill and say to him the stone is lifted but whose is the pledge beneath it then show him the sword and the sandals and take what the gods shall send", "subset": "none", "task_type": "understanding", "prediction": "king of athens who lives on palace hill and say to him the stone is lifted but whose is the pledge beneath it then show him the sword and the sandals and take what the gods shall send", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2149/Lab41-SRI-VOiCES-rm1-none-sp2149-ch007239-sg0015-mc02-lav-clo-dg070.wav", "answer": "boasters proud blasphemers disobedient to parents unthankful", "subset": "none", "task_type": "understanding", "prediction": "boasters proud blasphemers disobedient to parents unthankful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm1-none-sp2156-ch025563-sg0042-mc01-stu-clo-dg120.wav", "answer": "the buttons on phelan's coat were fairly undulating with the emotions that stirred within him in his seething gray matter there stirred the remembrance that bateato had told him that women were robbing the house you mean the women", "subset": "none", "task_type": "understanding", "prediction": "the buttons on phelan s coat were fairly undulating with the emotions that stirred within him in his seething gray matter there stirred the remembrance that bateato had told him that women were robbing the house you mean the women", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2162/Lab41-SRI-VOiCES-rm1-none-sp2162-ch164461-sg0006-mc01-stu-clo-dg140.wav", "answer": "since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves", "subset": "none", "task_type": "understanding", "prediction": "since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2162/Lab41-SRI-VOiCES-rm1-none-sp2162-ch164461-sg0026-mc02-lav-clo-dg110.wav", "answer": "or go off on something different altogether this crucial point in his life is marked by nicholas nickleby it must be remembered that before this issue of nicholas nickleby his work successful as it was", "subset": "none", "task_type": "understanding", "prediction": "or go off on something different altogether this crucial point in his life is marked by nicholas nickleby it must be remembered that before this issue of nicholas nickleby his work successful as it was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm1-none-sp2285-ch149890-sg0024-mc02-lav-clo-dg070.wav", "answer": "where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mister hurstwood came from the first individual recognised glad to see you said the latter grasping his hand lightly", "subset": "none", "task_type": "understanding", "prediction": "where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mr hurstwood came from the first individual recognized glad to see you said the latter grasping his hand lightly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm1-none-sp2285-ch163380-sg0014-mc01-stu-clo-dg110.wav", "answer": "after a long time the rain let up but the clouds stayed and the lightning kept whimpering and by and by a flash showed us a black thing ahead floating and we made for it it was the raft and mighty glad was we to get aboard of it again", "subset": "none", "task_type": "understanding", "prediction": "after a long time the rain let up but the clouds stayed and the lightning kept whimpering and by and by a flash showed us a black thing ahead floating and we made for it it was the raft and mighty glad was we to get aboard of it again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm1-none-sp2285-ch163380-sg0034-mc02-lav-clo-dg050.wav", "answer": "for helping these rapscallions because rapscallions and dead beats is the kind the widow and good people takes the most interest in well before long here comes the wreck dim and dusky sliding along down a kind of", "subset": "none", "task_type": "understanding", "prediction": "for helping these rapscallions cause rapscallions and deadbeats is the kind a widow and good people take the most interest in well before long here comes the wreck dim and dusky sliding along down a kind of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm1-none-sp2285-ch163381-sg0034-mc01-stu-clo-dg020.wav", "answer": "does a cat talk like a cow or a cow talk like a cat no dey don't it's natural and right for em to talk different from each other ain't it course and ain't it natural and right", "subset": "none", "task_type": "understanding", "prediction": "Does a cat talk like a cow or a cow talk like a cat, No, they don't. It's natural and right for em to talk different from each other, ain't it. Course, and ain't it natural and right.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm1-none-sp2289-ch152258-sg0005-mc01-stu-clo-dg030.wav", "answer": "that people gave him the name of el amin which means the truthful at this time he was only sixteen years of age but the rich traders had so much confidence in him that they gave him important business to attend to and trusted him with large sums of money", "subset": "none", "task_type": "understanding", "prediction": "that people gave him the name of el amin which means the truthful at this time he was only sixteen years of age but the rich traders had so much confidence in him that they gave him important business to attend to and trusted him with large sums of money", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm1-none-sp2412-ch153948-sg0000-mc02-lav-clo-dg080.wav", "answer": "if the reader will excuse me i will say nothing of my antecedents nor of the circumstances which led me to leave my native country the narrative would be tedious to him and painful to myself", "subset": "none", "task_type": "understanding", "prediction": "if the reader will excuse me i will say nothing of my antecedents nor of the circumstances which led me to leave my native country the narrative would be tedious to him and painful to myself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2573/Lab41-SRI-VOiCES-rm1-none-sp2573-ch178450-sg0027-mc01-stu-clo-dg150.wav", "answer": "aren't you ever goin to bed sheridan halted all right mamma he said with a vast sigh let's go up and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising lopsidedly in her drowsiness", "subset": "none", "task_type": "understanding", "prediction": "arent you ever going to bed sheridan halted all right mamma he said with a vast sigh lets go up and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising lopsidedly in her drowsiness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2691/Lab41-SRI-VOiCES-rm1-none-sp2691-ch156745-sg0027-mc01-stu-clo-dg160.wav", "answer": "merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances", "subset": "none", "task_type": "understanding", "prediction": "merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm1-none-sp2764-ch036616-sg0038-mc02-lav-clo-dg110.wav", "answer": "not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day's delay would have been unforgivable", "subset": "none", "task_type": "understanding", "prediction": "not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day s delay would have been unforgivable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm1-none-sp2764-ch036617-sg0016-mc01-stu-clo-dg130.wav", "answer": "don't bother counting just squeeze it all in and hurry what about master's collections conseil ventured to observe we'll deal with them later what the archaeotherium hyracotherium oreodonts cheiropotamus and master's other fossil skeletons", "subset": "none", "task_type": "understanding", "prediction": "dont bother counting just squeeze it all in and hurry what about masters collections conseil ventured to observe we will deal with them later what the archaeotherium hyracotherium oreodonts carpothermus and masters other fossil skeletons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm1-none-sp2803-ch154320-sg0004-mc02-lav-clo-dg150.wav", "answer": "much as they had been interested in his dissertation on the pampas or australia his lectures on new zealand fell on cold and indifferent ears", "subset": "none", "task_type": "understanding", "prediction": "Much as they had been interested in his dissertation on the Pampas or Australia, his lectures on New Zealand fell on cold and indifferent ears", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm1-none-sp2803-ch154328-sg0018-mc02-lav-clo-dg120.wav", "answer": "their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sounds that only a thin layer of earth prevented immediate communication", "subset": "none", "task_type": "understanding", "prediction": "their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sounds that only a thin layer of earth prevented immediate communication", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm1-none-sp2911-ch015045-sg0011-mc02-lav-clo-dg170.wav", "answer": "or prowling warrior we have said that this group of tribes was relatively very populous yet it is more than doubtful whether all of them united had union been possible could have mustered eight thousand fighting men to speak further of them is needless", "subset": "none", "task_type": "understanding", "prediction": "or prowling warrior we have said that this group of tribes was relatively very populous yet it is more than doubtful whether all of them united had union been possible could have mustered eight thousand fighting men to speak further of them is needless", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm1-none-sp2911-ch015084-sg0007-mc02-lav-clo-dg070.wav", "answer": "not by a depleted antagonist still feeble from the exhaustion of a starved and persecuted infancy but by an athletic champion of the principles of richelieu and of loyola liberty may thank the iroquois that by their insensate fury", "subset": "none", "task_type": "understanding", "prediction": "not by a depleted antagonist still feeble from the exhaustion of a starved and persecuted infancy but by an athletic champion of the principles of richelieu and of boyola liberty may thank the iroquois that by their incessant fury", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3235/Lab41-SRI-VOiCES-rm1-none-sp3235-ch011599-sg0012-mc02-lav-clo-dg010.wav", "answer": "into several constituent groups the principal compound measures are four beat and six beat both being referred to as compound duple measures five beat seven beat nine beat and twelve beat measures", "subset": "none", "task_type": "understanding", "prediction": "in a several constituent groups the principal compound measures are four beat and six beat both being referred to as compound duple measures five beat seven beat nine beat and twelve beat measures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3235/Lab41-SRI-VOiCES-rm1-none-sp3235-ch028433-sg0007-mc02-lav-clo-dg150.wav", "answer": "and crowded to the utmost capacity for comfort every stateroom was full each seat at the tables occupied not a foot of space above or below decks was left unused but provision was made for all", "subset": "none", "task_type": "understanding", "prediction": "and crowded to the utmost capacity for comfort every state room was full each seat at the tables occupied not a foot of space above or below decks was left unused but provision was made for all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm1-none-sp3368-ch170950-sg0014-mc02-lav-clo-dg020.wav", "answer": "why he said are they not capable of defending themselves no i said not if we were right in the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success", "subset": "none", "task_type": "understanding", "prediction": "why he said are they not capable of defending themselves no i said not if we were right that the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm1-none-sp3368-ch170951-sg0047-mc01-stu-clo-dg010.wav", "answer": "he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a chorus neither shall we allow teachers to make use of them in the instruction of the young meaning", "subset": "none", "task_type": "understanding", "prediction": "he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a corpse neither shall we allow teachers to make use of them in the instruction of the young meaning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm1-none-sp3368-ch170952-sg0041-mc02-lav-clo-dg140.wav", "answer": "any more than i can allow our citizens to believe that he the wise cheiron's pupil the son of a goddess and of peleus who was the gentlest of men and third in descent from zeus was so disordered in his wits as to be at one time the slave of two seemingly inconsistent passions", "subset": "none", "task_type": "understanding", "prediction": "any more than i can allow our citizens to believe that he the wise charon s pupil the son of a goddess and of pelias who was the gentlest of men and third in descent from zeus was so disordered in his wits as to be at one time the slave of two seemingly inconsistent passions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm1-none-sp3483-ch115968-sg0003-mc01-stu-clo-dg090.wav", "answer": "and laid out new camp locations scattering them farther to the south and avoiding ground which had been seared by the han beams and the immediate locations of the han wrecks during this period a sharp check was kept upon han messages", "subset": "none", "task_type": "understanding", "prediction": "and laid out new camp locations scattering them farther to the south and avoiding ground which had been seared by the han beams and the immediate locations of the han wrecks during this period a sharp check was kept upon han messages", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm1-none-sp3483-ch174132-sg0010-mc01-stu-clo-dg000.wav", "answer": "but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study", "subset": "none", "task_type": "understanding", "prediction": "but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_1212-3521/sp3521/Lab41-SRI-VOiCES-rm1-none-sp3521-ch007591-sg0036-mc01-stu-clo-dg050.wav", "answer": "but in the next his brow reddened with rage who dares he demanded hoarsely of the courtiers who stood near him who dares insult us with this blasphemous mockery seize him and unmask him that we may know whom we have to hang at sunrise from the battlements", "subset": "none", "task_type": "understanding", "prediction": "but in the next his brow reddened with rage who dares he demanded hoarsely of the courtiers who stood near him who dares insult us with this blasphemous mockery seize him and unmask him that we may know whom we have to hang at sunrise from the battlements", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm1-none-sp3835-ch178030-sg0013-mc02-lav-clo-dg170.wav", "answer": "nicholas rostov took a close and prolonged part in the defense of his country but did so casually without any aim at self sacrifice and he therefore looked at what was going on in russia without despair and without dismally racking his brains over it", "subset": "none", "task_type": "understanding", "prediction": "nicholas rostov took a close and prolonged part in the defense of his country but did so casually without any aim at self sacrifice and he therefore looked at what was going on in russia without despair and without dismally racking his brains over it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm1-none-sp3923-ch181420-sg0027-mc01-stu-clo-dg080.wav", "answer": "pious and god fearing most of them but largely at the mercy of the local traders who took their pay in fish for the bare necessities of living with a large account always on the trader's side with such medical aid and ministration as came only occasionally by the infrequent mail boat", "subset": "none", "task_type": "understanding", "prediction": "pious and god fearing most of them but largely at the mercy of the local traders who took their pay in fish for the bare necessities of living with a large account always on the traders side with such medical aid and ministration as came only occasionally by the infrequent mail boat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp3994/Lab41-SRI-VOiCES-rm1-none-sp3994-ch149798-sg0002-mc02-lav-clo-dg020.wav", "answer": "raise the sunken island and save our friends and the imprisoned skeezers afterward we can visit the mountain and punish the cruel magician of the flatheads that is sensible approved the shaggy man i quite agree with you", "subset": "none", "task_type": "understanding", "prediction": "raise the sunken island and save our friends and the imprisoned skeezers afterward we can visit the mountain and punish the cruel magician of the flatheads that is sensible approved the shaggy man i quite agree with you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-none-sp4014-ch186175-sg0019-mc01-stu-clo-dg180.wav", "answer": "and he started down the passageway toward a narrow stairs leading to a still lower chamber in the vessel three turns two to the right and one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock", "subset": "none", "task_type": "understanding", "prediction": "and he started down the passageway towards a narrow stairway leading to a still lower chamber in the vessel three turns two to the right and one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-none-sp4014-ch186176-sg0004-mc02-lav-clo-dg140.wav", "answer": "evidently also from the boiler or engine room brushed by us he had disappeared when the sailor said to me i think that was the fellow the one that just went by not wanting to arouse his suspicions i ended the conversation with a casual remark and then strolled away until i was out of the sailor's sight", "subset": "none", "task_type": "understanding", "prediction": "And gently, also from the boiler or engine room, brushed by us. He had disappeared. The sailor said to me, I think that was the fellow. The one that just went by not wanting to rouse his suspicions. I entered the conversation with a casual remark and then strolled away until I was out of the sailor sight.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-none-sp4014-ch186183-sg0024-mc01-stu-clo-dg170.wav", "answer": "he pointed her nose downward toward the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer's place in the taube was making desperate signals", "subset": "none", "task_type": "understanding", "prediction": "he pointed her nose downward towards the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer s place in the top was making desperate signals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4057/Lab41-SRI-VOiCES-rm1-none-sp4057-ch012085-sg0006-mc02-lav-clo-dg150.wav", "answer": "hand out your valuables a man of medium height wearing a mask and full beard stood over him darrell quietly handed over his watch and purse noting as he did so the man's hands white well formed well kept", "subset": "none", "task_type": "understanding", "prediction": "hand out your valuables a man of medium height wearing a mask and full beard stood over him darrell quietly handed over his watch and purse noting as he did so the man s hands white well formed well kept", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm1-none-sp4064-ch019132-sg0011-mc02-lav-clo-dg010.wav", "answer": "mister gamble proposed that they visit one of the theatres he had a box all ready it seemed and oliver accepted for alice before montague could say a word for her he spoke for himself however he had important work to do and must be excused", "subset": "none", "task_type": "understanding", "prediction": "mr gamble proposed that they visit one of the theatres he had a box all ready it seemed and oliver accepted for alice before montague could say a word for her he spoke for himself however he had important work to do and must be excused", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm1-none-sp4064-ch019132-sg0034-mc01-stu-clo-dg060.wav", "answer": "nothing said the other she is simply ruining herself said oliver i've been trying to get reggie mann to have her introduced to missus devon but he says he wouldn't dare to take the risk no i presume not said montague", "subset": "none", "task_type": "understanding", "prediction": "nothing said the other she is simply ruining herself said oliver i have been trying to get reggie mann to have her introduced to mrs devon but he says he wouldn't dare to take the risk no i presume not said montague", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm1-none-sp4064-ch077779-sg0014-mc02-lav-clo-dg010.wav", "answer": "and provokes a great deal of innocent mirth you don't yourself believe that last yarn about the prohibition candidate do you i haven't heard any yarn about him said the bibliomaniac that he is the owner of a brewery up in rochester", "subset": "none", "task_type": "understanding", "prediction": "and provokes a great deal of innocent mirth you dont yourself believe that last yarn about the prohibition candidate do you i haven t heard any yarn about him said the bibliomaniac that he is the owner of a brewery up in rochester", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm1-none-sp4064-ch077779-sg0028-mc01-stu-clo-dg170.wav", "answer": "can have no private life then you approve of these stories of candidates cousins the prattling anecdotes of their grandchildren these paragraphs narrating the doings of their uncles in law and all that sneered the bibliomaniac", "subset": "none", "task_type": "understanding", "prediction": "can have no private life then you approve of these stories of candidates cousins the prattling anecdotes of their grandchildren these paragraphs narrating the doings of their uncles in law and all that sneered the bibliomaniac", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4110/Lab41-SRI-VOiCES-rm1-none-sp4110-ch011533-sg0018-mc01-stu-clo-dg150.wav", "answer": "he hoped also to see from above something of the result of the strange aerial bombardment of which his father had spoken in their flight which had been to them a flight through the glories of a super heavenly universe they had lost all count of time", "subset": "none", "task_type": "understanding", "prediction": "he hoped also to see from above something of the result of the strange aerial bombardment of which his father had spoken in their flight which had been to them a flight through the glories of a super heavenly universe they had lost all count of time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4116/Lab41-SRI-VOiCES-rm1-none-sp4116-ch003582-sg0035-mc02-lav-clo-dg140.wav", "answer": "for we should never get the child here again if we let her go now and i talked well i had to talk some but well the upshot is i did get her and i did bring her and here she is and the old gentleman was so delighted with his success", "subset": "none", "task_type": "understanding", "prediction": "for we should never get the child here again if we let her go now and i talked well i had to talk some but well the upshot is i did get her and i did bring her and here she is and the old gentleman was so delighted with his success", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4116/Lab41-SRI-VOiCES-rm1-none-sp4116-ch013256-sg0021-mc02-lav-clo-dg020.wav", "answer": "the devil is waiting for me see him she exclaimed hoarsely she turned and pointed with a shaking finger at the saloon keeper the crowd laughed virginia stepped up to her and put her arm about her loreen she said firmly come with me", "subset": "none", "task_type": "understanding", "prediction": "the devil is waiting for me see him she exclaimed hoarsely she turned and pointed with a shaking finger at the saloon keeper the crowd laughed virginia stepped up to her and put her arm about her laurine she said firmly come with me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4116/Lab41-SRI-VOiCES-rm1-none-sp4116-ch013265-sg0019-mc02-lav-clo-dg010.wav", "answer": "people can't live at that concert pitch all the time you see if rachel doesn't give it up soon it's a great pity she doesn't come to chicago and sing in the auditorium concerts she has received an offer i'm going to write and urge her to come i'm just dying to hear her sing felicia", "subset": "none", "task_type": "understanding", "prediction": "people can live at that concert pitch all the time you see if rachel doesn't give it up soon it is a great pity she doesn't come to chicago and sing in the auditorium concerts she has received an offer i am going to write and urge her to come i am just dying to hear her sing valasia", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4145/Lab41-SRI-VOiCES-rm1-none-sp4145-ch104606-sg0003-mc02-lav-clo-dg050.wav", "answer": "in her astonishment she all but knocked the lamp over jack laughed i believe he said you two have met before madge continued speechless she passed her hand before her eyes as if to make sure she was not dreaming", "subset": "none", "task_type": "understanding", "prediction": "in her astonishment she all but knocked the lamp over jack laughed i believe he said you two have met before madge continued speechless she passed her hand before her eyes as if to make sure she was not dreaming", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4331/Lab41-SRI-VOiCES-rm1-none-sp4331-ch057179-sg0037-mc01-stu-clo-dg040.wav", "answer": "to the duchess condemnation from lady augustus almost amounted to praise she felt sure that mister morton was a worthy man who would not probably behave badly and though she could not unravel the mystery and certainly had no suspicion in regard to lord rufford", "subset": "none", "task_type": "understanding", "prediction": "to the duchess condemnation from lady augustus almost amounted to praise she felt sure that mr morton was a worthy man who had not probably behaved badly and though she could not unravel the mystery and certainly had no suspicion in regard to lord rufford", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4331/Lab41-SRI-VOiCES-rm1-none-sp4331-ch057180-sg0021-mc02-lav-clo-dg110.wav", "answer": "an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said up stairs they could not have talked as they were then talking", "subset": "none", "task_type": "understanding", "prediction": "an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said upstairs they could not have talked as they were then talking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm1-none-sp4427-ch041933-sg0034-mc01-stu-clo-dg020.wav", "answer": "and were feeling quite happy when suddenly they heard the sound of a gallop far behind them the prince sprang from the saddle and laid his ear to the ground they are pursuing us he said then there is no time to be lost answered the princess", "subset": "none", "task_type": "understanding", "prediction": "and were feeling quite happy when suddenly they heard the sound of a gallop far behind them the prince sprang from the saddle and laid his ear to the ground they are pursuing us he said then there is no time to be lost answered the princess", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm1-none-sp4438-ch048525-sg0011-mc01-stu-clo-dg080.wav", "answer": "the kindest and gentlest of men hadn't been kind and gentle but unjust by explaining well that was at the very beginning she soon learned that a doubt in her mind was better kept there", "subset": "none", "task_type": "understanding", "prediction": "the kindest and gentlest of men hadnt been kind and gentle but unjust by explaining well that was at the very beginning she soon learned that a doubt in her mind was better kept there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm1-none-sp4441-ch076250-sg0004-mc01-stu-clo-dg050.wav", "answer": "vex you old man you expect me to keep my vexations to myself but you lie lay old girl i say lie your burdens on my shoulders too was that what you promised me when we got married", "subset": "none", "task_type": "understanding", "prediction": "vex you old man you expect me to keep my vexation to myself but you lie lay old girl i said lie your burden is on my shoulders too was that what you promised me when we got married", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm1-none-sp4441-ch076262-sg0018-mc01-stu-clo-dg030.wav", "answer": "as if he wanted to force his thoughts into another groove it's my birthday and i want you to have breakfast with me agnes who had seen the train rushing straight at her felt relieved she burst into merry laughter and embraced falander but as breakfast has been ordered for eleven we'll have to wait a while", "subset": "none", "task_type": "understanding", "prediction": "as if he wanted to force his thoughts into another groove it is my birthday and i want you to have breakfast with me agnes who had seen the train rushing straight at her felt relieved she burst into merry laughter and embraced philander but as breakfast has been ordered for eleven we will have to wait a while", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm1-none-sp4535-ch279849-sg0019-mc01-stu-clo-dg030.wav", "answer": "brown took the throttle and pushed the general onward toward green's station tom put the last of the fuel in the fire and leaned wearily against the cab drops of rain carried by the wind splashed upon him and ran down his body streaking the soot which covered his chest and stomach", "subset": "none", "task_type": "understanding", "prediction": "brown took the throttle and pushed the gentle onward toward green station tom put the last of the fuel in the fire and leaned wearily against the cab drops of rain carried by the wind splashed upon him and ran down his body streaking the soot which covered his chest and stomach", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm1-none-sp4535-ch279856-sg0001-mc02-lav-clo-dg170.wav", "answer": "she answered crying i won't let you here joe and sam put those things down and stay here oh tom they'll surely catch you if you try it she clutched his arm as though to hold him from running into the woods but marjorie there's nothing we can do he protested please go back", "subset": "none", "task_type": "understanding", "prediction": "she answered crying i won t let you here joe and sam put those things down and stay here oh tom they ll surely catch you if you try it she clutched his arm as though to hold him from running into the woods but marjorie there s nothing we can do he protested please go back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm1-none-sp4839-ch015307-sg0016-mc02-lav-clo-dg060.wav", "answer": "to save it who would refuse to risk his own life and that of his children if the defence of padua is the pledge for the salvation of venice who would hesitate to go and defend it and though the forces already there were sufficient is not our honor also concerned therein", "subset": "none", "task_type": "understanding", "prediction": "to save it who would refuse to risk his own life and that of his children if the defence of padua is the pledge for the salvation of venice who would hesitate to go and defend it and though the forces already there were sufficient is not our honour also concerned therein", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm1-none-sp4839-ch015307-sg0030-mc01-stu-clo-dg010.wav", "answer": "it needs not so much thought my lord send word to the emperor that we are all ready i am even now a weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of ymbercourt", "subset": "none", "task_type": "understanding", "prediction": "it needs not so much thought my lord send word to the emperor that we are all ready i am even now weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of imbocor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm1-none-sp4848-ch029108-sg0006-mc01-stu-clo-dg050.wav", "answer": "the nearer it grows to the time when it will start same as every day you live brings you nearer to nearer the grave well no not that exactly but you can't understand these things", "subset": "none", "task_type": "understanding", "prediction": "the nearer it grows to the time when it will start same as every day you live brings you nearer to nearer the grave well no not that exactly but you cannot understand these things", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm1-none-sp4848-ch101836-sg0026-mc01-stu-clo-dg170.wav", "answer": "the man who was released from the trap persuaded the people that some evil would come out of it and affect the children of the sultan and the children of the vizir then the people became excited and tied the hands of mvoo laana behind him", "subset": "none", "task_type": "understanding", "prediction": "the man who was released from the trap persuaded the people that some evil would come out of it and affect the children of the sultan and the children of the vizier then the people became excited and tied the hands of mvoo laana behind him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4859/Lab41-SRI-VOiCES-rm1-none-sp4859-ch029340-sg0018-mc01-stu-clo-dg080.wav", "answer": "fichte chateaubriand and others the historian evidently decomposes alexander's power into the components talleyrand chateaubriand and the rest but the sum of the components that is the interactions of chateaubriand", "subset": "none", "task_type": "understanding", "prediction": "fichte chateaubriand and others the historian evidently decomposes alexander s power into the components talleyrand chateaubriand and the rest but the sum of the components that is the interactions of chateaubriand", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp4957/Lab41-SRI-VOiCES-rm1-none-sp4957-ch023295-sg0030-mc02-lav-clo-dg120.wav", "answer": "not entirely replied matilda and since it is granted i am careless but she told me her letter concerned none but me to explain perfectly to matilda lady elmwood's letter and that she might perfectly understand upon what terms she was admitted into elmwood castle", "subset": "none", "task_type": "understanding", "prediction": "not entirely replied matilda and since it is granted i am careless but she told me her letter concerned not but me to explain perfectly to matilda lady elmwood's letter and that she might perfectly understand upon what terms she was admitted into elmwood castle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5126/Lab41-SRI-VOiCES-rm1-none-sp5126-ch027504-sg0008-mc02-lav-clo-dg140.wav", "answer": "and falls backards and breaks his neck if he ain't watched whose business was it to have learned me better that i can't rightly say but it seemed it was the business of the government people to gaol me and iron me and flog me was that justice", "subset": "none", "task_type": "understanding", "prediction": "and falls backward and breaks his neck if he ain t watched whose business was it to have learned me better that i can t rightly say but it seemed it was the business of the government people to gall me and iron me and flog me was that justice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 467, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5126/Lab41-SRI-VOiCES-rm1-none-sp5126-ch034483-sg0012-mc02-lav-clo-dg170.wav", "answer": "but nice for the object which she now had in view in the church there was no one but the peasants the servants and their women folk but darya alexandrovna saw or fancied she saw", "subset": "none", "task_type": "understanding", "prediction": "but nice for the object which he now had in view in the church there was no one but the peasants the servants and their women folk but darya alexandrovna saw or fancied she saw", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 468, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm1-none-sp5154-ch006174-sg0005-mc01-stu-clo-dg180.wav", "answer": "although they were many she could only play with one at a time and that indeed troubled her a little or live lambs that were not all wool or the sheep dogs which were very friendly with her and the best of playfellows as she thought for she had no human ones to compare them with", "subset": "none", "task_type": "understanding", "prediction": "although there were many she could only play with one at a time and that indeed troubled her a little or live lambs that were not all wool or the sheep dogs which were very friendly with her and the best of playfellows as she thought for she had no human ones to compare them with", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 469, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm1-none-sp5154-ch006174-sg0028-mc01-stu-clo-dg100.wav", "answer": "was not so terrible or dangerous as the wrathful one the conceited one however was sometimes very angry and then her anger was more spiteful than the other's and again the wrathful one was often very conceited too", "subset": "none", "task_type": "understanding", "prediction": "was not so terrible or dangerous as the wrathful one the conceited one however was sometimes very angry and then her anger was more spiteful than the others and again the wrathful one was often very conceited too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 470, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm1-none-sp5154-ch026559-sg0010-mc02-lav-clo-dg080.wav", "answer": "when the little boy was rubbing his eyes to get the dirt out of them the monkey made a sudden dash out of the cave and escaped to the tree tops when the man returned the little boy did not dare to tell him that the monkey had escaped the man waited and waited and waited", "subset": "none", "task_type": "understanding", "prediction": "when the little boy was rubbing his eyes to get the dirt out of them the monkey made a sudden dash out of the cave and escaped to the tree tops when the man returned the little boy did not dare to tell him that the monkey had escaped the man waited and waited and waited", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 471, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm1-none-sp5154-ch026559-sg0016-mc02-lav-clo-dg160.wav", "answer": "so they let the monkey fill the pot as he liked he put into it some little dry sticks and an empty cocoanut shell then he said o children o children i cannot dance any more it is so hot here in this room the children", "subset": "none", "task_type": "understanding", "prediction": "so they let the monkey fill the pot as he liked he put into it some little dry sticks and an empty cocoanut shell then he said oh children oh children i cannot dance any more it is so hot here in this room the children", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 472, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5157/Lab41-SRI-VOiCES-rm1-none-sp5157-ch047238-sg0003-mc02-lav-clo-dg170.wav", "answer": "which should join you as soon as the weather would permit at present indeed it is not very encouraging for row boats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry", "subset": "none", "task_type": "understanding", "prediction": "would should join you as soon as the weather would permit at present indeed it is not very encouraging for rowboats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 473, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm1-none-sp5189-ch037999-sg0001-mc01-stu-clo-dg030.wav", "answer": "for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries to the trip east together with minute instructions as to the journey itself selecting a proper school", "subset": "none", "task_type": "understanding", "prediction": "for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries of the trip east together with minute instructions as to the journey itself selecting a proper school", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 474, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5386/Lab41-SRI-VOiCES-rm1-none-sp5386-ch004145-sg0012-mc02-lav-clo-dg110.wav", "answer": "should do our utmost to extirpate slavery from the land for my own part i shall do all i can when the redeemer was about to ascend to the bosom of the father and resume the glory which he had with him before the world was he promised his disciples that the power of the holy ghost should come upon them", "subset": "none", "task_type": "understanding", "prediction": "should do our utmost to extirpate slavery from the land for my own part i shall do all i can when the redeemer was about to ascend to the bosom of the father and resume the glory which he had with him before the world was he promised his disciples that the power of the holy ghost should come upon them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 475, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm1-none-sp5401-ch039508-sg0007-mc01-stu-clo-dg150.wav", "answer": "and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly play a very important part which will be more strongly altered", "subset": "none", "task_type": "understanding", "prediction": "and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly played a very important part which will be more strongly altered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 476, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm1-none-sp5456-ch062014-sg0000-mc02-lav-clo-dg180.wav", "answer": "the woman who married an owl by anne virginia culbertson when the children got home from the nutting expedition and had eaten supper they sat around discontentedly wishing every few minutes that their mother had returned i wish mamma would come back", "subset": "none", "task_type": "understanding", "prediction": "the woman who married an owl by ann virginia culbertson when the children got home from the nutting expedition and had eaten supper they sat around discontentedly wishing every few minutes that their mother had returned i wish mamma would come back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 477, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm1-none-sp5635-ch044582-sg0022-mc01-stu-clo-dg080.wav", "answer": "such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration", "subset": "none", "task_type": "understanding", "prediction": "such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 478, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm1-none-sp5717-ch061421-sg0010-mc01-stu-clo-dg150.wav", "answer": "as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and you'll forget there was no answer billy and you'll forget bertram's voice was insistent reproachful", "subset": "none", "task_type": "understanding", "prediction": "as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and youll forget there was no answer billy and youll forget bertram's voice was insistent reproachful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 479, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm1-none-sp5717-ch100145-sg0019-mc02-lav-clo-dg030.wav", "answer": "that is the problem of the adityan mastership they are your slaves we have neither the intention nor the right to free them but let me remind you that slavery is specifically prohibited by the imperial constitution", "subset": "none", "task_type": "understanding", "prediction": "that is the problem of the addykin mastership they are your slaves we have neither the intention nor the right to free them but let me remind you that slavery is specifically prohibited by the imperial constitution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 480, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5740/Lab41-SRI-VOiCES-rm1-none-sp5740-ch097610-sg0039-mc02-lav-clo-dg160.wav", "answer": "for a christmas present pretty little fido said kitty taking the soft curly creature in her arms i think it's the best present in the world and to morrow is to be real christmas because you are home papa and we'll eat the turkey said harry", "subset": "none", "task_type": "understanding", "prediction": "for a christmas present pretty little fido said kitty taking the soft curly creature in her arms i think it is the best present in the world and to morrow is to be real christmas because you are home papa and we will eat the turkey said harry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 481, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5789/Lab41-SRI-VOiCES-rm1-none-sp5789-ch057158-sg0008-mc01-stu-clo-dg080.wav", "answer": "and missus masters had more than once said that that kind of thing must be all over meaning that mary was to drop her intimacy with high born people that were of no real use and then there was mister twentyman and his suit", "subset": "none", "task_type": "understanding", "prediction": "and mrs masters had more than once said that that kind of thing must be all over meaning that mary was to drop her intimacy with high born people that were of no real use and then there was mr twentyman and his suit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 482, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5802/Lab41-SRI-VOiCES-rm1-none-sp5802-ch076043-sg0024-mc02-lav-clo-dg150.wav", "answer": "he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burthen without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great gnomon of silbury", "subset": "none", "task_type": "understanding", "prediction": "he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burden without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great knoll of silbury", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 483, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm1-none-sp5868-ch066166-sg0027-mc01-stu-clo-dg120.wav", "answer": "according to his own account he must have been shipwrecked at least twice a year ever since his birth he had served under decatur when that gallant officer peppered the algerines and made them promise not to sell their prisoners of war into slavery he had worked a gun at the bombardment of vera cruz in the mexican war", "subset": "none", "task_type": "understanding", "prediction": "according to his own account he must have been shipwrecked at least twice a year ever since his birth he had served under decatur when that gallant officer peppered the algerines and made them promise not to sell their prisoners of war into slavery he had worked a gun at the bombardment of vera cruz in the mexican war", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 484, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp6099/Lab41-SRI-VOiCES-rm1-none-sp6099-ch069550-sg0029-mc01-stu-clo-dg170.wav", "answer": "there was jimmu tenno the first real emperor his hair was done in a curious fashion and his dress was of a wonderful brocade while his hands clasped two fierce looking swords", "subset": "none", "task_type": "understanding", "prediction": "there was jiboutenno the first real emperor his hair was done in a curious fashion and his dress was of a wonderful brocade while his hands clasped two fierce looking swords", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 485, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm1-none-sp6147-ch034605-sg0025-mc01-stu-clo-dg020.wav", "answer": "to whom it was said he had sold his sister miss churchill bolingbroke was in his meridian and richelieu in his dawn gallantry found its convenience in a certain medley of ranks men were equalized by the same vices as they were later on perhaps by the same ideas", "subset": "none", "task_type": "understanding", "prediction": "to whom it was said he had sold his sister miss churchill bolingbroke was in his meridian and richelieu in his dawn gallantry found its convenience in a certain medley of ranks men were equalized by the same vices as they were later on perhaps by the same ideas", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 486, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm1-none-sp6241-ch066616-sg0011-mc02-lav-clo-dg010.wav", "answer": "consequently both mother and father began their education at the post they were sent to the factor's school and two winters were passed in port arthur that they might have the advantage of thoroughly equipped schools", "subset": "none", "task_type": "understanding", "prediction": "consequently both mother and father began their education at the post they were sent to the factor school and two winters were passed in port arthur that they might have the advantage of thoroughly equipped schools", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 487, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6319/Lab41-SRI-VOiCES-rm1-none-sp6319-ch275224-sg0005-mc02-lav-clo-dg130.wav", "answer": "still the rose tree stood out that there must be some great advantages in a gardener's care for she could not pretend to be ignorant of her own superiority to all her wild relations in the woods", "subset": "none", "task_type": "understanding", "prediction": "still the rose tree stood out that there must be some great advantages in a gardener s care for she could not pretend to be ignorant of her own superiority to all her wild relations in the woods", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 488, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm1-none-sp6385-ch034655-sg0022-mc01-stu-clo-dg170.wav", "answer": "representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners", "subset": "none", "task_type": "understanding", "prediction": "representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 489, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm1-none-sp6395-ch087997-sg0045-mc02-lav-clo-dg090.wav", "answer": "but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive", "subset": "none", "task_type": "understanding", "prediction": "but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 490, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm1-none-sp6395-ch087997-sg0046-mc01-stu-clo-dg000.wav", "answer": "upon the whole i have always considered him both in his lifetime and since his death as approaching as nearly to the idea of a perfectly wise and virtuous man as perhaps the nature of human frailty will permit i ever am dear sir", "subset": "none", "task_type": "understanding", "prediction": "upon the whole i have always considered him both in his lifetime and since his death as approaching as nearly to the idea of a perfectly wise and virtuous man as perhaps the nature of human frailty will permit i ever am dear sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 491, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm1-none-sp6415-ch111615-sg0011-mc02-lav-clo-dg170.wav", "answer": "came very near ending as a complete cynic though in what f p a would call his lastline he managed to wriggle into a more hopeful mood the first valuable discovery that the colyumist is likely to make is that all minds are very much the same", "subset": "none", "task_type": "understanding", "prediction": "came very near ending as a complete cynic though in what fpa would call his last line he managed to wriggle into a more hopeful mood the first valuable discovery that the columnists is likely to make is that all minds are very much the same", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 492, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm1-none-sp6415-ch116629-sg0007-mc01-stu-clo-dg060.wav", "answer": "come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to", "subset": "none", "task_type": "understanding", "prediction": "come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 493, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm1-none-sp6454-ch093938-sg0018-mc02-lav-clo-dg000.wav", "answer": "two hundred feet therefore brought me to the edge of the town and i wheeled my pony and rode down behind the rear of the buildings in turning i looked back and saw half a dozen mounted men already in pursuit", "subset": "none", "task_type": "understanding", "prediction": "two hundred feet therefore brought me to the edge of the town and i wheeled my pony and rode down behind the rear of the buildings in turning i looked back and saw half a dozen mounted men already in pursuit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 494, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm1-none-sp6454-ch107462-sg0008-mc02-lav-clo-dg140.wav", "answer": "and setting the whisky bottle betwixt his customer and himself with a nod which said help yourself he would lean forward with the soft indulgent grin of the human man of the world and begin now", "subset": "none", "task_type": "understanding", "prediction": "and setting the whiskey bottle betwixt his customer and himself with a nod which said help yourself he would lean forward with the soft indulgent grin of the human man of the world and begin now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 495, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm1-none-sp6454-ch107462-sg0013-mc02-lav-clo-dg120.wav", "answer": "deasey would make reply but twas from a certain person whom perhaps we need not name then the whiskey bottle would move forward like a pawn in chess and the next soothing words would be", "subset": "none", "task_type": "understanding", "prediction": "d c would make reply but twas from a certain person whom perhaps we need not name then the whiskey bottle would move forward like a pawn in chess and the next soothing words would be", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 496, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm1-none-sp6519-ch231834-sg0033-mc01-stu-clo-dg080.wav", "answer": "tossing her head and gliding towards the door it ain't for me to say what i think i am the last person in the world to meddle with what don't concern me that i am and thus ending the conversation miss greeb vanished with significant look and pursed up lips", "subset": "none", "task_type": "understanding", "prediction": "tossing her head and gliding toward the door it ain't for me to say what i think i am the last person in the world to meddle with what don't concern me that i am and thus ending the conversation miss screeb vanished with significant look and pursed up lips", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 497, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm1-none-sp6544-ch067863-sg0023-mc02-lav-clo-dg110.wav", "answer": "and aunt connie rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with missus carleton a little while before supper and told her of what uncle peter had said that ships from the north were on the way to the aid of fort sumter", "subset": "none", "task_type": "understanding", "prediction": "and aunt conny rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with mrs carlton a little while before supper and told her of what uncle peter had said that ships from the north were on their way to the aid of fort sumter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 498, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm1-none-sp6544-ch231862-sg0011-mc01-stu-clo-dg020.wav", "answer": "and as link was the moving spirit in the matter his vanity was sufficiently gratified as to make him quite amiable we've got him this time mister denzil he said with enthusiasm you and i and a couple of policemen will go down to that house in geneva square by the front sir by the front", "subset": "none", "task_type": "understanding", "prediction": "and as link was the moving spirit in the matter his vanity was sufficiently gratified as to make him quite amiable we have got him this time mr denzil he said with enthusiasm you and i and a couple of policemen will go down to that house in geneva square by the front sir by the front", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 499, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6696/Lab41-SRI-VOiCES-rm1-none-sp6696-ch068773-sg0018-mc01-stu-clo-dg070.wav", "answer": "he was not yet thoroughly rested but night was approaching and he reflected that he could obtain all the sleep that he needed then so greatly refreshed and in a quieter mood than he had been for days the young man dressed and entered the hall to find his way downstairs", "subset": "none", "task_type": "understanding", "prediction": "he was not yet thoroughly rested but night was approaching and he reflected that he could obtain all the sleep that he needed then so greatly refreshed and in a quieter mood than he had been for days the young man dressed and entered the hall to find his way downstairs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 500, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-none-sp6895-ch092805-sg0034-mc01-stu-clo-dg020.wav", "answer": "but cling to their cities hem as a child to the mother's gown not so e rushmore coglan with the whole world for his my meditations were interrupted by a tremendous noise and conflict in another part of the cafe i saw above the heads of the seated patrons", "subset": "none", "task_type": "understanding", "prediction": "but cling to their citys hem as a child to the mothers gown not so e rushmore coblen with the whole world for his my meditations were interrupted by a tremendous noise and conflict in another part of the cafe i saw above the heads of the seated patrons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 501, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm1-none-sp7000-ch083708-sg0020-mc01-stu-clo-dg130.wav", "answer": "he drew one out and threw it up to me my second ball was a colourable imitation of my first only this time it was wide to leg to long leg mister benyon sent it flying put down tom benyon another six he cried i do like your bowling mister", "subset": "none", "task_type": "understanding", "prediction": "he drew one out and threw it up to me my second ball was a colourable imitation of my first only this time it was wide to leg to long leg mr benyon sent it flying put down tom benyon another six he cried i do like your bowling mister", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 502, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm1-none-sp7148-ch007763-sg0001-mc02-lav-clo-dg130.wav", "answer": "it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing", "subset": "none", "task_type": "understanding", "prediction": "it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 503, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7247/Lab41-SRI-VOiCES-rm1-none-sp7247-ch077778-sg0026-mc02-lav-clo-dg050.wav", "answer": "the awful pain that was gradually gnawing away at his vitals seemed to lose its poignancy in the face of the greater suffering and physical relief was instant as the musician proceeded the internal disorder yielded gradually to the external and finally passed away", "subset": "none", "task_type": "understanding", "prediction": "the awful pain that was gradually gnawing away at his vitals seemed to lose its poignancy in the face of the greater suffering and physical relief was instant as the musician proceeded the internal disorder yielded gradually to the external and finally passed away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 504, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7247/Lab41-SRI-VOiCES-rm1-none-sp7247-ch094108-sg0022-mc02-lav-clo-dg020.wav", "answer": "while upon the left bank surmounting a high rock strewn beach is the dilapidated frame house of a west virginia cracker through whose garden patch the line takes its way unobserved and unthought of by pigs chickens and children which in hopeless promiscuity swarm the interstate premises", "subset": "none", "task_type": "understanding", "prediction": "while upon the left bank surrounding a high rock strewn beach is the dilapidated frame house of a west virginia cracker through whose garden patch the line takes its way unobserved and unthought of by pigs chickens and children which in hopeless promiscuity swarm the interstate premises", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 505, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7264/Lab41-SRI-VOiCES-rm1-none-sp7264-ch092310-sg0003-mc01-stu-clo-dg140.wav", "answer": "where a great daily paper is concerned he was compelled then to respect his advertisers as his paymasters to that extent therefore his power of giving true news and of printing sound opinion was limited even though his own inclinations should lean towards such news and such opinion", "subset": "none", "task_type": "understanding", "prediction": "where a great daily paper is concerned he was compelled then to respect his advertisers as his paymasters to that extent therefore his power of giving true news and of printing sound opinion was limited even though his own inclinations should lean towards such news and such opinion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 506, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm1-none-sp7278-ch091083-sg0018-mc01-stu-clo-dg120.wav", "answer": "as a publisher but the prize that he had set out to win was to own the public ledger the opportunity came in december eighteen sixty four but his paper was losing money his friends advised against taking such a burden he would surely fail", "subset": "none", "task_type": "understanding", "prediction": "as a publisher but the prize that he had set out to win was to own the public ledger the opportunity came in december eighteen sixty four but his paper was losing money his friends advised against taking such a burden he would surely fail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 507, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm1-none-sp7278-ch104730-sg0026-mc01-stu-clo-dg060.wav", "answer": "as then made up the house of representatives wore hardly even upon the iron temper and inflexible disposition of mister adams the most insignificant error of conduct in me at this time he writes in april", "subset": "none", "task_type": "understanding", "prediction": "as then made up the house of representatives were hardly even upon the iron temper and inflexible disposition of mr. ames the most insignificant error of conduct in may at this time he writes in april", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 508, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm1-none-sp7278-ch104730-sg0039-mc01-stu-clo-dg090.wav", "answer": "i said that in another part of the capitol it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence' here a loud cry of order order burst forth in which the speaker yelled the loudest", "subset": "none", "task_type": "understanding", "prediction": "i said that in another part of the capitol it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence here a loud cry of order order burst forth in which the speaker yelled the loudest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 509, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm1-none-sp7278-ch246956-sg0032-mc01-stu-clo-dg110.wav", "answer": "let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves", "subset": "none", "task_type": "understanding", "prediction": "let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 510, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7517/Lab41-SRI-VOiCES-rm1-none-sp7517-ch100442-sg0005-mc01-stu-clo-dg110.wav", "answer": "we grocers only put the currants out for show and so that we may run our fingers through them luxuriously when business is slack i have a good line in shortbreads madam if i can find the box", "subset": "none", "task_type": "understanding", "prediction": "we grocers only put the currants out for show and so that we may run our fingers through them luxuriously when business is slack i have a good line in shortbreads madam if i can find the box", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 511, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm1-none-sp7850-ch111771-sg0007-mc01-stu-clo-dg160.wav", "answer": "time wore away and on the ninth of april eighteen sixty five grant captured the confederate army under lee thus virtually ending the war", "subset": "none", "task_type": "understanding", "prediction": "time wore away and on the ninth of april eighteen sixty five grant captured the confederate army under lee thus virtually ending the war", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 512, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm1-none-sp7850-ch286674-sg0005-mc01-stu-clo-dg140.wav", "answer": "they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies", "subset": "none", "task_type": "understanding", "prediction": "They did not breathe it into their mouths or through gills. But took it in through some openings in the back part of their bodies.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 513, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm1-none-sp7850-ch286674-sg0005-mc02-lav-clo-dg140.wav", "answer": "they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies", "subset": "none", "task_type": "understanding", "prediction": "they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 514, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7867/Lab41-SRI-VOiCES-rm1-none-sp7867-ch275218-sg0001-mc01-stu-clo-dg150.wav", "answer": "when the gulf of mexico rolled its warm and shallow waters as far north as escanaba and eau claire in fact an immensely long time ago there lived somewhere in oconto county wisconsin a little jelly fish", "subset": "none", "task_type": "understanding", "prediction": "When the Gulf of Mexico rolled its warm and shallow waters as far north as Escanaba and Eau Claire, in fact. An immensely long time ago, there lived somewhere in Oconto County, Wisconsin, a little jellyfish.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 515, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm1-none-sp7868-ch110705-sg0018-mc02-lav-clo-dg040.wav", "answer": "something like that of a kettle on the boil gluck looked out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment", "subset": "none", "task_type": "understanding", "prediction": "something like that of a kettle on the boil luck was out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 516, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm1-none-sp7881-ch105574-sg0015-mc01-stu-clo-dg040.wav", "answer": "yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us", "subset": "none", "task_type": "understanding", "prediction": "yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 517, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm1-none-sp7881-ch109662-sg0027-mc02-lav-clo-dg180.wav", "answer": "and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet", "subset": "none", "task_type": "understanding", "prediction": "and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 518, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm1-none-sp7932-ch110056-sg0022-mc01-stu-clo-dg180.wav", "answer": "and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by", "subset": "none", "task_type": "understanding", "prediction": "and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 519, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-none-sp7976-ch105575-sg0013-mc02-lav-clo-dg010.wav", "answer": "when morning came the firing opened and for all that day the battle raged fiercely at the left and center left we getting the worst of it too", "subset": "none", "task_type": "understanding", "prediction": "when morning came the firing opened and for all that day the battle raged fiercely at the left and center left we getting the worst of it too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 520, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-none-sp7976-ch105575-sg0029-mc01-stu-clo-dg050.wav", "answer": "a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war", "subset": "none", "task_type": "understanding", "prediction": "a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 521, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-none-sp7976-ch110124-sg0006-mc02-lav-clo-dg110.wav", "answer": "it's surely a terrible storm outside said the merchant's eldest daughter as the wind rattled the tiles of the roof and the rain beat in torrents against the doors and windows", "subset": "none", "task_type": "understanding", "prediction": "it is surely a terrible storm outside said the merchant s eldest daughter as the wind rattled the tiles of the roof and the rain beat in torrents against the doors and windows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 522, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm1-none-sp7976-ch110523-sg0010-mc02-lav-clo-dg110.wav", "answer": "hansel thought the roof tasted very nice and so he tore off a great piece while grethel broke a large round pane out of the window and sat down quite contentedly", "subset": "none", "task_type": "understanding", "prediction": "hansel thought the roof tasted very nice and so he tore off a great piece while grethel broke a large round pane out of the window and sat down quite contentedly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 523, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-none-sp7981-ch112057-sg0025-mc02-lav-clo-dg170.wav", "answer": "madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money", "subset": "none", "task_type": "understanding", "prediction": "madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 524, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-none-sp7981-ch112057-sg0035-mc01-stu-clo-dg030.wav", "answer": "this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns taking marseilles as his first station here where the conditions were perhaps even worse than in paris", "subset": "none", "task_type": "understanding", "prediction": "this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns picking marseilles as his first station here where the conditions were perhaps even worse than in paris", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 525, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-none-sp7981-ch112058-sg0024-mc01-stu-clo-dg070.wav", "answer": "and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries", "subset": "none", "task_type": "understanding", "prediction": "and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 526, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8051/Lab41-SRI-VOiCES-rm1-none-sp8051-ch118101-sg0035-mc02-lav-clo-dg090.wav", "answer": "rather smart black well made and well calculated for a canadian he was prompted to escape purely from the desire to be free he fled from a very insulting man by the name of edward schriner from the neighborhood of sairsville mills", "subset": "none", "task_type": "understanding", "prediction": "rather smart black well made and well calculated for a canadian he was prompted to escape purely from the desire to be free he fled from a very insulting man by the name of edward schreiner from the neighborhood of sairsville mills", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 527, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8057/Lab41-SRI-VOiCES-rm1-none-sp8057-ch284428-sg0034-mc02-lav-clo-dg010.wav", "answer": "and the only thing i object to is electing the boolooroo for only three hundred years it ought to be for life my successor has already been elected but he can't reign for a hundred years to come i think three hundred years is plenty long enough", "subset": "none", "task_type": "understanding", "prediction": "and the only thing i object to is electing the boolooroo for only three hundred years it ought to be for life my successor has already been elected but he can t reign for a hundred years to come i think three hundred years is plenty long enough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 528, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm1-none-sp8108-ch274318-sg0046-mc02-lav-clo-dg130.wav", "answer": "and uttering little soft sounds of affection in his throat the doctor lit the candle and brought it over he saw the collie lying on its side against the wall it was utterly exhausted and foam still hung about its jaws its tail and eyes responded to the sound of its name", "subset": "none", "task_type": "understanding", "prediction": "and uttering little soft sounds of affection in his throat the doctor lit the candle and brought it over he saw the collie lying on its side against the wall it was utterly exhausted and foam still hung about its jaws its tail and eyes responded to the sound of its name", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 529, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm1-none-sp8108-ch280359-sg0017-mc01-stu-clo-dg010.wav", "answer": "and drag out whatever living thing they could find there it was done as he desired thor held one end of the net and all the rest of the gods drew the other through the water when they pulled it up the first time however it was empty and they would have gone away disappointed", "subset": "none", "task_type": "understanding", "prediction": "and drag out whatever living thing they could find there it was done as he desired thor held one end of the net and all the rest of the gods drew the other through the water when they pulled it up the first time however it was empty and they would have gone away disappointed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 530, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8118/Lab41-SRI-VOiCES-rm1-none-sp8118-ch114469-sg0032-mc01-stu-clo-dg160.wav", "answer": "a mile or two further and in the swish of the storm he heard hoofbeats again looking forth from the bushes he saw another line of horsemen but now they were going in the direction of pope's army dick recognized these figures shapeless as he might appear on his horse that was colonel winchester", "subset": "none", "task_type": "understanding", "prediction": "a mile or two further and in the swish of the storm he heard hoof beats again looking forth from the bushes he saw another line of horsemen but now they were going in the direction of polk s army dick recognized these figures shapeless as he might appear on his horse that was colonel winchester", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 531, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8222/Lab41-SRI-VOiCES-rm1-none-sp8222-ch274380-sg0015-mc02-lav-clo-dg060.wav", "answer": "whether if unlimited power were intrusted to the parliament during so long a period it would not be easy for them to frame the subsequent bill in the manner most agreeable to themselves and keep forever possession of the sword as well as of every article of civil power and jurisdiction", "subset": "none", "task_type": "understanding", "prediction": "whether if unlimited power were intrusted to the parliament during so long a period it would not be easy for them to frame the subsequent bill in the manner most agreeable to themselves and keep for ever possession of the sword as well as of every article of civil power and jurisdiction", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 532, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm1-none-sp8225-ch274375-sg0001-mc02-lav-clo-dg110.wav", "answer": "those parliamentary leaders it must be owned who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity", "subset": "none", "task_type": "understanding", "prediction": "those parliamentary leaders it must be owned who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 533, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-none-sp8425-ch246962-sg0025-mc02-lav-clo-dg130.wav", "answer": "yea all grand discovery for things must be foreseen ere they can be realized apprehended ere they be comprehended this much he could say for himself and no more that he was ready to lay down his life for the mere chance", "subset": "none", "task_type": "understanding", "prediction": "yea all grand discovery for things must be foreseen ere they can be realized apprehended ere they be comprehended this much he could say for himself and no more that he was ready to lay down his life for the mere chance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 534, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-none-sp8425-ch287387-sg0003-mc01-stu-clo-dg130.wav", "answer": "and ancient art a museum for his dreaming spirit already as a child as a boy he had felt that passion for antiquity developing he learnt how to rummage through the stocks of old jewish dealers", "subset": "none", "task_type": "understanding", "prediction": "and ancient art a museum for his dreaming spirit already as a child as a boy he had felt that passion for antiquity developing he learnt how to rummage through the stocks of old jewish dealers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 535, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-none-sp8425-ch292520-sg0014-mc01-stu-clo-dg120.wav", "answer": "and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wave and solemnly sway to the wash and swell of our passing", "subset": "none", "task_type": "understanding", "prediction": "and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wave and solemnly sway to the wash and swell of our passing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 536, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/none/sp_6241-8713/sp8605/Lab41-SRI-VOiCES-rm1-none-sp8605-ch291172-sg0007-mc02-lav-clo-dg150.wav", "answer": "and when deprived of their kittens feel very wretched indeed under these circumstances they will nurse and suckle almost any creature cats rearing dogs a cat of mine a few years ago suckled and reared a beautiful pomeranian dog", "subset": "none", "task_type": "understanding", "prediction": "and when deprived of their kittens feel very wretched indeed under these circumstances they will nurse and suckle almost any creature cats rearing dogs a cat of mine a few years ago suckled and reared a beautiful pomeranian dog", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 537, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-tele-sp0112-ch123216-sg0003-mc02-lav-clo-dg030.wav", "answer": "said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can't said anne sorrowfully", "subset": "tele", "task_type": "understanding", "prediction": "said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can t said anne sorrowfully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 538, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-tele-sp0112-ch123216-sg0022-mc02-lav-clo-dg000.wav", "answer": "gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written him a nice little note of thanks but she had never worn the trinket tonight she fastened it about her white throat with a dreamy smile she and phil walked to redmond together", "subset": "tele", "task_type": "understanding", "prediction": "gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written him a nice little note of thanks but she had never worn the trinket tonight she fastened it around her white throat with a dreamy smile she and phil walked to redmond together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 539, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-tele-sp0122-ch121730-sg0019-mc02-lav-clo-dg150.wav", "answer": "probably because the peach is largely a skin and stony at heart pearl a small round product manufactured by an oyster bought by a lobster and worn by a butterfly penitent from pen meaning to write and", "subset": "tele", "task_type": "understanding", "prediction": "probably because the peach is largely skin and stony at heart pearl a small round product manufactured by an oyster bought by a lobster and worn by a butterfly penitent from pen meaning to write and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 540, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-tele-sp0122-ch121734-sg0016-mc02-lav-clo-dg160.wav", "answer": "yellow fever a passion for reading the hearst newspapers yolk the legacy of the hen and the burden of its lay yoke the inheritance of the hen pecked and the burden of the married", "subset": "tele", "task_type": "understanding", "prediction": "yellow fever a passion for reading the hearst newspapers yolk the legacy of the hen and the burden of its lay yoke the inheritance of the hen pecked and the burden of the merry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 541, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-tele-sp0122-ch129752-sg0022-mc01-stu-clo-dg180.wav", "answer": "sift three and one half cups of flour with five level teaspoons of baking powder and add to the first mixture stir well and fold in the beaten whites of two eggs beat in layer cake tins and spread the following mixture between", "subset": "tele", "task_type": "understanding", "prediction": "sift three and one half cups of flour with five level teaspoons of baking powder and add to the first mixture stir well and fold in the beaten whites of two eggs beat in layer cake tins and spread the following mixture between", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 542, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0159/Lab41-SRI-VOiCES-rm1-tele-sp0159-ch121891-sg0012-mc01-stu-clo-dg040.wav", "answer": "for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature", "subset": "tele", "task_type": "understanding", "prediction": "for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 543, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0174/Lab41-SRI-VOiCES-rm1-tele-sp0174-ch050561-sg0008-mc01-stu-clo-dg160.wav", "answer": "but if i play you a roundel lady get me a gift from the emperor's daughter her finger ring for my finger bring though she's pledged a thousand leagues over the water lady lady my fair lady o my rose white lady", "subset": "tele", "task_type": "understanding", "prediction": "but if i play you around o lady get me a gift from the emperor s daughter her finger ring for my finger bring though she s pledged a thousand leagues over the water lady lady my fair lady o my rose white lady", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 544, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0174/Lab41-SRI-VOiCES-rm1-tele-sp0174-ch168635-sg0018-mc02-lav-clo-dg040.wav", "answer": "he had returned to prison this time for having done right he had quaffed fresh bitterness disgust and lassitude were overpowering him even the memory of the bishop probably suffered a temporary eclipse though sure to reappear later on luminous and triumphant but after all that sacred memory was growing dim", "subset": "tele", "task_type": "understanding", "prediction": "he had returned to prison this time for having done right he had quaffed fresh vigor this disgust and lassitude were overpowering him even the memory of the bishop probably suffered a temporary eclipse so sure to reappear later on luminous since triumphant but after all that sacred memory was growing dim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 545, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm1-tele-sp0204-ch148920-sg0022-mc01-stu-clo-dg070.wav", "answer": "interested them for a while and ben had to be almost pulled away from the dingy old portrait of van der werf the town hall as well as the egyptian museum is on the breedstraat the longest and finest street in leyden", "subset": "tele", "task_type": "understanding", "prediction": "interested them for a while and ben had to be almost pulled away from the dingy old portrait of van der kroos the town hall as well as the egyptian museum is on the breedstraat the longest and finest street in leyden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 546, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm1-tele-sp0204-ch287139-sg0033-mc02-lav-clo-dg050.wav", "answer": "so it was no great matter for surprise that when they got down to the hole the lugger was already under way though still close in he hailed her a voice replied telling him to keep out of the moonlight or he would get some lead in him", "subset": "tele", "task_type": "understanding", "prediction": "so it was no great matter for surprise that when they got down to the hole the lugger was already under way though still close in he hailed her a voice replied telling him to keep out of the moonlight or he would get some lead in him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 547, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm1-tele-sp0204-ch287139-sg0037-mc01-stu-clo-dg070.wav", "answer": "and to tell you the truth i should like to get it put in safety to be sure boy quite right said he i'll take it if you like i thought perhaps doctor livesey i began perfectly right", "subset": "tele", "task_type": "understanding", "prediction": "and to tell you the truth i should like to get it put in safety to be sure boy quite right said he i ll take it if you like i thought perhaps dr livesey i began perfectly right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 548, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-tele-sp0205-ch159056-sg0036-mc02-lav-clo-dg000.wav", "answer": "when the squire handed him his first commission and there it is to day and on it are the verses ending this spot so sacred will forever claim a proud alliance with its hero's name wolfe was at last an officer", "subset": "tele", "task_type": "understanding", "prediction": "when the squire handed him his first commission and there it is to day and on it are the verses ending this spot so sacred will forever claim a proud alliance with its hero s name wolfe was at last an officer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 549, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm1-tele-sp0209-ch004731-sg0000-mc02-lav-clo-dg160.wav", "answer": "from his fortune his house and his daughter he could command the visits of his own little circle in a great measure as he liked he had not much intercourse with any families beyond that circle his horror of late hours and large dinner parties", "subset": "tele", "task_type": "understanding", "prediction": "From his fortune, his house and his daughter, he could command the visits of his own little circle in great measure as he liked. He had not much intercourse with any families beyond that circle. His horror of late hours and large dinner parties.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 550, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0224/Lab41-SRI-VOiCES-rm1-tele-sp0224-ch129790-sg0054-mc01-stu-clo-dg080.wav", "answer": "we desire to make for the dutch settlement of curacao as straightly as possible will you pledge me your honour if i release you upon parole that you will navigate us thither if so we will release you and your surviving men upon arrival there", "subset": "tele", "task_type": "understanding", "prediction": "we desire to make for the dutch settlement of curacoa as straightly as possible will you pledge me your honor if i release you upon parole that you will navigate us thither if so we will release you and your surviving men upon arrival there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 551, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch122625-sg0006-mc02-lav-clo-dg070.wav", "answer": "men too often confound them they should not be confounded appearance should not be mistaken for truth narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of christ", "subset": "tele", "task_type": "understanding", "prediction": "Men too often confound them. They should not be confounded. Appearance should not be mistaken for truth. Narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of Christ.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 552, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch122625-sg0009-mc02-lav-clo-dg090.wav", "answer": "as the very master of that working corps who would restore to rectitude the warped system of things because i think no commentator on his writings has yet found the comparison that suits him the terms which rightly characterise his talent", "subset": "tele", "task_type": "understanding", "prediction": "as the very master of that working corps who would restore to rectitude the warped system of things because i think no commentator on his writings has yet found the comparison that suits him the terms which rightly characterize his talent", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 553, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch122626-sg0030-mc01-stu-clo-dg170.wav", "answer": "did she say that to me did you hear her eliza and georgiana won't i tell mama but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing", "subset": "tele", "task_type": "understanding", "prediction": "did she say that to me do you hear her eliza and georgiana wont i tell mamma but first he ran headlong at me i felt him grasp my hair and my shoulder he it closed with a desperate thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 554, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch126842-sg0018-mc01-stu-clo-dg000.wav", "answer": "after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cecily desperately drawing lots is wickeder that fighting said dan", "subset": "tele", "task_type": "understanding", "prediction": "after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cicely desperately drawing lots is wickeder than fighting said dan", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 555, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch126842-sg0034-mc01-stu-clo-dg110.wav", "answer": "uncle alec walked around the corner of the granary with cecily behind him he was not angry there was a quizzical look in his eyes but he took the combatants by their shirt collars and dragged them apart this stops right here boys", "subset": "tele", "task_type": "understanding", "prediction": "uncle alec walked around the corner of the granary with cicely behind him he was not angry there was a quizzical look in his eyes but he took the combatants by their shirt collars and dragged them apart this stops right here boys", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 556, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm1-tele-sp0459-ch127522-sg0016-mc02-lav-clo-dg020.wav", "answer": "the rocks of the spy glass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain", "subset": "tele", "task_type": "understanding", "prediction": "the rocks of the spyglass reechoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 557, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm1-tele-sp0472-ch129983-sg0005-mc02-lav-clo-dg070.wav", "answer": "with almost every other man in the world it would be an alarming prospect but edward's affection and constancy nothing can deprive me of i know that conviction must be every thing to you and he is undoubtedly supported by the same trust in your's", "subset": "tele", "task_type": "understanding", "prediction": "with almost every other man in the world it would be an alarming prospect but edward's affection and constancy nothing can deprive me of i know that conviction must be everything to you and he is undoubtedly supported by the same trust in yours", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 558, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm1-tele-sp0479-ch107479-sg0005-mc01-stu-clo-dg150.wav", "answer": "and in order to quiet all suspicion of my real status in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and", "subset": "tele", "task_type": "understanding", "prediction": "and in order to quiet all suspicion of my real status in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 559, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm1-tele-sp0479-ch134717-sg0035-mc02-lav-clo-dg010.wav", "answer": "as i held as if by their hands my comrades in the night and the voice of my spirit tallied the song of the bird come lovely and soothing death undulate round the world serenely arriving arriving in the day in the night to all to each", "subset": "tele", "task_type": "understanding", "prediction": "as i held as if by their hands my comrades in the night and the voice of my spirit tallied the song of the girl to come lovely and soothing death undulate round the world serenely arriving arriving in the day and the night to all to each", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 560, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-tele-sp0480-ch123176-sg0039-mc02-lav-clo-dg150.wav", "answer": "pat a tea spoonful in a pot that will hold about two cups and pour boiling water on it let it set by the fire to draw five or ten minutes rye mush this is a nourishing and light diet for the sick", "subset": "tele", "task_type": "understanding", "prediction": "Pat a tea spoonful in a pot that will hold about 2 cups and pour boiling water on it. Let it set by the fire to draw 5 or 10 minutes. Rye mush. This is a nourishing and light diet for the sick.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 561, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm1-tele-sp0480-ch126336-sg0017-mc01-stu-clo-dg170.wav", "answer": "and broke all her goods into a thousand pieces then she began to cry and knew not what to do ah what will become of me said she what will my husband say", "subset": "tele", "task_type": "understanding", "prediction": "and broke all her goods into a thousand pieces then she began to cry and knew not what to do ah what will become of me said she what will my husband say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 562, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm1-tele-sp0492-ch131890-sg0031-mc02-lav-clo-dg140.wav", "answer": "on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the roadstead and was soon once more on the indian ocean", "subset": "tele", "task_type": "understanding", "prediction": "on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the rogestead and was soon once more on the indian ocean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 563, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm1-tele-sp0510-ch130101-sg0012-mc02-lav-clo-dg180.wav", "answer": "the youth cried out to him hysterically i ll take care of yeh jim i ll take care of yeh i swear t gawd i will sure will yeh henry the tall soldier beseeched yes yes i tell yeh i'll take care of yeh jim protested the youth", "subset": "tele", "task_type": "understanding", "prediction": "the youth cried out to him hysterically i ll take care of you jim i ll take care of you i swear to god i will sure will you henry the tall soldier besieged yes yes i tell you i ll take care of you jim protested the youth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 564, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm1-tele-sp0510-ch130103-sg0027-mc01-stu-clo-dg010.wav", "answer": "as he was at last compelled to pay attention to them his capacity for self hate was multiplied in despair he declared that he was not like those others he now conceded it to be impossible that he should ever become a hero", "subset": "tele", "task_type": "understanding", "prediction": "as he was at last compelled to pay attention to them his capacity for self hate was multiplied in despair he declared that he was not like those others he now conceded it to be impossible that he should ever become a hero", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 565, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm1-tele-sp0510-ch130103-sg0047-mc02-lav-clo-dg180.wav", "answer": "then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled", "subset": "tele", "task_type": "understanding", "prediction": "then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 566, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm1-tele-sp0636-ch123163-sg0006-mc02-lav-clo-dg160.wav", "answer": "fresh shad is better to be sprinkled with salt an hour before it is put to broil put a plate over the top to keep the heat in in broiling shad or other fresh fish you should dust them with corn meal before you put them down to bake a fresh shad", "subset": "tele", "task_type": "understanding", "prediction": "fresh shad is better to be sprinkled with salt an hour before it is put to broil put a plate over the top to keep the heat in in broiling shad or other fresh fish you should dust them with corn meal before you put them down to bake a fresh shad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 567, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm1-tele-sp0637-ch127597-sg0016-mc01-stu-clo-dg050.wav", "answer": "it was also by night alone that i could hope to accomplish my object and then only by adopting the utmost precaution the entrance to marheyo's habitation was through a low narrow opening in its wicker work front", "subset": "tele", "task_type": "understanding", "prediction": "it was also by night alone that i could hope to accomplish my object and then only by adopting the utmost precaution the entrance to marheyo s habitation was through a low narrow opening in its wickerwork front", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 568, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0652/Lab41-SRI-VOiCES-rm1-tele-sp0652-ch130737-sg0009-mc02-lav-clo-dg120.wav", "answer": "lacrima christi a still wine of excellent flavor and bouquet", "subset": "tele", "task_type": "understanding", "prediction": "macrimacristi a still wine of excellent flavour and bouquet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 569, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0770/Lab41-SRI-VOiCES-rm1-tele-sp0770-ch134592-sg0013-mc01-stu-clo-dg120.wav", "answer": "there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcotes and aclands and many other newer names that she had forgotten", "subset": "tele", "task_type": "understanding", "prediction": "there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcoats and athlens and many other newer names that she had forgotten", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 570, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp0882/Lab41-SRI-VOiCES-rm1-tele-sp0882-ch123268-sg0033-mc01-stu-clo-dg090.wav", "answer": "this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour", "subset": "tele", "task_type": "understanding", "prediction": "this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 571, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm1-tele-sp1050-ch134120-sg0029-mc02-lav-clo-dg150.wav", "answer": "missus peterkin wishes to go to drive one morning missus peterkin was feeling very tired as she had been having a great many things to think of and she said to mister peterkin i believe i shall take a ride this morning", "subset": "tele", "task_type": "understanding", "prediction": "mrs peterkin wishes to go to drive one morning mrs peterkin was feeling very tired as she had been having a great many things to think of and she said to mr peterkin i believe i shall take a ride this morning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 572, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp1052/Lab41-SRI-VOiCES-rm1-tele-sp1052-ch139307-sg0007-mc02-lav-clo-dg010.wav", "answer": "about fourteen i don't understand very probably not our social order will probably seem very complex to you to tell you the truth i don't understand it myself very clearly nobody does you will perhaps bye and bye", "subset": "tele", "task_type": "understanding", "prediction": "About 14. I don't understand. Very probably not. Our social order will probably seem very complex to you. To tell you the truth, I don't understand it myself very clearly. Nobody does. You will, perhaps, by and by.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 573, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm1-tele-sp1066-ch005330-sg0006-mc01-stu-clo-dg110.wav", "answer": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune", "subset": "tele", "task_type": "understanding", "prediction": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 574, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm1-tele-sp1066-ch103481-sg0026-mc01-stu-clo-dg080.wav", "answer": "each huddled dumbly to each but eyes could not lift from the sea only hands touched in the dawn he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream", "subset": "tele", "task_type": "understanding", "prediction": "each huddled dumbly to each but eyes could not lift from the sea only hands touched in the dawn he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 575, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm1-tele-sp1116-ch132851-sg0021-mc01-stu-clo-dg020.wav", "answer": "while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her", "subset": "tele", "task_type": "understanding", "prediction": "while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 576, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp1121/Lab41-SRI-VOiCES-rm1-tele-sp1121-ch176698-sg0035-mc02-lav-clo-dg010.wav", "answer": "smiling and placid as though in all this great world there were no such thing to be found as an auctioneer's hammer and presently they swung into the drive and drew up in the courtyard and there was adam", "subset": "tele", "task_type": "understanding", "prediction": "smiling and placid as though in all this great world there were no such thing to be found as an auctioneer s hammer and presently they swung to the drive and drew up in the courtyard and there was adam", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 577, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm1-tele-sp1160-ch139730-sg0002-mc02-lav-clo-dg020.wav", "answer": "a present of a glass tube with some account of the use of it in making such experiments i eagerly seized the opportunity of repeating what i had seen at boston", "subset": "tele", "task_type": "understanding", "prediction": "a present of a glass tube with some account of the use of it in making such experiments i eagerly seized the opportunity of repeating what i had seen at boston", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 578, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1212/Lab41-SRI-VOiCES-rm1-tele-sp1212-ch014653-sg0000-mc02-lav-clo-dg070.wav", "answer": "he started as though he couldn't believe his eyes when he saw me the lord hath delivered mine enemy into my hand shone in his evil little face why mister tausig i cried before he could get his breath how odd to", "subset": "tele", "task_type": "understanding", "prediction": "he started as though he couldn believe his eyes when he saw me the lord hath delivered mine enemy into my hand shown in his evil little face why mr tausig i cried before he could get his breath how odd", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 579, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1212/Lab41-SRI-VOiCES-rm1-tele-sp1212-ch075242-sg0029-mc02-lav-clo-dg160.wav", "answer": "and several people were talking all at once he made bold to open the door and step in what he saw you already know as by this time the children had started to bathe zip the doctor was told to go right upstairs", "subset": "tele", "task_type": "understanding", "prediction": "and several people were talking all at once he made bold to open the door and step in what he saw you already know as by this time the children had started to bang zip the doctor was told to go right upstairs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 580, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1212/Lab41-SRI-VOiCES-rm1-tele-sp1212-ch185485-sg0025-mc01-stu-clo-dg130.wav", "answer": "and introduced myself without ceremony i told him my experiences he was delighted i next heartily indorsed every word stated in his advertisements he was not surprised for he knew the effects of his pills were such as i described", "subset": "tele", "task_type": "understanding", "prediction": "and introduced myself without ceremony i told him my experiences he was delighted i next heartily endorsed every word stated in his advertisements he was not surprised for he knew the effects of his pills were such as i described", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 581, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1259/Lab41-SRI-VOiCES-rm1-tele-sp1259-ch137770-sg0029-mc01-stu-clo-dg030.wav", "answer": "no sooner did i sign the agreement than she got engaged poor little girl she was so keen on it all and wouldn't even wait to make proper inquiries about the shooting afraid it would get snapped up just like all of your sex well no harm's done", "subset": "tele", "task_type": "understanding", "prediction": "no sooner did i sign the agreement than she got engaged poor little girl she was so keen on it all and wouldn't even wait to make proper inquiries about the shooting afraid it would get snapped up just like all of your sex well no harm done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 582, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm1-tele-sp1335-ch160602-sg0013-mc01-stu-clo-dg160.wav", "answer": "deep in its quiet mossy bed sheltered from sun and shower the grateful worm spun its winter tomb in the shadow of the flower and clover guarded well its rest till autumn's leaves were sere", "subset": "tele", "task_type": "understanding", "prediction": "deep in its quiet mossy bed sheltered from sun and shower the grateful worm spun its winter tomb in the shadow of the flower and clover guarded well its rest till autumn leaves were sere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 583, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm1-tele-sp1392-ch128226-sg0016-mc02-lav-clo-dg090.wav", "answer": "they now fancied themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport to their body and this earth gentle is zarathustra to the sickly verily", "subset": "tele", "task_type": "understanding", "prediction": "they now fancied themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport to their bodies and this earth gentle is zarathustra to the sickly verily", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 584, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm1-tele-sp1392-ch140654-sg0011-mc02-lav-clo-dg000.wav", "answer": "and does not give himself to meditation forgetting the real aim of life and grasping at pleasure will in time envy him", "subset": "tele", "task_type": "understanding", "prediction": "and does not give himself to meditation forgetting the real aim of life and grasping at pleasure will in time envy him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 585, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1417/Lab41-SRI-VOiCES-rm1-tele-sp1417-ch001536-sg0003-mc02-lav-clo-dg010.wav", "answer": "ha i am observed he murmured the words broke the spell instantly the five visitors burst simultaneously into speech are you the acting editor of this paper i wish to have a word with you sir mister windsor i presume", "subset": "tele", "task_type": "understanding", "prediction": "ha i am observed he had murmured the words broke the spell instantly the five visitors burst simultaneously into speech are you the acting editor of this paper i wish to have a word with you sir mr windsor i presume", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 586, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1425/Lab41-SRI-VOiCES-rm1-tele-sp1425-ch139291-sg0034-mc01-stu-clo-dg120.wav", "answer": "the songs of the slave represent the sorrows of his heart and he is relieved by them only as an aching heart is relieved by its tears at least such is my experience i have often sung to drown my sorrow but seldom to express my happiness", "subset": "tele", "task_type": "understanding", "prediction": "the songs of the slave represent the sorrows of his heart and he is relieved by them only as an aching heart is relieved by its tears at least such is my experience i have often sung to drown my sorrow but seldom to express my happiness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 587, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1425/Lab41-SRI-VOiCES-rm1-tele-sp1425-ch139297-sg0013-mc02-lav-clo-dg170.wav", "answer": "would be our inevitable condition a condition held by us all in the utmost horror and dread i suffered more anxiety than most of my fellow slaves i had known what it was to be kindly treated they had known nothing of the kind", "subset": "tele", "task_type": "understanding", "prediction": "would be our inevitable condition a condition held by us all in the utmost horror and dread i suffered more anxiety than most of my fellow slaves i had known what it was to be kindly treated they had known nothing of the kind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 588, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-tele-sp1472-ch142848-sg0009-mc02-lav-clo-dg160.wav", "answer": "the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves one selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation", "subset": "tele", "task_type": "understanding", "prediction": "the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves when selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 589, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm1-tele-sp1472-ch285314-sg0011-mc01-stu-clo-dg040.wav", "answer": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up", "subset": "tele", "task_type": "understanding", "prediction": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i s'pose he is there now very good i ll hunt him up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 590, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1536/Lab41-SRI-VOiCES-rm1-tele-sp1536-ch137608-sg0013-mc01-stu-clo-dg020.wav", "answer": "i have not deserved that ye should show me this strangeness and i had weened that i should have right good cheer with you and unto my power i have deserved thank and well i am sure i have bought your love with part of the best blood within my body fair courteous knight said dame lionesse", "subset": "tele", "task_type": "understanding", "prediction": "i have not deserved that ye should show me this strangeness and i had weened that i should have reft good cheer with you and unto my power i have deserved thank and well i am sure i have bought your love with part of the best blood within my body fair courteous knight said dame lyones", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 591, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1536/Lab41-SRI-VOiCES-rm1-tele-sp1536-ch138488-sg0025-mc02-lav-clo-dg090.wav", "answer": "two generations of public men have since laboured with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment", "subset": "tele", "task_type": "understanding", "prediction": "two generations of public men have since labored with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 592, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1737/Lab41-SRI-VOiCES-rm1-tele-sp1737-ch142396-sg0008-mc01-stu-clo-dg130.wav", "answer": "there was an exception in the curate who would receive unblenching the information that the meadow beyond the orchard was a prairie studded with herds of buffalo which it was our delight moccasined and tomahawked to ride down with those whoops that announce the scenting of blood", "subset": "tele", "task_type": "understanding", "prediction": "there was an exception in the curate who would receive unblenchingly information that the meadow beyond the orchard was a prairie studded with herds of buffalo which it was our delight moccasined and tomahawked to ride down with those whoops that announced the scenting of blood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 593, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1737/Lab41-SRI-VOiCES-rm1-tele-sp1737-ch146161-sg0002-mc02-lav-clo-dg150.wav", "answer": "knit two together knit two fourth row seamed making one at the beginning fifth row make one knit two knit two together knit one make one", "subset": "tele", "task_type": "understanding", "prediction": "knit two together knit two fourth row seam making one at the beginning fifth row make one knit two knit two together knit one make one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 594, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm1-tele-sp1867-ch154071-sg0043-mc01-stu-clo-dg170.wav", "answer": "you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i'll smash every bone in his ugly head", "subset": "tele", "task_type": "understanding", "prediction": "you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i ll smash every bone in his ugly head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 595, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm1-tele-sp1867-ch154075-sg0018-mc02-lav-clo-dg130.wav", "answer": "as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance", "subset": "tele", "task_type": "understanding", "prediction": "as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 596, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm1-tele-sp1874-ch089898-sg0022-mc01-stu-clo-dg050.wav", "answer": "this being heard the pope and all the rest said that a man of so great authority who had held the office of a bishop for nearly forty years ought by no means to be condemned but being altogether cleared of the faults laid to his charge should return home with honour", "subset": "tele", "task_type": "understanding", "prediction": "this being heard the pope and all the rest said that a man of so great authority who had held the office of a bishop for nearly forty years ought by no means to be condemned but being altogether cleared of the false late to his charge should return home with honour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 597, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm1-tele-sp1874-ch089898-sg0027-mc01-stu-clo-dg050.wav", "answer": "but be ready for i will return and visit you at the end of four years and when you come into your country you shall recover the greater part of the possessions that have been taken from you and shall end your days in peace and quiet the bishop accordingly recovered", "subset": "tele", "task_type": "understanding", "prediction": "but be ready for i will return and visit you at the end of four years and when you come into your country you shall recover the greater part of the possessions that have been taken from you and shall end your days in peace and quiet the bishop accordingly recovered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 598, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm1-tele-sp1874-ch165702-sg0020-mc02-lav-clo-dg150.wav", "answer": "april fourteenth assassinated in ford's theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett", "subset": "tele", "task_type": "understanding", "prediction": "april fourteenth assassinated in ford s theater washington by a mad actor wilkes booth april nineteenth body laid in state at washington april twenty sixth booth slain in resisting arrest by sergeant boscan corbett", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 599, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1926/Lab41-SRI-VOiCES-rm1-tele-sp1926-ch143879-sg0015-mc01-stu-clo-dg010.wav", "answer": "missus ludlow sacrificed as i say to paris yet had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations", "subset": "tele", "task_type": "understanding", "prediction": "mrs ludlow sacrificed as i say to paris yet had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 600, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm1-tele-sp1961-ch149738-sg0036-mc01-stu-clo-dg100.wav", "answer": "some of his specimens were so rare that she was unfamiliar with them and with the flower book between them they knelt studying the different varieties she wandered the length of the cathedral aisle with him and it was at her suggestion that he lighted his altar with a row of flaming foxfire", "subset": "tele", "task_type": "understanding", "prediction": "some of his specimens were so rare that she was unfamiliar with them and with the flower book between them they knelt studying the different varieties she wandered the length of the cathedral aisle with him and it was at her suggestion that he lighted his altar with a row of flaming foxfire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 601, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm1-tele-sp1970-ch028415-sg0006-mc01-stu-clo-dg050.wav", "answer": "some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another", "subset": "tele", "task_type": "understanding", "prediction": "some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 602, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm1-tele-sp2012-ch139358-sg0007-mc01-stu-clo-dg080.wav", "answer": "what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words", "subset": "tele", "task_type": "understanding", "prediction": "what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 603, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2060/Lab41-SRI-VOiCES-rm1-tele-sp2060-ch150855-sg0011-mc02-lav-clo-dg130.wav", "answer": "there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie's bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy", "subset": "tele", "task_type": "understanding", "prediction": "there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie s bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 604, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2074/Lab41-SRI-VOiCES-rm1-tele-sp2074-ch147193-sg0033-mc02-lav-clo-dg120.wav", "answer": "but theseus wept shall i leave you o my mother but she answered weep not for me that which is fated must be and grief is easy to those who do nought but grieve", "subset": "tele", "task_type": "understanding", "prediction": "but theseus wept shall i leave you o my mother but she answered weep not for me that which is fated must be and grief is easy to those who do not but grieve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 605, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2074/Lab41-SRI-VOiCES-rm1-tele-sp2074-ch149033-sg0017-mc01-stu-clo-dg040.wav", "answer": "as soon as he is alone he rushes to ethel's door i say said mister salteena excitedly i have had some tea in bed sometimes visitors came to the house nothing much in that to us but how consummately this child must have studied them", "subset": "tele", "task_type": "understanding", "prediction": "as soon as he is alone he rushes to ethel s door i say said mr salteena excitedly i have had some tea in bed sometimes visitors came to the house nothing much in that to us but how consummately this child must have studied em", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 606, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm1-tele-sp2110-ch161100-sg0030-mc02-lav-clo-dg110.wav", "answer": "he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died", "subset": "tele", "task_type": "understanding", "prediction": "he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 607, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm1-tele-sp2156-ch025563-sg0014-mc01-stu-clo-dg180.wav", "answer": "there is not nor play neither snapped phelan i've got to go out and chase up a drunk or throw a faint or git run over or somethin desperate to square mesilf with the captain i'm an hour overdue at the station", "subset": "tele", "task_type": "understanding", "prediction": "there is not nor play neither snapped fayler i ve got to go out and chase up a drunk or throw a faint or get run over or something desperate to square meself with the captain i m an hour overdue at the station", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 608, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2294/Lab41-SRI-VOiCES-rm1-tele-sp2294-ch161707-sg0011-mc02-lav-clo-dg100.wav", "answer": "and the next instant there was a thud and a bump a bump again a half stifled cry and then a hurried vision of some black carpeting that flapped and shook as though all the winds of eblis were in its folds and then apparently disgorged from its inmost recesses a little man", "subset": "tele", "task_type": "understanding", "prediction": "and the next instant there was a thud and a bump a bump again a half stifled cry and then a hurried vision of some black carpeting that flapped and shook as though all the winds of eddlys were in its folds and then apparently disgorged from its innermost recesses a little man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 609, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm1-tele-sp2412-ch153947-sg0010-mc01-stu-clo-dg150.wav", "answer": "i see from my second preface that i took the book to messrs chapman and hall may first eighteen seventy one and on their rejection of it under the advice of one who has attained the highest rank among living writers i let it sleep till i took it to mister trubner early in eighteen seventy two", "subset": "tele", "task_type": "understanding", "prediction": "i see from my second preface that i took the book to messrs chapman and hall may first eighteen seventy one and on their rejection of it under the advice of one who has attained the highest rank among living writers i let it sleep till i took it to mr trubner early in eighteen seventy two", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 610, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm1-tele-sp2412-ch153954-sg0015-mc01-stu-clo-dg040.wav", "answer": "suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome", "subset": "tele", "task_type": "understanding", "prediction": "suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 611, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2532/Lab41-SRI-VOiCES-rm1-tele-sp2532-ch157475-sg0007-mc01-stu-clo-dg120.wav", "answer": "and there is nothing but a hole they must have scooted right into the hole henny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down there penny dolls he called there was no answer", "subset": "tele", "task_type": "understanding", "prediction": "and there is nothing but a hole they must have scooted right into the hole penny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down there penny dolls he called there was no answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 612, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2532/Lab41-SRI-VOiCES-rm1-tele-sp2532-ch157475-sg0007-mc02-lav-clo-dg120.wav", "answer": "and there is nothing but a hole they must have scooted right into the hole henny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down there penny dolls he called there was no answer", "subset": "tele", "task_type": "understanding", "prediction": "and there was nothing but a hole they must have scooted right into the hole penny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down in there penny dolls he called there was no answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 613, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2673/Lab41-SRI-VOiCES-rm1-tele-sp2673-ch156474-sg0006-mc02-lav-clo-dg030.wav", "answer": "but before it could be executed circumstances intervened effectually to thwart that object while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress", "subset": "tele", "task_type": "understanding", "prediction": "but before it could be executed circumstances intervened effectually to thwart that object where you going while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 614, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2673/Lab41-SRI-VOiCES-rm1-tele-sp2673-ch162130-sg0022-mc02-lav-clo-dg150.wav", "answer": "and both temperate drinking and total abstinence correspondingly increasing it is unnecessary to appeal to statistics the familiar experience of every man whose memory runs back twenty or forty or sixty years", "subset": "tele", "task_type": "understanding", "prediction": "in both temperate drinking and total abstinence correspondingly increasing it is unnecessary to appeal to statistics the familiar experience of every man whose memory runs back twenty or forty or sixty years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 615, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2691/Lab41-SRI-VOiCES-rm1-tele-sp2691-ch156745-sg0027-mc01-stu-clo-dg160.wav", "answer": "merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances", "subset": "tele", "task_type": "understanding", "prediction": "merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground francis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 616, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm1-tele-sp2758-ch086588-sg0029-mc02-lav-clo-dg030.wav", "answer": "fifteen sixty two has collected a great number of classic anecdotes to illustrate this saying recapitulation those who desire to become artists can greatly facilitate their work", "subset": "tele", "task_type": "understanding", "prediction": "fifteen sixty two has collected a great number of classic anecdotes to illustrate this saying recapitulation those who desire to become artists can greatly facilitate their work", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 617, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm1-tele-sp2764-ch036619-sg0024-mc01-stu-clo-dg000.wav", "answer": "and each man now wanted only to catch up on his eating and sleeping to make up for the time he had so stupidly sacrificed with typical human fickleness they jumped from one extreme to the other inevitably the most enthusiastic supporters of the undertaking became its most energetic opponents", "subset": "tele", "task_type": "understanding", "prediction": "and each man now wanted only to catch up on his eating and sleeping to make up for the time he had so stupidly sacrificed with typical human fickleness they jumped from one extreme to the other inevitably the most enthusiastic supporters of the undertaking became its most energetic opponents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 618, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm1-tele-sp2803-ch154320-sg0003-mc01-stu-clo-dg060.wav", "answer": "their minds were so distracted at this change of route as to be quite unhinged", "subset": "tele", "task_type": "understanding", "prediction": "their minds were so distracted at this change of route as to be quite unhinged", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 619, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm1-tele-sp2803-ch161169-sg0005-mc02-lav-clo-dg110.wav", "answer": "walk down the sloping foot path now and be careful to keep out of the way of the little cars that are coming and going on each side of you loaded on one side and empty on the other and seeming to run up and down by themselves", "subset": "tele", "task_type": "understanding", "prediction": "walk down the sloping footpath now and be careful to keep out of the way of the little cars that are coming and going on each side of you loaded on one side and empty on the other and seeming to run up and down by themselves", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 620, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm1-tele-sp2911-ch007601-sg0022-mc02-lav-clo-dg010.wav", "answer": "in approaching him had stalked with his black shadow before him and enveloped the victim and it was the mournful influence of the unperceived shadow that caused him to feel although he neither saw nor heard to feel the presence of my head within the room", "subset": "tele", "task_type": "understanding", "prediction": "in approaching him had stalked with his black shadow before him and enveloped the victim and it was the mournful influence of the unprescient shadow that caused him to feel although he neither saw nor heard to feel the presence of my hand within the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 621, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm1-tele-sp2911-ch007601-sg0045-mc01-stu-clo-dg110.wav", "answer": "and became more distinct i talked more freely to get rid of the feeling but it continued and gained definiteness until at length i found that the noise was not within my ears no doubt i now grew very pale but i talked more fluently", "subset": "tele", "task_type": "understanding", "prediction": "and became more distinct i talked more freely to get rid of the feeling but it continued and gained definiteness until at length i found that the noise was not within my ears no doubt i now grew very pale but i talked more fluently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 622, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm1-tele-sp2911-ch012359-sg0019-mc01-stu-clo-dg100.wav", "answer": "for either port or stout is put into counterfeit cheshire cheese to make up for the richness it lacks while some combinations of cheeses and wines may turn out palatable we prefer taking ours straight when something more fiery is needed", "subset": "tele", "task_type": "understanding", "prediction": "for either port or stout is put into counterfeit cheshire cheese to make up for the richness it lacks while some combinations of cheeses and wines may turn out palatable we prefer taking ours straight when something more fiery is needed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 623, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm1-tele-sp3368-ch170950-sg0014-mc02-lav-clo-dg020.wav", "answer": "why he said are they not capable of defending themselves no i said not if we were right in the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success", "subset": "tele", "task_type": "understanding", "prediction": "why you said are they not capable of defending themselves no i said now if we were right that the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 624, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm1-tele-sp3368-ch170951-sg0018-mc01-stu-clo-dg110.wav", "answer": "and no good thing is hurtful no indeed and that which is not hurtful hurts not certainly not and that which hurts not does no evil no and can that which does no evil be a cause of evil impossible and the good is advantageous yes", "subset": "tele", "task_type": "understanding", "prediction": "and no good thing is hurtful no indeed and that which is not hurtful hurts not certainly not and that which hurts not does no evil no and can that which does no evil be a cause of evil impossible and the good is advantageous yes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 625, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp3521/Lab41-SRI-VOiCES-rm1-tele-sp3521-ch007591-sg0013-mc02-lav-clo-dg010.wav", "answer": "there was no light of any kind emanating from lamp or candle within the suite of chambers but in the corridors that followed the suite there stood opposite to each window a heavy tripod bearing a brazier of fire that projected its rays through the tinted glass and so glaringly illumined the room", "subset": "tele", "task_type": "understanding", "prediction": "there was no light of any kind emanating from lamp or candle within the suite of chambers but in the corridors that followed the suite there stood opposite each window a heavy tripod bearing a brazier of fire that projected its rays through the tinted glass and so glaringly illumined the room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 626, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_1212-3521/sp3521/Lab41-SRI-VOiCES-rm1-tele-sp3521-ch012715-sg0020-mc02-lav-clo-dg030.wav", "answer": "boil a small handful of hops in a couple of quarts of water when the strength is obtained from them strain the liquor put it back on the fire take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour stir it into the liquor when it boils", "subset": "tele", "task_type": "understanding", "prediction": "Boil a small handful of hops in a couple of quarts of water. When the strength is obtained from them. Strain the liquor. Put it back on the fire. Take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour. Stir it into the liquor, when it boils.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 627, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm1-tele-sp3549-ch008890-sg0023-mc02-lav-clo-dg080.wav", "answer": "his daughter being a few steps in advance it is hardly the line of life for a girl like grace after what she's been accustomed to i didn't foresee that in sending her to boarding school and letting her travel and what not to make her a good bargain for giles", "subset": "tele", "task_type": "understanding", "prediction": "his daughter being a few steps in advance it is hardly the line of life for a girl like grace after what she has been accustomed to i did foresee that in sending her to boarding school and letting her travel and what not to make her a good bargain for giles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 628, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm1-tele-sp3549-ch171171-sg0001-mc01-stu-clo-dg040.wav", "answer": "and so much of the wall as enclosed the city on the west side this wall was spared in order to afford a camp for such as were to lie in garrison as were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified", "subset": "tele", "task_type": "understanding", "prediction": "And so much of the wall as enclosed, the city on the west side, this wall was spared in order to afford a camp for such as were to lie a garrison. As were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 629, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3645/Lab41-SRI-VOiCES-rm1-tele-sp3645-ch077173-sg0036-mc01-stu-clo-dg160.wav", "answer": "and beg to assure you of my devoted services i am madam yours obediently alfonso pinzato editor for a long time the excuse that she would have to make to galva before she could leave the island had been worrying anna", "subset": "tele", "task_type": "understanding", "prediction": "and beg to assure you of my devoted services i am madam yours obediently alphonso pinzato editor for a long time the excuse that she would have to make to galva before she could leave the island had been worrying anna", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 630, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm1-tele-sp3923-ch153309-sg0039-mc01-stu-clo-dg060.wav", "answer": "and manufactures his own concoctions in a house he has rented here on a lonely road some half mile out of town wellgood does the man named wellgood mister grey exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town", "subset": "tele", "task_type": "understanding", "prediction": "and manufactures his own concoctions in a house he has rented here on a lonely road some half mile out of town wellgood does the man named wellgood mr gray exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 631, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3972/Lab41-SRI-VOiCES-rm1-tele-sp3972-ch005791-sg0023-mc02-lav-clo-dg030.wav", "answer": "which must draw much blood on both sides before his royal father's presence can regain what he has lost ah my lord replied wallace is it to be nothing but war have you now a stronghold of any force in all the highlands is not the greater part of the lowlands free", "subset": "tele", "task_type": "understanding", "prediction": "which must draw much blood on both sides before his royal father s presence can regain what he has lost ah my lord replied wallace is it to be nothing but war have you now a stronghold of any force in all the highlands is not the greater part of the lowlands free", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 632, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3972/Lab41-SRI-VOiCES-rm1-tele-sp3972-ch185074-sg0018-mc02-lav-clo-dg150.wav", "answer": "on the spot where he was killed no one can judge of my feelings on seeing this mournful spectacle and what greatly added to my distress was the fact that he had fallen by the murderous hand of his brother i felt my situation unsupportable", "subset": "tele", "task_type": "understanding", "prediction": "on the spot where he was killed no one can judge of my feelings on seeing this mournful spectacle and what greatly added to my distress was the fact that he had fallen by the murderous hand of his brother i felt my situation unsupportable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 633, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3989/Lab41-SRI-VOiCES-rm1-tele-sp3989-ch182389-sg0005-mc02-lav-clo-dg150.wav", "answer": "gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mister rabbit the grandfather a thousand times removed of peter rabbit was always getting into trouble yes sir old mister rabbit was always getting into trouble", "subset": "tele", "task_type": "understanding", "prediction": "gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mr rabbit the grandfather a thousand times removed of peter rabbit was always getting into trouble yes sir old mr rabbit was always getting into trouble", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 634, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3989/Lab41-SRI-VOiCES-rm1-tele-sp3989-ch182389-sg0019-mc02-lav-clo-dg040.wav", "answer": "now in spite of the trouble mister rabbit was forever making for other people by his dreadful curiosity and meddling with other people's affairs all his neighbors had a warm place in their hearts for mister rabbit and they all promised that they would help him", "subset": "tele", "task_type": "understanding", "prediction": "now in spite of the trouble mr rabbit was for ever making for other people by his dreadful curiosity and meddling with other people s affairs all his neighbours held a warm place in their hearts for mr rabbit and they all promised that they would help him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 635, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3989/Lab41-SRI-VOiCES-rm1-tele-sp3989-ch182402-sg0012-mc01-stu-clo-dg010.wav", "answer": "now peter knew that there must be a good story about spotty and his house and you know peter dearly loves a good story so at the very first opportunity the next day he hurried over to the smiling pool to ask grandfather frog about it", "subset": "tele", "task_type": "understanding", "prediction": "now peter knew that there must be a good story about spotty and his house and you know peter dearly loves a good story so at the very first opportunity the next day he hurried over to the smiling pool to ask grandfather frog about it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 636, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp3994/Lab41-SRI-VOiCES-rm1-tele-sp3994-ch011512-sg0017-mc01-stu-clo-dg130.wav", "answer": "the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved", "subset": "tele", "task_type": "understanding", "prediction": "the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 637, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4010/Lab41-SRI-VOiCES-rm1-tele-sp4010-ch010801-sg0011-mc01-stu-clo-dg070.wav", "answer": "and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operations of the spiritual as of the physical world are simply a turning again to the source", "subset": "tele", "task_type": "understanding", "prediction": "and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operation of the spiritual as of the physical world are simply a turning again to the source", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 638, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-tele-sp4014-ch186176-sg0015-mc02-lav-clo-dg120.wav", "answer": "won't do it slim muttered oh yes you will counseled joe shake hands the two of you slim's good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we're square said slim", "subset": "tele", "task_type": "understanding", "prediction": "won t do it slim muttered oh yes you will counseled joe shake hands the two of you slim s good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we re square said slim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 639, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm1-tele-sp4014-ch186176-sg0043-mc01-stu-clo-dg170.wav", "answer": "and made me run a mile in nothing flat added jerry and fought me to a knockout finish later mused joe and nearly smothered me to death spoke the lieutenant and was finally corralled by an irish engineer said slim gone concluded jerry", "subset": "tele", "task_type": "understanding", "prediction": "it made me run a mile nothing flat added jerry and fought me to a knock out finish later used joe and nearly smothered me to death spoke lieutenant and was finally corralled by an irish engineer said slim gone concluded jerry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 640, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4110/Lab41-SRI-VOiCES-rm1-tele-sp4110-ch011535-sg0002-mc01-stu-clo-dg130.wav", "answer": "as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming", "subset": "tele", "task_type": "understanding", "prediction": "as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 641, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4145/Lab41-SRI-VOiCES-rm1-tele-sp4145-ch034497-sg0032-mc02-lav-clo-dg100.wav", "answer": "inevitable he thought things could not go on as before but he said something different it can't go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life", "subset": "tele", "task_type": "understanding", "prediction": "inevitable he thought things could not go on as before but he said something different it can t go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 642, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm1-tele-sp4535-ch279852-sg0000-mc01-stu-clo-dg180.wav", "answer": "captured halt there the command came from behind they whipped about and found themselves facing a raised rifle the man was a civilian tall and lanky he waved the rifle from one to the other where're you going he demanded chattanooga", "subset": "tele", "task_type": "understanding", "prediction": "captured halt there command came from behind they whipped about and found themselves facing a raised rifle the man was a civilian tall and lanky he waved the rifle from one to the other where you going he demanded chattanooga", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 643, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4586/Lab41-SRI-VOiCES-rm1-tele-sp4586-ch061776-sg0022-mc01-stu-clo-dg050.wav", "answer": "nor show any sign of an intention to do so but sate in the saddle stooped forward his eyes turned upon the ground in that vacant gaze which denotes reflection dog gone my cats he drawled out in slow soliloquy", "subset": "tele", "task_type": "understanding", "prediction": "nor show any sign of an intention to do so but sat in the saddle stooped forward his eyes turned upon the ground in that vacant gaze which denotes reflection doggone my cats he drawled out in slow soliloquy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 644, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4586/Lab41-SRI-VOiCES-rm1-tele-sp4586-ch061776-sg0028-mc01-stu-clo-dg030.wav", "answer": "as if fully satisfied on this score he took up his bridle rein muttered some words to his mare and commenced moving off along the edge of the chapparal having advanced about a mile in the direction of the nueces river he abruptly changed his course", "subset": "tele", "task_type": "understanding", "prediction": "as if fully satisfied on the score he took up his bridle rein muttered some words to his mare and commenced moving off along the edge of the chaparral having advanced about a mile in the direction of the neches river he abruptly changed his course", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 645, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4590/Lab41-SRI-VOiCES-rm1-tele-sp4590-ch018005-sg0011-mc02-lav-clo-dg010.wav", "answer": "as i was by this time worn out for want of sleep having spent so many nights on the look out i was just dozing off comfortably when suddenly i felt my arm seized and on looking up saw mahina pointing in the direction of the goats sher", "subset": "tele", "task_type": "understanding", "prediction": "as i was by this time worn out for want of sleep having spent so many nights on the look out i was just dozing off comfortably when suddenly i felt my arm seized and on looking up saw mahina pointing in the direction of the gallops", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 646, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm1-tele-sp4839-ch015304-sg0025-mc01-stu-clo-dg040.wav", "answer": "and raising his eyes he said to lord ludovico my lord i thank you for the courtesy you have done me please god to pay it back to you he was in a fine large court yard then he began to set spurs to his horse the which gave four or five jumps so gayly that it could not be better done", "subset": "tele", "task_type": "understanding", "prediction": "and raising his eyes he said to lord ludovico my lord i thank you for the courtesy you have done me please god to pay it back to you he was in a fine large courtyard then he began to set spurs to his horse the which gave four or five jumps so gayly that it could not be better done", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 647, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm1-tele-sp4839-ch015307-sg0003-mc01-stu-clo-dg050.wav", "answer": "and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at treviso when emperor maximilian's commissioner presented himself in order to take possession of it", "subset": "tele", "task_type": "understanding", "prediction": "and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at trevisa when emperor maximilian s commissioner presented himself in order to take possession of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 648, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp4967/Lab41-SRI-VOiCES-rm1-tele-sp4967-ch028868-sg0016-mc02-lav-clo-dg080.wav", "answer": "i only meant that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for awhile and then repeated his words i think i will go abroad not for long i hope sir", "subset": "tele", "task_type": "understanding", "prediction": "i only bet that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for a while and then repeated his words i think i will go abroad not for long i hope sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 649, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5157/Lab41-SRI-VOiCES-rm1-tele-sp5157-ch047238-sg0003-mc01-stu-clo-dg170.wav", "answer": "which should join you as soon as the weather would permit at present indeed it is not very encouraging for row boats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry", "subset": "tele", "task_type": "understanding", "prediction": "which should join you as soon as the weather would permit at present indeed it is not very encouraging for rowboats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 650, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5338/Lab41-SRI-VOiCES-rm1-tele-sp5338-ch024615-sg0013-mc01-stu-clo-dg000.wav", "answer": "the court was spacious well paved and perfectly clean there being probably another entrance behind the stables for removing the litter", "subset": "tele", "task_type": "understanding", "prediction": "The court was spacious, well paved and perfectly clean there, being probably another entrance behind the stables for removing the litter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 651, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5386/Lab41-SRI-VOiCES-rm1-tele-sp5386-ch004145-sg0009-mc01-stu-clo-dg010.wav", "answer": "her next aim was to vindicate the bible from sustaining the monstrous institution of slavery she said god has created of one blood all the nations of men to dwell on all the face of the earth to claim hold and treat a human being as property is felony against god and man", "subset": "tele", "task_type": "understanding", "prediction": "her next aim was to vindicate the bible from sustaining the monstrous institution of slavery she said god has created of one blood all the nations of men to dwell on all the face of the earth to claim hold and treat a human being as property is felony against god and man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 652, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5400/Lab41-SRI-VOiCES-rm1-tele-sp5400-ch034478-sg0009-mc01-stu-clo-dg090.wav", "answer": "i know all about that but really what you're saying either has no meaning or it has a very wrong meaning how can you think it a matter of no importance whether the peasant whom you love as you assert i never did assert it thought konstantin levin dies without help", "subset": "tele", "task_type": "understanding", "prediction": "i know all about that but really what you are saying either has no meaning or it has a very wrong meaning how can you think it a matter of no importance whether the peasant whom you love as you assert i never did assert it thought konstantin rovain dies without help", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 653, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm1-tele-sp5401-ch039508-sg0004-mc02-lav-clo-dg090.wav", "answer": "thus next to a dike bituminous coal may be baked to coke or anthracite and chalk and limestone to crystalline marble sandstone may be converted into quartzite and shale into argillite a compact massive clay rock", "subset": "tele", "task_type": "understanding", "prediction": "thus next to a dike a tumulus coil may be baked to coke or anthracite and chalk and limestone to crystalline marble sandstone may be converted into quartzite and shale into argillite a compact massive clay rock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 654, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm1-tele-sp5401-ch039508-sg0007-mc01-stu-clo-dg150.wav", "answer": "and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly play a very important part which will be more strongly altered", "subset": "tele", "task_type": "understanding", "prediction": "and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly played a very important part which will be more strongly altered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 655, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm1-tele-sp5401-ch039515-sg0008-mc02-lav-clo-dg010.wav", "answer": "these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood", "subset": "tele", "task_type": "understanding", "prediction": "these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 656, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm1-tele-sp5456-ch058161-sg0009-mc01-stu-clo-dg020.wav", "answer": "his was the rental of half havana and all matanzas and santa anna rich as he was could hardly hold a candle to light the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers", "subset": "tele", "task_type": "understanding", "prediction": "his was the rental of half a van and all matanzas and santa anna rich as he was could hardly hold a candle to like the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 657, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm1-tele-sp5456-ch062014-sg0015-mc02-lav-clo-dg030.wav", "answer": "o o goo coo o o goo coo ez he flewed off inter de darkness here aunt phrony spread her arms like wings and made a swoop half way across the room to the bedside of the startled children an she continued", "subset": "tele", "task_type": "understanding", "prediction": "ubu coo ubu coo as he flew off into the darkness here aunt frony spread her arms like wings and made a swoop half way across the room to the bedside of the startled children and she continued", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 658, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5583/Lab41-SRI-VOiCES-rm1-tele-sp5583-ch041259-sg0033-mc02-lav-clo-dg110.wav", "answer": "laura letter the fifteenth laura in continuation when we arrived at the town where we were to breakfast i was determined to speak with philander and gustavus and to that purpose as soon as i left the carriage", "subset": "tele", "task_type": "understanding", "prediction": "laura letter the fifteenth laura in continuation when we arrived at the town where we were to breakfast i was determined to speak with filander on gustavus and to that purpose as soon as i left the carriage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 659, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm1-tele-sp5635-ch053458-sg0026-mc01-stu-clo-dg040.wav", "answer": "said popopo sternly for he felt the birds were getting the best of the argument the poor milliner's business will be ruined if i do not return you to her shop it seems you are necessary to trim the hats properly it is the fashion for women to wear birds upon their headgear so the poor milliner's wares", "subset": "tele", "task_type": "understanding", "prediction": "said popopo sternly for he felt the birds were getting the best of the argument the poor milliner s business will be ruined if i do not return you to her shop it seems you are necessary to trim the hats properly it is the fashion for women to wear birds upon their headgear so the poor milliner s wares", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 660, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm1-tele-sp5635-ch053458-sg0027-mc01-stu-clo-dg080.wav", "answer": "although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a black bird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion", "subset": "tele", "task_type": "understanding", "prediction": "although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a blackbird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 661, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm1-tele-sp5868-ch055088-sg0015-mc02-lav-clo-dg050.wav", "answer": "and the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth is whirled through europe without gaining a single idea worth crossing the street for", "subset": "tele", "task_type": "understanding", "prediction": "on the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth is whirled through europe without gaining a single idea worth crossing the street for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 662, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm1-tele-sp5935-ch055927-sg0020-mc01-stu-clo-dg140.wav", "answer": "and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps", "subset": "tele", "task_type": "understanding", "prediction": "and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 663, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp6099/Lab41-SRI-VOiCES-rm1-tele-sp6099-ch067860-sg0005-mc02-lav-clo-dg130.wav", "answer": "i believe you are right estralla is a clever little darky and if she started in search of sylvia perhaps she has been able to find her i had not thought of it and mister fulton's voice had a new note of hope", "subset": "tele", "task_type": "understanding", "prediction": "i believe you are right estralla is a clever little darky and if she started in search of sylvia perhaps she has been able to find her i had not thought of it and mr fulton s voice had a new note of hope", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 664, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_3549-6147/sp6099/Lab41-SRI-VOiCES-rm1-tele-sp6099-ch069550-sg0012-mc02-lav-clo-dg160.wav", "answer": "and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful", "subset": "tele", "task_type": "understanding", "prediction": "and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 665, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm1-tele-sp6241-ch061946-sg0023-mc01-stu-clo-dg040.wav", "answer": "accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion", "subset": "tele", "task_type": "understanding", "prediction": "accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 666, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm1-tele-sp6385-ch034655-sg0022-mc01-stu-clo-dg170.wav", "answer": "representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners", "subset": "tele", "task_type": "understanding", "prediction": "representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 667, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm1-tele-sp6385-ch034669-sg0003-mc01-stu-clo-dg160.wav", "answer": "the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to gwynplaine the wolf appeared to him", "subset": "tele", "task_type": "understanding", "prediction": "the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to gwynplaine the wolf appeared to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 668, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm1-tele-sp6385-ch034669-sg0003-mc02-lav-clo-dg160.wav", "answer": "the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to gwynplaine the wolf appeared to him", "subset": "tele", "task_type": "understanding", "prediction": "the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to quinplane the wolf appeared to him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 669, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm1-tele-sp6395-ch084349-sg0006-mc01-stu-clo-dg030.wav", "answer": "and if possible made him a greater idol than before in the eyes of the court at four years of age he is described as of slight but well shaped figure with a broad open forehead finely arched eyebrows and large blue eyes", "subset": "tele", "task_type": "understanding", "prediction": "and if possible made him a greater idol than before in the eyes of the court at four years of age he is described as of slight but well shaped figure with a broad open forehead finely arched eyebrows and large blue eyes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 670, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm1-tele-sp6395-ch084349-sg0009-mc02-lav-clo-dg070.wav", "answer": "the people in their destitute condition could only think of bread and believing the king could command possession of it familiarly styled him the baker so that now seeing the royal family's return they shouted joyously no more poverty", "subset": "tele", "task_type": "understanding", "prediction": "The people in their destitute condition could only think of bread and believing the king could command possession of it. Familiarly styled him, the baker. So that now seeing the royal family's return, they shouted joyously, no more poverty.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 671, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm1-tele-sp6454-ch120342-sg0005-mc02-lav-clo-dg050.wav", "answer": "and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people in the very lowest bolgie being ill natured enough to grieve", "subset": "tele", "task_type": "understanding", "prediction": "and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people and the very lowest fogey being ill natured enough to grieve", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 672, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm1-tele-sp6519-ch231834-sg0034-mc01-stu-clo-dg000.wav", "answer": "which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greeb's very lively imagination yet even though he reduced her communications to bare facts", "subset": "tele", "task_type": "understanding", "prediction": "which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greeb s very lively imagination yet even though he reduced her communications to bare facts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 673, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm1-tele-sp6544-ch071420-sg0000-mc02-lav-clo-dg130.wav", "answer": "chapter twenty nine a glass of poison margaret could do nothing but stare at the man before her he was heavy set and powerful and wont to having his own way mister styles she began but he put his hand over her mouth you are sick", "subset": "tele", "task_type": "understanding", "prediction": "chapter twenty nine a glass of poison margaret could do nothing but stare at the man before her he was heavy set and powerful in want to having his own way mr styles she began but he put his hand over her mouth you are sick", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 674, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6696/Lab41-SRI-VOiCES-rm1-tele-sp6696-ch073296-sg0005-mc01-stu-clo-dg020.wav", "answer": "it makes me envious and miserable i who have never seen it south end is prohibited if you please my dear isabella i have not heard you make one inquiry after mister perry yet and he never forgets you oh good mister perry how is he sir", "subset": "tele", "task_type": "understanding", "prediction": "it makes me envious and miserable i who have never seen it south end is prohibited if you please my dear isabella i have not heard you make one inquiry after mr carey yet and he never forgets you oh good mr payne how is he sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 675, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6848/Lab41-SRI-VOiCES-rm1-tele-sp6848-ch252323-sg0009-mc02-lav-clo-dg040.wav", "answer": "broke in craggs i was brigaded with arentschild's hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you're right", "subset": "tele", "task_type": "understanding", "prediction": "broken crags i was brigaded with arnoldscharz hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you are right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 676, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-tele-sp6895-ch092806-sg0009-mc02-lav-clo-dg180.wav", "answer": "there was something in her manner that warned mister mc caskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware pig's face is it said missus mc caskey and hurled a stewpan full of bacon and turnips at her lord", "subset": "tele", "task_type": "understanding", "prediction": "there was something in her manner that warned mr maccaskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware big space is it said mrs maccaskey and hurled a stewpan full of bacon and turnips at her lord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 677, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm1-tele-sp6895-ch096175-sg0004-mc02-lav-clo-dg160.wav", "answer": "and the bones of your mother and you can feel the bones in your fingers your fingers will become mere bone after you are dead as die you must those bones which you see around you are of course the bones of the men of whom we often speak", "subset": "tele", "task_type": "understanding", "prediction": "and the bones of your mother and you can feel the bones in your fingers your fingers will become mere bone after you are dead as die you must those bones which you see around you are of course the bones of the men of whom we often speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 678, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm1-tele-sp6965-ch277898-sg0011-mc01-stu-clo-dg030.wav", "answer": "was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs", "subset": "tele", "task_type": "understanding", "prediction": "was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 679, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm1-tele-sp7000-ch083708-sg0021-mc01-stu-clo-dg120.wav", "answer": "i've got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy", "subset": "tele", "task_type": "understanding", "prediction": "i have got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 680, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm1-tele-sp7095-ch088483-sg0019-mc01-stu-clo-dg000.wav", "answer": "that during the middle ages the priests and monks kept up the torch of learning that being the only literate people they brought back the study of the classics historically speaking this is about the most impudent statement that one could imagine", "subset": "tele", "task_type": "understanding", "prediction": "that during the middle ages the priests and monks kept up the torch of learning that being the only literate people they brought back the study of the classics historically speaking this is about the most impudent statement that one could imagine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 681, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm1-tele-sp7095-ch088483-sg0020-mc01-stu-clo-dg100.wav", "answer": "later learned to read and write from the arabs jews and greeks exiled from constantinople after fourteen fifty three it is because they wanted to keep the power in their hands the people they did not permit to learn either to read or write", "subset": "tele", "task_type": "understanding", "prediction": "later learned to read and write from the arabs jews and greeks exiled from constantinople after fourteen fifty three it is because they wanted to keep the power in their hands the people they did not permit to learn either to read or write", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 682, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7247/Lab41-SRI-VOiCES-rm1-tele-sp7247-ch094108-sg0021-mc02-lav-clo-dg000.wav", "answer": "below which is a shelving stone beach of generous width two high iron towers supporting the cable of a current ferry add dignity to the twin settlements a stone monument six feet high just observable through the willows on the right shore marks the boundary", "subset": "tele", "task_type": "understanding", "prediction": "below which is a shelving stone beach of generous width two high iron towers supporting the cable of a current ferry add dignity to the twin settlements a stone monument six feet high just observable through the willows on the right shore marks the boundary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 683, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7264/Lab41-SRI-VOiCES-rm1-tele-sp7264-ch092310-sg0007-mc01-stu-clo-dg100.wav", "answer": "the proprietor was always at the choice of publishing matter which did not affect him and saving his fortune or refusing it and jeopardizing his fortune he chose the former course in the second place there was an even more serious development advertisement", "subset": "tele", "task_type": "understanding", "prediction": "the proprietor was always at the choice of publishing matter which did not affect him and saving his fortune or refusing it and jeopardizing his fortune he chose the former course in the second place there was an even more serious development advertisement", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 684, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7264/Lab41-SRI-VOiCES-rm1-tele-sp7264-ch092316-sg0034-mc02-lav-clo-dg140.wav", "answer": "but not a cabinet minister that could not pass an examination in the life vices vulnerability fortune investments and favours of the owner the change was rapidly admitted it came quickly but thoroughly at last like most rapid developments it exceeded itself", "subset": "tele", "task_type": "understanding", "prediction": "but not a cabinet minister that could not pass an examination in the life vices vulnerability fortune investments and favours of the owner the change was rapidly admitted it came quickly but thoroughly at last like most rapid developments it exceeded itself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 685, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm1-tele-sp7278-ch104730-sg0026-mc02-lav-clo-dg060.wav", "answer": "as then made up the house of representatives wore hardly even upon the iron temper and inflexible disposition of mister adams the most insignificant error of conduct in me at this time he writes in april", "subset": "tele", "task_type": "understanding", "prediction": "as then made up the house of representatives were hardly even upon the iron temper and inflexible disposition of mr adams the most insignificant error of conduct in me at this time he writes in april", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 686, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094522-sg0005-mc02-lav-clo-dg040.wav", "answer": "naturally received an accession of power during the minority and as it was now becoming a scene of business the members chose for the first time a speaker who might preserve order in their debates and maintain those forms which are requisite in all numerous assembles", "subset": "tele", "task_type": "understanding", "prediction": "naturally received an accession of power during the minority and as it was now becoming a scene of business the members chose for the first time a speaker who might preserve order in their debates and maintain those forms which are requisite in all numerous assemblies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 687, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094522-sg0028-mc02-lav-clo-dg130.wav", "answer": "freedom of commerce in market towns without toll or impost and a fixed rent on lands instead of the services due by villainage these requests which though extremely reasonable in themselves the nation was not sufficiently prepared to receive", "subset": "tele", "task_type": "understanding", "prediction": "freedom of commerce and market towns without toll or impost and a fixed rent on lands instead of the services due by villeinage these requests which though extremely reasonable in themselves the nation was not sufficiently prepared to receive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 688, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094522-sg0037-mc01-stu-clo-dg160.wav", "answer": "the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country", "subset": "tele", "task_type": "understanding", "prediction": "the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 689, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094526-sg0027-mc02-lav-clo-dg020.wav", "answer": "england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vicar of christ", "subset": "tele", "task_type": "understanding", "prediction": "england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vigour of christ", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 690, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm1-tele-sp7498-ch099156-sg0013-mc02-lav-clo-dg000.wav", "answer": "we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time", "subset": "tele", "task_type": "understanding", "prediction": "we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till clodstock came again to hamburg this he did a year after we had seen one another for the first time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 691, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7517/Lab41-SRI-VOiCES-rm1-tele-sp7517-ch100442-sg0003-mc01-stu-clo-dg170.wav", "answer": "and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer's shop and you will find me in my spare evenings", "subset": "tele", "task_type": "understanding", "prediction": "and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer shop and you will find me in my spare evenings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 692, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm1-tele-sp7540-ch101262-sg0013-mc02-lav-clo-dg010.wav", "answer": "soon got tired of being by himself and began to look about for something to amuse him what can there be in that twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other", "subset": "tele", "task_type": "understanding", "prediction": "soon got tired of being by himself and began to look about for something to amuse him what can there be in the twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 693, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm1-tele-sp7540-ch101799-sg0030-mc01-stu-clo-dg080.wav", "answer": "but contrary to usual experience they fought with the utmost valour and determination so that for some time after the ships had become engaged at close quarters the struggle was simply one for bare life on the part of the english", "subset": "tele", "task_type": "understanding", "prediction": "but contrary to usual experience they fought with yellowish valor and determination so that for some time after the ships had become engaged at close quarter the struggle was simply one for bare life on the part of the english", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 694, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7704/Lab41-SRI-VOiCES-rm1-tele-sp7704-ch106965-sg0010-mc01-stu-clo-dg000.wav", "answer": "and killed so many men you would have burst and lost all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with severity in her tone", "subset": "tele", "task_type": "understanding", "prediction": "and killed so many men you would have burst and lost all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with severity in her tone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 695, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm1-tele-sp7850-ch111771-sg0000-mc02-lav-clo-dg090.wav", "answer": "through the influence of hon thomas l hamer he was admitted at west point in eighteen thirty nine", "subset": "tele", "task_type": "understanding", "prediction": "through the influence of hon thomas l hammer he was admitted at west point in eighteen thirty nine", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 696, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm1-tele-sp7850-ch111771-sg0002-mc01-stu-clo-dg080.wav", "answer": "grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field", "subset": "tele", "task_type": "understanding", "prediction": "grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 697, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm1-tele-sp7868-ch110705-sg0008-mc01-stu-clo-dg030.wav", "answer": "and these wreaths descended into and mixed with a beard and whiskers of the same exquisite workmanship which surrounded and decorated a very fierce little face of the reddest gold imaginable right in the front of the mug", "subset": "tele", "task_type": "understanding", "prediction": "and these wreathed studded into and mixed with a beard and whiskers of the same exquisite workmanship which surrounded and decorated a very fierce little face of the reddest gold imaginable right in the front of the mug", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 698, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm1-tele-sp7868-ch110706-sg0021-mc02-lav-clo-dg160.wav", "answer": "and fell thundering across his path and though he had repeatedly faced these dangers on the most terrific glaciers and in the wildest weather it was with a new and oppressive feeling of panic terror that he leaped the last chasm and flung himself", "subset": "tele", "task_type": "understanding", "prediction": "and fell thundering across the pass and though he had repeatedly faced these dangers on the most terrific glaciers and in the wildest weather it was with a new and oppressive feeling of panic terror that he leaped the last chasm and flung himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 699, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm1-tele-sp7881-ch110131-sg0018-mc02-lav-clo-dg100.wav", "answer": "as he picked him up roughly and set him on his neck jose seized the giant's long beard and drew it around his neck so tightly that the giant fell to the floor dead then jose seized one of the money bags and ran home with it to his mother", "subset": "tele", "task_type": "understanding", "prediction": "as he picked him up roughly and set him on his neck jose seized the giant s long beard and drew it around his neck so tightly that the giant fell to the floor dead then jose seized one of the money bags and ran home with it to his mother", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 700, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7910/Lab41-SRI-VOiCES-rm1-tele-sp7910-ch080534-sg0049-mc02-lav-clo-dg000.wav", "answer": "i've broke myself off that but if you was to leave me i've had hard things to go through do you know the burial club broke up just before she died i couldn't get not a ha'penny a lot o the money was stolen you may think how i felt clara with her lyin there", "subset": "tele", "task_type": "understanding", "prediction": "i broke myself off that but if you was to leave me i had hard things to go through do you know the burial club broke up just before she died i could get not a hay penny a lot of the money was stolen you may think how i felt clara with her lying there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 701, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7910/Lab41-SRI-VOiCES-rm1-tele-sp7910-ch294690-sg0005-mc02-lav-clo-dg180.wav", "answer": "the parlor was empty i went into the kitchen i went into the upper rooms solitude everywhere the bailiff had left the place and his mother and his daughter had gone with him no friend or neighbor lingered near with a message", "subset": "tele", "task_type": "understanding", "prediction": "the parlor was empty i went into the kitchen i went into the upper rooms solitude everywhere the bailiff had left the place and his mother and his daughter had gone with him no friend or neighbor lingered near with a message", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 702, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm1-tele-sp7932-ch093470-sg0010-mc01-stu-clo-dg070.wav", "answer": "i believe that there is a struggle going on in her mind on the subject and that if she is to have peace and as you say health she must unburden her mind however mister powlett my advice in the matter is leave her alone do not press her in any way", "subset": "tele", "task_type": "understanding", "prediction": "i believe that there is a struggle going on in her mind on the subject and that if she is to have peace and as you say health she must unburden her mind however mr powlett my advice in the matter is leave her alone do not press her in any way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 703, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-tele-sp7981-ch112057-sg0025-mc01-stu-clo-dg170.wav", "answer": "madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money", "subset": "tele", "task_type": "understanding", "prediction": "madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 704, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm1-tele-sp7981-ch112058-sg0024-mc01-stu-clo-dg070.wav", "answer": "and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries", "subset": "tele", "task_type": "understanding", "prediction": "in these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 705, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp8057/Lab41-SRI-VOiCES-rm1-tele-sp8057-ch296395-sg0002-mc01-stu-clo-dg130.wav", "answer": "and with more or less indistinct markings of the tabby character it is of about ordinary size the tail is in form somewhat like that of most of our cats and the ears are largish and pointed in a slightly lynx like fashion", "subset": "tele", "task_type": "understanding", "prediction": "and with more or less indistinct markings of the tabby character it is of about ordinary size the tail is in form somewhat like that of most of our cats and the ears are large and pointed in a slightly lynx like fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 706, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm1-tele-sp8225-ch274376-sg0002-mc01-stu-clo-dg060.wav", "answer": "than the english parliament in order to allure that nation into a close confederacy openly declared their wishes of ecclesiastical reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used", "subset": "tele", "task_type": "understanding", "prediction": "then the english parliament in order to allure that nation into a close confederacy openly declared their wishes of embracing the articles of reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 707, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm1-tele-sp8225-ch274376-sg0017-mc01-stu-clo-dg180.wav", "answer": "and passively yielded to the torrent the general assembly of the church met at the same time with the convention and exercising an authority almost absolute over the whole civil power made every political consideration yield to their theological zeal and prejudices", "subset": "tele", "task_type": "understanding", "prediction": "and passively yielded to the torrent the general assembly of the church met at the same time with the convention and exercising an authority almost absolute over the whole civil power made every political consideration yield to their theological zeal and prejudices", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 708, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm1-tele-sp8425-ch291444-sg0008-mc02-lav-clo-dg060.wav", "answer": "sweetened it with the graces of sentiment like tacitus and infused into the whole the dignity the grandeur and magnificence of livy i am aware that i shall incur the censure of numerous very learned and judicious critics for", "subset": "tele", "task_type": "understanding", "prediction": "sweetened it with the graces of sentiment like dactylist and infused into the whole the dignity the grandeur and magnificence of lythie i am aware that i shall incur the censure of numerous very learned and judicious critics for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 709, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp8575/Lab41-SRI-VOiCES-rm1-tele-sp8575-ch290349-sg0022-mc02-lav-clo-dg010.wav", "answer": "it is also evident that it must touch one part of the flesh first and another after and so in succession and yet i believe nobody who ever felt the pain of such a shot or heard the blow against the two distant walls could perceive any succession either in the pain or sound of so swift a stroke", "subset": "tele", "task_type": "understanding", "prediction": "it is also evident that it must touch one part of the flesh first and another after and so in succession and yet i believe nobody who ever felt the pain of such a shot or heard the blow against the two distant walls could perceive any succession either in the pain or sound of so swift a stroke", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 710, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp8605/Lab41-SRI-VOiCES-rm1-tele-sp8605-ch292138-sg0022-mc01-stu-clo-dg110.wav", "answer": "and clarence looked very approvingly at the nice plum cake and the madeira cake which is a sort of sponge cake with slices of preserved citron on top of it a favourite cake for teas in a few minutes the water boiled in spite of everybody watching it attentively", "subset": "tele", "task_type": "understanding", "prediction": "and clarence looked very approvingly at the nice plum cake and the madeira cake which is a sort of sponge cake with slices of preserved citron on top of it a favourite cake for teas in a few minutes the water boiled in spite of everybody watching it attentively", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 711, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/tele/sp_6241-8713/sp8635/Lab41-SRI-VOiCES-rm1-tele-sp8635-ch295759-sg0012-mc02-lav-clo-dg100.wav", "answer": "and in the rear of it the men of rank marched two and two when the corpse was put in the ground the guard fired their guns three times and then all the troops marched back to camp the red men the del a wares and shaw nees came to aid gen er al brad dock", "subset": "tele", "task_type": "understanding", "prediction": "and in the rear of it the men of rank marched two and two when the corpse was put in the ground the guard fired their guns three times and then all the troops marched back to camp the red men the delawares and the shawnees came to aid general braddock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 712, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm2-babb-sp0112-ch121671-sg0025-mc02-lav-clo-dg040.wav", "answer": "the children all painted their faces to look as indians do when they are on the warpath and they caught the roosters and the turkey cock and pulled feathers from their tails to stick in their hair and then the boys made wooden tomahawks for the girls and bows and arrows for their own use", "subset": "babb", "task_type": "understanding", "prediction": "the children all painted their faces to look as indians do when they are on the warpath and they caught the roosters and the turkey cock and pulled feathers from their tails to stick in their hair and then the boys made wooden tomahawks for the girls and bows and arrows for their own use", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 713, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm2-babb-sp0112-ch123216-sg0003-mc02-lav-clo-dg030.wav", "answer": "said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can't said anne sorrowfully", "subset": "babb", "task_type": "understanding", "prediction": "said anne never mind i begin faintly to discern clear water ahead where no examination breakers live girls do you can you realize that our redmond life is almost over i can t said anne sorrowfully", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 714, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0188/Lab41-SRI-VOiCES-rm2-babb-sp0188-ch135249-sg0019-mc01-stu-clo-dg080.wav", "answer": "came with her mother and missus jasper bell but in jane the milk of human kindness had not been curdled by years of matrimonial bickerings her lines had fallen in pleasant places in spite of the fact as missus rachel lynde would say", "subset": "babb", "task_type": "understanding", "prediction": "came with her mother and mrs jasper bell but in jane the milk of human kindness had not been curdled by years of matrimonial bickerings her lines had fallen in pleasant places in spite of the fact as mrs rachel lynde would say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 715, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0188/Lab41-SRI-VOiCES-rm2-babb-sp0188-ch135249-sg0030-mc01-stu-clo-dg170.wav", "answer": "but when we get a phone in that won't matter so much the situation is beautiful it looks to the sunset and has the great blue harbor before it the sand dunes aren't very far away the sea winds blow over them and the sea spray drenches them", "subset": "babb", "task_type": "understanding", "prediction": "but when we get a phone in that won t matter so much the situation is beautiful it looks to the sunset and has the great blue harbour before it the sand dunes aren t very far away the sea winds blow over them and the sea spray drenches them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 716, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm2-babb-sp0204-ch287139-sg0020-mc01-stu-clo-dg170.wav", "answer": "squalling was the word for it pew's anger rose so high at these objections till at last his passion completely taking the upper hand he struck at them right and left in his blindness and his stick sounded heavily on more than one", "subset": "babb", "task_type": "understanding", "prediction": "squalling was the word for it pughes anger rose so high at these objections till at last his passion completely taking the upper hand he struck at them right and left in his blindness and his stick sounded heavily on more than one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 717, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm2-babb-sp0205-ch157088-sg0027-mc02-lav-clo-dg050.wav", "answer": "but we can not because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains", "subset": "babb", "task_type": "understanding", "prediction": "but we cannot because everything up here is locked away from us i repeat that isn t conservation if they had applied a little of it to the salmon industry but they didn t and the salmon are going like the buffalo of the plains", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 718, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm2-babb-sp0208-ch126600-sg0011-mc02-lav-clo-dg090.wav", "answer": "freddie fisher fairly fussed when he came to eat his crust often on the floor he'd throw it hoping mother wouldn't know it goops all hate to eat the crust if you're told to then you must", "subset": "babb", "task_type": "understanding", "prediction": "Freddy fished fairly fast when he came to eat his crust. Often on the floor, he d throw it, hoping mother wouldn t know it. Goofs all hate to eat the crust. If you re told to, then you must.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 719, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm2-babb-sp0208-ch128036-sg0004-mc02-lav-clo-dg180.wav", "answer": "the cowslip has been much admired altho its proper name we're told is really the marsh marigold the cow bird picture i suspect is absolutely incorrect we make such errors now and then a sort of cow slip of the pen a sparrer", "subset": "babb", "task_type": "understanding", "prediction": "the cowslip has been much admired although its proper name retold is really the marsh marigold the cupboard picture i suspect is absolutely incorrect you make such errors now and then i started off cowslip off the pan asparagus", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 720, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0240/Lab41-SRI-VOiCES-rm2-babb-sp0240-ch144999-sg0038-mc02-lav-clo-dg000.wav", "answer": "and by no means is it really necessary to a successful outing twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals", "subset": "babb", "task_type": "understanding", "prediction": "and by no means is it really necessary to a successful hunter twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 721, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm2-babb-sp0242-ch122626-sg0030-mc01-stu-clo-dg170.wav", "answer": "did she say that to me did you hear her eliza and georgiana won't i tell mama but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing", "subset": "babb", "task_type": "understanding", "prediction": "did she say that to me do you hear her eliza and georgiana won t i tell mamma but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 722, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0296/Lab41-SRI-VOiCES-rm2-babb-sp0296-ch142727-sg0031-mc01-stu-clo-dg090.wav", "answer": "these derangements are the basis of emotion its physical basis and to be moved is to perceive them take away from the consciousness this physical reflex and emotion ceases it is no longer anything but an idea", "subset": "babb", "task_type": "understanding", "prediction": "These derangements are the basis of emotion. Its physical basis and to be moved is to perceive them. Take away from the consciousness, this physical reflex and emotion ceases. It is no longer anything but an idea.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 723, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm2-babb-sp0459-ch127522-sg0015-mc01-stu-clo-dg030.wav", "answer": "here at that same moment came news of another far away out in the marsh there arose all of a sudden a sound like the cry of anger then another on the back of it and then one horrid long drawn scream", "subset": "babb", "task_type": "understanding", "prediction": "here at that same moment came news of another far away out in the marsh there arose all of a sudden a sound like the cry of anger then another on the back of it and then one horrid long drawn scream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 724, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm2-babb-sp0472-ch129983-sg0011-mc02-lav-clo-dg180.wav", "answer": "which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth", "subset": "babb", "task_type": "understanding", "prediction": "which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 725, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm2-babb-sp0479-ch126480-sg0005-mc02-lav-clo-dg040.wav", "answer": "i really couldn't couldn't eat mouse pie and i shall have to eat it because it is a party and my pie was going to be veal and ham a pink and white pie dish and so is mine just like ribby's dishes they were both bought at tabitha twitchit's", "subset": "babb", "task_type": "understanding", "prediction": "i really couldnt couldnt eat nose pie and i shall have to eat it because it is party and my pie was going to be veal and ham a pink and white pie dish and so is mine just like ruby s dishes they were both bought in town with the titchwitz", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 726, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm2-babb-sp0479-ch134717-sg0034-mc02-lav-clo-dg020.wav", "answer": "and the singer so shy to the rest receiv'd me the gray brown bird i know receiv'd us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird", "subset": "babb", "task_type": "understanding", "prediction": "and the singer so shy to the rest received me the gray brown bird i know received us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 727, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm2-babb-sp0479-ch134717-sg0056-mc01-stu-clo-dg050.wav", "answer": "weapons and each with musing soul retire to celebrate our dear commander's death no more for him life's stormy conflicts nor victory nor defeat no more time's dark events charging like ceaseless clouds across the sky but sing poet in our name", "subset": "babb", "task_type": "understanding", "prediction": "weapons in each with musing soul retired a celebrator of dear commander s death no more for him life s stormy conflicts nor victory nor defeat no more time s dark events charging like ceaseless clouds across the sky but sing poet in our name", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 728, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm2-babb-sp0480-ch123176-sg0004-mc01-stu-clo-dg080.wav", "answer": "pour it in a bowl on a slice of toast cut up and grate a little nutmeg over panada put some crackers crusts of dry bread or dried rusk in a sauce pan with cold water and a few raisins", "subset": "babb", "task_type": "understanding", "prediction": "Pour it in a bowl on a slice of toast, cut up and grate a little nutmeg over it. Panada put some crackers, crusts of dry bread, or dried rusk in a saucepan with cold water and a few raisins.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 729, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm2-babb-sp0480-ch126336-sg0000-mc02-lav-clo-dg110.wav", "answer": "king grisly beard a great king of a land far away in the east had a daughter who was very beautiful but so proud and haughty and conceited", "subset": "babb", "task_type": "understanding", "prediction": "king grizzly bear a great king of a land far away in the east had a daughter who was very beautiful but so proud and haughty conceited", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 730, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131882-sg0000-mc01-stu-clo-dg030.wav", "answer": "burlington gardens the house in which sheridan died in eighteen fourteen he was one of the most noticeable members of the reform club though he seemed always to avoid attracting attention an enigmatical personage", "subset": "babb", "task_type": "understanding", "prediction": "burlington gardens the house in which sheraton died in eighteen forty he was one of the most noticeable members of the reform club though he seemed always to avoid attracting attention an anegmatical person", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 731, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131887-sg0009-mc02-lav-clo-dg100.wav", "answer": "nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger", "subset": "babb", "task_type": "understanding", "prediction": "nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 732, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131887-sg0022-mc01-stu-clo-dg080.wav", "answer": "it is thirteen hundred and ten miles from suez to aden at the other end of the red sea and she has to take in a fresh coal supply and does she go from suez directly to bombay", "subset": "babb", "task_type": "understanding", "prediction": "it is thirteen hundred and ten miles from suez to aden at the other end of the red sea and she has to take in a fresh coal supply and does she go from suez directly to bombay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 733, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131899-sg0008-mc01-stu-clo-dg010.wav", "answer": "he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation", "subset": "babb", "task_type": "understanding", "prediction": "he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 734, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm2-babb-sp0510-ch130101-sg0009-mc01-stu-clo-dg010.wav", "answer": "they occupied themselves again in dragging their own tragedies toward the rear suddenly as the two friends marched on the tall soldier seemed to be overcome by a tremor his face turned to a semblance of gray paste", "subset": "babb", "task_type": "understanding", "prediction": "they occupied themselves again in dragging their own tragedies toward the rear suddenly as the two friends marched on the tall soldier seemed to be overcome by a tremor his face turned to a semblance of gray paste", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 735, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm2-babb-sp0510-ch130101-sg0021-mc01-stu-clo-dg180.wav", "answer": "he protested in a dulled way keeping his eyes fastened on the mystic place of his intentions no no don't tech me leave me be leave me be the youth aghast and filled with wonder at the tall soldier", "subset": "babb", "task_type": "understanding", "prediction": "he protested in a dulled way keeping his eyes fastened on the mystic place of his intentions no no dont touch me leave me be leave me be the youth aghast and filled with wonder at the tall soldier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 736, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm2-babb-sp0636-ch123163-sg0012-mc02-lav-clo-dg140.wav", "answer": "the jar or pan should be of stone ware or fire proof yellow ware to boil salt cod put your fish to soak over night change the water in the morning and let it stay till you put it on which should be two hours before dinner", "subset": "babb", "task_type": "understanding", "prediction": "the jar or pan should be of stoneware or fireproof yellow ware to boil salt cod put your fish to soak over night change the water in the morning and let it stay till you put it on it should be two hours before dinner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 737, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127579-sg0004-mc01-stu-clo-dg040.wav", "answer": "i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat", "subset": "babb", "task_type": "understanding", "prediction": "i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 738, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127579-sg0029-mc02-lav-clo-dg170.wav", "answer": "from whence they are drawn as occasion may require in this condition the tutao sometimes remains for years and even is thought to improve by age before it is fit to be eaten however it has to undergo an additional process", "subset": "babb", "task_type": "understanding", "prediction": "promonts they are drawn as occasion may require in this condition the tutao sometimes remains for years and even is thought to improve by age before it is fit to be eaten however it has to undergo an additional process", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 739, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127595-sg0028-mc01-stu-clo-dg060.wav", "answer": "i am convinced that it is as natural for a human being to swim as it is for a duck and yet in civilized communities how many able bodied individuals die like so many drowning kittens from the occurrence of the most trivial accidents", "subset": "babb", "task_type": "understanding", "prediction": "i am convinced that it is as natural for a human being to swim as it is for a duck and yet in civilized communities how many able bodied individuals die like so many drowning kittens from the occurrence of the most trivial accidents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 740, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127597-sg0017-mc02-lav-clo-dg120.wav", "answer": "this passage for no conceivable reason that i could devise was always closed after the household had retired to rest by drawing a heavy slide across it composed of a dozen or more bits of wood ingeniously fastened together by seizings of sinnate", "subset": "babb", "task_type": "understanding", "prediction": "this passage for no conceivable reason that i could devise was always closed after the household had retired to rest by drawing a heavy slide across it composed of a dozen or more bits of wood ingeniously fastened together by seizings of sinnet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 741, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0770/Lab41-SRI-VOiCES-rm2-babb-sp0770-ch131704-sg0003-mc01-stu-clo-dg170.wav", "answer": "a region as large as the entire union of thirteen states at the close of the war of independence moreover within its boundaries was embraced all the great american gold field just on the eve of discovery for marshall had detected the shining particles in the mill race", "subset": "babb", "task_type": "understanding", "prediction": "a region as large as the entire union of thirteen states at the close of the war of independence moreover within its boundaries was embraced all the great american gold field just on the eve of discovery for marshall had detected the shining particles in the mill race", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 742, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0948/Lab41-SRI-VOiCES-rm2-babb-sp0948-ch132705-sg0009-mc01-stu-clo-dg090.wav", "answer": "a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said", "subset": "babb", "task_type": "understanding", "prediction": "a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 743, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0948/Lab41-SRI-VOiCES-rm2-babb-sp0948-ch132707-sg0020-mc01-stu-clo-dg140.wav", "answer": "we have made a bow and many arrows we can kill more birds than we need for our food we find water and fruit in the forest at night we choose a clearing and we build a ring of fires around it", "subset": "babb", "task_type": "understanding", "prediction": "we have made a bow and many arrows we can kill more birds than we need for our food we find water and fruit in the forest at night we choose a clearing and we build a ring of fires around it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 744, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0948/Lab41-SRI-VOiCES-rm2-babb-sp0948-ch132707-sg0027-mc01-stu-clo-dg160.wav", "answer": "and they wait obediently without questions till it pleases us to turn and go on we go on and we bless the earth under our feet but questions come to us again as we walk in silence", "subset": "babb", "task_type": "understanding", "prediction": "and they wait obediently without question till it pleases us to turn and go on we go on and we bless the earth under our feet but questions come to us again as we walk in silence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 745, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm2-babb-sp0949-ch134660-sg0008-mc02-lav-clo-dg140.wav", "answer": "as seemed necessary to account for its extraordinary preservation and seasonable discovery were gradually propagated without opposition the custody of the true cross which on easter sunday was solemnly exposed to the people was intrusted to the bishop of", "subset": "babb", "task_type": "understanding", "prediction": "as seemed necessary to account for its extraordinary preservation and seasonable discovery were gradually propagated without opposition the custody of the true cross which on easter sunday was solemnly exposed to the people was entrusted to the bishop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 746, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm2-babb-sp0949-ch138545-sg0036-mc01-stu-clo-dg120.wav", "answer": "the slaves nearly equalled or actually exceeded the whites in number in south carolina they formed almost two thirds of the population even in the middle colonies of delaware and pennsylvania about one fifth of the inhabitants were from africa to the north the proportion of slaves steadily diminished", "subset": "babb", "task_type": "understanding", "prediction": "the slaves nearly equaled or actually exceeded the whites in number in south carolina they formed almost two thirds of the population even in the middle colonies of delaware and pennsylvania about one fifth of the inhabitants were from africa to the north the proportion of slaves steadily diminished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 747, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm2-babb-sp1050-ch134119-sg0034-mc01-stu-clo-dg140.wav", "answer": "but the little boys had their india rubber boots at last they discovered the little old woman they knew her by her hat it was steeple crowned without any vane they saw her digging with her trowel round a sassafras bush", "subset": "babb", "task_type": "understanding", "prediction": "but the little boys had their india rubber boots at last they discovered the little old woman they knew her by her hat it was steeple crowned without any vane they saw her digging with her trowel round a sassafras bush", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 748, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm2-babb-sp1112-ch128136-sg0019-mc02-lav-clo-dg090.wav", "answer": "are excessively tedious but when mister rodd leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed", "subset": "babb", "task_type": "understanding", "prediction": "are excessively tedious but when mr rod leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 749, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm2-babb-sp1116-ch132847-sg0029-mc01-stu-clo-dg050.wav", "answer": "the swallow is less swift than the wind the wind is less swift than the lightning but you my horse if you love me must be swifter than them all for there is a part of my heart that suffers the best part of my heart that is in danger and the horse heard her", "subset": "babb", "task_type": "understanding", "prediction": "The swallow is less swift than the wind. The wind is less swift than the lightning. But you, my horse, if you love me, must be swifter than them all. There is a part of my heart that suffers the best part of my heart that is in danger. And the horse heard her.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 750, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm2-babb-sp1116-ch137572-sg0032-mc01-stu-clo-dg170.wav", "answer": "this is why the unique value of children is their service as an entering wedge in the close grown love of husband and wife a wedge that widens and holds forever wider the unity of love it has penetrated other responsibilities other interests may serve a similar purpose", "subset": "babb", "task_type": "understanding", "prediction": "This is why the unique value of children is their service as an entering wedge in the close grown love of husband and wife, a wedge that widens and holds forever wider. The unity of love, it has penetrated other responsibilities, other interests may serve a similar purpose.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 751, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1121/Lab41-SRI-VOiCES-rm2-babb-sp1121-ch135824-sg0037-mc01-stu-clo-dg150.wav", "answer": "then when i do wake up i have plenty to eat i might add said old mother nature that when he goes to sleep for the winter he curls up in a little ball with his long tail wrapped around him and in his bed of soft grass he sleeps very sound indeed", "subset": "babb", "task_type": "understanding", "prediction": "then when i do wake up i have plenty to eat i might add said old mother nature that when he goes to sleep for the winter he curls up in a little ball with his long tail wrapped around him and in his bed of soft grass he sleeps very sound indeed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 752, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm2-babb-sp1160-ch134674-sg0005-mc02-lav-clo-dg050.wav", "answer": "from the evidence of reason as well as history that the two marriages of valentinian with severa and with justina were successively contracted and that he used the ancient permission of divorce which was still allowed by the laws though it was condemned by the church", "subset": "babb", "task_type": "understanding", "prediction": "from the evidence of reason as well as history that the two marriages of valentinian with sevira and with justina were successively contracted and that he used the ancient permission of divorce which was still allowed by the laws though it was condemned by the church", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 753, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm2-babb-sp1160-ch139336-sg0020-mc01-stu-clo-dg090.wav", "answer": "and the happiness of the governed here then is the origin and rise of government namely a mode rendered necessary by the inability of moral virtue to govern the world here too is the design and end of government viz", "subset": "babb", "task_type": "understanding", "prediction": "and the happiness of the governed here then is the origin and rise of government namely a mode rendered necessary by the inability of moral virtue to govern the world here too is the design and end of government viz", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 754, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_0032-1182/sp1182/Lab41-SRI-VOiCES-rm2-babb-sp1182-ch133396-sg0034-mc02-lav-clo-dg030.wav", "answer": "inky with the soot of years hans straightened himself and tilting his leathern cap to one side began scratching his bullet head at last he drew a long breath yes good he muttered to himself he who jumps into the river must e e n swim the best he can", "subset": "babb", "task_type": "understanding", "prediction": "inky with the sweat of years hawes straightened himself out tilting his leather cap to one side began scratching his bullet head at last he drew a long breath yes good he muttered to himself he who jumps into the river must even swim the best he can", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 755, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1235/Lab41-SRI-VOiCES-rm2-babb-sp1235-ch135884-sg0012-mc02-lav-clo-dg160.wav", "answer": "and resisting an order which disappointed her malice she cried out what are you doing husband sacrifice that cow your farmer has not a finer nor one fitter for the festival out of deference to my wife i came again to the cow", "subset": "babb", "task_type": "understanding", "prediction": "at resisting an order which disappointed her malice she cried out what are you doing husband sacrifice that cow your farmer has not a finer nor one fitter for the festival out of deference to my wife i came again to the cow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 756, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1259/Lab41-SRI-VOiCES-rm2-babb-sp1259-ch137770-sg0038-mc01-stu-clo-dg170.wav", "answer": "and the servants to humanize and several kettles of helen's to keep on the boil her conscience pricked her a little about the basts she was not sorry to have lost sight of them no doubt leonard was worth helping but being henry's wife she preferred to help someone else", "subset": "babb", "task_type": "understanding", "prediction": "and the servants to humanize and several kettles of hallens to keep on the boil her conscience pricked her a little about the basques she was not sorry to have lost sight of them no doubt leonard was worth helping but being henry s wife she preferred to help some one else", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 757, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm2-babb-sp1272-ch128104-sg0009-mc01-stu-clo-dg180.wav", "answer": "he laments most bitterly the divorce that has been made between decorative art and what we usually call pictures makes the customary appeal to the last judgment and reminds us that in the great days of art michael angelo was the furnishing upholsterer", "subset": "babb", "task_type": "understanding", "prediction": "he laments most bitterly the divorce that has been made between decorative art and what we usually call pictures makes a customary appeal to the last judgment and reminds us that in the great days of art michael angelo was the furnishing upholsterer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 758, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm2-babb-sp1272-ch135031-sg0024-mc02-lav-clo-dg150.wav", "answer": "having returned to the royal cavern kaliko first pounded the gong and then sat in the throne wearing ruggedo's discarded ruby crown and holding in his hand the sceptre which ruggedo had so often thrown at his head", "subset": "babb", "task_type": "understanding", "prediction": "Having returned to the royal cavern, Calico first pounded the gong and then SAT in the throne, wearing Ruggedo discarded ruby crown and folding in his hand. The scepter, which Ruggedo had so often thrown at his head.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 759, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm2-babb-sp1335-ch160602-sg0009-mc02-lav-clo-dg160.wav", "answer": "whose fluttering leaves seemed beckoning him to come it dwelt in a sunny little nook where cool winds rustled by and murmuring bees and butterflies came on the flower's breast to lie", "subset": "babb", "task_type": "understanding", "prediction": "whose fluttering leaves seemed beckoning him to come it dwelt in a sunny little nook where cool winds rustled by and murmuring bees and butterflies came on the flower s breast to lie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 760, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm2-babb-sp1335-ch163935-sg0005-mc01-stu-clo-dg110.wav", "answer": "then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander", "subset": "babb", "task_type": "understanding", "prediction": "then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 761, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm2-babb-sp1383-ch130489-sg0031-mc01-stu-clo-dg120.wav", "answer": "his troubled spirit shifted its load his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm", "subset": "babb", "task_type": "understanding", "prediction": "his troubled spirit shifted and slowed his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 762, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm2-babb-sp1383-ch130533-sg0008-mc01-stu-clo-dg030.wav", "answer": "i think we need neither doubt nor fear i think we ought to recur a moment to i think we shall all recognize i think we should do well to call to mind", "subset": "babb", "task_type": "understanding", "prediction": "i think we need neither doubt nor fear i think we ought to recur a moment to i think we shall all recognize i think we should do well to call to mind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 763, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-babb-sp1392-ch128226-sg0016-mc02-lav-clo-dg090.wav", "answer": "they now fancied themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport to their body and this earth gentle is zarathustra to the sickly verily", "subset": "babb", "task_type": "understanding", "prediction": "they now fancy themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport their body and the earth gentle as aratus treated the subject barely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 764, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1425/Lab41-SRI-VOiCES-rm2-babb-sp1425-ch139297-sg0036-mc01-stu-clo-dg120.wav", "answer": "for during this interval a great change had taken place in master hugh and his once kind and affectionate wife the influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both", "subset": "babb", "task_type": "understanding", "prediction": "For during this interval, a great change had taken place in Master Hugh and his once kind and affectionate wife. The influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 765, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1425/Lab41-SRI-VOiCES-rm2-babb-sp1425-ch139297-sg0036-mc02-lav-clo-dg120.wav", "answer": "for during this interval a great change had taken place in master hugh and his once kind and affectionate wife the influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both", "subset": "babb", "task_type": "understanding", "prediction": "For during this interval, a great change had taken place in Master Hugh and his once kind and affectionate wife. The influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 766, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm2-babb-sp1472-ch139797-sg0004-mc02-lav-clo-dg180.wav", "answer": "it would not make one sphere as immense as this star or sun around which revolve about five hundred worlds or planets many of which are greater than our jupiter with abounding interest i visited all the inhabited worlds of this vast system how long it took i have no way of knowing", "subset": "babb", "task_type": "understanding", "prediction": "it would not make one sphere as immense as this star sign around which revolve about five hundred worlds or planets many of which are greater than our jupiter with abounding interest i visited all the inhabited worlds of this vast system how long it took i have no way of knowing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 767, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm2-babb-sp1472-ch285314-sg0011-mc02-lav-clo-dg040.wav", "answer": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up", "subset": "babb", "task_type": "understanding", "prediction": "but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 768, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1536/Lab41-SRI-VOiCES-rm2-babb-sp1536-ch141791-sg0006-mc01-stu-clo-dg090.wav", "answer": "as soon as londonderry had fallen and it was universally supposed that the fall of londonderry could not be long delayed he might cross the sea with part of his forces and land in scotland where his friends were supposed to be numerous when he was once on british ground and in the midst of british adherents", "subset": "babb", "task_type": "understanding", "prediction": "as soon as londonderry had fallen and it was universally supposed that the fall of londonderry could not be long delayed he might cross the sea with part of his forces and land in scotland where his friends were supposed to be numerous when he was once on british ground and in the midst of british adherents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 769, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1607/Lab41-SRI-VOiCES-rm2-babb-sp1607-ch149245-sg0039-mc02-lav-clo-dg160.wav", "answer": "which had served in holland and which bore the names of their colonels mackay himself balfour and ramsay there was also a gallant regiment of infantry from england then called hastings's but now known as the thirteenth of the line", "subset": "babb", "task_type": "understanding", "prediction": "which had served in holland and which bore the name of their colonel mackay himself delfour ramsay there was also a gallant regiment of infantry from england then called hastings but now known as the thirteenth of the line", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 770, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1841/Lab41-SRI-VOiCES-rm2-babb-sp1841-ch150351-sg0013-mc01-stu-clo-dg070.wav", "answer": "and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the indian came out and plunged into the cold water of a near by stream", "subset": "babb", "task_type": "understanding", "prediction": "and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the antaeon came out and plunged into the cold water of a near by stream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 771, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1851/Lab41-SRI-VOiCES-rm2-babb-sp1851-ch151817-sg0036-mc01-stu-clo-dg150.wav", "answer": "or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course they must be totally ignorant of all such things as flying machines and the like", "subset": "babb", "task_type": "understanding", "prediction": "or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course they must be totally ignorant of all such things as flying machines and the like", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 772, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm2-babb-sp1867-ch148436-sg0020-mc02-lav-clo-dg020.wav", "answer": "and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothin", "subset": "babb", "task_type": "understanding", "prediction": "and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 773, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm2-babb-sp1867-ch154071-sg0017-mc01-stu-clo-dg050.wav", "answer": "the same distinction between their clothes was in their faces the finely modeled prettiness of her features and the big careless chiseling of the features of bill gregg ronicky doone did not wonder that after her first fear her gesture was one of disdain and surprise", "subset": "babb", "task_type": "understanding", "prediction": "the same distinction between their clothes was in their faces the finely modelled prettiness of her features and the big careless chiselling of the features of bill gregg ronicky doone did not wonder that after her first fear her gesture was one of disdain and surprise", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 774, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1926/Lab41-SRI-VOiCES-rm2-babb-sp1926-ch147987-sg0019-mc01-stu-clo-dg010.wav", "answer": "and had left again on the six o'clock train for denver that morning the agent said his face was striped with court plaster and he carried his left hand in a sling he looked so used up that the agent asked him what had happened to him since ten o'clock the night before", "subset": "babb", "task_type": "understanding", "prediction": "and had left again on the six o clock train for denver that morning the agent said his face was striped with cork plaster and he carried his left hand in a sling he looked so used up that the agent asked him what had happened to him since ten o clock the night before", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 775, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm2-babb-sp1961-ch149739-sg0018-mc02-lav-clo-dg070.wav", "answer": "he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor", "subset": "babb", "task_type": "understanding", "prediction": "he could find no trace of a clue to confirm his belief yet so intimately was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 776, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1963/Lab41-SRI-VOiCES-rm2-babb-sp1963-ch142776-sg0013-mc02-lav-clo-dg060.wav", "answer": "a little nutmeg one teaspoonful of flour one pint of cream one pint of milk forcemeat balls mace salt and pepper to taste bread crumbs one egg two quarts of water mode", "subset": "babb", "task_type": "understanding", "prediction": "a little nutmeg one teaspoonful of flour one pint of cream one pint of milk horse meat balls mace salt and pepper to taste bread crumbs one egg two quarts of water melt", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 777, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm2-babb-sp1970-ch010594-sg0033-mc02-lav-clo-dg020.wav", "answer": "at another time she might have resented these words especially the last but i had roused her curiosity her panting eager curiosity and she let them pass altogether unchallenged did you see this woman", "subset": "babb", "task_type": "understanding", "prediction": "at another time she might have resented these words especially the last but i had roused her curiosity her panting eager curiosity and she let them pass altogether unchallenged did you see this woman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 778, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm2-babb-sp1970-ch026100-sg0015-mc01-stu-clo-dg030.wav", "answer": "everything points to an aeroplane it was done a hundred yes a thousand times in the war while i was over there with my hospital unit we used to get a lot of cases of motorcycle despatch riders who had been picked off by german aviators", "subset": "babb", "task_type": "understanding", "prediction": "everything points to an airplane it was done a hundred yes a thousand times in the war while i was over there with my hospital unit we used to get a lot of cases of motorcycle dispatch riders who had been picked off by german aviators", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 779, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm2-babb-sp1970-ch028415-sg0006-mc01-stu-clo-dg050.wav", "answer": "some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another", "subset": "babb", "task_type": "understanding", "prediction": "some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 780, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2093/Lab41-SRI-VOiCES-rm2-babb-sp2093-ch143262-sg0015-mc01-stu-clo-dg080.wav", "answer": "and apparently bent on getting us away i caught such words as fever prisoner my head years misery despair always", "subset": "babb", "task_type": "understanding", "prediction": "and apparently bent on getting us away i caught such words as fever prisoner my head years misery despair always", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 781, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2093/Lab41-SRI-VOiCES-rm2-babb-sp2093-ch143271-sg0020-mc01-stu-clo-dg040.wav", "answer": "we'll go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply", "subset": "babb", "task_type": "understanding", "prediction": "will go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 782, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm2-babb-sp2110-ch161101-sg0036-mc01-stu-clo-dg050.wav", "answer": "you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it", "subset": "babb", "task_type": "understanding", "prediction": "you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 783, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2149/Lab41-SRI-VOiCES-rm2-babb-sp2149-ch007239-sg0021-mc01-stu-clo-dg120.wav", "answer": "what things came upon me at antioch at iconium at lystra what persecutions i endured", "subset": "babb", "task_type": "understanding", "prediction": "what things came upon me at antioch at iconium at lystra what persecutions i endured", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 784, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm2-babb-sp2156-ch025563-sg0005-mc01-stu-clo-dg020.wav", "answer": "that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan's name missus phelan's son came a running he had been on his way", "subset": "babb", "task_type": "understanding", "prediction": "that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan s name mrs phelan s son came a running he had been on his way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 785, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm2-babb-sp2285-ch149890-sg0019-mc02-lav-clo-dg100.wav", "answer": "moderately interested in its welfare hurstwood's word however had gone the rounds it was to be a full dress affair the four boxes had been taken doctor norman mc neill hale and his wife were to occupy one", "subset": "babb", "task_type": "understanding", "prediction": "moderately interested in its welfare hurstwood s word however had gone the rounds it was to be a full dress affair the four boxes had been taken dr norman mc neil hale and his wife were to occupy one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 786, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm2-babb-sp2289-ch152254-sg0028-mc02-lav-clo-dg020.wav", "answer": "in among the roman ships towing behind them large boats filled with material that would easily burn these boats were set on fire and floated against the roman vessels which also were soon on fire the flames quickly spread", "subset": "babb", "task_type": "understanding", "prediction": "animal ships towing behind them large boats filled with material that would easily burn these boats were set on fire and floated against the roman vessels which also were soon on fire the flames quickly spread", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 787, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm2-babb-sp2289-ch152258-sg0035-mc01-stu-clo-dg170.wav", "answer": "of the mosque and chanting in a loud voice such words as these come to prayer come to prayer there is no god but god he giveth life and he dieth not i praise his perfection god is great in mecca", "subset": "babb", "task_type": "understanding", "prediction": "of the mosque and chanting in a loud voice such words as these come to prayer come to prayer there is no god but god he giveth life and he dieth not i praise his perfection god is great in mecca", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 788, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-babb-sp2412-ch153947-sg0014-mc01-stu-clo-dg000.wav", "answer": "i made a few further very trifling alterations before moulds were taken but since the summer of eighteen seventy two as new editions were from time to time wanted they have been printed from stereos then made", "subset": "babb", "task_type": "understanding", "prediction": "i made a few further very trifling alterations before moulds were taken but since the summer of eighteen seventy two as new editions were from time to time wanted they have been printed from stereos then made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 789, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-babb-sp2412-ch153954-sg0009-mc01-stu-clo-dg140.wav", "answer": "i have always delighted in and reverenced beauty but i felt simply abashed in the presence of such a splendid type a compound of all that is best in egyptian greek and italian", "subset": "babb", "task_type": "understanding", "prediction": "i have always delighted in and reverenced beauty but i felt simply abashed in the presence of such a splendid type a compound of all that is best in egyptian greek and italian", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 790, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-babb-sp2412-ch153954-sg0015-mc01-stu-clo-dg040.wav", "answer": "suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome", "subset": "babb", "task_type": "understanding", "prediction": "suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well in the answer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 791, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2481/Lab41-SRI-VOiCES-rm2-babb-sp2481-ch012731-sg0026-mc01-stu-clo-dg080.wav", "answer": "cold soap heat twenty six pounds of strained grease when melted mix it with four pailsful of lye made of twenty pounds of white potash let the whole stand in the sun stirring it frequently in the course of a week", "subset": "babb", "task_type": "understanding", "prediction": "cold soap heat twenty six pounds of strained grease when melted mix it with four pails full of ley made of twenty pounds of white potash let the whole stand in the sun stirring it frequently in the course of a week", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 792, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2481/Lab41-SRI-VOiCES-rm2-babb-sp2481-ch163597-sg0025-mc01-stu-clo-dg140.wav", "answer": "with the intention of taking them out into the upper world for they all loved him and would not be separated from him each of them turned her palace into an egg for they were all enchantresses and they taught him how to turn the eggs into palaces and back again", "subset": "babb", "task_type": "understanding", "prediction": "with the intention of taking them out into the upper world for they all loved him and would not be separated from him each of them turned her palace into an egg for they were all enchantresses and they taught him how to turn the eggs into palaces and back again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 793, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2573/Lab41-SRI-VOiCES-rm2-babb-sp2573-ch178450-sg0027-mc02-lav-clo-dg150.wav", "answer": "aren't you ever goin to bed sheridan halted all right mamma he said with a vast sigh let's go up and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising lopsidedly in her drowsiness", "subset": "babb", "task_type": "understanding", "prediction": "arent you ever going to bed sheridan halted all right mamma he said with a vast sigh lets go out and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising up sadly in her drowsiness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 794, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2573/Lab41-SRI-VOiCES-rm2-babb-sp2573-ch186232-sg0008-mc02-lav-clo-dg110.wav", "answer": "and you would be doing the right thing at last i won't said aunt jane angrily it would also be considerate and just to the memory of mister bradley continued the girl what's going to became of kenneth", "subset": "babb", "task_type": "understanding", "prediction": "and you would be doing the right thing at last i won't said aunt jane angrily it would also be considerate and just to the memory of mr bradley continued the girl what is going to become of kenneth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 795, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2673/Lab41-SRI-VOiCES-rm2-babb-sp2673-ch162130-sg0014-mc01-stu-clo-dg020.wav", "answer": "it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution", "subset": "babb", "task_type": "understanding", "prediction": "it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 796, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2691/Lab41-SRI-VOiCES-rm2-babb-sp2691-ch156745-sg0027-mc02-lav-clo-dg160.wav", "answer": "merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances", "subset": "babb", "task_type": "understanding", "prediction": "merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground francis", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 797, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm2-babb-sp2758-ch086588-sg0001-mc02-lav-clo-dg160.wav", "answer": "he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth", "subset": "babb", "task_type": "understanding", "prediction": "he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 798, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm2-babb-sp2758-ch161217-sg0012-mc01-stu-clo-dg170.wav", "answer": "the power which they wielded over the fate of man was significantly indicated under the figure of a thread which they spun out for the life of each human being from his birth to the grave this occupation they divided between them", "subset": "babb", "task_type": "understanding", "prediction": "The power, which they wielded over the fate of man, was significantly indicated under the figure of a thread, which they spun out for the life of each human being from his birth to the grave. This occupation, they divided between them.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 799, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm2-babb-sp2758-ch161217-sg0012-mc02-lav-clo-dg170.wav", "answer": "the power which they wielded over the fate of man was significantly indicated under the figure of a thread which they spun out for the life of each human being from his birth to the grave this occupation they divided between them", "subset": "babb", "task_type": "understanding", "prediction": "the power which they wielded over the fate of man was significantly indicated under the figure of a thread which they spun out for the life of each human being from his birth to the grave this occupation they divided between them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 800, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm2-babb-sp2803-ch154328-sg0018-mc01-stu-clo-dg120.wav", "answer": "their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sounds that only a thin layer of earth prevented immediate communication", "subset": "babb", "task_type": "understanding", "prediction": "their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sound that only a thin layer of earth prevented immediate communication", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 801, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm2-babb-sp2911-ch007601-sg0036-mc02-lav-clo-dg060.wav", "answer": "if still you think me mad you will think so no longer when i describe the wise precautions i took for the concealment of the body the night waned and i worked hastily but in silence first of all i dismembered the corpse i cut off the head", "subset": "babb", "task_type": "understanding", "prediction": "if still you think me mad you will think so no longer when i describe the wise precautions i took for the concealment of the body the night waned and i worked hastily but in silence first of all i dismembered the corpse i cut off the head", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 802, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm2-babb-sp3368-ch170951-sg0016-mc01-stu-clo-dg090.wav", "answer": "now the founders of a state ought to know the general forms in which poets should cast their tales and the limits which must be observed by them but to make the tales is not their business very true he said but what are these forms of theology which you mean something of this kind i replied", "subset": "babb", "task_type": "understanding", "prediction": "now the founders of a state ought to know the general forms in which poets should cast their tales and the limits which must be observed by them but to make the tales is not their business very true he said but what are these forms of theology which you mean something of this kind i replied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 803, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-babb-sp3446-ch144021-sg0018-mc01-stu-clo-dg090.wav", "answer": "mate down with fever ngora ngora sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset", "subset": "babb", "task_type": "understanding", "prediction": "mate down with fever negoro negoro sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 804, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-babb-sp3446-ch176270-sg0045-mc01-stu-clo-dg020.wav", "answer": "which had been commenced long ago as to enable them to perform divine service in it requested his holiness to consecrate it to this the pontiff willingly agreed and the florentines to exhibit the wealth of the city and the splendor of the edifice and do greater honor to the pope", "subset": "babb", "task_type": "understanding", "prediction": "which had been commenced long ago as to enable them to perform divine service in it requested his holiness to consecrate it to this the pontiff willingly agreed and the florentines to exhibit the wealth of the city and the splendor of the edifice and do greater honor to the pope", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 805, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm2-babb-sp3835-ch178029-sg0008-mc01-stu-clo-dg060.wav", "answer": "which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire", "subset": "babb", "task_type": "understanding", "prediction": "which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 806, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp3972/Lab41-SRI-VOiCES-rm2-babb-sp3972-ch005791-sg0005-mc01-stu-clo-dg090.wav", "answer": "which would make me revere its possessor were he the lowliest man in your legions allow me noblest of scots to plead one word in vindication of him to whom my allegiance is pledged had he come hither conducted by war alone what would edward have been worse than any other conqueror", "subset": "babb", "task_type": "understanding", "prediction": "which would make me revere its possessor were he the lowliest man in your legions allow me noblest of scots to plead one word in vindication of him to whom my allegiance is pledged had he come hither conducted by war alone what would edward have been worse than any other conqueror", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 807, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp3994/Lab41-SRI-VOiCES-rm2-babb-sp3994-ch011512-sg0017-mc02-lav-clo-dg130.wav", "answer": "the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved", "subset": "babb", "task_type": "understanding", "prediction": "the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 808, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4010/Lab41-SRI-VOiCES-rm2-babb-sp4010-ch010798-sg0024-mc01-stu-clo-dg180.wav", "answer": "is indeed the centre of your being your very heart nor does the lesson apply to those only who worship mammon who give their lives their best energies to the accumulation of wealth", "subset": "babb", "task_type": "understanding", "prediction": "is indeed the center of your being your very heart nor does the lesson apply to those only who worship mammon who give their lives their best energies to the accumulation of wealth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 809, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4057/Lab41-SRI-VOiCES-rm2-babb-sp4057-ch011254-sg0013-mc01-stu-clo-dg070.wav", "answer": "or the lectures of the london institution of a third a city snob of taste at picture auctions at private views of exhibitions or at the opera or the philharmonic but intimacy is impossible in most cases", "subset": "babb", "task_type": "understanding", "prediction": "or the lectures of the london institution of the third a city snob of taste at picture auctions at private views of exhibitions or at the opera or the philharmonic but intimacy is impossible in most cases", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 810, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4110/Lab41-SRI-VOiCES-rm2-babb-sp4110-ch011528-sg0022-mc01-stu-clo-dg060.wav", "answer": "unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and", "subset": "babb", "task_type": "understanding", "prediction": "unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 811, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4160/Lab41-SRI-VOiCES-rm2-babb-sp4160-ch011549-sg0016-mc02-lav-clo-dg060.wav", "answer": "my late lamented parents at the respective ages of fifty and fifty seven my sister anastasia my only brother my sister in law his wife and my dear priscilla at seventeen years theo turned from the others to look at this last with a deeper interest", "subset": "babb", "task_type": "understanding", "prediction": "my late lamented parents at the respective ages of fifty and fifty seven my sister anastasia my only brother my sister in law his wife and my dear priscilla at seventeen years theo turned from the others to look at this last with a deeper interest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 812, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-babb-sp4427-ch020023-sg0014-mc01-stu-clo-dg020.wav", "answer": "i believe i have never mistaken a cow for a human being as was done by old doctor e it was many years ago when boston common was still used as a pasture and cows were daily to be met in the crooked streets of the city that this gentleman", "subset": "babb", "task_type": "understanding", "prediction": "i believe i have never mistaken a cow for a human being as was done by old doctor e it was many years ago when boston common was still used as pasture and cows were daily to be met in the crooked streets of the city that this gentleman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 813, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm2-babb-sp4438-ch052195-sg0010-mc02-lav-clo-dg100.wav", "answer": "anger and hurt were beneath him he had seen a great vision and was as a god and he could feel only profound and awful pity for this maggot of a man he did not look at him and though his eyes passed over him he did not see him", "subset": "babb", "task_type": "understanding", "prediction": "anger and hurt were beneath him he had seen a great vision and was as a god and he could feel only profound and awful pity for this maggot of a man he did not look at him and though his eyes passed over him he did not see him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 814, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm2-babb-sp4441-ch076262-sg0020-mc01-stu-clo-dg160.wav", "answer": "and was making violent efforts to regain it i saw a spider this morning said rehnhjelm that predicts happiness araignee matin chagrin said falander have you never heard that what does that mean asked agnes a spider on the morrow grief and sorrow", "subset": "babb", "task_type": "understanding", "prediction": "and was making violent efforts to regain it i saw a spider this morning said ranald that predicts happiness araigne matin chagrin said philander have you never heard of that what does that mean asked agnes a spider on the morrow grief and sorrow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 815, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm2-babb-sp4441-ch076263-sg0017-mc02-lav-clo-dg090.wav", "answer": "quite true i'm going to lecture there on sunday next on sweden a good subject plenty to say if i should fall asleep on your sofa don't waken me i'm dead beat all right old chap go to sleep a few moments later olle was fast asleep and snoring loudly", "subset": "babb", "task_type": "understanding", "prediction": "quite true i am going to lecture there on sunday next on sweden a good subject plenty to say if i should fall asleep on your sofa dont waken me i am dead beat all right old chap go to sleep a few moments later polly was fast asleep and snoring loudly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 816, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279849-sg0033-mc02-lav-clo-dg130.wav", "answer": "fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller", "subset": "babb", "task_type": "understanding", "prediction": "fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 817, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279849-sg0044-mc02-lav-clo-dg070.wav", "answer": "while the fireman hammered the top over now run back slowly an inch at a time ordered fuller the engineer opened the throttle and the texas crept away taking up the slack in the couplings the left wheel followed back along the groove its flange had cut in the tie", "subset": "babb", "task_type": "understanding", "prediction": "while the firemen hammer the top over now run back slowly an inch at a time ordered ford the engineer opened the throttle and the texas crept away taking up the slack in the couplings the left wheel followed back along the groove its flange had cut in the timbers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 818, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279852-sg0028-mc01-stu-clo-dg050.wav", "answer": "joe handed them candles and they followed him upstairs here's one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here's the other said joe leading the way down the corridor", "subset": "babb", "task_type": "understanding", "prediction": "joe handed them candles and they followed him upstairs here is one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here is the other said joe leading the way down the corridor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 819, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279852-sg0028-mc02-lav-clo-dg050.wav", "answer": "joe handed them candles and they followed him upstairs here's one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here's the other said joe leading the way down the corridor", "subset": "babb", "task_type": "understanding", "prediction": "joe handed them candles and they followed him upstairs here is one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here is the other said joe leading the way down the corridor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 820, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm2-babb-sp4839-ch015304-sg0022-mc01-stu-clo-dg030.wav", "answer": "i have a good mind that the king of france's army and mine should come together in order that by battle it may be known to whom of right belongs this heritage for i see no other way to it by my sacred oath my lord said the good knight i would that it might be to morrow provided that i were out of captivity", "subset": "babb", "task_type": "understanding", "prediction": "i have a good mind that the king of france s army and mine should come together in order that by battle it may be known to whom of rights belongs this heritage for i see no other way to it by my sacred oath my lord said the good knight i would that it might be to morrow provided that i were out of captivity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 821, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm2-babb-sp4848-ch028247-sg0043-mc01-stu-clo-dg150.wav", "answer": "vil villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion", "subset": "babb", "task_type": "understanding", "prediction": "ville villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 822, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4859/Lab41-SRI-VOiCES-rm2-babb-sp4859-ch026870-sg0018-mc01-stu-clo-dg130.wav", "answer": "but often felt ill will toward her which she could not overcome once she had a talk with her friend natasha about sonya and about her own injustice toward her you know said natasha you have read the gospels a great deal there is a passage in them that just fits sonya what asked countess mary surprised", "subset": "babb", "task_type": "understanding", "prediction": "but often felt ill will toward her which she could not overcome once she had a talk with her friend natasha about sonya and about her own injustice toward her you know said natasha you have read the gospels a great deal there is a passage in them that just fits sonya what asked countess mary surprised", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 823, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4957/Lab41-SRI-VOiCES-rm2-babb-sp4957-ch023295-sg0026-mc02-lav-clo-dg130.wav", "answer": "it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you", "subset": "babb", "task_type": "understanding", "prediction": "it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 824, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp4967/Lab41-SRI-VOiCES-rm2-babb-sp4967-ch028868-sg0004-mc01-stu-clo-dg000.wav", "answer": "but yet as he thought of what he had seen he shuddered with vexation i was thinking of the governor he said he shall be told everything that you met tregear certainly and that i kissed him", "subset": "babb", "task_type": "understanding", "prediction": "but yet as he thought of what he had seen he shuddered with vexation i was thinking of the governor he said he shall be told everything that you met tregear certainly and that i kissed him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 825, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5126/Lab41-SRI-VOiCES-rm2-babb-sp5126-ch027504-sg0031-mc02-lav-clo-dg060.wav", "answer": "there's no saying what mister knightley might do if his wife had been here thank god she's away at bathurst said starlight i hate seeing women put out besides everybody bows down to missus knightley she's as good as she's handsome i believe and", "subset": "babb", "task_type": "understanding", "prediction": "there is no saying what mr knightley might do if his wife had been here thank god she is away at battersea said starlight i hate seeing women put out besides everybody bows down to mrs knightley she is as good as she is handsome i believe and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 826, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm2-babb-sp5154-ch026558-sg0009-mc02-lav-clo-dg130.wav", "answer": "the image of wax answered never a word again the monkey said this time in a little louder voice o peddler boy peddler boy please give me a banana just one little ripe little", "subset": "babb", "task_type": "understanding", "prediction": "the image of what he asked again this time in a little louder voice oh peppa boy peppa boy please give me a banana just one little ripe little", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 827, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm2-babb-sp5189-ch059288-sg0027-mc01-stu-clo-dg060.wav", "answer": "expressing their pleasure at the expected treat by gentle bleatings the squire stooped to spread the salt the black ram either from most uncivil impatience or mistaking the movement of the proprietor's coat tail for a challenge pitched into him incontinently", "subset": "babb", "task_type": "understanding", "prediction": "expressing their pleasure at the expected treat by gentle bleatings the squire stooped to spread the salt the black ram either from most uncivil impatience or mistaking the movement of the proprietor s coat tail for a challenge pitched into him incontinently", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 828, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5319/Lab41-SRI-VOiCES-rm2-babb-sp5319-ch084357-sg0004-mc01-stu-clo-dg150.wav", "answer": "published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers", "subset": "babb", "task_type": "understanding", "prediction": "published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 829, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5338/Lab41-SRI-VOiCES-rm2-babb-sp5338-ch024615-sg0002-mc01-stu-clo-dg160.wav", "answer": "occasionally indeed when such a consummation seemed inevitable a watchful old grandam with her close cap distaff and spindle rushed like a sibyl in frenzy out of one of these miserable cells dashed into the middle of the path and snatching up her own charge from among the sunburnt loiterers saluted him with a sound cuff and transported him back to his dungeon the little white headed varlet screaming all the while from the very top of his lungs a shrilly treble to the growling remonstrances of the enraged matron", "subset": "babb", "task_type": "understanding", "prediction": "occasionally indeed when such a consummation seemed inevitable a watchful old grandam with her close capped distaff and spindle rushed like a sibyl in frenzy out of one of these miserable cells dashed into the middle of the pack and snatching up her own charge from among the sunburnt loiterers saluted him with a sound cuff and transported him back to his dungeon the little white headed varlet screaming all the while from the very top of his lungs a shrilly treble to the growling remonstrances of the enraged matron", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 830, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5338/Lab41-SRI-VOiCES-rm2-babb-sp5338-ch284437-sg0015-mc02-lav-clo-dg180.wav", "answer": "perhaps you are trying to ridicule me she continued regarding the sailor's face closely", "subset": "babb", "task_type": "understanding", "prediction": "perhaps you are trying to ridicule me she continued regarding the sailor s face closely", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 831, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5386/Lab41-SRI-VOiCES-rm2-babb-sp5386-ch008684-sg0041-mc01-stu-clo-dg050.wav", "answer": "and showing himself very different from what he had been before he went out to see the world but one day he said to his father that he should like to marry and have a house of his own when i served the king's chief herdsman added he i saw his daughter and i am resolved to try if i cannot win her for my wife", "subset": "babb", "task_type": "understanding", "prediction": "and showing himself very different from what he had been before he went out to see the world but one day he said to his father that he should like to marry and have a house of his own when i served the king s chief herdsman added he i saw his daughter and i am resolved to try if i cannot win her for my wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 832, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5400/Lab41-SRI-VOiCES-rm2-babb-sp5400-ch034479-sg0026-mc02-lav-clo-dg060.wav", "answer": "the crescent shaped curve of the cut grass the grass and flower heads slowly and rhythmically falling before the blade of his scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came", "subset": "babb", "task_type": "understanding", "prediction": "the crescent shaped curve of the cut grass the grass and flower head slowly and rhythmically falling before the blade of the scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 833, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm2-babb-sp5401-ch102526-sg0028-mc02-lav-clo-dg090.wav", "answer": "at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter", "subset": "babb", "task_type": "understanding", "prediction": "at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 834, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm2-babb-sp5456-ch062043-sg0023-mc01-stu-clo-dg170.wav", "answer": "they wanted to learn the game at two o'clock the captain asked the mate how we were getting on oh pretty glibly sir replied the mate we can scarcely tell what headway we are making for we are obliged to keep the middle of the river and there is the shadow of a fog rising", "subset": "babb", "task_type": "understanding", "prediction": "they wanted to learn the game at two o clock the captain asked the mate how we were getting on oh pretty glibly sir replied the mate we can scarcely tell what headway we are making for we are obliged to keep the middle of the river and there is the shadow of a fog rising", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 835, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm2-babb-sp5456-ch062043-sg0024-mc02-lav-clo-dg020.wav", "answer": "this wood seems rather better than that we took in at yellow face's but we're nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask em what's the price of wood up here i've got you again", "subset": "babb", "task_type": "understanding", "prediction": "this wood seems rather better than that we took in yellow faces but we are nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask them what is the price of wood up here i have got you again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 836, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm2-babb-sp5635-ch044582-sg0004-mc01-stu-clo-dg040.wav", "answer": "is really very rapid rotation from the first thought to the second and back again just as in the above cited experiment the attention must shift from one hand to the other until one or the other movement becomes partly or wholly automatic whatever is the psychological truth of this contention", "subset": "babb", "task_type": "understanding", "prediction": "is really very rapid rotation from the first thought to the second and back again just as in the above cited experiment the attention must shift from one hand to the other until one or the other movement becomes partly or wholly automatic whatever is the psychological truth of this contention", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 837, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm2-babb-sp5635-ch044582-sg0010-mc02-lav-clo-dg020.wav", "answer": "don't anticipate divide your attention and you divide your power this matter of the effect of the inner man upon the outer needs a further word here particularly as touching concentration what do you read my lord", "subset": "babb", "task_type": "understanding", "prediction": "dont anticipate divide your attention and you divide your power the matter of the effect of the inner man upon the outer needs a further word here particularly as touching concentration what do you read my lord", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 838, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm2-babb-sp5635-ch058137-sg0014-mc01-stu-clo-dg060.wav", "answer": "with a party of friends mister jimmy hurrying out with a slate in his hand begged me to stop a moment and thus addressed me well mister carlton this algebra is a most powerful thing ain't it indeed it is mister jimmy have you been looking into it", "subset": "babb", "task_type": "understanding", "prediction": "with a party of friends mr jimmy hurrying out with a slate in his hand begged me to stop a moment and thus addressed me well mr carlton this algebra is a most powerful thing ain t it indeed it is mr jimmy have you been looking into it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 839, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm2-babb-sp5678-ch043303-sg0015-mc01-stu-clo-dg070.wav", "answer": "mister phillips arrived the next morning as usual just as mabel had left the old lady's room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver's room", "subset": "babb", "task_type": "understanding", "prediction": "mister phillips arrived the next morning as usual just as mabel had left the old lady's room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver's room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 840, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm2-babb-sp5717-ch100145-sg0017-mc02-lav-clo-dg070.wav", "answer": "of course obray count erskyll planetary proconsul of aditya didn't realize that he didn't even know what javasan meant just free them commodore vann shatrak couldn't see much of a problem either he would have answered", "subset": "babb", "task_type": "understanding", "prediction": "of course obray count briscoe planetary proconsul of aditya didn t realize that he didn t even know what javasan meant just free them commodore van shechtach couldn t see much of a problem either he would have answered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 841, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5740/Lab41-SRI-VOiCES-rm2-babb-sp5740-ch097610-sg0031-mc02-lav-clo-dg110.wav", "answer": "for while rejoicings were still loud over the departure of the enemy there came a knock at missus tracy's door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier", "subset": "babb", "task_type": "understanding", "prediction": "for while rejoicings were still loud over the departure of the enemy there came a knock at missus tracy s door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 842, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5789/Lab41-SRI-VOiCES-rm2-babb-sp5789-ch057158-sg0004-mc01-stu-clo-dg100.wav", "answer": "she wants you to go to her at cheltenham for a month oh mister morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me", "subset": "babb", "task_type": "understanding", "prediction": "she wants you to go to her at cheltenham for a month oh mr morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 843, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5789/Lab41-SRI-VOiCES-rm2-babb-sp5789-ch057158-sg0013-mc01-stu-clo-dg150.wav", "answer": "i don't want any amusement at any rate you will answer lady ushant of course i shall answer her perhaps you can let me know she wishes me to take you to cheltenham i shall go for a couple of days but i shall not stay longer", "subset": "babb", "task_type": "understanding", "prediction": "i don t want any amusement at any rate you will answer lady ushant of course i shall answer her perhaps you can let me know she wishes me to take you to cheltenham i shall go for a couple of days but i shall not stay long", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 844, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5802/Lab41-SRI-VOiCES-rm2-babb-sp5802-ch066347-sg0026-mc02-lav-clo-dg050.wav", "answer": "the conflicting tints began to get in their deadly work and within two hours he was completely doubled up the pain he suffered was awful agony was bliss alongside of the pangs that now afflicted him and all the palliatives and pain killers known to man were tried without avail", "subset": "babb", "task_type": "understanding", "prediction": "the conflicting tints began to get in their deadly work and within two hours he was completely doubled up the pain he suffered was awful agony was bliss alongside of the pangs that now afflicted him and all the palliatives or pain killers known to man were tried without avail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 845, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch055088-sg0028-mc02-lav-clo-dg100.wav", "answer": "and that which is above men you began to find out that truly divine mystery that you had a mother on earth simply by lying soft and warm upon her bosom and so as our lord told the jews of old", "subset": "babb", "task_type": "understanding", "prediction": "back which is above me you began to find out that truly divine mystery that you had a mother on earth simply by lying soft and so as our lord told the jews of old", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 846, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch055088-sg0034-mc01-stu-clo-dg170.wav", "answer": "over the whole earth for my part i know not save that all shall be as god wills the tree has been cut down already again and again and yet has always thrown out fresh shoots and dropped fresh poison from its boughs", "subset": "babb", "task_type": "understanding", "prediction": "of the whole earth for my part i know not save that all shall be as god wills the tree has been cut down already again and again and yet has always thrown out fresh shoots and dropped fresh poison from its boughs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 847, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch066166-sg0005-mc02-lav-clo-dg160.wav", "answer": "and a fringe of gray hair circling his head like a crown as he took off his tarpaulin i observed that the top of his head was quite smooth and flat as if somebody had sat down on him when he was very young there was something noticeably hearty in this man's bronzed face", "subset": "babb", "task_type": "understanding", "prediction": "and a fringe of grey hair circling his head like a crown as he took off his topper i observed that the top of his head was quite smooth and flat as if some weight had sat down on him when he was very young there was something noticeably haughty in this man s bronzed face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 848, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5868/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch066166-sg0031-mc02-lav-clo-dg140.wav", "answer": "and i've no doubt that other parts of his body were illustrated in the same agreeable manner i imagine he was fond of drawings and took this means of gratifying his artistic taste it was certainly very ingenious and convenient a portfolio might be misplaced or dropped overboard", "subset": "babb", "task_type": "understanding", "prediction": "and i have no doubt that other parts of his body were illustrated in the same agreeable manner i imagine he was fond of drawings and took this means of gratifying his artistic taste it was certainly very ingenious and convenient for torrio might be misplaced or dropped overboard", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 849, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-babb-sp5935-ch043322-sg0015-mc02-lav-clo-dg170.wav", "answer": "will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure", "subset": "babb", "task_type": "understanding", "prediction": "will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 850, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-babb-sp5935-ch055927-sg0020-mc01-stu-clo-dg140.wav", "answer": "and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps", "subset": "babb", "task_type": "understanding", "prediction": "and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 851, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-babb-sp5935-ch055927-sg0026-mc02-lav-clo-dg080.wav", "answer": "each screw requires a separate set of engines and the main object of the duplication is to lessen the risk of the vessel being left helpless in case of accident to one or other the advisability of placing each engine and shafting in a separate water tight compartment", "subset": "babb", "task_type": "understanding", "prediction": "each screw requires a separate set of engines and the main object of the duplication is to lessen the risk of the vessel being left helpless in case of accident to one or other the advisability of placing each engine and shafting in a separate water tight compartment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 852, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp5968/Lab41-SRI-VOiCES-rm2-babb-sp5968-ch061356-sg0007-mc02-lav-clo-dg020.wav", "answer": "the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father's house in london and alice peel was she thinking of him", "subset": "babb", "task_type": "understanding", "prediction": "the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father s house in london and alice peel was she thinking of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 853, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp6099/Lab41-SRI-VOiCES-rm2-babb-sp6099-ch067860-sg0033-mc01-stu-clo-dg120.wav", "answer": "speaking very slowly i think mister robert waite is just like the knights in that book the age of chivalry they always did exactly what was right", "subset": "babb", "task_type": "understanding", "prediction": "Speaking very slowly. I think Mr. Robert Waite is just like the knights in that book. The age of chivalry. They always did. exactly what was right.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 854, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm2-babb-sp6147-ch034606-sg0021-mc02-lav-clo-dg140.wav", "answer": "just like any one else he would gaily set fire to a cot of woodwork and thatch and just scorch those within but he would rebuild their houses in stone he insulted two ladies one was unmarried he gave her a portion the other was married he had her husband appointed chaplain", "subset": "babb", "task_type": "understanding", "prediction": "just like anyone else even gaius set fire to a cottage of woodwork and thatch it just scorched those within but he rebuilt their houses in stone he insulted two ladies one was unmarried he gave her a portion the other was married he had her husband appointed chaplain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 855, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm2-babb-sp6241-ch061943-sg0005-mc01-stu-clo-dg060.wav", "answer": "the fact is the castle is much later than the time of the heroic prince of denmark", "subset": "babb", "task_type": "understanding", "prediction": "Fact is, the castle is much later than the time of the heroic prince of Denmark.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 856, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm2-babb-sp6395-ch086708-sg0030-mc01-stu-clo-dg120.wav", "answer": "and danglars wrote the address as he spoke yes and that's all settled exclaimed caderousse who by a last effort of intellect had followed the reading of the letter and instinctively comprehended all the misery which such a denunciation must entail", "subset": "babb", "task_type": "understanding", "prediction": "danglars wrote the address as he spoke yes and that is all settled exclaimed caterus who by a last effort of intellect had followed the reading of the letter and instinctively comprehended all the misery which such a denunciation must entail", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 857, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm2-babb-sp6395-ch087997-sg0003-mc01-stu-clo-dg180.wav", "answer": "he wrote that account of his own life which together with his other papers he has left to your care my account therefore shall begin where his ends he set out for london towards the end of april and at morpeth", "subset": "babb", "task_type": "understanding", "prediction": "he wrote that account of his own life which together with his other papers he has left to your care my account therefore shall begin where his ends he set out for london towards the end of april and at bordeaux", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 858, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm2-babb-sp6415-ch116629-sg0020-mc02-lav-clo-dg050.wav", "answer": "this very reserve however was rather distasteful to judith as regarded herself but she liked it towards others she had planned it all out that dietrich should marry veronica soon after the confirmation that they should set up a pretty little establishment and be her beloved neighbors", "subset": "babb", "task_type": "understanding", "prediction": "this very reserve however was rather distasteful to judith as regarded herself but she liked it towards others she had planned it all out that dietrich should marry veronica soon after confirmation that they should set up a pretty little establishment and be her beloved neighbours", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 859, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm2-babb-sp6454-ch107462-sg0026-mc02-lav-clo-dg100.wav", "answer": "deasey concluded at once it was a foully murdered corpse but then again you could not well conceal a corpse in someone's waistcoat and gold coins would melt or be mislaid amongst the loose bricks of a sooty chimney", "subset": "babb", "task_type": "understanding", "prediction": "these he concluded at once it was a foully murdered corpse but then again you could not well conceal a corpse in some one s waistcoat and gold coins would melt or be mislaid amongst the loose bricks of a sooty chimney", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 860, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm2-babb-sp6519-ch069411-sg0032-mc02-lav-clo-dg070.wav", "answer": "and afterwards taken such advantage of by herself and others a pebble had done it all a pebble placed in the gateway by bela's hands as she described this and insisted upon the fact in face of the judge's almost frenzied disclaimer", "subset": "babb", "task_type": "understanding", "prediction": "and afterward taken such advantage of by herself and others a pebble had done it all a pebble placed in the gateway by bella s hands as she described this and insisted on the fact in the face of the judges in almost frenzied disclaimer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 861, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-babb-sp6544-ch067863-sg0004-mc02-lav-clo-dg050.wav", "answer": "and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had not come into the house he seemed much older to sylvia than he did on her visit to the plantation in october", "subset": "babb", "task_type": "understanding", "prediction": "and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had now come into the house he seemed much older to sylvia than he did at her visit to the plantation in october", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 862, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-babb-sp6544-ch067863-sg0023-mc01-stu-clo-dg110.wav", "answer": "and aunt connie rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with missus carleton a little while before supper and told her of what uncle peter had said that ships from the north were on the way to the aid of fort sumter", "subset": "babb", "task_type": "understanding", "prediction": "and aunt connie rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with mrs carlton a little while before supper and told her of what uncle peter had said that ships from the north were on their way to the aid of fort sumter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 863, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-babb-sp6544-ch231862-sg0036-mc02-lav-clo-dg000.wav", "answer": "he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost", "subset": "babb", "task_type": "understanding", "prediction": "he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 864, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm2-babb-sp6574-ch070756-sg0035-mc01-stu-clo-dg170.wav", "answer": "the labour of winding among the little paths of the mountain and fixing my feet firmly as i advanced perplexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the halfway resting place and seated myself beside the fountain", "subset": "babb", "task_type": "understanding", "prediction": "the labor of winding among the little paths of the mountain and fixing my feet firmly as i advanced perplexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the half way resting place and seated myself beside the fountain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 865, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6696/Lab41-SRI-VOiCES-rm2-babb-sp6696-ch068773-sg0013-mc01-stu-clo-dg060.wav", "answer": "me mister forbes me yes tom i'll pay you twenty dollars a week to start with and more if you serve me faithfully and you'll board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself", "subset": "babb", "task_type": "understanding", "prediction": "me mr forbes me yes tom i will pay you twenty dollars a week to start with and more if you serve me faithfully and you board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 866, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6788/Lab41-SRI-VOiCES-rm2-babb-sp6788-ch092420-sg0019-mc02-lav-clo-dg180.wav", "answer": "but happening to read on we became fixed and charmed and have retained from its perusal the sweetest picture of life lived in this land ever afforded us out of the pale of personal observation that such things are", "subset": "babb", "task_type": "understanding", "prediction": "but happening to read on we became fixed and charmed and have retained from its perusal the sweetest picture of life lived in this land ever afforded us out of the pale of personal observation that such things are", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 867, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm2-babb-sp6965-ch277898-sg0002-mc02-lav-clo-dg180.wav", "answer": "some fraction of a shilling or franc or whatever the prevailing coinage might be should be diverted from his pocket or service into that of a hard up companion a two franc cigar would be cheerfully offered to a wealthy patron", "subset": "babb", "task_type": "understanding", "prediction": "some fraction of a shilling or franc or whatever the prevailing coinage might be should be diverted from his pocket or service into that of a hard up companion a two franc cigar would be cheerfully offered to a wealthy patron", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 868, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm2-babb-sp7000-ch083708-sg0025-mc01-stu-clo-dg170.wav", "answer": "he remarked as he produced a fourth ball from the same pocket of his tightly fitting trousers which had contained the other three a swipe does warm me so your kind of bowling mister s just the thing it was kind of him to say so though to my thinking", "subset": "babb", "task_type": "understanding", "prediction": "he remarked as he produced a fourth ball from the same pocket of his tightly fitting trousers which had contained the other three a swipe does warm me so your kind of bowling mister is just the thing it was kind of him to say so though to my thinking", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 869, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm2-babb-sp7095-ch088489-sg0035-mc02-lav-clo-dg000.wav", "answer": "both leading authorities at princeton university fundamentalism in the united states furnished the spectacle of the trial in nineteen twenty five of a school teacher named scopes for teaching the theory of evolution", "subset": "babb", "task_type": "understanding", "prediction": "both leading authorities at princeton university fundamentalism in the united states furnished the spectacle of the trial in nineteen twenty five of a schoolteacher named scopes for teaching the theory of evolution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 870, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-babb-sp7148-ch007763-sg0008-mc02-lav-clo-dg140.wav", "answer": "the whole foundation on which my life was constructed fell down all my happiness was to have been found in the continual pursuit of this end the end had ceased to charm and how could there ever again be any interest in the means", "subset": "babb", "task_type": "understanding", "prediction": "the whole foundation on which my life was constructed fell down all my happiness was to have been found in the continual pursuit of this end the end had ceased to charm and how could there ever again be any interest in the means", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 871, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-babb-sp7148-ch007763-sg0027-mc02-lav-clo-dg160.wav", "answer": "were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connexions between things not dependent on our will and feelings natural laws by virtue of which in many cases", "subset": "babb", "task_type": "understanding", "prediction": "were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connections between things not dependent on our will and feelings natural laws by virtue of which in many cases", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 872, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7247/Lab41-SRI-VOiCES-rm2-babb-sp7247-ch101864-sg0020-mc02-lav-clo-dg180.wav", "answer": "and for four years she lived on the streets and in the sweat shops enduring almost unbelievable poverty and hardships by jove exclaimed ned under his breath it was only seven or eight months before the wedding that she was found went on frank", "subset": "babb", "task_type": "understanding", "prediction": "and for four years she lived on the streets and in the sweatshops enduring almost unbelievable poverty and hardships by jove exclaimed ned under his breath it was only seven or eight months before the wedding that she was found went on frank", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 873, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7264/Lab41-SRI-VOiCES-rm2-babb-sp7264-ch092314-sg0011-mc02-lav-clo-dg050.wav", "answer": "never deals with matters vital to its prestige on the contrary it deliberately side tracks any vital discussion that sincere conviction may have forced upon the public and spoils the scent with false issues", "subset": "babb", "task_type": "understanding", "prediction": "never deals with matters vital to its prestige handicapper it deliberately sidetracks any vital discussion that sincere conviction may have forced upon the public and spoils the scent with false issues", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 874, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7264/Lab41-SRI-VOiCES-rm2-babb-sp7264-ch092316-sg0021-mc01-stu-clo-dg180.wav", "answer": "the great dailies were thought grey not wicked only general and vague the free press in its beginnings did not attack as an enemy it only timidly claimed to be heard it regarded itself as a speciality it was humble and there went with it a mass of ex centric stuff", "subset": "babb", "task_type": "understanding", "prediction": "the great dailies were thought great not wicked only general and vague the free press in its beginnings did not attack as an enemy it only timidly claimed to be heard it regarded itself as a speciality it was humble and there went with it a mass of eccentric stuff", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 875, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7276/Lab41-SRI-VOiCES-rm2-babb-sp7276-ch092427-sg0032-mc01-stu-clo-dg000.wav", "answer": "but we have not people over us whose careless hasty anger drives us to seek excuses for our failures if so perhaps perhaps who knows we the better educated rigidly immaculately true as we are at present might tell falsehoods", "subset": "babb", "task_type": "understanding", "prediction": "but we have not people over us whose careless hasty anger drives us to seek excuses for our failures if so perhaps perhaps who knows we the better educated originally immaculately true as we are at present might tell falsehoods", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 876, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm2-babb-sp7278-ch104730-sg0039-mc02-lav-clo-dg090.wav", "answer": "i said that in another part of the capitol it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence' here a loud cry of order order burst forth in which the speaker yelled the loudest", "subset": "babb", "task_type": "understanding", "prediction": "i said that in another part of the capital it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence here a loud cry of order order burst forth in which the speaker yelled the loudest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 877, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm2-babb-sp7445-ch094526-sg0039-mc02-lav-clo-dg070.wav", "answer": "the appearance of valor spirit abilities in any great man extended his interest very far and if the sovereign were deficient in these qualities he was no less if not more exposed to the usurpations of the aristocracy than even during the vigor of the feudal system", "subset": "babb", "task_type": "understanding", "prediction": "the appearance of valor spirit abilities in any great man extended his interest very far and if the sovereign were deficient in these qualities he was no less if not more exposed to the usurpations of the aristocracy than even during the vigor of the feudal system", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 878, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7517/Lab41-SRI-VOiCES-rm2-babb-sp7517-ch100442-sg0003-mc02-lav-clo-dg170.wav", "answer": "and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer's shop and you will find me in my spare evenings", "subset": "babb", "task_type": "understanding", "prediction": "and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer shop and you will find me in my spare evenings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 879, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm2-babb-sp7540-ch101258-sg0030-mc01-stu-clo-dg110.wav", "answer": "and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the whale had thrown up came sailing along and anchored close by", "subset": "babb", "task_type": "understanding", "prediction": "and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the well had thrown up came sailing along and anchored close by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 880, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7704/Lab41-SRI-VOiCES-rm2-babb-sp7704-ch106965-sg0010-mc02-lav-clo-dg000.wav", "answer": "and killed so many men you would have burst and lost all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with severity in her tone", "subset": "babb", "task_type": "understanding", "prediction": "and killed so many men you would have burst to most all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with spirit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 881, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7704/Lab41-SRI-VOiCES-rm2-babb-sp7704-ch106969-sg0013-mc01-stu-clo-dg080.wav", "answer": "will that be deserting to the enemy it will be sure and certain defeat but then of course my captain won't let me be beaten if i stick close to him and so they talked a strange couple but the younger of them had a faith which the elder might envy", "subset": "babb", "task_type": "understanding", "prediction": "will that be deserting to the enemy it will be sure and certain defeat but then of course my captain well that may be beanie if i stick close to him so they talked a strange couple but the younger of them had a faith which the elder might envy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 882, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-babb-sp7850-ch111771-sg0004-mc01-stu-clo-dg010.wav", "answer": "indeed if ever a general deserved honor grant had won it he had opened the mississippi to navigation and had captured nearly one hundred thousand prisoners and arms", "subset": "babb", "task_type": "understanding", "prediction": "indeed if ever a general deserved honor grant had won it he had opened the mississippi to navigation and had captured nearly one hundred thousand prisoners and arms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 883, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-babb-sp7850-ch281318-sg0017-mc02-lav-clo-dg160.wav", "answer": "here wood pigeon said mother magpie you must place those sticks through and across criss cross criss cross so", "subset": "babb", "task_type": "understanding", "prediction": "Here, woodpigeon said, mother magpie, you must place those sticks through and across crisscross, crisscross so.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 884, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-babb-sp7850-ch286674-sg0005-mc01-stu-clo-dg140.wav", "answer": "they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies", "subset": "babb", "task_type": "understanding", "prediction": "they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 885, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7867/Lab41-SRI-VOiCES-rm2-babb-sp7867-ch110528-sg0013-mc02-lav-clo-dg100.wav", "answer": "which she had taken from the lock but dropped in her fright she hastily quitted the room shut and locked the door and ran to her own chamber to calm herself before returning to her guests but she was unable to rest for an instant so dreadful were her feelings", "subset": "babb", "task_type": "understanding", "prediction": "which she had taken from the lock but dropped in her fright she hastily quitted the room shut and locked the door and ran to her own chamber to calm herself before returning to her guests but she was unable to rest for an instant so dreadful were her feelings", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 886, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7867/Lab41-SRI-VOiCES-rm2-babb-sp7867-ch110742-sg0034-mc02-lav-clo-dg090.wav", "answer": "he went a long voyage he is my kinsman if i could see him he could give me some account of missus rugg sir said missus croft i never heard of john foy where did he live just above here in orange tree lane there is no such place in this neighbourhood", "subset": "babb", "task_type": "understanding", "prediction": "you went a long voyage he is my kinsman if i could see him he could give me some account of mrs rugg sir said mrs cragge i never heard of john foy where did he live just above here in orange tree lane there is no such place in this neighbourhood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 887, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-babb-sp7868-ch246932-sg0019-mc02-lav-clo-dg030.wav", "answer": "i heard what was plainly a lady's voice right sweet and womanly it was though full of pain even agony i thought but heroically suppressed she soothed she expostulated she condoled she coaxed", "subset": "babb", "task_type": "understanding", "prediction": "i heard what was plainly a lady s voice bright sweet and womanly it was though full of pain even agony i thought but heroically suppressed she soothed she expostulated she condoled she coaxed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 888, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm2-babb-sp7932-ch110056-sg0022-mc01-stu-clo-dg180.wav", "answer": "and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by", "subset": "babb", "task_type": "understanding", "prediction": "and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 889, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm2-babb-sp7981-ch112056-sg0007-mc02-lav-clo-dg060.wav", "answer": "and that as he was evidently destined to do great work for god it would be to his advantage to have powerful and influential friends although the prospect of such a post filled the humble parish priest with consternation", "subset": "babb", "task_type": "understanding", "prediction": "and that as he was evidently destined to do great work for god it would be to his advantage that a call should be made upon his talents all the prospect of such a call filled the humble parish priest with consternation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 890, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm2-babb-sp7981-ch112058-sg0010-mc01-stu-clo-dg040.wav", "answer": "and a poor priest who had lately joined them before setting out on their mission journeys they used to give the key of the house to a neighbor but as there was nothing in it to steal there was little cause for anxiety in the course of their travels other priests realizing the greatness of the work asked", "subset": "babb", "task_type": "understanding", "prediction": "and a poor priest who had lately joined them before setting out on their mission journeys they used to give the key of the house to a neighbor but as there was nothing in it to steal there was little cause for anxiety in the course of their travels other priests realizing the greatness of the work asked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 891, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8057/Lab41-SRI-VOiCES-rm2-babb-sp8057-ch284428-sg0028-mc01-stu-clo-dg150.wav", "answer": "no i didn't know that admitted the sailor it's a fact said the king nothing can kill us until we've lived to the last day of our appointed lives when the final minute is up we die but we're obliged to live all of the six hundred years whether we want to or not", "subset": "babb", "task_type": "understanding", "prediction": "no i didn t know that admitted the sailor it s a fact said the king nothing can kill us until we have lived to the last day of our appointed lives when the final minute is up we die but we re obliged to live all of the six hundred years whether we want to or not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 892, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm2-babb-sp8108-ch280354-sg0022-mc02-lav-clo-dg160.wav", "answer": "oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus's lyre", "subset": "babb", "task_type": "understanding", "prediction": "oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus lyre", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 893, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm2-babb-sp8108-ch280359-sg0022-mc02-lav-clo-dg120.wav", "answer": "loki wriggled his slippery slimy length through thor's fingers but the thunderer grasped him tightly by the tail and holding him in this manner in this hand waded to the shore there father odin and the other gods met him and", "subset": "babb", "task_type": "understanding", "prediction": "Loki wriggled his slippery, slimy length through Thor's fingers, but the thunderer grasped him tightly by the tail and holding him in this manner in his hand, waded to the shore there. Father Odin and the other gods met him, and.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 894, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8118/Lab41-SRI-VOiCES-rm2-babb-sp8118-ch114476-sg0004-mc02-lav-clo-dg130.wav", "answer": "and as we have come three miles it must be only five miles away correct said warner who was in an uncommonly fine humor your mathematical power grows every day frank let x equal the whole distance from the gap to the antietam which is eight miles", "subset": "babb", "task_type": "understanding", "prediction": "and as we have come three miles it must be only five miles away correct said warner who was in an uncommonly fine humor your mathematical power grows every day frank let x equal the whole distance from the gap to the antietam which is eight miles", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 895, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8152/Lab41-SRI-VOiCES-rm2-babb-sp8152-ch258974-sg0000-mc01-stu-clo-dg130.wav", "answer": "as the field and its fertile qualities and those called artificial as improvements and machinery according as these resources are more or less developed as labor is employed in a fertile or a barren field with a sharp tool or a dull one", "subset": "babb", "task_type": "understanding", "prediction": "as the field and its fertile qualities and those called artificial as improvements and machinery according as these resources are more or less developed as labor is employed in a fertile or barren field with a sharp tool or a dull one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 896, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm2-babb-sp8225-ch274375-sg0038-mc01-stu-clo-dg120.wav", "answer": "and had expressed an intention of delivering hull into his hands but their conspiracy being detected they were arrested and sent prisoners to london where without any regard to their former services they fell both of them victims to the severity of the parliament", "subset": "babb", "task_type": "understanding", "prediction": "and had expressed an intention of delivering hull into his hands but their conspiracy being detected they were arrested and sent prisoners to london where without any regard to their former services they fell both of them victims to the severity of the parliament", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 897, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-babb-sp8266-ch258263-sg0021-mc02-lav-clo-dg100.wav", "answer": "and lullilooed with cries of joy so that all the palace rang again and the captains of the army awoke and said what is to do so they made for the palace and asked the eunuchs hath one of the king's women given birth to a child and they answered", "subset": "babb", "task_type": "understanding", "prediction": "and lulli lude with cries of joy so that all the palace rang again and the captains of the army awoke and said what is to do so they made for the palace and asked the eunuchs hath one of the king s women given birth to a child and they answered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 898, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-babb-sp8266-ch258263-sg0022-mc02-lav-clo-dg000.wav", "answer": "no but rejoice ye for king gharib hath returned to you so they rejoiced and gharib after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him", "subset": "babb", "task_type": "understanding", "prediction": "no but rejoice ye for king harim hath returned to you so they rejoiced and harim after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 899, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm2-babb-sp8425-ch291444-sg0000-mc02-lav-clo-dg020.wav", "answer": "of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative old age and day by day dropping piecemeal into the tomb in a little while thought i and those revered dutch burghers", "subset": "babb", "task_type": "understanding", "prediction": "of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative all the age and day by day dropping piecemeal into the tomb in a little while how far high had those revered dutch burghers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 900, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm2-babb-sp8425-ch292520-sg0013-mc02-lav-clo-dg040.wav", "answer": "light green in the deeps like your eyes in sunshine winds the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel", "subset": "babb", "task_type": "understanding", "prediction": "light green in the deeps like your eyes in sunshine winds the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 901, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8677/Lab41-SRI-VOiCES-rm2-babb-sp8677-ch296078-sg0001-mc02-lav-clo-dg130.wav", "answer": "and perhaps make a motion to lay the book down wait a moment girls and boys too i advise you to read on and see what came in this case of playing with dolls there were a good many thousands of boys in england at that time", "subset": "babb", "task_type": "understanding", "prediction": "and perhaps make a motion to lay the book down wait a moment girls and boys too i invite you to read on and see what came in this case of playing with dolls there were a good many thousands of boys in england at that time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 902, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm2-babb-sp8713-ch296159-sg0005-mc02-lav-clo-dg010.wav", "answer": "for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling", "subset": "babb", "task_type": "understanding", "prediction": "for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 903, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/babb/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm2-babb-sp8713-ch296159-sg0045-mc01-stu-clo-dg110.wav", "answer": "and know what reaction it was capable of in a word to experimentalise in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use", "subset": "babb", "task_type": "understanding", "prediction": "and know what reaction it was capable of in a word to experimentalize in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 904, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0093/Lab41-SRI-VOiCES-rm2-musi-sp0093-ch126208-sg0003-mc02-lav-clo-dg000.wav", "answer": "an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a whity brown tilt obtained for a few pounds more and in this turn out it became jude's business thrice a week to carry loaves of bread to the villagers", "subset": "musi", "task_type": "understanding", "prediction": "an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a witty brown tilt obtained for a few pounds more and in this turn out it became jude s business thrice a week to carry loaves of bread to the villagers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 905, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm2-musi-sp0112-ch121671-sg0027-mc02-lav-clo-dg010.wav", "answer": "then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaves of bread altogether the baker man was terribly frightened", "subset": "musi", "task_type": "understanding", "prediction": "then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaf of bread altogether the baker man was terribly frightened", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 906, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm2-musi-sp0112-ch123216-sg0022-mc02-lav-clo-dg000.wav", "answer": "gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written him a nice little note of thanks but she had never worn the trinket tonight she fastened it about her white throat with a dreamy smile she and phil walked to redmond together", "subset": "musi", "task_type": "understanding", "prediction": "gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written her a nice little note of thanks but she had never worn the trinket tonight she fastened it around her white throat with a dreamy smile she and phil walked to redmond together", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 907, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm2-musi-sp0122-ch129752-sg0000-mc01-stu-clo-dg100.wav", "answer": "cakes crullers and eclairs almond cakes one pound sifted flour one half pound butter three fourths pound sugar two eggs one half teaspoon ground cinnamon", "subset": "musi", "task_type": "understanding", "prediction": "cakes crullers and eclairs almond cakes one pound sifted flour one half pound butter three fourths pound sugar two eggs one half teaspoon ground cinnamon", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 908, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0159/Lab41-SRI-VOiCES-rm2-musi-sp0159-ch121902-sg0000-mc01-stu-clo-dg010.wav", "answer": "verily wondrous great are thy promises yet i do not doubt but thou canst make them good only keep me not in suspense after raising such hopes learn then first said she how that power ever waits upon the good", "subset": "musi", "task_type": "understanding", "prediction": "verily wondrous great are thy promises yet i do not doubt but thou canst make them good only keep me not in suspense after raising such hopes learn then first said she how that power ever waits upon the good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 909, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm2-musi-sp0204-ch148920-sg0005-mc01-stu-clo-dg180.wav", "answer": "but as they were not learned men they could only walk about and stare enjoy the little knowledge of natural history they possessed and wish with all their hearts they had acquired more even the skeleton of the mouse puzzled jacob what wonder", "subset": "musi", "task_type": "understanding", "prediction": "but as they were not learned men they could only walk about and stare enjoy the little knowledge of natural history they possessed and wish with all their hearts they had acquired more even the skeleton of the mouse puzzled jacob what wonder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 910, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm2-musi-sp0205-ch157088-sg0027-mc02-lav-clo-dg050.wav", "answer": "but we can not because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains", "subset": "musi", "task_type": "understanding", "prediction": "but we cannot because everything up here is locked away from us i repeat that isn t conservation if they had applied a little of it to the salmon industry but they didn t and the salmon are going like the buffalo of the plains", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 911, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm2-musi-sp0209-ch157830-sg0033-mc02-lav-clo-dg130.wav", "answer": "and on many lesser occasions had endeavoured to give elizabeth the advantage of her own better judgement and experience but always in vain elizabeth would go her own way and never had she pursued it in more decided opposition to lady russell than in this selection of missus clay", "subset": "musi", "task_type": "understanding", "prediction": "and on many lesser occasions had endeavoured to give elizabeth the advantage of her own better judgment and experience but always in vain elizabeth would go her own way and never had she pursued it in more decided opposition to lady russell than in this selection of mrs clay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 912, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0224/Lab41-SRI-VOiCES-rm2-musi-sp0224-ch128660-sg0018-mc01-stu-clo-dg020.wav", "answer": "hair one hundred twenty four coarse hair indicates good nature fine hair quick temper northern ohio one hundred twenty five red hair indicates a spit fire massachusetts and chestertown maryland", "subset": "musi", "task_type": "understanding", "prediction": "hair one hundred twenty four coarse hair indicates good nature fine hair quick temper northern ohio one hundred twenty five red hair indicates a spitfire massachusetts and chestertown maryland", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 913, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0224/Lab41-SRI-VOiCES-rm2-musi-sp0224-ch128660-sg0019-mc02-lav-clo-dg060.wav", "answer": "beware of that man be he friend or brother whose hair is one color and moustache another portland me one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of one's future husband", "subset": "musi", "task_type": "understanding", "prediction": "beware of that man be he friend or brother whose hair is one color and mustache another portland may one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of ones future husband", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 914, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm2-musi-sp0242-ch122625-sg0004-mc02-lav-clo-dg090.wav", "answer": "conventionality is not morality self righteousness is not religion to attack the first is not to assail the last to pluck the mask from the face of the pharisee is not to lift an impious hand to the crown of thorns", "subset": "musi", "task_type": "understanding", "prediction": "Conventiuality is not morality. Self righteousness is not religion to attack. The first is not to assail the last, to pluck the mask from the face of the Pharisee is not to lift an impious hand to the crown of thorns.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 915, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0288/Lab41-SRI-VOiCES-rm2-musi-sp0288-ch121741-sg0015-mc02-lav-clo-dg150.wav", "answer": "and enough likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god's making one would say", "subset": "musi", "task_type": "understanding", "prediction": "and in that likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god s making one would say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 916, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0288/Lab41-SRI-VOiCES-rm2-musi-sp0288-ch131220-sg0017-mc01-stu-clo-dg150.wav", "answer": "and diamond's chief pleasure seemed to be to lie amongst them and breathe the pure air but all the time he was dreaming of the country at the back of the north wind and trying to recall the songs the river used to sing for this was more like being at the back of the north wind", "subset": "musi", "task_type": "understanding", "prediction": "and diamond s chief pleasure seemed to be to lie amongst them and breathe the pure air but all the time he was dreaming of the country at the back of the north wind and trying to recall the song the river used to sing for this was more like being at the back of the north wind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 917, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0296/Lab41-SRI-VOiCES-rm2-musi-sp0296-ch129659-sg0002-mc01-stu-clo-dg150.wav", "answer": "to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding", "subset": "musi", "task_type": "understanding", "prediction": "to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 918, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm2-musi-sp0479-ch134717-sg0050-mc02-lav-clo-dg040.wav", "answer": "comrades mine and i in the midst and their memory ever to keep for the dead i loved so well for the sweetest wisest soul of all my days and lands and this for his dear sake lilac and star and bird twined with the chant of my soul", "subset": "musi", "task_type": "understanding", "prediction": "comrades mine and i in the midst and their memory ever to keep for the dead i loved so well for the sweetest wisest soul of all my days and lands and this for his dear sake lilac and star and bird twine with the chant of my soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 919, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-musi-sp0492-ch131887-sg0025-mc02-lav-clo-dg030.wav", "answer": "fix left alone was more impatient than ever having a presentiment that the robber was on board the mongolia if he had indeed left london intending to reach the new world", "subset": "musi", "task_type": "understanding", "prediction": "fixed left alone was more impotent than ever having a presentiment that the robber was on board the mongolia if he had indeed left london intentionally to reach the new world", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 920, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-musi-sp0492-ch131899-sg0001-mc02-lav-clo-dg090.wav", "answer": "blew a gale and retarded the steamer the rangoon rolled heavily and the passengers became impatient of the long monstrous waves which the wind raised before their path", "subset": "musi", "task_type": "understanding", "prediction": "blew a gale and retarded the steamer the raccoon rolled heavily and the passengers became impatient of the long monstrous waves which the wind raised before their path", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 921, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-musi-sp0492-ch131899-sg0023-mc02-lav-clo-dg070.wav", "answer": "who heard what passed would willingly have embraced the pilot while fix would have been glad to twist his neck what is the steamer's name asked mister fogg the carnatic", "subset": "musi", "task_type": "understanding", "prediction": "who heard what pat would willingly have embraced the pilot while fix would have been glad to twist his neck what is this steamer s name asked mr fogg the kantik", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 922, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm2-musi-sp0510-ch130103-sg0015-mc02-lav-clo-dg180.wav", "answer": "the clanking arms of the column near him made him soar on the red wings of war for a few moments he was sublime he thought that he was about to start for the front indeed he saw a picture of himself", "subset": "musi", "task_type": "understanding", "prediction": "the clanking arms of the column near him made him soar on the red wings of war for a few moments he was sublime he thought that he was about to start for the front indeed he saw a picture of himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 923, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm2-musi-sp0510-ch130560-sg0000-mc02-lav-clo-dg060.wav", "answer": "karmu was a farmer and dharmu was a trader once when dharmu was away from home karmu gave a religious feast and did not invite dharmu's household when dharmu returned and learnt this", "subset": "musi", "task_type": "understanding", "prediction": "karmu was a farmer and dharmu was a trader once when dharmu was away from home karmu gave a religious feast and did not invite dharmu s household when dharmu returned and learnt this", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 924, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm2-musi-sp0636-ch128331-sg0015-mc01-stu-clo-dg090.wav", "answer": "with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building", "subset": "musi", "task_type": "understanding", "prediction": "with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 925, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm2-musi-sp0637-ch127579-sg0010-mc02-lav-clo-dg070.wav", "answer": "induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object", "subset": "musi", "task_type": "understanding", "prediction": "induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 926, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0652/Lab41-SRI-VOiCES-rm2-musi-sp0652-ch130737-sg0002-mc02-lav-clo-dg080.wav", "answer": "with entrees serve clarets or other red wines such as swiss bordeaux hungarian or italian wines", "subset": "musi", "task_type": "understanding", "prediction": "With entrees, serve clarets or other red wines such as Swiss. Bordeaux, Hungarian or Italian wines.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 927, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0652/Lab41-SRI-VOiCES-rm2-musi-sp0652-ch130737-sg0010-mc01-stu-clo-dg060.wav", "answer": "sauterne is a white bordeaux a strong luscious wine the best known varieties being", "subset": "musi", "task_type": "understanding", "prediction": "sauterne is a white bordeaux a strong luscious wine the best known varieties being", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 928, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0770/Lab41-SRI-VOiCES-rm2-musi-sp0770-ch134592-sg0010-mc02-lav-clo-dg000.wav", "answer": "now he was just a blind breathing carcase nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there were something in these wise old dogs that did not perish utterly with death", "subset": "musi", "task_type": "understanding", "prediction": "now it was just a blind breathing carcass nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there was something in these wise old dogs that did not perish utterly with death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 929, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0868/Lab41-SRI-VOiCES-rm2-musi-sp0868-ch131295-sg0032-mc02-lav-clo-dg020.wav", "answer": "why not as welcome death as life they are but counterparts one of the other the night and day of brahma through the disintegration of the old re creation becomes possible we have worshipped death", "subset": "musi", "task_type": "understanding", "prediction": "why not as welcome death as life they are but counterparts one of the other the night and day of brahma through the disintegration of the old re creation becomes possible we have worshipped death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 930, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0882/Lab41-SRI-VOiCES-rm2-musi-sp0882-ch123268-sg0033-mc02-lav-clo-dg090.wav", "answer": "this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour", "subset": "musi", "task_type": "understanding", "prediction": "this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 931, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm2-musi-sp0949-ch134657-sg0023-mc02-lav-clo-dg040.wav", "answer": "but his knowledge of his own temper prompted him to encourage and even to solicit the reproof of his friends and ministers and whenever they ventured to oppose the irregular sallies of his passions the spectators could observe the shame as well as the gratitude of their monarch", "subset": "musi", "task_type": "understanding", "prediction": "but his knowledge of his own temper prompted him to encourage and even to solicit the reproof of his friends and ministers and whenever they ventured to oppose the irregular sallies of his passions the spectators could observe the shame as well as the gratitude of the monarch", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 932, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm2-musi-sp0949-ch138545-sg0032-mc02-lav-clo-dg120.wav", "answer": "this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown", "subset": "musi", "task_type": "understanding", "prediction": "this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 933, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp0949/Lab41-SRI-VOiCES-rm2-musi-sp0949-ch162667-sg0034-mc01-stu-clo-dg020.wav", "answer": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "subset": "musi", "task_type": "understanding", "prediction": "and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 934, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp1052/Lab41-SRI-VOiCES-rm2-musi-sp1052-ch139307-sg0027-mc01-stu-clo-dg160.wav", "answer": "he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what council could it be that gathered there", "subset": "musi", "task_type": "understanding", "prediction": "he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what council could it be that gathered there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 935, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm2-musi-sp1066-ch103481-sg0026-mc02-lav-clo-dg080.wav", "answer": "each huddled dumbly to each but eyes could not lift from the sea only hands touched in the dawn he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream", "subset": "musi", "task_type": "understanding", "prediction": "each huddled dumbly to each but eyes could not lift from the sea only hands touched in the darkness he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 936, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm2-musi-sp1112-ch001043-sg0006-mc01-stu-clo-dg070.wav", "answer": "but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cozy", "subset": "musi", "task_type": "understanding", "prediction": "but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cozy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 937, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm2-musi-sp1160-ch139717-sg0004-mc01-stu-clo-dg160.wav", "answer": "however it gave him so high an opinion of my abilities in the confuting way that he seriously proposed my being his colleague in a project he had of setting up a new sect he was to preach the doctrines and i was to confound all opponents", "subset": "musi", "task_type": "understanding", "prediction": "however it gave him so high an opinion of my abilities in the confuting way that he seriously proposed my being his colleague in the project he had of setting up a new sect he was to preach the doctrines and i was to confound all opponents", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 938, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm2-musi-sp1160-ch139730-sg0019-mc01-stu-clo-dg050.wav", "answer": "undertook to repeat what he called the philadelphia experiments and after they were performed before the king and court all the curious of paris flocked to see them i will not swell this narrative with an account of that capital experiment", "subset": "musi", "task_type": "understanding", "prediction": "Undertook to repeat what he called the Philadelphia experiments. And after they were performed before the king and court, all the curious of Paris flocked to see them. I will not swell this narrative with an account of that capital experiment.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 939, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_0032-1182/sp1182/Lab41-SRI-VOiCES-rm2-musi-sp1182-ch133396-sg0014-mc01-stu-clo-dg150.wav", "answer": "he waited for a while and then knocked again rap tap tap presently with a click a little square wicket that pierced the door was opened and a woman's face peered out through the iron bars the one eyed hans whipped off his leathern cap", "subset": "musi", "task_type": "understanding", "prediction": "he waited for a while and then knocked again presently with a click a little square wicket that pierced the door was opened and the woman's face peered out through the iron bars the one eyed hans whipped off his leather cap", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 940, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch124548-sg0029-mc01-stu-clo-dg140.wav", "answer": "pointing with pride harry haydock as chairman introduced honest jim blausser and i am proud to say my fellow citizens that in his brief stay here mister blausser has become my warm personal friend as well as my fellow booster", "subset": "musi", "task_type": "understanding", "prediction": "pointing with pride harry haydock as chairman introduced honest jim blausser and i am proud to say my fellow citizens that in his brief stay here mr blausser has become my warm personal friend as well as my fellow booster", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 941, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch135815-sg0009-mc01-stu-clo-dg150.wav", "answer": "johnny here is not fond of the green forest but loves the old orchard and the green meadows in some parts of the country there are members of his family who prefer to live just on the edge of the green forest you will notice that johnny has stout claws", "subset": "musi", "task_type": "understanding", "prediction": "johnny here is not fond of the green forest but loves the old orchard and the green meadows in some parts of the country there are members of this family who prefer to live just on the edge of the green forest you will notice that johnny has stout claws", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 942, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch135815-sg0010-mc01-stu-clo-dg140.wav", "answer": "i can climb if i have to retorted johnny chuck indignantly i've climbed up bushes and low trees lots of times and if i can get a good run first i can climb up the straight trunk of a tree with rough bark to the first branches if they are not too far above ground", "subset": "musi", "task_type": "understanding", "prediction": "i can climb if i have to retorted johnny chuck indignantly i have climbed up bushes and low trees lots of times and if i can get a good run first i can climb up the straight trunk of a tree with rough bark to the first branches if they are not too far above ground", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 943, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch135815-sg0012-mc02-lav-clo-dg000.wav", "answer": "peter was delighted to air his knowledge the last one i was in said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it", "subset": "musi", "task_type": "understanding", "prediction": "peter was delighted to air his knowledge the last one i was in he said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 944, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm2-musi-sp1335-ch027593-sg0036-mc01-stu-clo-dg180.wav", "answer": "and simmer for twenty minutes in one quart of milk being careful that it does not boil season with salt pepper mace and cayenne add one cup of cream stir until very smooth", "subset": "musi", "task_type": "understanding", "prediction": "and simmer for twenty minutes in one quart of milk being careful that it does not boil season with salt pepper mace and cayenne add one cup of cream stir until very smooth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 945, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm2-musi-sp1335-ch163935-sg0023-mc01-stu-clo-dg060.wav", "answer": "boil with this a little bag of mixed spices and two onions unless the meat has a good deal of fat use crisco or oil two cups of rice will be the right amount to use with two pounds of meat", "subset": "musi", "task_type": "understanding", "prediction": "Boil with this. A little bag of mixed spices and two onions. Unless the meat has a good deal of fat, use Crisco or oil,2 cups of rice will be the right amount to use with £2 of meat.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 946, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm2-musi-sp1383-ch130489-sg0031-mc02-lav-clo-dg120.wav", "answer": "his troubled spirit shifted its load his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm", "subset": "musi", "task_type": "understanding", "prediction": "his troubled spirit shifted and slowed his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 947, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-musi-sp1392-ch128240-sg0014-mc02-lav-clo-dg020.wav", "answer": "fain likewise would it play with the fire of the fagot and stake and be on thy guard also against the assaults of thy love too readily doth the recluse reach his hand to any one who meeteth him", "subset": "musi", "task_type": "understanding", "prediction": "fain likewise would it play with the fire of the faggot and stake and be on thy guard also against the assaults of thy love too readily doff the recluse reach his hand to any one who needed it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 948, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-musi-sp1392-ch135659-sg0021-mc01-stu-clo-dg010.wav", "answer": "is derived merely from custom it may be asked how it happens that men so much surpass animals in reasoning and one man so much surpasses another has not the same custom the same influence on all", "subset": "musi", "task_type": "understanding", "prediction": "is derived merely from custom it may be asked how it happens that man so much surpasses animals in reasoning and one man so much surpasses another has not the same custom the same influence on all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 949, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1417/Lab41-SRI-VOiCES-rm2-musi-sp1417-ch001539-sg0019-mc02-lav-clo-dg160.wav", "answer": "here fanned by cool breezes and surrounded by fair women and brave men one may do a bit of tissue restoring moreover there is little danger up here of being slugged by our moth eaten acquaintance of this morning a man with trousers like his would not be allowed in", "subset": "musi", "task_type": "understanding", "prediction": "here fanned by cool breezes and surrounded by fair women and brave men what may do a bit of tissue restoring moreover there is little danger up here of being snubbed by our moth eaten acquaintance of this morning a man with trousers like his would not be allowed in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 950, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1425/Lab41-SRI-VOiCES-rm2-musi-sp1425-ch139291-sg0008-mc02-lav-clo-dg040.wav", "answer": "here too the slaves of all the other farms received their monthly allowance of food and their yearly clothing the men and women slaves received as their monthly allowance of food eight pounds of pork or its equivalent in fish and one bushel of corn meal", "subset": "musi", "task_type": "understanding", "prediction": "Here, too, the slaves of all the other farms received their monthly allowance of food and their yearly clothing. The men and women slaves received as their monthly allowance of food,£8 of pork or its equivalent in fish, and one bushel of corn meal.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 951, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1607/Lab41-SRI-VOiCES-rm2-musi-sp1607-ch134636-sg0016-mc01-stu-clo-dg070.wav", "answer": "and africa were accustomed to revere constans the third of his sons as the representative of the great constantine he fixed dalmatius on the gothic frontier to which he annexed the government of thrace macedonia and greece", "subset": "musi", "task_type": "understanding", "prediction": "and africa were accustomed to revere constans the third of his sons as the representative of the great constantine he fixed dalmatius on the gothic frontier to which he annexed the government of thrace macedonia and greece", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 952, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1607/Lab41-SRI-VOiCES-rm2-musi-sp1607-ch150715-sg0043-mc01-stu-clo-dg010.wav", "answer": "and the heiress of the norman line might struggle to check her despotic husband and to save the patrimony of her new born son of an emperor so famous in the next age under the name of frederic the second ten years after this revolution", "subset": "musi", "task_type": "understanding", "prediction": "and the heiress of the norman line might struggle to check her despotic husband and to save the patrimony of her new born son of an emperor so famous in the next age under the name of frederic the second ten years after this revolution", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 953, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1841/Lab41-SRI-VOiCES-rm2-musi-sp1841-ch179183-sg0017-mc01-stu-clo-dg110.wav", "answer": "now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful", "subset": "musi", "task_type": "understanding", "prediction": "now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 954, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm2-musi-sp1874-ch165701-sg0007-mc01-stu-clo-dg090.wav", "answer": "but also recited doggerel satire of his own concoction punning and emitting sparks of wit lincoln was hailed as the capper of any good things on the rounds even then his friends saw the germs of the statesman in the lank homely crack voiced hobbledehoy", "subset": "musi", "task_type": "understanding", "prediction": "but also recited doggerel satire of his own concoction punning and emitting sparks of wit lincoln was hailed as the capper of any good things on the rounds even then his friends saw the germs of the statesman in the lank homely cracked voiced hobbledehoy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 955, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm2-musi-sp1961-ch145733-sg0011-mc02-lav-clo-dg030.wav", "answer": "here he had to stay but the whole day he sat working and when evening was come he had made a pretty little pot all round it were little bells and when the pot boiled they jingled most beautifully and played the old tune where is augustus dear", "subset": "musi", "task_type": "understanding", "prediction": "here he had to stay but the whole day he sat working and when evening was come he had made a pretty little pot all around it were little bells and when the pot boiled they jingled most beautifully and played the old tune where is augustus dear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 956, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm2-musi-sp1961-ch149739-sg0018-mc02-lav-clo-dg070.wav", "answer": "he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor", "subset": "musi", "task_type": "understanding", "prediction": "he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 957, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2269/Lab41-SRI-VOiCES-rm2-musi-sp2269-ch088761-sg0002-mc02-lav-clo-dg010.wav", "answer": "but i developed with great rapidity and i believe men of science will tell you that this is always the case with low organisms that for instance while it takes years to develop the man from the baby and months to develop the dog from the puppy", "subset": "musi", "task_type": "understanding", "prediction": "but i developed with great rapidity and i believe men of science will tell you that this is always the case with low organisms that for instance while it takes years to develop the man from the baby and months to develop the dog from the puppy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 958, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2269/Lab41-SRI-VOiCES-rm2-musi-sp2269-ch088761-sg0032-mc01-stu-clo-dg160.wav", "answer": "for it seems such a dreadful fate for poor gertrude the curate looked startled why i don't profess to like mister zaluski he said but i don't know anything exactly against him but i do", "subset": "musi", "task_type": "understanding", "prediction": "poor it seems such a dreadful fate for poor gertrude the curate looks startled why i don't profess to like mr zaluski he said but i don't know anything exactly against him but i do", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 959, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm2-musi-sp2285-ch149890-sg0019-mc02-lav-clo-dg100.wav", "answer": "moderately interested in its welfare hurstwood's word however had gone the rounds it was to be a full dress affair the four boxes had been taken doctor norman mc neill hale and his wife were to occupy one", "subset": "musi", "task_type": "understanding", "prediction": "moderately interested in its welfare hurstwood s word however had gone the rounds it was to be a full dress affair the four boxes had been taken dr norman mc neil hale and his wife were to occupy one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 960, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm2-musi-sp2285-ch149890-sg0024-mc02-lav-clo-dg070.wav", "answer": "where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mister hurstwood came from the first individual recognised glad to see you said the latter grasping his hand lightly", "subset": "musi", "task_type": "understanding", "prediction": "where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mr hurstwood came from the first individual recognized glad to see you said the latter grasping his hand lightly", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 961, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm2-musi-sp2285-ch163381-sg0018-mc02-lav-clo-dg010.wav", "answer": "en give half un it to you en de yuther half to de yuther woman dat's de way sollermun was gwyne to do wid de chile now i want to ast you", "subset": "musi", "task_type": "understanding", "prediction": "and give half on it to you and de yuther half to de yuther woman dat s de way solomon was gwine to do wid de chile now i want to ask you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 962, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2289/Lab41-SRI-VOiCES-rm2-musi-sp2289-ch152258-sg0008-mc01-stu-clo-dg030.wav", "answer": "this woman was a widow who was carrying on the business left her by her husband as soon as the camel driver saw mohammed he stopped him and said my mistress wishes to see you before noon i think she intends to engage you to take charge of her caravans", "subset": "musi", "task_type": "understanding", "prediction": "this woman was a widow who was carrying on the business left her by her husband as soon as the camel driver saw mohammed he stopped him and said my mistress wishes to see you before noon i think she intends to engage you to take charge of her caravans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 963, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2294/Lab41-SRI-VOiCES-rm2-musi-sp2294-ch161707-sg0041-mc02-lav-clo-dg180.wav", "answer": "and finally shoot out point foremost into space through the open window and go up and up and up with a sound of rending atmospheres that seemed to tear like riven silk in one prolonged shriek under my head and to close up in thunder astern until my reeling senses could stand it no longer", "subset": "musi", "task_type": "understanding", "prediction": "and finally shoot up point foremost into space through the open window and go up and up and up with sound of rending atmospheres that seemed to tear like ribboned silk in one prolonged shriek under my head and to close up and thunder astern until my reeling senses could stand it no longer", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 964, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2294/Lab41-SRI-VOiCES-rm2-musi-sp2294-ch161714-sg0009-mc02-lav-clo-dg060.wav", "answer": "and there in the twilight was the litter of the feast still about gold cups and silver broken bread and meat the convolvulus flowers all turning their pallid faces to the rosy daylight making pools of brightness between the shadows", "subset": "musi", "task_type": "understanding", "prediction": "and there in the twilight was the litter of the feast still about gold cups and silver broken bread and meat the convolvulus flowers all turning their pallid faces to the rosy daylight making pools of brightness between the shadows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 965, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2294/Lab41-SRI-VOiCES-rm2-musi-sp2294-ch161714-sg0019-mc01-stu-clo-dg090.wav", "answer": "this latter was careening over as a dusky group of men lifted aboard to a heap of tumbled silks and stuffs in the stern such a sweet piece of insensible merchandise as no man i at least of all could mistake it was heru herself and the rogues were ladling her on board like so much sandal wood or cotton sheeting", "subset": "musi", "task_type": "understanding", "prediction": "this latter was careering over as a dusky group of men lifted aboard to a heap of tumbled silks and stuffs in the stern such a sweet piece of insensible merchandise as no man ay least of all could mistake it was heru herself and the robes were lailing her on board like so much sandal wood or cotton sheet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 966, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-musi-sp2412-ch153948-sg0006-mc02-lav-clo-dg100.wav", "answer": "i was to see the sheep not necessarily close at hand nor to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet", "subset": "musi", "task_type": "understanding", "prediction": "i was to see the sheep not necessarily close at hand or to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 967, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-musi-sp2412-ch153954-sg0015-mc02-lav-clo-dg040.wav", "answer": "suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome", "subset": "musi", "task_type": "understanding", "prediction": "suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 968, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2532/Lab41-SRI-VOiCES-rm2-musi-sp2532-ch157475-sg0017-mc02-lav-clo-dg070.wav", "answer": "marcella came up to the nursery and played all day watching the rain patter upon the new tin gutter she wondered where raggedy andy was although she did not get worried about him until she had asked mama where he might be he must be just where you left him mama said", "subset": "musi", "task_type": "understanding", "prediction": "marcella came up to the nursery and played all day watching the rain patter upon the new tin gutter she wondered where raggily andy was although she did not get worried about him until she had asked mamma where he might be he must be just where you left him mamma said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 969, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2573/Lab41-SRI-VOiCES-rm2-musi-sp2573-ch178449-sg0048-mc01-stu-clo-dg140.wav", "answer": "he could only stare bewildered every evening i want you they sha'n't hurt you again and she held out her hand to him it was strong and warm in his tremulous clasp if i could i'd go and feed the strips of zinc to the machine with you she said", "subset": "musi", "task_type": "understanding", "prediction": "he could only stare bewildered every evening i want you they shan hurt you again and she held out her hand to him it was strong and warm in his tremulous clasp if i could i go and feed the strips of zinc to the machine with you she said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 970, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp2691/Lab41-SRI-VOiCES-rm2-musi-sp2691-ch156750-sg0023-mc02-lav-clo-dg100.wav", "answer": "for it had a beautiful picture near the back showing a little girl with a sprinkling pot watering her garden of stocks sweet williams and hollyhocks her hair was in four long curls and she had trimming on her dress apron and long pantalets", "subset": "musi", "task_type": "understanding", "prediction": "for it had a beautiful picture near the back showing a little girl with a sprinkling pot watering her garden of stocks sweet williams and hollyhocks her hair was in four long curls and she had trimming on her dress apron and long pantaloons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 971, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3235/Lab41-SRI-VOiCES-rm2-musi-sp3235-ch028433-sg0003-mc01-stu-clo-dg060.wav", "answer": "where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more", "subset": "musi", "task_type": "understanding", "prediction": "where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 972, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3235/Lab41-SRI-VOiCES-rm2-musi-sp3235-ch028433-sg0003-mc02-lav-clo-dg060.wav", "answer": "where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more", "subset": "musi", "task_type": "understanding", "prediction": "where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 973, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3235/Lab41-SRI-VOiCES-rm2-musi-sp3235-ch028452-sg0013-mc02-lav-clo-dg110.wav", "answer": "for which she has a whole heartful of love and the sight of which is better to her than medicine during the month of july we eagerly watched the incoming steamers and welcomed all new comers who landed in chinik", "subset": "musi", "task_type": "understanding", "prediction": "for which she has a whole heart full of love and the sight of which is better to her than medicine during the month of july we eagerly watched the incoming steamers and welcomed all newcomers who landed in chinik", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 974, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm2-musi-sp3368-ch170951-sg0019-mc01-stu-clo-dg130.wav", "answer": "and therefore the cause of well being yes it follows therefore that the good is not the cause of all things but of the good only assuredly then god if he be good is not the author of all things as the many assert but he is the cause of", "subset": "musi", "task_type": "understanding", "prediction": "and therefore the cause of well being yes it follows therefore that the good is not the cause of all things but of the good only assuredly then god if he be good is not the author of all things as the many assert but he is the cause", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 975, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-musi-sp3446-ch144021-sg0018-mc02-lav-clo-dg090.wav", "answer": "mate down with fever ngora ngora sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset", "subset": "musi", "task_type": "understanding", "prediction": "mate down with fever negoro negoro sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 976, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-musi-sp3446-ch176270-sg0003-mc02-lav-clo-dg030.wav", "answer": "the inhabitants of which although faithful to their rulers being influenced more by immediate danger than by attachment to their distant friends surrendered in the same manner they obtained massa and serezana toward the end of may they proceeded in the direction of lucca", "subset": "musi", "task_type": "understanding", "prediction": "the inhabitants of which although faithful to their rulers being influenced more by immediate danger than by attachment to their distant friends surrendered in the same manner they obtained massa and serenzana towards the end of may they proceeded in the direction of lucca", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 977, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm2-musi-sp3483-ch119637-sg0013-mc01-stu-clo-dg110.wav", "answer": "that did not seem real to me and my mind still resisted i remember gazing with staring eyes at that picture the sweat pouring down my face searching eagerly for some visible evidence of fraud and being unable to find it it was the identical likeness of wilma", "subset": "musi", "task_type": "understanding", "prediction": "they did not seem real to me and my mind still resisted i remember gazing with staring eyes at that picture the sweat pouring down my face searching eagerly for some visible evidence of fraud and being unable to find it it was the identical likeness of wilmot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 978, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm2-musi-sp3483-ch119637-sg0028-mc02-lav-clo-dg040.wav", "answer": "this creature his most prized possession san lan with the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil arts had i not seen the naked horror of her soul", "subset": "musi", "task_type": "understanding", "prediction": "this creature his most prized possession san lawn of the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil arts had i not seen the naked horror of her soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 979, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm2-musi-sp3549-ch171171-sg0023-mc02-lav-clo-dg070.wav", "answer": "and as great a quantity of provisions as would suffice them for a long time and let himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old", "subset": "musi", "task_type": "understanding", "prediction": "and as great a quantity of provisions as would suffice them for a long time and led himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 980, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm2-musi-sp3549-ch173591-sg0001-mc01-stu-clo-dg090.wav", "answer": "but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots", "subset": "musi", "task_type": "understanding", "prediction": "but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 981, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm2-musi-sp3835-ch178029-sg0001-mc02-lav-clo-dg100.wav", "answer": "caused russians to grieve he had such a sad face when shown into the emperor's study that the latter at once asked have you brought me sad news colonel very sad sire replied michaud lowering his eyes with a sigh the abandonment of moscow", "subset": "musi", "task_type": "understanding", "prediction": "caused russians to grieve he had such a sad face when shown into the emperor s study that the latter at once asked have you brought me sad news colonel very sad sir replied mashuk covering his eyes with a sigh the abandonment of moscow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 982, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm2-musi-sp3835-ch178030-sg0027-mc01-stu-clo-dg010.wav", "answer": "everything went well and easily the landowner to whom nicholas went was a bachelor an old cavalryman a horse fancier a sportsman the possessor of some century old brandy and some old hungarian wine who had a snuggery where he smoked", "subset": "musi", "task_type": "understanding", "prediction": "everything went well and easily the landowner to whom nicholas went was a bachelor an old cavalryman a horse fancier a sportsman the possessor of some century old brandy and some old hungarian wine who had a snuggery where he smoked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 983, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm2-musi-sp3923-ch153309-sg0024-mc02-lav-clo-dg100.wav", "answer": "he took it for the instinctive recognition it undoubtedly was he therefore watched him narrowly and succeeded in getting one glance from his eye it was enough the man was commonplace commonplace in feature dress and manner but his eye gave him away", "subset": "musi", "task_type": "understanding", "prediction": "took it for the instinctive recognition it undoubtedly was he therefore watched him narrowly and succeeded in getting one glance from his eyes it was enough the man was commonplace commonplace in feature and dress and manner but his eye gave him away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 984, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm2-musi-sp3923-ch174992-sg0031-mc02-lav-clo-dg050.wav", "answer": "to whom can i apply to appoint others don't you know what vested interests mean lord chiltern then nobody can manage his own property as he pleases nobody can unless he does the work himself if i were to go and live in trumpeton wood i could do it but you see i have to live here", "subset": "musi", "task_type": "understanding", "prediction": "to whom can i apply to appoint others don t you know what vested interests mean orchard that nobody can manage his own property as he pleases nobody can unless he does the work himself if i were to go and live in trumpeton what i could do but you see i have to live here", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 985, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp3972/Lab41-SRI-VOiCES-rm2-musi-sp3972-ch185074-sg0012-mc02-lav-clo-dg020.wav", "answer": "no one can conceive of the constant trouble that i daily endured on their account on the account of my two oldest sons whom i loved equally and with all the feelings and affection of a tender mother stimulated by an anxious concern for their fate", "subset": "musi", "task_type": "understanding", "prediction": "no one can conceive of the constant trouble that i daily endured on their account on the account of my two oldest sons whom i loved equally and with all the feelings and affection of a tender mother stimulated by an anxious concern for their fate", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 986, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm2-musi-sp4014-ch186176-sg0015-mc01-stu-clo-dg120.wav", "answer": "won't do it slim muttered oh yes you will counseled joe shake hands the two of you slim's good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we're square said slim", "subset": "musi", "task_type": "understanding", "prediction": "won t do it slim muttered oh yes you will counseled joe shake hands the two of you slim s good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we re square said slim", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 987, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4057/Lab41-SRI-VOiCES-rm2-musi-sp4057-ch011254-sg0000-mc01-stu-clo-dg000.wav", "answer": "great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse", "subset": "musi", "task_type": "understanding", "prediction": "great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 988, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4057/Lab41-SRI-VOiCES-rm2-musi-sp4057-ch011254-sg0000-mc02-lav-clo-dg000.wav", "answer": "great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse", "subset": "musi", "task_type": "understanding", "prediction": "great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 989, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm2-musi-sp4064-ch012118-sg0036-mc02-lav-clo-dg020.wav", "answer": "his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her", "subset": "musi", "task_type": "understanding", "prediction": "his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 990, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm2-musi-sp4064-ch077779-sg0014-mc02-lav-clo-dg010.wav", "answer": "and provokes a great deal of innocent mirth you don't yourself believe that last yarn about the prohibition candidate do you i haven't heard any yarn about him said the bibliomaniac that he is the owner of a brewery up in rochester", "subset": "musi", "task_type": "understanding", "prediction": "and provokes a great deal of innocent mirth you dont yourself believe that last yarn about the prohibition candidate do you i havent heard any yarn about him said the bibliomaniac that he is the owner of the brewery of the brochester", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 991, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4110/Lab41-SRI-VOiCES-rm2-musi-sp4110-ch011528-sg0022-mc02-lav-clo-dg060.wav", "answer": "unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and", "subset": "musi", "task_type": "understanding", "prediction": "unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 992, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4110/Lab41-SRI-VOiCES-rm2-musi-sp4110-ch011533-sg0015-mc01-stu-clo-dg130.wav", "answer": "jaska merely smiled her inscrutable smile and did not answer by intuition she already knew let sarka arrive at her conclusion by scientific methods if he desired and she would simply smile anew", "subset": "musi", "task_type": "understanding", "prediction": "jaska merely smiled her inscrutable smile and did not answer by intuition she already knew let sarka arrive at her conclusion by scientific methods if he desired and she would simply smile anew", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 993, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4145/Lab41-SRI-VOiCES-rm2-musi-sp4145-ch034497-sg0032-mc02-lav-clo-dg100.wav", "answer": "inevitable he thought things could not go on as before but he said something different it can't go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life", "subset": "musi", "task_type": "understanding", "prediction": "inevitable he thought things could not go on as before but he said something different it can go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 994, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4160/Lab41-SRI-VOiCES-rm2-musi-sp4160-ch011549-sg0020-mc01-stu-clo-dg120.wav", "answer": "she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin's wishes in the matter of military balls and blue satin slippers", "subset": "musi", "task_type": "understanding", "prediction": "she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin s wishes in the matter of military balls and blue satin slippers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 995, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4331/Lab41-SRI-VOiCES-rm2-musi-sp4331-ch057179-sg0029-mc01-stu-clo-dg170.wav", "answer": "with a great effort she restrained all emotion and simply shook her head she did it very well and betrayed nothing i ask said the duchess because i have been very glad to hear that you are engaged to marry him lord drummond tells me that he is a most respectable young man", "subset": "musi", "task_type": "understanding", "prediction": "with a great effort she restrained all emotion and simply shook her head she did it very well and betrayed nothing i ask said the duchess because i have been very glad to hear that you are engaged to marry him lord drummond tells me that he is a most respectable young man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 996, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch012471-sg0006-mc02-lav-clo-dg090.wav", "answer": "and had promised to render the water such as they desired it to be in case they would be subservient to him in what he should enjoin them to do and this not after a remiss or negligent manner and when they asked what they were to do in order to have the water changed for the better", "subset": "musi", "task_type": "understanding", "prediction": "and had promised to render the water such as they desired it to be in case they would be subservient to him in what he should enjoin them to do and this not after a remiss or negligent manner and when they asked what they were to do in order to have the water changed for the better", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 997, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch012471-sg0008-mc01-stu-clo-dg160.wav", "answer": "and meeting with no relief they were in a very desponding condition and by fixing their attention upon nothing but their present misfortunes they were hindered from remembering what deliverances they had received from god and those by the virtue and wisdom of moses also", "subset": "musi", "task_type": "understanding", "prediction": "and meeting with no relief they were in a very desponding condition and by fixing their attention upon nothing but their present misfortunes they were hindered from remembering what deliverances they had received from god and those by the virtue and wisdom of moses also", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 998, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch020028-sg0020-mc01-stu-clo-dg140.wav", "answer": "she never forgot it and always packed it very carefully too i asked her two or three times to let me put it in my trunk where i had slyly arranged a nice little place full of hard surfaces and sharp corners but she always had plenty of room", "subset": "musi", "task_type": "understanding", "prediction": "she never forgot it and always packed it very carefully too i asked her two or three times to let me put it in my trunk where i had slyly arranged a nice little place full of hard surfaces and sharp corners but she always had plenty of room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 999, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch041933-sg0009-mc01-stu-clo-dg040.wav", "answer": "but as he felt much stronger and better he made up his mind that this strange adventure must really have happened and he sprang on his horse and rode off with a light heart to look for his companions in a few weeks they began to set out on their return home", "subset": "musi", "task_type": "understanding", "prediction": "but as he felt much stronger and better he made up his mind that this strange adventure must really have happened and he sprang on his horse and rode off with a light heart to look for his companions in a few weeks they began to set out on their return home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1000, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm2-musi-sp4438-ch048513-sg0013-mc01-stu-clo-dg170.wav", "answer": "when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her", "subset": "musi", "task_type": "understanding", "prediction": "when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1001, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm2-musi-sp4441-ch076263-sg0010-mc02-lav-clo-dg160.wav", "answer": "partly because he had no servant and partly because he had nothing with which to make a fire no servant had brushed his clothes or brought his coffee and yet he was standing before his easel whistling merrily engaged in painting a brilliant sunset when there came four knocks at the door", "subset": "musi", "task_type": "understanding", "prediction": "partly because he had no servant and partly because he had nothing with which to make a fire no servant had brushed his clothes or brought his coffee and yet he was standing before his easel whistling merrily and engaged in painting a brilliant sunset when there came four knocks at the door", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1002, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm2-musi-sp4441-ch076263-sg0031-mc02-lav-clo-dg050.wav", "answer": "the figure the amount i could do with say sixty crowns good lord how modest you are remarked borg and turned to levin yes it is very little said the latter take as much as you can get falk while the purse is open", "subset": "musi", "task_type": "understanding", "prediction": "the figure the amount i could do with say sixty crowns good lord how modest you are remarked bour and turned to levin yes it is very little said the latter take as much as you can get fob while the purse is open", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1003, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-musi-sp4535-ch279849-sg0033-mc01-stu-clo-dg130.wav", "answer": "fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller", "subset": "musi", "task_type": "understanding", "prediction": "fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1004, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-musi-sp4535-ch279852-sg0008-mc02-lav-clo-dg120.wav", "answer": "i'll let a bullet go smack into the first man that makes a move he shouldn't here was a man they couldn't talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later", "subset": "musi", "task_type": "understanding", "prediction": "i ll let a bullet go smack into the first man that makes a move he shouldn t here was a man they couldn t talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1005, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4586/Lab41-SRI-VOiCES-rm2-musi-sp4586-ch061758-sg0016-mc01-stu-clo-dg160.wav", "answer": "were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of head gear it was possible he might have seen fit to change the fashion", "subset": "musi", "task_type": "understanding", "prediction": "were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of headgear it was possible he might have seen fit to change the fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1006, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4586/Lab41-SRI-VOiCES-rm2-musi-sp4586-ch061758-sg0016-mc02-lav-clo-dg160.wav", "answer": "were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of head gear it was possible he might have seen fit to change the fashion", "subset": "musi", "task_type": "understanding", "prediction": "were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of headgear it was possible he might have seen fit to change the fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1007, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4744/Lab41-SRI-VOiCES-rm2-musi-sp4744-ch031668-sg0002-mc02-lav-clo-dg000.wav", "answer": "it was curious this instinctive aversion she felt to being shut in by trees especially a kind of claustrophobia almost probably due as has been said to the days in india when the trees took her husband off and surrounded him with dangers", "subset": "musi", "task_type": "understanding", "prediction": "it was curious this instinctive aversion she felt to being shut in by trees especially a kind of claustrophobia almost probably due as had been said to the days in india when the trees took her husband off and surrounded him with dangers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1008, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4744/Lab41-SRI-VOiCES-rm2-musi-sp4744-ch031668-sg0017-mc01-stu-clo-dg120.wav", "answer": "this she could understand in a fashion at least and make allowances for she had yielded gently even sweetly to his choice of their english home for in the little island there is nothing that suggests the woods of wilder countries so nearly as the new forest", "subset": "musi", "task_type": "understanding", "prediction": "this she could understand in a fashion at least and make allowances for she had yielded gently even sweetly to his choice of their english home for in the little island there is nothing that suggests the woods of wilder countries so nearly as the new forest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1009, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm2-musi-sp4839-ch015307-sg0003-mc01-stu-clo-dg050.wav", "answer": "and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at treviso when emperor maximilian's commissioner presented himself in order to take possession of it", "subset": "musi", "task_type": "understanding", "prediction": "and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor von jedlau and his allies of combrein but at treviso when emperor maximilian s commissioner presented himself in order to take possession of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1010, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm2-musi-sp4848-ch101836-sg0009-mc01-stu-clo-dg180.wav", "answer": "let me out of this trap and i will not hurt you save me from the rain that i may save you from the sun if you should need help so mvoo laana believed him and let him out of the trap and simba kongway before going his way said", "subset": "musi", "task_type": "understanding", "prediction": "let me out of this trap and i will not hurt you save me from the rain that i may save you from the sun if you should need help so mavoullon had believed him and let him out of the trap and simbaconway before going his way said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1011, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4859/Lab41-SRI-VOiCES-rm2-musi-sp4859-ch022176-sg0008-mc02-lav-clo-dg110.wav", "answer": "and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman", "subset": "musi", "task_type": "understanding", "prediction": "and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1012, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4957/Lab41-SRI-VOiCES-rm2-musi-sp4957-ch023295-sg0011-mc02-lav-clo-dg120.wav", "answer": "without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sandford interrupted the menace prepared for utterance saying and you still mean i suppose to make mister rushbrook your heir", "subset": "musi", "task_type": "understanding", "prediction": "without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sanford interrupted the menace prepared for utterance saying and you still mean i suppose to make mr rushworth your heir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1013, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4967/Lab41-SRI-VOiCES-rm2-musi-sp4967-ch026520-sg0005-mc02-lav-clo-dg170.wav", "answer": "because it could not be avoided but their bodies and colors must be changed with their diet especially while they would be clearly discovered by the finer appearance of the other children who would fare better and thus they should bring him into danger and occasion him to be punished", "subset": "musi", "task_type": "understanding", "prediction": "because it could not be avoided but their bodies and colours must be changed with their dying especially while it would be clearly discovered by the finer appearance of the other children who would fare better and thus they should bring him into danger and occasion him to be punished", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1014, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp4967/Lab41-SRI-VOiCES-rm2-musi-sp4967-ch028868-sg0016-mc01-stu-clo-dg080.wav", "answer": "i only meant that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for awhile and then repeated his words i think i will go abroad not for long i hope sir", "subset": "musi", "task_type": "understanding", "prediction": "i only meant that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for a while and then repeated his words i think i will go abroad not for long i hope sir", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1015, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5126/Lab41-SRI-VOiCES-rm2-musi-sp5126-ch034483-sg0024-mc01-stu-clo-dg000.wav", "answer": "but this time she found a big one quite of herself and there was a general scream of delight lily has found a mushroom then they reached the river put the horses under the birch trees and went to the bathing place", "subset": "musi", "task_type": "understanding", "prediction": "but this time she found a big one quite of herself and there was a general scream of delight lily has found a mushroom then they reached the river put the horses under the birch trees and went to the bathing place", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1016, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm2-musi-sp5154-ch026558-sg0010-mc01-stu-clo-dg140.wav", "answer": "sweet little banana the image of wax answered never a word then the monkey called out in his loudest voice o peddler boy peddler boy if you don't give me a banana i'll give you such a push that it will upset", "subset": "musi", "task_type": "understanding", "prediction": "sweet little banana the image of wax as if never a word then the monkey called out in his loudest voice oh peddler boy peddler boy if you don t give me a banana i ll give you such a push that it will upset", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1017, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5154/Lab41-SRI-VOiCES-rm2-musi-sp5154-ch026558-sg0022-mc01-stu-clo-dg150.wav", "answer": "the monkey was at last able to pull out one of his hands the sun poured down more of his hottest rays and soon the monkey was able to pull out his two hands then he could pull out one foot then another and in a little while his body too", "subset": "musi", "task_type": "understanding", "prediction": "The monkey was at last able to pull out one of his hands. The sun poured down more of his hottest rays, and soon the monkey was able to pull out his two hands. Then he could pull out 1 ft. Then another. And in a little while, his body, too.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1018, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5157/Lab41-SRI-VOiCES-rm2-musi-sp5157-ch047238-sg0003-mc02-lav-clo-dg170.wav", "answer": "which should join you as soon as the weather would permit at present indeed it is not very encouraging for row boats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry", "subset": "musi", "task_type": "understanding", "prediction": "which should join you as soon as the weather would permit at present indeed it is not very encouraging for rupees we wait a courier from vienna to decide the march of eight thousand eight hundred infantry", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1019, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm2-musi-sp5189-ch056574-sg0007-mc02-lav-clo-dg120.wav", "answer": "sich a magnificent chance to make it manifest try yoor self particularly on custer tho after all continyood he in a musin abstracted sort a way wich he's fallen into lately the fellow is sich a triflin bein", "subset": "musi", "task_type": "understanding", "prediction": "such a magnificent chance to make it manifest try yourself particularly on custer though after all continued he in a musing abstracted sort of way which he has fallen into lately the fellow is such a trifling being", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1020, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm2-musi-sp5189-ch059288-sg0037-mc01-stu-clo-dg060.wav", "answer": "combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting", "subset": "musi", "task_type": "understanding", "prediction": "combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1021, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5319/Lab41-SRI-VOiCES-rm2-musi-sp5319-ch084357-sg0004-mc01-stu-clo-dg150.wav", "answer": "published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers", "subset": "musi", "task_type": "understanding", "prediction": "published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1022, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm2-musi-sp5401-ch039515-sg0002-mc01-stu-clo-dg020.wav", "answer": "the mesozoic comprises three systems the triassic named from its threefold division in germany the jurassic which is well displayed in the jura mountains and the cretaceous which contains the extensive chalk latin creta deposits of europe in eastern north america", "subset": "musi", "task_type": "understanding", "prediction": "the mesozoic comprises three systems the triassic named from its threefold division in germany the jurassic which is well displayed in the jura mountains and the cretaceous which contains the extensive chalk latin creta deposits of europe in eastern north america", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1023, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm2-musi-sp5401-ch039515-sg0008-mc01-stu-clo-dg010.wav", "answer": "these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood", "subset": "musi", "task_type": "understanding", "prediction": "these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1024, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch024741-sg0014-mc01-stu-clo-dg050.wav", "answer": "which association arises in the mind according to the order and association of the modifications affectiones of the human body i say first it is an association of those ideas only", "subset": "musi", "task_type": "understanding", "prediction": "which associations arises in the mind according to the order and association of the modifications affections of the human body i say first it is an association of those ideas only", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1025, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch024741-sg0019-mc01-stu-clo-dg070.wav", "answer": "and hence we can further clearly understand why the mind from the thought of one thing should straightway arrive at the thought of another thing which has no similarity with the first for instance from the thought of the word pomum an apple", "subset": "musi", "task_type": "understanding", "prediction": "and hence we can further clearly understand why the mind from the thought of one thing should straightway arrive at the thought of another thing which has no similarity with the first for instance from the thought of the word pomum an apple", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1026, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch062014-sg0015-mc01-stu-clo-dg030.wav", "answer": "o o goo coo o o goo coo ez he flewed off inter de darkness here aunt phrony spread her arms like wings and made a swoop half way across the room to the bedside of the startled children an she continued", "subset": "musi", "task_type": "understanding", "prediction": "ooh goo coo ooh goo coo as he flewed off into de darkness here aunt phrony spread her arms like wings and made a swoop halfway across the room to the bedside of the startled troy and she continued", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1027, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch062043-sg0024-mc02-lav-clo-dg020.wav", "answer": "this wood seems rather better than that we took in at yellow face's but we're nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask em what's the price of wood up here i've got you again", "subset": "musi", "task_type": "understanding", "prediction": "this wood seems rather better than that we took in at yellow faces but we are nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask them what is the price of wood up here i have got you again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1028, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm2-musi-sp5635-ch044582-sg0022-mc01-stu-clo-dg080.wav", "answer": "such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration", "subset": "musi", "task_type": "understanding", "prediction": "such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1029, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm2-musi-sp5678-ch043302-sg0023-mc01-stu-clo-dg030.wav", "answer": "she loved to see him like this his confident flushed face the enthusiasm in his blue eyes and the knowledge of his pain pricked her feeling with passion she bent forward and kissed him suddenly my dear i am so proud of you oh oliver he said nothing", "subset": "musi", "task_type": "understanding", "prediction": "she loved to see him like this his confident flushed face the enthusiasm in his blue eyes and the knowledge of his pain pricked her feeling with passion she bent forward and kissed him suddenly my dear i am so proud of you oh oliver he said nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1030, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm2-musi-sp5717-ch094876-sg0029-mc01-stu-clo-dg140.wav", "answer": "but what's happened to you where did you get that donkey head really i wouldn't have known you at all shaggy man if i hadn't looked at your feet the shaggy man introduced johnny dooit to dorothy and toto and button bright and the rainbow's daughter", "subset": "musi", "task_type": "understanding", "prediction": "but what has happened to you where did you get that donkey head really i wouldn't have known you at all shaggy man if i hadn't looked at your feet the shaggy man introduced johnny dooit to dorothy and toto and button bright and the rainbow star", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1031, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5740/Lab41-SRI-VOiCES-rm2-musi-sp5740-ch039910-sg0011-mc01-stu-clo-dg030.wav", "answer": "sat before the fire and listened to the wind howling about the house i'm glad i'm not driving over the prairie tonight said mister joseph it's quite a storm i hope it will be fine tomorrow for the children's sake they've set their hearts on having a sleigh ride", "subset": "musi", "task_type": "understanding", "prediction": "sat before the fire and listened to the wind howling about the house i am glad i am not driving over the prairie to night said mr joseph it is quite a storm i hope it will be fine to morrow for the childrens sake they have set their hearts on having a sleigh ride", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1032, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5740/Lab41-SRI-VOiCES-rm2-musi-sp5740-ch097593-sg0001-mc02-lav-clo-dg080.wav", "answer": "he was a young scarecrow and this was his first one he was strongly made and although his wooden joints creaked a little when the wind blew he did not grow in the least rickety every morning when the wintry sun peered like a hard yellow eye across the dry corn stubble", "subset": "musi", "task_type": "understanding", "prediction": "he was a young scarecrow and this was his first one he was strongly made and although his wooden joints creaked a little when the wind blew he did not grow the least rickety every morning when the wintry sun peered like a hard yellow eye across the dry corn stubble", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1033, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-musi-sp5935-ch043305-sg0006-mc02-lav-clo-dg120.wav", "answer": "that they were already in the tunnel the stoppage might arise from many causes and he was not greatly excited nor did it seem that others in the carriage took it very seriously he could hear after a moment's silence the talking recommence beyond the partition", "subset": "musi", "task_type": "understanding", "prediction": "that they were already in the tunnel the stoppage might arise from many causes and he was not greatly excited nor did it seem that others in the carriage took it very seriously he could hear after a moment s silence the talking recommence beyond the partition", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1034, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-musi-sp5935-ch043322-sg0019-mc01-stu-clo-dg020.wav", "answer": "after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not", "subset": "musi", "task_type": "understanding", "prediction": "after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1035, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-musi-sp5935-ch055927-sg0036-mc02-lav-clo-dg100.wav", "answer": "had the effect of enabling shippers to realise upon the goods carried more speedily than would have been possible under the old system of sail power alone it is already found that in the matter of economy of working including interest on cost of vessel and cargo", "subset": "musi", "task_type": "understanding", "prediction": "had the effect of enabling shippers to realize upon the goods carried more speedily than would have been possible under the old system of sail power alone it is already found that in the matter of economy of working including interest on cost of vessel and cargo", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1036, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp5968/Lab41-SRI-VOiCES-rm2-musi-sp5968-ch061356-sg0007-mc02-lav-clo-dg020.wav", "answer": "the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father's house in london and alice peel was she thinking of him", "subset": "musi", "task_type": "understanding", "prediction": "the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father s house in london and alice peel was she thinking of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1037, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm2-musi-sp6147-ch034607-sg0017-mc02-lav-clo-dg170.wav", "answer": "predicted that being the elder sister of fire she would be queen and so she was thanks to astrology and the revolution of sixteen eighty eight she had the humiliation of having only gilbert archbishop of canterbury for godfather to be godchild of the pope was no longer possible in england", "subset": "musi", "task_type": "understanding", "prediction": "predicted that being the elder sister of fire she would be queen and so she was thanks to astrology and the revolution of sixteen eighty eight she had the humiliation of having only gilbert archbishop of canterbury for godfather to be godchild of the pope was no longer possible in england", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1038, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm2-musi-sp6147-ch034607-sg0031-mc02-lav-clo-dg080.wav", "answer": "in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher wren is a very passable mansard somers is as good as lamoignon anne has a racine in dryden", "subset": "musi", "task_type": "understanding", "prediction": "in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher red is a very passable mousart somers is as good as le moignon anne has a racine in dryden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1039, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061943-sg0013-mc02-lav-clo-dg080.wav", "answer": "then without further remark he put his finger to his lips frowned darkly and descended into the small boat which awaited us", "subset": "musi", "task_type": "understanding", "prediction": "Then, without further remark, he put his finger to his lips. Frowned darkly and descended into the small boat, which awaited us.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1040, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061946-sg0006-mc01-stu-clo-dg130.wav", "answer": "i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur", "subset": "musi", "task_type": "understanding", "prediction": "i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1041, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061946-sg0011-mc01-stu-clo-dg130.wav", "answer": "here and there could be seen an isolated farm some solitary bur or icelandic house built of wood earth fragments of lava looking like beggars on the highway of life", "subset": "musi", "task_type": "understanding", "prediction": "here and there could be seen an isolated farm some solitary ver or icelandic house built of wood earth fragments of lava looking like beggars on the highway of life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1042, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061946-sg0020-mc01-stu-clo-dg060.wav", "answer": "at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor's legs and left him standing with both feet on a separate stone like the colossus of rhodes", "subset": "musi", "task_type": "understanding", "prediction": "at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor s legs and left him standing with both feet on a separate stone like the colossus of rhodes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1043, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch066616-sg0008-mc01-stu-clo-dg140.wav", "answer": "curiously enough the blood of wabi ran almost pure to his indian forefathers while minnetaki as she became older developed less of the wild beauty of her mother and more of the softer loveliness of the white race her wealth of soft jet black hair and her great dark eyes contrasting with the lighter skin of her father's blood", "subset": "musi", "task_type": "understanding", "prediction": "Curiously enough, the blood of Wabi ran almost pure to his Indian forefathers, while Minnetaki, as she became older, developed less of the wild beauty of her mother and more of the softer loveliness of the white race. Her wealth of soft jet black hair and her great dark eyes, contrasting with the lighter skin of her father's blood.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1044, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm2-musi-sp6385-ch220959-sg0035-mc01-stu-clo-dg000.wav", "answer": "which can be compared to father and mother and it is absolute perfection but the darkness has neither substance nor form neither father nor mother and it is absolute imperfection the substance of adam's physical life was earth", "subset": "musi", "task_type": "understanding", "prediction": "which can be compared to father and mother and it is absolute perfection but the darkness has neither substance nor form neither father nor mother and it is absolute imperfection the substance of adam s physical life was earth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1045, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm2-musi-sp6395-ch084349-sg0027-mc02-lav-clo-dg070.wav", "answer": "for months this system of solitary confinement was endured by the child who reduced to a state of helpless stupidity no longer attempted to change his linen or cleanse himself and was allowed to drift into a condition of utter imbecility", "subset": "musi", "task_type": "understanding", "prediction": "For months, this system of solitary confinement was endured by the child who reduced to the state of helpless stupidity, no longer attempted to change his linen or cleanse himself and was allowed to drift into a condition of utter imbecility.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1046, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm2-musi-sp6519-ch231834-sg0034-mc02-lav-clo-dg000.wav", "answer": "which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greeb's very lively imagination yet even though he reduced her communications to bare facts", "subset": "musi", "task_type": "understanding", "prediction": "which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greene s very lively imagination yet even though he reduced her communications to bare facts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1047, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-musi-sp6544-ch071420-sg0016-mc02-lav-clo-dg150.wav", "answer": "if you go back do you know what they will do they will surely hang you oh merciful heaven do not say that i wouldn't if it wasn't so but i've been talking to the coroner and the chief of police and they have all of the evidence as straight as a string", "subset": "musi", "task_type": "understanding", "prediction": "if you go back do you know what they will do they will surely hang you oh merciful heaven do not say that i wouldnt if it wasnt so but i have been talking to the coroner and the chief of police and they have all the evidence as straight as a string", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1048, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-musi-sp6544-ch231862-sg0036-mc02-lav-clo-dg000.wav", "answer": "he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost", "subset": "musi", "task_type": "understanding", "prediction": "he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1049, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm2-musi-sp6574-ch070753-sg0034-mc01-stu-clo-dg000.wav", "answer": "the arrival of the arabian now infused new life into his soul when the news reached leghorn that felix was deprived of his wealth and rank the merchant commanded his daughter to think no more of her lover but to prepare to return to her native country", "subset": "musi", "task_type": "understanding", "prediction": "The arrival of the Arabian now infused new life into his soul. When the news reached Leghorn that Felix was deprived of his wealth and rank, the merchant commanded his daughter to think no more of her lover. But to prepare to return to her native country.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1050, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm2-musi-sp6574-ch070756-sg0028-mc01-stu-clo-dg070.wav", "answer": "and become linked to the chain of existence and events from which i am now excluded i paused some time to reflect on all he had related and the various arguments which he had employed i thought of the promise of virtues which he had displayed on the opening of his existence", "subset": "musi", "task_type": "understanding", "prediction": "and become linked to the chain of existence and events from which i am now excluded i paused some time to reflect on all he had related and the various arguments which he had employed i thought of the promise of virtues which he had displayed on the opening of his existence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1051, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6696/Lab41-SRI-VOiCES-rm2-musi-sp6696-ch073296-sg0037-mc02-lav-clo-dg080.wav", "answer": "emma's attempts to stop her father had been vain and when he had reached such a point as this she could not wonder at her brother in law's breaking out mister perry said he in a voice of very strong displeasure would do as well to keep his opinion till it is asked for", "subset": "musi", "task_type": "understanding", "prediction": "emmas attempts to stop her father had been vain and when he had reached such a point as this she could not wonder at her brother in laws breaking out mr perry said he in a voice of very strong displeasure would do as well to keep his opinion till it is asked for", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1052, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6788/Lab41-SRI-VOiCES-rm2-musi-sp6788-ch111574-sg0028-mc02-lav-clo-dg010.wav", "answer": "the oyster fixed in its bed unable to hunt for food thus makes its dinner come to it what a strange use for a beard it not only serves as lungs but also helps the animal to catch its daily bread", "subset": "musi", "task_type": "understanding", "prediction": "the oyster fixed in its bed unable to hunt for food thus makes its dinner come to it what a strange use for a beard it not only serves as lungs but also helps the animal to catch its daily bread", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1053, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6848/Lab41-SRI-VOiCES-rm2-musi-sp6848-ch076049-sg0018-mc01-stu-clo-dg060.wav", "answer": "she had had no husband of the lord and master type so to speak but only a prince consort well in hand why shouldn't the grammont heiress dominate her male belonging if it came to that in the same fashion", "subset": "musi", "task_type": "understanding", "prediction": "she had had no husband of the lord and master type so to speak but only a prince consort well in hand why shouldn t the grammont heiress dominate her male belonging if it came to that in the same fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1054, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6848/Lab41-SRI-VOiCES-rm2-musi-sp6848-ch252323-sg0009-mc01-stu-clo-dg040.wav", "answer": "broke in craggs i was brigaded with arentschild's hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you're right", "subset": "musi", "task_type": "understanding", "prediction": "broken crags i was brigaded with arnolds and hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you are right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1055, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm2-musi-sp6965-ch277898-sg0011-mc02-lav-clo-dg030.wav", "answer": "was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs", "subset": "musi", "task_type": "understanding", "prediction": "was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1056, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm2-musi-sp6965-ch277898-sg0012-mc01-stu-clo-dg100.wav", "answer": "but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart's action was the doctor's verdict", "subset": "musi", "task_type": "understanding", "prediction": "but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart s action was the doctor s verdict", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1057, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm2-musi-sp6965-ch291718-sg0013-mc02-lav-clo-dg100.wav", "answer": "and have only the old pieces which nobody wants two things troubled me very much while i was confined to the cradle one was that everybody who came in to see your mother laughed as if they never could stop", "subset": "musi", "task_type": "understanding", "prediction": "and have only the old pieces which nobody wants two things troubled me very much when i was confined to the cradle one was that everybody who came in to see your mother laughed as if they never could stop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1058, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm2-musi-sp7000-ch083696-sg0027-mc02-lav-clo-dg000.wav", "answer": "well he said it's a pity it should be wasted i'll eat it myself which he did and me standing in the rain there looking on that did put my back up mister evans i said short and sharp i wish you a good day i am going", "subset": "musi", "task_type": "understanding", "prediction": "well he said it is a pity it should be wasted i will eat it myself which he did and me standing in the rain there looking on that did put my back up mr evans i said short and sharp i wish you a good day i am going", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1059, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm2-musi-sp7000-ch083706-sg0015-mc01-stu-clo-dg000.wav", "answer": "if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mister hedges any objections which i might urge would appear quite trivial", "subset": "musi", "task_type": "understanding", "prediction": "if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mr hedges any objections which i might urge would appear quite trivial", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1060, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-musi-sp7148-ch059157-sg0015-mc02-lav-clo-dg050.wav", "answer": "she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny brawne", "subset": "musi", "task_type": "understanding", "prediction": "she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny bron.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1061, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-musi-sp7148-ch082991-sg0020-mc02-lav-clo-dg020.wav", "answer": "and i will add to it a wish that the pope may forge her marriage chains to her royal husband faster than ever a foolish wish cried bryan why mark you are clean crazed", "subset": "musi", "task_type": "understanding", "prediction": "and i will add to it a wish that the pope may forge her marriage chains to her royal husband faster than ever a foolish wish cried bryan why mark you are clean crazed", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1062, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7276/Lab41-SRI-VOiCES-rm2-musi-sp7276-ch090847-sg0006-mc02-lav-clo-dg060.wav", "answer": "alas what are we to do i can not take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing", "subset": "musi", "task_type": "understanding", "prediction": "alas what are we to do i cannot take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1063, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm2-musi-sp7278-ch246956-sg0017-mc02-lav-clo-dg030.wav", "answer": "she was a free woman and as leopold had chosen other counsellors had thus declared her unworthy of confidence and after all that she had suffered and done for love of him", "subset": "musi", "task_type": "understanding", "prediction": "she was a free woman and as leopold had chosen other counsellors had thus declared her unworthy of confidence and after all that she had suffered and done for love of him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1064, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7445/Lab41-SRI-VOiCES-rm2-musi-sp7445-ch094523-sg0014-mc02-lav-clo-dg040.wav", "answer": "and though the term of the commission was limited it was easy to foresee that the intentions of the party were to render it perpetual and that power would with great difficulty be wrested from those grasping hands to which it was once committed richard however was obliged to submit", "subset": "musi", "task_type": "understanding", "prediction": "and though the term of the commission was limited it was easy to foresee that the intentions of the party were to render it perpetual and that power would with great difficulty be wrested from those grasping hands to which it was once committed richard however was obliged to submit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1065, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm2-musi-sp7498-ch099124-sg0010-mc01-stu-clo-dg040.wav", "answer": "humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former", "subset": "musi", "task_type": "understanding", "prediction": "humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1066, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7517/Lab41-SRI-VOiCES-rm2-musi-sp7517-ch100442-sg0004-mc02-lav-clo-dg090.wav", "answer": "aproned behind the counter look out for the currants in the window as you come in i have an idea for something artistic in the way of patterns there but as you love me do not offer to buy any", "subset": "musi", "task_type": "understanding", "prediction": "aproned behind the counter look out for the currants in the window as you come in i have an idea for something artistic in the way of patterns there but as you love me do not offer to buy any", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1067, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm2-musi-sp7540-ch101258-sg0030-mc01-stu-clo-dg110.wav", "answer": "and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the whale had thrown up came sailing along and anchored close by", "subset": "musi", "task_type": "understanding", "prediction": "and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the well had thrown up came sailing along and anchored close by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1068, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm2-musi-sp7540-ch101262-sg0013-mc01-stu-clo-dg010.wav", "answer": "soon got tired of being by himself and began to look about for something to amuse him what can there be in that twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other", "subset": "musi", "task_type": "understanding", "prediction": "soon got tired of being by himself and began to look about for something to amuse him what can there be in the twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1069, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7688/Lab41-SRI-VOiCES-rm2-musi-sp7688-ch109656-sg0016-mc02-lav-clo-dg080.wav", "answer": "it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing a meal or two and sleeping comfortably on your saddle blankets on a soft mattress of mesquite grass", "subset": "musi", "task_type": "understanding", "prediction": "it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing a meal or two and sleeping comfortably on your saddle blankets in a soft mattress of mesquite grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1070, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-musi-sp7850-ch111771-sg0001-mc01-stu-clo-dg140.wav", "answer": "at this time grant was not taken with war and probably evinced little interest in army tactics", "subset": "musi", "task_type": "understanding", "prediction": "at this time grant was not taken with bore had probably evinced little interest in army tactics", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1071, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-musi-sp7868-ch110705-sg0027-mc01-stu-clo-dg090.wav", "answer": "for five minutes without stopping apparently with the view of ascertaining if he were quite correctly put together while gluck stood contemplating him in speechless amazement he was dressed in a stashed doublet of spun gold so fine in its texture", "subset": "musi", "task_type": "understanding", "prediction": "for five minutes without stopping apparently with the view of ascertaining if he were quite correctly put together while gluck stood contemplating him speechless amazed he was dressed in a stach doublet of spun gold so fine in its texture", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1072, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-musi-sp7868-ch110706-sg0013-mc01-stu-clo-dg030.wav", "answer": "which sprang from one of the lower and snowless elevations was now nearly in shadow all but the uppermost jets of spray which rose like slow smoke above the undulating line of the cataract and floated away in feeble wreaths upon the morning wind", "subset": "musi", "task_type": "understanding", "prediction": "which sprang from when the lower and snowless elevations was now merely in shadow all but the uttermost jets of spray which rose like slow smoke above the undulating line of the cataract and floated away in feeble wreaths upon the morning wind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1073, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-musi-sp7868-ch110706-sg0035-mc01-stu-clo-dg040.wav", "answer": "and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball", "subset": "musi", "task_type": "understanding", "prediction": "and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1074, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7910/Lab41-SRI-VOiCES-rm2-musi-sp7910-ch105673-sg0041-mc01-stu-clo-dg130.wav", "answer": "there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries", "subset": "musi", "task_type": "understanding", "prediction": "there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1075, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch093470-sg0011-mc02-lav-clo-dg120.wav", "answer": "i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruth's own wish that it should be told to others", "subset": "musi", "task_type": "understanding", "prediction": "i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruths own wish that it should be told to others", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1076, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch110056-sg0022-mc01-stu-clo-dg180.wav", "answer": "and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by", "subset": "musi", "task_type": "understanding", "prediction": "and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1077, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch278228-sg0011-mc01-stu-clo-dg070.wav", "answer": "in spite of those heartless words which she had spoken in the bitter hour of their parting clement could not thoroughly believe in the baseness of the woman he had trusted again and again he went over the same ground trying to find some lurking circumstance no matter how unlikely in its nature", "subset": "musi", "task_type": "understanding", "prediction": "in spite of those heartless words which she had spoken in the bitter hour of their parting clement could not thoroughly believe in the baseness of the woman he had trusted again and again he went over the same ground trying to find some lurking circumstance no matter how unlikely in its nature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1078, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch278228-sg0025-mc02-lav-clo-dg180.wav", "answer": "said the detective i was away in glasgow hunting up the particulars of the great scotch plaid robberies all last summer and i can't say i remember much of what was done in the wilmot business mister dunbar himself offered a reward for the apprehension of the guilty party didn't he", "subset": "musi", "task_type": "understanding", "prediction": "said the detective i was away in glasgow hunting up the particulars of the great scotch plaid robberies all last summer and i can t say i remember much of what was done in the will not business mr dunbar himself offered a reward for the apprehension of the guilty party didn t he", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1079, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm2-musi-sp7976-ch105575-sg0013-mc02-lav-clo-dg010.wav", "answer": "when morning came the firing opened and for all that day the battle raged fiercely at the left and center left we getting the worst of it too", "subset": "musi", "task_type": "understanding", "prediction": "when morning came the firing opened and for all that day the battle raged fiercely at the left center left we getting the worst of it too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1080, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm2-musi-sp7976-ch110523-sg0017-mc02-lav-clo-dg020.wav", "answer": "creep in said the witch and see if it is hot enough and then we will put in the bread but she intended when grethel got in to shut up the oven and let her bake so that she might eat her as well as hansel", "subset": "musi", "task_type": "understanding", "prediction": "preheat said the witch and see if it is hot enough and then we will put in the bread but she intended when gretel got in to shut up the oven and let her bake so that she might eat her as well as hansel", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1081, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm2-musi-sp7995-ch276908-sg0012-mc02-lav-clo-dg070.wav", "answer": "of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature", "subset": "musi", "task_type": "understanding", "prediction": "of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1082, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8051/Lab41-SRI-VOiCES-rm2-musi-sp8051-ch119902-sg0019-mc01-stu-clo-dg000.wav", "answer": "and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits", "subset": "musi", "task_type": "understanding", "prediction": "and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1083, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8118/Lab41-SRI-VOiCES-rm2-musi-sp8118-ch114476-sg0027-mc01-stu-clo-dg090.wav", "answer": "here was a full half day for the army of the potomac enough in which to destroy a divided portion of the army of northern virginia but colonel winchester raged again and again in vain there was no attack brigade after brigade in blue came up and sat down before the antietam", "subset": "musi", "task_type": "understanding", "prediction": "here was a full half day for the army of the potomac enough in which to destroy a divided portion of the army of northern virginia but colonel winchester raged again and again in vain there was no attack brigade after brigade in blue came up and sat down before the intrenchment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1084, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm2-musi-sp8225-ch274375-sg0001-mc02-lav-clo-dg110.wav", "answer": "those parliamentary leaders it must be owned who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity", "subset": "musi", "task_type": "understanding", "prediction": "those parliamentary leaders say it must be the holland who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1085, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-musi-sp8266-ch258262-sg0001-mc01-stu-clo-dg020.wav", "answer": "they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered", "subset": "musi", "task_type": "understanding", "prediction": "they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1086, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-musi-sp8266-ch258263-sg0037-mc01-stu-clo-dg030.wav", "answer": "then she abode in the castle and her son grew up and was reared with the children of the king they used to ride forth together a hunting and birding and he became skilled in the chase of wild beasts and ravening lions and ate of their flesh till his heart became harder than the rock", "subset": "musi", "task_type": "understanding", "prediction": "then she abode in the castle and her son grew up and was reared with the children of the king they used to ride forth together a hunting and birding and he became skilled in the chase of wild beasts and ravening lions and ate of their flesh till his heart became harder than the rock", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1087, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-musi-sp8266-ch279363-sg0000-mc01-stu-clo-dg140.wav", "answer": "colonel woodville had begun to swear it was not the torrent of loud imprecation that dick had heard in jackson but subdued and all the more fierce because it was so like the ferocious whine of a powerful and hurt wild animal swearing was common enough among the older men of the south", "subset": "musi", "task_type": "understanding", "prediction": "colonel woodville had begun to swear it was not the torrent of loud imprecation that dick had heard in jackson but subdued and all the more fierce because it was so like the ferocious whine of a powerful and hurt wild animal swearing was common enough among the older men of the south", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1088, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm2-musi-sp8425-ch291444-sg0000-mc02-lav-clo-dg020.wav", "answer": "of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative old age and day by day dropping piecemeal into the tomb in a little while thought i and those revered dutch burghers", "subset": "musi", "task_type": "understanding", "prediction": "of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative old age and day by day dropping piecemeal into the tomb then a little while afar high had those revered dutch burghers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1089, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm2-musi-sp8425-ch292520-sg0014-mc02-lav-clo-dg120.wav", "answer": "and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wave and solemnly sway to the wash and swell of our passing", "subset": "musi", "task_type": "understanding", "prediction": "and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wraith and solemnly sway to the wash and swell of our passage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1090, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8575/Lab41-SRI-VOiCES-rm2-musi-sp8575-ch290350-sg0034-mc01-stu-clo-dg080.wav", "answer": "should be co existent to the motion we measure by or any other periodical revolution but it suffices to this purpose that we have the idea of the length of any regular periodical appearances which we can in our minds apply to duration with which the motion or appearance never co existed", "subset": "musi", "task_type": "understanding", "prediction": "should be coexistent to the motion we measure by or any other periodical revolution but it suffices to this purpose that we have the idea of the length of any regular periodical appearances which we can in our minds apply to duration with which the motion or appearance never coexisted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1091, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8635/Lab41-SRI-VOiCES-rm2-musi-sp8635-ch295759-sg0011-mc01-stu-clo-dg140.wav", "answer": "the guard formed two lines that stood face to face let their guns rest on the ground and leaned their heads on the butts the corpse was borne twixt these two rows of men with the sword and sash on the top of the box in which he lay", "subset": "musi", "task_type": "understanding", "prediction": "the guard formed two lines that stood face to face let their guns rest on the ground and lean their heads on the butts the corpse was borne twixt these two rows of men with the sword and sash on the top of the box in which he lay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1092, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8677/Lab41-SRI-VOiCES-rm2-musi-sp8677-ch296078-sg0025-mc02-lav-clo-dg130.wav", "answer": "there were many sheep on the downs and there was one special flock that florence knew very well it belonged to old roger a shepherd who had often worked for her father roger and his good dog cap were both friends of florence's", "subset": "musi", "task_type": "understanding", "prediction": "There were many sheep on the downs. And there was one special flock that Florence knew very well. It belonged to old Roger, a shepherd who had often worked for her father, Roger and his good dog cap were both friends of Florence's.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1093, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/musi/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm2-musi-sp8713-ch302111-sg0010-mc02-lav-clo-dg080.wav", "answer": "answered in the words which follow song of birds is idle chatter and the throstle's merely chirping as a child a daughter's treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seat thee", "subset": "musi", "task_type": "understanding", "prediction": "answered in the words which follow song of birds is idle chatter and the thrushes merely chirping as a child the daughter is treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seek thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1094, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0093/Lab41-SRI-VOiCES-rm2-none-sp0093-ch126208-sg0003-mc02-lav-clo-dg000.wav", "answer": "an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a whity brown tilt obtained for a few pounds more and in this turn out it became jude's business thrice a week to carry loaves of bread to the villagers", "subset": "none", "task_type": "understanding", "prediction": "an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a witty brown tilt obtained for a few pounds more and in this turn out it became jude s business thrice a week to carry loaves of bread to the villagers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1095, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0093/Lab41-SRI-VOiCES-rm2-none-sp0093-ch126209-sg0001-mc02-lav-clo-dg120.wav", "answer": "having promised to call at a flour mill near cresscombe to execute a commission for his aunt he was in an enthusiastic mood he seemed to see his way to living comfortably in christminster in the course of a year or two and knocking at the doors of one of those strongholds of learning", "subset": "none", "task_type": "understanding", "prediction": "having promised to call at a flour mill near crescomb to execute a commission for his aunt he was in an enthusiastic mood he seemed to see his way to living comfortably in christminster in the course of a year or two and knocking at the doors of one of the strongholds of learning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1096, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0093/Lab41-SRI-VOiCES-rm2-none-sp0093-ch126209-sg0027-mc01-stu-clo-dg030.wav", "answer": "springing to her feet she said bring back what is lying there jude was now aware that no message on any matter connected with her father's business had prompted her signal to him he set down his basket of tools", "subset": "none", "task_type": "understanding", "prediction": "springing to her feet she said bring back what is lying there jude was now aware that no message on any matter connected with her father s business had prompted her signal to him he set down his basket of tools", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1097, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm2-none-sp0112-ch121671-sg0004-mc01-stu-clo-dg050.wav", "answer": "with white gravel paths and many beds of bright colored flowers the old woman was very happy and contented there until one day she received a letter saying that her daughter hannah was dead and had sent her family of five children to their grandmother to be taken care of", "subset": "none", "task_type": "understanding", "prediction": "with white gravel paths and many beds of bright colored flowers the old woman was very happy and contented there until one day she received a letter saying that her daughter hannah was dead and had sent her family of five children to their grandmother to be taken care of", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1098, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm2-none-sp0112-ch121671-sg0027-mc01-stu-clo-dg010.wav", "answer": "then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaves of bread altogether the baker man was terribly frightened", "subset": "none", "task_type": "understanding", "prediction": "then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaves of bread altogether the baker man was terribly frightened", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1099, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0174/Lab41-SRI-VOiCES-rm2-none-sp0174-ch168635-sg0003-mc01-stu-clo-dg070.wav", "answer": "he suffered all the pangs of a mother and he knew not what it meant for that great and singular movement of a heart which begins to love is a very obscure and a very sweet thing", "subset": "none", "task_type": "understanding", "prediction": "he suffered all the pangs of a mother and he knew not what it meant for that great and singular movement of a heart which begins to love is a very obscure and a very sweet thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1100, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm2-none-sp0204-ch148920-sg0015-mc02-lav-clo-dg020.wav", "answer": "knew no better than to be venturesome why let him tumble horror what mean that heavy crashing sound ben could not stir he could only gasp jacob jacob cried another startled voice", "subset": "none", "task_type": "understanding", "prediction": "do know better than to be venturesome why let him tumble horror what mean that heavy crashing sound ben could not stir he could only gasp jacob jacob cried another startled voice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1101, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm2-none-sp0205-ch123882-sg0036-mc02-lav-clo-dg020.wav", "answer": "bill and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely as the great swamp just this side of the bridge over the ossawippi", "subset": "none", "task_type": "understanding", "prediction": "bell and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely is the great swamp just this side of the bridge over the osawimpee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1102, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm2-none-sp0205-ch157088-sg0027-mc01-stu-clo-dg050.wav", "answer": "but we can not because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains", "subset": "none", "task_type": "understanding", "prediction": "but we cannot because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1103, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm2-none-sp0208-ch126600-sg0025-mc01-stu-clo-dg150.wav", "answer": "when john d pell wants something done d'you think he asks of anyone oh no he orders someone to with get my hat or tie my shoe the goops all say rude things like these but you of course say", "subset": "none", "task_type": "understanding", "prediction": "When John D. Pell wants something done, do you think he asks of anyone. Oh, no. He orders somebody with get my hat or tie my shoe. The goops all say, with things like these. But you, of course, say.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1104, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm2-none-sp0209-ch004731-sg0033-mc01-stu-clo-dg050.wav", "answer": "that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware", "subset": "none", "task_type": "understanding", "prediction": "that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1105, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0240/Lab41-SRI-VOiCES-rm2-none-sp0240-ch160592-sg0001-mc01-stu-clo-dg080.wav", "answer": "as he defeated dying on whose forbidden ear the distant strains of triumph break agonized and clear two our share of night to bear", "subset": "none", "task_type": "understanding", "prediction": "as he defeated dying on whose forbidden ear the distant strains of triumph break agonized and clear two our share of night to bear", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1106, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm2-none-sp0242-ch122625-sg0002-mc01-stu-clo-dg170.wav", "answer": "i turn to another class a small one so far as i know but not therefore to be overlooked i mean the timorous or carping few who doubt the tendency of such books as jane eyre in whose eyes whatever is unusual is wrong", "subset": "none", "task_type": "understanding", "prediction": "i turn to another class a small one so far as i know but not therefore to be overlooked i mean the timorous or carping few who doubt the tendency of such books as jane eyre in whose eyes whatever is unusual is wrong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1107, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm2-none-sp0242-ch126842-sg0035-mc02-lav-clo-dg010.wav", "answer": "peter no i don't want to hear about it said uncle alec sternly i don't care what you were fighting about but you must settle your quarrels in a different fashion remember my commands felix peter", "subset": "none", "task_type": "understanding", "prediction": "peter no i don t want to hear about it said uncle alec sternly i don t care what you were fighting about but you must settle your quarrel in a different fashion remember my commands felix peter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1108, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0288/Lab41-SRI-VOiCES-rm2-none-sp0288-ch130994-sg0002-mc02-lav-clo-dg000.wav", "answer": "i shall now proceed in the enumeration of the most important of those defects which have hitherto disappointed our hopes from the system established among ourselves to form a safe and satisfactory judgment of the proper remedy it is absolutely necessary", "subset": "none", "task_type": "understanding", "prediction": "i shall now proceed to the enumeration of the most important of those defects which have hitherto disappointed our hopes from the system established among ourselves to form a safe and satisfactory judgment of the proper remedy it is absolutely necessary", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1109, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0296/Lab41-SRI-VOiCES-rm2-none-sp0296-ch142727-sg0031-mc01-stu-clo-dg090.wav", "answer": "these derangements are the basis of emotion its physical basis and to be moved is to perceive them take away from the consciousness this physical reflex and emotion ceases it is no longer anything but an idea", "subset": "none", "task_type": "understanding", "prediction": "these derangements are the basis of emotion its physical basis and to be moved is to perceive them take away from the consciousness this physical reflex and emotion ceases it is no longer anything but an idea", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1110, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm2-none-sp0459-ch127522-sg0016-mc01-stu-clo-dg020.wav", "answer": "the rocks of the spy glass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain", "subset": "none", "task_type": "understanding", "prediction": "the rocks of the spyglass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1111, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm2-none-sp0472-ch129979-sg0025-mc01-stu-clo-dg100.wav", "answer": "i am so glad we are got acquainted at last continued charlotte and now i hope we shall always be great friends you can't think how much i longed to see you it is so delightful that you should live at the cottage nothing can be like it to be sure", "subset": "none", "task_type": "understanding", "prediction": "i am so glad we are got acquainted at last continued charlotte and now i hope we shall always be great friends you can not think how much i longed to see you it is so delightful that you should live at the cottage nothing can be like it to be sure", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1112, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm2-none-sp0472-ch129983-sg0011-mc01-stu-clo-dg180.wav", "answer": "which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth", "subset": "none", "task_type": "understanding", "prediction": "which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1113, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm2-none-sp0479-ch134717-sg0034-mc01-stu-clo-dg020.wav", "answer": "and the singer so shy to the rest receiv'd me the gray brown bird i know receiv'd us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird", "subset": "none", "task_type": "understanding", "prediction": "and the singer so shy to the rest received me the gray brown bird i know received us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1114, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm2-none-sp0480-ch126292-sg0015-mc02-lav-clo-dg020.wav", "answer": "to mister korbes the fox today soon after came up a millstone an egg a duck and a pin and chanticleer gave them all leave to get into the carriage and go with them when they arrived at mister korbes's house", "subset": "none", "task_type": "understanding", "prediction": "to mr korbes the fox today soon after came up a millstone an egg a duck and a pin and chanticleer gave them all leave to get into the carriage and go with them when they arrived at mr korbes house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1115, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm2-none-sp0480-ch127525-sg0029-mc02-lav-clo-dg150.wav", "answer": "not having reached him where the ball passed not one of us precisely knew but i fancy it must have been over our heads and that the wind of it may have contributed to our disaster", "subset": "none", "task_type": "understanding", "prediction": "not having reached it where the ball passed not one of us precisely knew but i fancy it must have been over our heads and that the wind of it may have contributed to our disaster", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1116, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-none-sp0492-ch131887-sg0009-mc01-stu-clo-dg100.wav", "answer": "nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger", "subset": "none", "task_type": "understanding", "prediction": "nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1117, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-none-sp0492-ch131887-sg0009-mc02-lav-clo-dg100.wav", "answer": "nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger", "subset": "none", "task_type": "understanding", "prediction": "nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1118, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-none-sp0492-ch131890-sg0031-mc01-stu-clo-dg140.wav", "answer": "on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the roadstead and was soon once more on the indian ocean", "subset": "none", "task_type": "understanding", "prediction": "on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the roghstead and was soon once more on the indian ocean", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1119, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0510/Lab41-SRI-VOiCES-rm2-none-sp0510-ch130103-sg0047-mc01-stu-clo-dg180.wav", "answer": "then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled", "subset": "none", "task_type": "understanding", "prediction": "then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1120, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0597/Lab41-SRI-VOiCES-rm2-none-sp0597-ch133239-sg0006-mc02-lav-clo-dg060.wav", "answer": "the interjection shows surprise as oh how pretty ah how wise the whole are called nine parts of speech which reading writing speaking teach to tell the age of horses", "subset": "none", "task_type": "understanding", "prediction": "the interjection shows surprise as oh how pretty ah how wise the whole are called nine parts of speech which reading writing speaking teach to tell the age of horses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1121, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm2-none-sp0637-ch127579-sg0002-mc02-lav-clo-dg030.wav", "answer": "for the purpose of collecting various species of rare sea weed some of which among these people are considered a great luxury after a whole day spent in this employment he would return about nightfall with several cocoanut shells filled with different descriptions of kelp", "subset": "none", "task_type": "understanding", "prediction": "for the purpose of collecting various species of rare seaweed some of which among these people are considered a great luxury after a whole day spent in this employment he would return about nightfall with several cocoanut shells filled with different descriptions of kelp", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1122, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0770/Lab41-SRI-VOiCES-rm2-none-sp0770-ch134592-sg0013-mc02-lav-clo-dg120.wav", "answer": "there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcotes and aclands and many other newer names that she had forgotten", "subset": "none", "task_type": "understanding", "prediction": "there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcotes and aclands and many other newer names that she had forgotten", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1123, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0868/Lab41-SRI-VOiCES-rm2-none-sp0868-ch131296-sg0005-mc02-lav-clo-dg170.wav", "answer": "the seven kilns of enshiu are well known to all students of japanese pottery many of our textile fabrics bear the names of tea masters who conceived their color or design it is impossible indeed to find any department of art", "subset": "none", "task_type": "understanding", "prediction": "the seven kilns of inshu are well known to all students of japanese pottery many of our textile fabrics bear the names of tea masters who conceived their color or design it is impossible indeed to find any department of art", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1124, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0882/Lab41-SRI-VOiCES-rm2-none-sp0882-ch123266-sg0040-mc01-stu-clo-dg000.wav", "answer": "we were kindly received and without taxing too much the goodness of these folks i would willingly have tarried here to recruit after my fatigues but my uncle who wanted no recruiting would not hear of it and the next morning we had to bestride our beasts again the soil told of the neighbourhood of the mountain", "subset": "none", "task_type": "understanding", "prediction": "we were kindly received and without taxing too much the goodness of these folks i would willingly have tarried here to recruit after my fatigue but my uncle who wanted no recruiting would not hear of it and the next morning we had to bestride our beasts again the soil told of the neighbourhood of the mountain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1125, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp0882/Lab41-SRI-VOiCES-rm2-none-sp0882-ch123268-sg0033-mc02-lav-clo-dg090.wav", "answer": "this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour", "subset": "none", "task_type": "understanding", "prediction": "this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1126, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm2-none-sp1050-ch134121-sg0013-mc01-stu-clo-dg120.wav", "answer": "but something was the matter she could not pull it up there was the dinner but she could not reach it all the family in turn went and tried all pulled together in vain the dinner could not be stirred", "subset": "none", "task_type": "understanding", "prediction": "but something was the matter she could not pull it up there was the dinner but she could not reach it all the family in turn went and tried all pulled together in vain the dinner could not be stirred", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1127, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm2-none-sp1066-ch005330-sg0005-mc01-stu-clo-dg130.wav", "answer": "should mamma see you it will kill her outright i can't live on as i am living he answered gloomily i have been working in london ever since in london interrupted barbara in london and have never stirred out of it", "subset": "none", "task_type": "understanding", "prediction": "should mamma see you it will kill her outright i can live on as i am living he answered gloomily i have been working in london ever since in london interrupted barbara in london and have never stirred out of it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1128, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm2-none-sp1066-ch005330-sg0006-mc02-lav-clo-dg110.wav", "answer": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune", "subset": "none", "task_type": "understanding", "prediction": "a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1129, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm2-none-sp1112-ch001043-sg0032-mc02-lav-clo-dg150.wav", "answer": "she wore nothing but a stocking on her right foot and in spite of the unlocked door she escaped by the window and again i thought of gertrude's sprained ankle", "subset": "none", "task_type": "understanding", "prediction": "she wore nothing but a stocking on her right foot and in spite of the unlocked door she escaped by the window and again i thought of gertrude sprained ankle", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1130, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1121/Lab41-SRI-VOiCES-rm2-none-sp1121-ch135824-sg0002-mc02-lav-clo-dg160.wav", "answer": "began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny's cousins more closely related to him than to any other members of the mouse family", "subset": "none", "task_type": "understanding", "prediction": "began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny s cousins more closely related to him than to any other members of the mouse family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1131, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1121/Lab41-SRI-VOiCES-rm2-none-sp1121-ch135824-sg0019-mc02-lav-clo-dg080.wav", "answer": "her eyes twinkled nimbleheels saw this and knew that she was only pretending to be severe before he could reply johnny chuck began to chuckle the chuckle became a laugh and presently johnny was laughing so hard he had to hold his sides", "subset": "none", "task_type": "understanding", "prediction": "her eyes twinkled nimbleheels saw this and knew that she was only pretending to be severe before he could reply johnny chuck began to chuckle the chuckle became a laugh and presently johnny was laughing so hard he had to hold his sides", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1132, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm2-none-sp1160-ch134674-sg0015-mc01-stu-clo-dg000.wav", "answer": "as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps", "subset": "none", "task_type": "understanding", "prediction": "as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1133, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_0032-1182/sp1182/Lab41-SRI-VOiCES-rm2-none-sp1182-ch134981-sg0026-mc02-lav-clo-dg100.wav", "answer": "as she and curdken were driving their flock through the gate she said as she passed under oh falada tis you hang there and the head replied tis you pass under princess fair if your mother only knew her heart would surely break in two", "subset": "none", "task_type": "understanding", "prediction": "as she and kirkkin were driving their flock through the gate she said as she passed under o falada tis you hang there and the hen replied tis you pass under princess fair if your mother only knew her heart would surely break in two", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1134, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1212/Lab41-SRI-VOiCES-rm2-none-sp1212-ch014653-sg0003-mc02-lav-clo-dg160.wav", "answer": "for for the sake of my reputation i suggested softly yes he looked doubtfully at me mistrusting the amiable deference of my manner that would be awfully good of you", "subset": "none", "task_type": "understanding", "prediction": "for for the sake of my reputation i suggested softly yes he looked doubtfully at me mistrusting the amiable deference of my manner that would be awfully good of you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1135, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1212/Lab41-SRI-VOiCES-rm2-none-sp1212-ch185485-sg0019-mc01-stu-clo-dg030.wav", "answer": "a funny incident occurred to me in connection with this great pill in the year eighteen thirty six while i was travelling through the states of alabama mississippi and louisiana i became convinced by reading doctor brandreth's advertisements that i needed his pills", "subset": "none", "task_type": "understanding", "prediction": "a funny incident occurred to me in connection with this great pill in the year eighteen thirty six while i was traveling through the states of alabama mississippi and louisiana i became convinced by reading dr brandreth s advertisements that i needed his pills", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1136, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1235/Lab41-SRI-VOiCES-rm2-none-sp1235-ch135884-sg0002-mc01-stu-clo-dg000.wav", "answer": "my desire of having children only induced me to purchase a slave by whom i had a son who was extremely promising my wife being jealous cherished a hatred for both mother and child", "subset": "none", "task_type": "understanding", "prediction": "my desire of having children only induced me to purchase a slave by whom i had a son who was extremely promising my wife being jealous cherished a hatred for both mother and child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1137, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm2-none-sp1246-ch124550-sg0011-mc02-lav-clo-dg090.wav", "answer": "were the members of the tincomb methodist church a vast red brick tabernacle vida sherwin had given her a letter to an earnest woman with eye glasses plaid silk waist and a belief in bible classes who introduced her to the pastor and the", "subset": "none", "task_type": "understanding", "prediction": "were the members of the tincomb methodist church a vast red brick tabernacle vinice sherman had given her a letter to an earnest woman with eyeglasses plaid silk waist and a belief in bible classes who introduced her to the pastor and the", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1138, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm2-none-sp1272-ch128104-sg0011-mc01-stu-clo-dg170.wav", "answer": "in fact he is quite severe on mister ruskin for not recognising that a picture should denote the frailty of man and remarks with pleasing courtesy and felicitous grace that many phases of feeling", "subset": "none", "task_type": "understanding", "prediction": "in fact he is quite severe on mr ruskin for not recognising that a picture should denote the frailty of man and remarks with pleasing courtesy and felicitous grace that many phases of feeling", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1139, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm2-none-sp1335-ch027593-sg0000-mc02-lav-clo-dg170.wav", "answer": "sweetbreads with mushrooms lay half a dozen sweetbreads in cold water for twelve hours changing the water several times then boil them five minutes drop into cold water", "subset": "none", "task_type": "understanding", "prediction": "sweetbreads with mushrooms lay half a dozen sweetbreads in cold water for twelve hours changing the water several times then boil them five minutes drop into cold water", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1140, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1335/Lab41-SRI-VOiCES-rm2-none-sp1335-ch027593-sg0034-mc01-stu-clo-dg050.wav", "answer": "mixed with a little good sauce espagnole fill the dish and on the top layer put truffles place in the oven a few minutes and serve with grated parmesan cheese on a separate dish", "subset": "none", "task_type": "understanding", "prediction": "mixed with a little good sauce espagnole fill the dish and on the top layer put truffles place in the oven a few minutes and serve with grated parmesan cheese on a separate dish", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1141, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm2-none-sp1383-ch130532-sg0018-mc02-lav-clo-dg020.wav", "answer": "i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions", "subset": "none", "task_type": "understanding", "prediction": "i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1142, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1383/Lab41-SRI-VOiCES-rm2-none-sp1383-ch130532-sg0033-mc02-lav-clo-dg090.wav", "answer": "i take it for granted i take leave to say i take one picture as an illustration i take pleasure in saying i take the liberty of observing", "subset": "none", "task_type": "understanding", "prediction": "i take it for granted i take leave to say i take one picture as an illustration i take pleasure in saying i take the liberty of observing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1143, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-none-sp1392-ch135654-sg0002-mc02-lav-clo-dg050.wav", "answer": "of the event more steady and secure this process of the thought or reasoning may seem trivial and obvious but to those who consider it more narrowly it may perhaps afford matter for curious speculation", "subset": "none", "task_type": "understanding", "prediction": "of the event more steady and secure this process of the thought or reasoning may seem trivial and obvious but to those who consider it more narrowly it may perhaps afford matter for curious speculation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1144, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1425/Lab41-SRI-VOiCES-rm2-none-sp1425-ch139290-sg0005-mc01-stu-clo-dg130.wav", "answer": "my mother and i were separated when i was but an infant before i knew her as my mother it is a common custom in the part of maryland from which i ran away to part children from their mothers at a very early age frequently before the child has reached its twelfth month", "subset": "none", "task_type": "understanding", "prediction": "my mother and i were separated when i was but an infant before i knew her as my mother it is a common custom in the part of maryland from which i ran away to part children from their mothers at a very early age frequently before the child has reached its twelfth month", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1145, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm2-none-sp1472-ch142848-sg0012-mc01-stu-clo-dg110.wav", "answer": "there are about a dozen different kinds but the principal are bohea congou and souchong and signify respectively inferior middling and superior teas are often perfumed and flavoured with the leaves of different kinds of plants grown on purpose", "subset": "none", "task_type": "understanding", "prediction": "there are about a dozen different kinds but the principal are bohea conju and suchong and signify respectively inferior middling and superior teas are often perfumed and flavoured with the leaves of different kinds of plants grown on purpose", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1146, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1536/Lab41-SRI-VOiCES-rm2-none-sp1536-ch138488-sg0025-mc02-lav-clo-dg090.wav", "answer": "two generations of public men have since laboured with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment", "subset": "none", "task_type": "understanding", "prediction": "two generations of public men have since labored with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1147, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1737/Lab41-SRI-VOiCES-rm2-none-sp1737-ch142396-sg0021-mc02-lav-clo-dg020.wav", "answer": "there was no handsome expression of regret on the discovery of the real culprit what harold had felt was not so much the imprisonment indeed he had very soon escaped by the window with assistance from his allies and had only gone back in time for his release as the olympian habit", "subset": "none", "task_type": "understanding", "prediction": "there was no handsome expression of regret on the discovery of the real culprit what harold had felt was not so much the imprisonment indeed he had very soon escaped by the window with assistance from his allies and had only gone back in time for his release as the olympian habit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1148, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1841/Lab41-SRI-VOiCES-rm2-none-sp1841-ch159771-sg0031-mc01-stu-clo-dg010.wav", "answer": "well peter mink had surprised many a one swimming in the brook if it hadn't been for the meadow mice perhaps he wouldn't have visited the brook so often even in winter master meadow mouse just had to have his cold dip now and then", "subset": "none", "task_type": "understanding", "prediction": "well peter meek had surprised many a one swimming in the brook if it hadn't been for the meadow mice perhaps he wouldn't have visited the brook so often even in winter master meadow mouse just had to have his cold dip now and then", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1149, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1841/Lab41-SRI-VOiCES-rm2-none-sp1841-ch159771-sg0042-mc02-lav-clo-dg000.wav", "answer": "and the day came at last when it was well worth his while to take the little extra trouble of peeping out before he had his swim for master meadow mouse caught a glimpse of a snakelike head that darted out from under the bank of the brook and darted back again out of sight", "subset": "none", "task_type": "understanding", "prediction": "and the day came at last when it was well worth his while to take the little extra trouble of peeping out before he had his swim for master mettamouse caught a glimpse of a snake like head that darted out from under the bank of the brook and darted back again out of sight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1150, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm2-none-sp1867-ch154075-sg0018-mc02-lav-clo-dg130.wav", "answer": "as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance", "subset": "none", "task_type": "understanding", "prediction": "as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1151, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm2-none-sp1874-ch165702-sg0020-mc01-stu-clo-dg150.wav", "answer": "april fourteenth assassinated in ford's theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett", "subset": "none", "task_type": "understanding", "prediction": "april fourteenth assassinated at ford s theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1152, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1926/Lab41-SRI-VOiCES-rm2-none-sp1926-ch143879-sg0015-mc01-stu-clo-dg010.wav", "answer": "missus ludlow sacrificed as i say to paris yet had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations", "subset": "none", "task_type": "understanding", "prediction": "mrs ludlow sacrificed as i say to paris it had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1153, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm2-none-sp1961-ch145733-sg0016-mc01-stu-clo-dg130.wav", "answer": "what does he say asked the princess i really hardly like to tell you answered the lady in waiting oh then you can whisper it to me he is disobliging said the princess and went away", "subset": "none", "task_type": "understanding", "prediction": "what does he say asked the princess i really hardly like to tell you answered the lady in waiting oh then you can whisper it to me ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1154, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm2-none-sp1970-ch010594-sg0003-mc01-stu-clo-dg120.wav", "answer": "under her great determination to keep gwendolen in her own care but with jupp to watch the dock and a man in plain clothes at the door of the small hotel she was at present bound for i thought i might remain in yonkers contentedly the whole day", "subset": "none", "task_type": "understanding", "prediction": "under her great determination to keep gwendolen in her own care but with jupp to watch the dock and a man in plain clothes at the door of the small hotel she was at present bound for i thought i might remain in yonkers contentedly the whole day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1155, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp1970/Lab41-SRI-VOiCES-rm2-none-sp1970-ch010594-sg0039-mc01-stu-clo-dg140.wav", "answer": "till yesterday yesterday her great eyes haggard with suffering rose to mine then they fell on the bead which i had taken from my pocket the cry she gave was not loud but it effectually settled all my doubts", "subset": "none", "task_type": "understanding", "prediction": "till yesterday yesterday her great eyes haggard with suffering rose to mine then they fell on the bead which i had taken from my pocket the cry she gave was not loud but it effectually settled all my doubts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1156, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm2-none-sp2012-ch139355-sg0023-mc02-lav-clo-dg030.wav", "answer": "another phenomenon on which the savants are not agreed perhaps said fragoso they might ask the opinions of the caymans dolphins and manatees for they certainly prefer the black waters to the others to enjoy themselves in", "subset": "none", "task_type": "understanding", "prediction": "another phenomenon on which the savants are not agreed perhaps said fragoso they might ask the opinions of the caymans dolphins and manatees for they certainly prefer the black waters to the others to enjoy themselves in", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1157, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm2-none-sp2012-ch139358-sg0006-mc02-lav-clo-dg030.wav", "answer": "nothing can be truer but while you have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency", "subset": "none", "task_type": "understanding", "prediction": "nothing can be truer but while you have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1158, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm2-none-sp2012-ch139358-sg0032-mc01-stu-clo-dg100.wav", "answer": "either by swimming through the waters propelled by their tails or running along the bank with a speed no man can equal it is on these huge beaches that the caymans are born live and die not without affording extraordinary examples of longevity", "subset": "none", "task_type": "understanding", "prediction": "either by swimming through the waters propelled by their tails or running along the bank with a speed no man can equal it is on these huge beaches that the caymans are born live and die not without affording extraordinary examples of longevity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1159, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2060/Lab41-SRI-VOiCES-rm2-none-sp2060-ch150855-sg0011-mc01-stu-clo-dg130.wav", "answer": "there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie's bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy", "subset": "none", "task_type": "understanding", "prediction": "there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was vardit who to rickie s bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1160, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2093/Lab41-SRI-VOiCES-rm2-none-sp2093-ch143262-sg0010-mc01-stu-clo-dg110.wav", "answer": "but he is saving us i said taking us to our friends jimmy no know jimmy tink doctor somewhere right long big hill gib black white fellow topper topper make um tink more", "subset": "none", "task_type": "understanding", "prediction": "but he is saving us i said taking us to our friends jimmy not know jimmy take doctor somewhere right long big hill give black white fellow topper topper make him think more", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1161, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm2-none-sp2110-ch161100-sg0026-mc02-lav-clo-dg180.wav", "answer": "it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing", "subset": "none", "task_type": "understanding", "prediction": "it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1162, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm2-none-sp2110-ch161101-sg0036-mc02-lav-clo-dg050.wav", "answer": "you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it", "subset": "none", "task_type": "understanding", "prediction": "you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1163, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2149/Lab41-SRI-VOiCES-rm2-none-sp2149-ch007239-sg0001-mc02-lav-clo-dg180.wav", "answer": "paul an apostle of jesus christ by the will of god according to the promise of life which is in christ jesus", "subset": "none", "task_type": "understanding", "prediction": "Paul, an apostle of Jesus Christ by the will of God. According to the promise of life, which is in Christ Jesus.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1164, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2149/Lab41-SRI-VOiCES-rm2-none-sp2149-ch008912-sg0009-mc01-stu-clo-dg120.wav", "answer": "they had heard of his arrival but had not seen him enter and imagining him still in the court discussed freely the possible reason of his calling they marvelled at his temerity for though most of the tongues which had been let loose attributed the chief blame worthiness to fitzpiers", "subset": "none", "task_type": "understanding", "prediction": "they had heard of his arrival but had not seen him enter and imagining him still in the court discussed freely the possible reason of his calling they marvelled at his temerity for though most of the tongues which had been let loose attributed the chief blameworthiness to fitzpiers", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1165, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm2-none-sp2156-ch025563-sg0005-mc01-stu-clo-dg020.wav", "answer": "that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan's name missus phelan's son came a running he had been on his way", "subset": "none", "task_type": "understanding", "prediction": "that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan s name mrs phelan s son came a running he had been on his way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1166, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm2-none-sp2156-ch025563-sg0005-mc02-lav-clo-dg020.wav", "answer": "that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan's name missus phelan's son came a running he had been on his way", "subset": "none", "task_type": "understanding", "prediction": "that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan s name mrs phelan s son came a running he had been on his way", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1167, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2156/Lab41-SRI-VOiCES-rm2-none-sp2156-ch025563-sg0014-mc01-stu-clo-dg180.wav", "answer": "there is not nor play neither snapped phelan i've got to go out and chase up a drunk or throw a faint or git run over or somethin desperate to square mesilf with the captain i'm an hour overdue at the station", "subset": "none", "task_type": "understanding", "prediction": "there is not nor a play neither snapped phelan i ve got to go out and chase up a drunk or throw a faint or get run over or something desperate to square myself with the captain i m an hour overdue at the station", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1168, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2269/Lab41-SRI-VOiCES-rm2-none-sp2269-ch165387-sg0033-mc02-lav-clo-dg040.wav", "answer": "he will pleasure you with one of his best dances before you go accordingly after thanking the bramin for the account he had given us we all promised to leave mister bruin to his own meditation upon which", "subset": "none", "task_type": "understanding", "prediction": "he will pleasure you with one of his best dances before you go accordingly after thanking the brahmin for the account he had given us we all promised to leave mr bruin to his own meditation upon which", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1169, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-none-sp2412-ch153947-sg0006-mc02-lav-clo-dg140.wav", "answer": "but this had an effect of which i have little reason to complain for i was allowed almost to call them life long self deceivers to their faces and they said it was quite true but that it did not matter", "subset": "none", "task_type": "understanding", "prediction": "but this had an effect of which i have little reason to complain for i was allowed almost to call them lifelong self deceivers to their faces and they said it was quite true but that it did not matter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1170, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2573/Lab41-SRI-VOiCES-rm2-none-sp2573-ch178450-sg0031-mc02-lav-clo-dg110.wav", "answer": "better do it roscoe assented sullenly when'd you begin this thing i always did drink a little ever since i grew up that is leave that talk out you know what i mean well i don't know as i ever had too much in office hours until the other day", "subset": "none", "task_type": "understanding", "prediction": "better do it rascal was saying sullenly when do you begin this thing i always did drink a little ever since i grew up that is leave that talk out you know what i mean well i don't know as i ever had too much in office hours until the other day", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1171, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2673/Lab41-SRI-VOiCES-rm2-none-sp2673-ch156474-sg0019-mc02-lav-clo-dg150.wav", "answer": "where the union ships congress and cumberland lay at anchor these saw the uncouth monster coming and prepared for action the minnesota the saint lawrence and the roanoke lying at fortress monroe also saw her", "subset": "none", "task_type": "understanding", "prediction": "where the union ships congress and cumberland lay at anchor these saw the uncouth monster coming and prepared for action the minnesota the st lawrence and the roanoke lying at port royce monroe also saw her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1172, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm2-none-sp2758-ch086588-sg0024-mc01-stu-clo-dg060.wav", "answer": "and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all", "subset": "none", "task_type": "understanding", "prediction": "and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1173, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm2-none-sp2758-ch086588-sg0024-mc02-lav-clo-dg060.wav", "answer": "and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all", "subset": "none", "task_type": "understanding", "prediction": "and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1174, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036616-sg0001-mc01-stu-clo-dg100.wav", "answer": "this mystery puzzled me finding it impossible to form any views i drifted from one extreme to the other something was out there that much was certain and any doubting thomas was invited to place his finger on the scotia's wound when i arrived in new york", "subset": "none", "task_type": "understanding", "prediction": "this mystery puzzled me finding it impossible to form any views i drifted from one extreme to the other something was out there that much was certain and any doubting thomas was invited to place his finger on the scotia's wound when i arrived in new york", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1175, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036616-sg0038-mc01-stu-clo-dg110.wav", "answer": "not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day's delay would have been unforgivable", "subset": "none", "task_type": "understanding", "prediction": "not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day s delay would have been unforgivable", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1176, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036617-sg0016-mc01-stu-clo-dg130.wav", "answer": "don't bother counting just squeeze it all in and hurry what about master's collections conseil ventured to observe we'll deal with them later what the archaeotherium hyracotherium oreodonts cheiropotamus and master's other fossil skeletons", "subset": "none", "task_type": "understanding", "prediction": "dont bother counting just squeeze it all in and hurry what about masters collections called say venture to observe we ll deal with them later what the archaeotherium hyracotherium oreodonts carpopotamus and masters other fossil skeletons", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1177, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2764/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036617-sg0038-mc01-stu-clo-dg110.wav", "answer": "it hugged this sand covered strip of land where thousands of spectators acclaimed us one more time the escort of boats and tenders still followed the frigate and only left us when we came abreast of the lightship whose two signal lights mark the entrance of the narrows to upper new york bay", "subset": "none", "task_type": "understanding", "prediction": "it hugged this sand covered strip of land where thousands of spectators acclaimed us one more time the escort of boats and tenders still followed the frigate and only left us when we came abreast of the lightship whose two signal lights mark the entrance of the narrows to upper new york bay", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1178, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm2-none-sp2803-ch154320-sg0014-mc01-stu-clo-dg060.wav", "answer": "but as to getting alongside the duncan god forbid", "subset": "none", "task_type": "understanding", "prediction": "but as to getting alongside the duncan god forbid", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1179, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm2-none-sp3368-ch170951-sg0047-mc02-lav-clo-dg010.wav", "answer": "he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a chorus neither shall we allow teachers to make use of them in the instruction of the young meaning", "subset": "none", "task_type": "understanding", "prediction": "he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a course neither shall we allow teachers to make use of them in the instruction of the young meaning", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1180, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-none-sp3446-ch144019-sg0042-mc01-stu-clo-dg140.wav", "answer": "so these two fella they go eat m when they finish eat m my word they fright like hell and they go hide along scrub and god he come walk about along garden and he sing out adam adam he no speak", "subset": "none", "task_type": "understanding", "prediction": "so these two fella they go eat em when they finish eat em my word they fright like hell and they go hide along scrub and god he come walk about along garden and he sing out adam adam he no speak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1181, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-none-sp3446-ch144021-sg0006-mc01-stu-clo-dg020.wav", "answer": "but neither of us was seriously maimed the voyage was our idea of a good time i built the snark and paid for it and for all expenses i contracted to write thirty five thousand words descriptive of the trip for a magazine which was to pay me the same rate i received for stories written at home", "subset": "none", "task_type": "understanding", "prediction": "but neither of us was seriously maimed the voyage was our idea of a good time i built the snark and paid for it and for all expenses i contracted to write thirty five thousand words descriptive of the trip for a magazine which was to pay me the same rate i received for stories written at home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1182, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-none-sp3446-ch144021-sg0018-mc01-stu-clo-dg090.wav", "answer": "mate down with fever ngora ngora sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset", "subset": "none", "task_type": "understanding", "prediction": "mate down with fever negoro negoro sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1183, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp3521/Lab41-SRI-VOiCES-rm2-none-sp3521-ch012715-sg0017-mc01-stu-clo-dg090.wav", "answer": "rice bread boil a pint of rice till soft then mix it with a couple of quarts of rice or wheat flour when cool add half a tea cup of yeast a little salt and milk to render it of the consistency of rye bread when light bake it in small buttered pans", "subset": "none", "task_type": "understanding", "prediction": "rice bread boil a pint of rice till soft then mix it with a couple of quarts of rice or wheat flour when cool add half a tea cup of yeast a little salt and milk to render it of the consistency of rye bread when light bake it in small buttered pans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1184, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_1212-3521/sp3521/Lab41-SRI-VOiCES-rm2-none-sp3521-ch012715-sg0020-mc02-lav-clo-dg030.wav", "answer": "boil a small handful of hops in a couple of quarts of water when the strength is obtained from them strain the liquor put it back on the fire take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour stir it into the liquor when it boils", "subset": "none", "task_type": "understanding", "prediction": "Boil a small handful of hops in a couple of quarts of water. When the strength is obtained from them, strain the liquor, put it back on the fire. Take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour. Stir it into the liquor, when it boils.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1185, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm2-none-sp3549-ch171171-sg0023-mc01-stu-clo-dg070.wav", "answer": "and as great a quantity of provisions as would suffice them for a long time and let himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old", "subset": "none", "task_type": "understanding", "prediction": "and as great a quantity of provisions as would suffice them for a long time and let himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1186, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm2-none-sp3835-ch178029-sg0001-mc01-stu-clo-dg100.wav", "answer": "caused russians to grieve he had such a sad face when shown into the emperor's study that the latter at once asked have you brought me sad news colonel very sad sire replied michaud lowering his eyes with a sigh the abandonment of moscow", "subset": "none", "task_type": "understanding", "prediction": "caused russians to grieve he had such a sad face when shown into the emperor s study that the latter at once asked have you brought me sad news colonel very sad sire replied mashuk covering his eyes with a sigh the abandonment of moscow", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1187, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm2-none-sp3835-ch178029-sg0008-mc02-lav-clo-dg060.wav", "answer": "which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire", "subset": "none", "task_type": "understanding", "prediction": "which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1188, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3835/Lab41-SRI-VOiCES-rm2-none-sp3835-ch178029-sg0017-mc02-lav-clo-dg080.wav", "answer": "the emperor suddenly turned away as if to hide from michaud the tears that rose to his eyes and went to the further end of his study having stood there a few moments he strode back to michaud and pressed his arm below the elbow with a vigorous movement the emperor's mild and handsome face", "subset": "none", "task_type": "understanding", "prediction": "the emperor suddenly turned away as if to hide from mishu the tears that rose to his eyes and went to the further end of his study having stood there a few moments he strode back to mishu and pressed his arm below the elbow with a vigorous movement the emperor s mild and handsome face", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1189, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm2-none-sp3923-ch181420-sg0015-mc02-lav-clo-dg030.wav", "answer": "thither came charles kingsley canon of chester who married a grenfell and who coupled his verse with scientific study and made geological excursions to the river's mouth with the then master of mostyn house school in these excursions the youthful wilfred was a participant", "subset": "none", "task_type": "understanding", "prediction": "thither came charles kingsley canon of chester who married a grenfell and who coupled his verse with scientific study and made geological excursions to the river s mouth with the then master of mostyn house school in these excursions the youthful wilfred was a participant", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1190, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3972/Lab41-SRI-VOiCES-rm2-none-sp3972-ch185074-sg0031-mc01-stu-clo-dg060.wav", "answer": "thomas was anxious to go with me but as i have before observed the chiefs would not suffer him to leave them on the account of his courage and skill in war expecting that they should need his assistance he was a great counsellor and a chief when quite young", "subset": "none", "task_type": "understanding", "prediction": "thomas was anxious to go with me but as i have before observed the chiefs would not suffer him to leave them on the account of his courage and skill in war expecting that they should need his assistance he was a great counsellor and a chief when quite young", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1191, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3989/Lab41-SRI-VOiCES-rm2-none-sp3989-ch182389-sg0002-mc02-lav-clo-dg010.wav", "answer": "shouted happy jack i i don't want to stammered peter you mean you can't jeered happy jack peter pretended not to hear and a few minutes later he hopped away towards the dear old briar patch lipperty lipperty lip", "subset": "none", "task_type": "understanding", "prediction": "shouted happy jack i i don t want to stammered peter you mean you can t jeered happy jack peter pretended not to hear and a few minutes later he hopped away towards the dear old briar patch lipperty lipperty lip", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1192, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3989/Lab41-SRI-VOiCES-rm2-none-sp3989-ch182394-sg0024-mc01-stu-clo-dg150.wav", "answer": "and they began to look down on those who still lived in the water and to put on airs and hold their heads very high now of course old mother nature didn't like this and to punish them she said that they should no longer be able to live in the water even if they wanted to", "subset": "none", "task_type": "understanding", "prediction": "and they began to look down on those who still lived in the water and to put on airs and hold their heads very high now of course old mother nature didn t like this and to punish them she said that they should no longer be able to live in the water even if they wanted to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1193, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp3994/Lab41-SRI-VOiCES-rm2-none-sp3994-ch156757-sg0000-mc01-stu-clo-dg010.wav", "answer": "chapter twenty nine great smallpox epidemic saint mary's hall thanksgiving day in california another brother in law missus brunner has become too childish to have the responsibility of young girls", "subset": "none", "task_type": "understanding", "prediction": "chapter twenty nine great smallpox epidemic st marys hall thanksgiving day in california another brother in law mrs brunner has become too childish to have the responsibility of young girls", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1194, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4010/Lab41-SRI-VOiCES-rm2-none-sp4010-ch010801-sg0016-mc01-stu-clo-dg000.wav", "answer": "is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne", "subset": "none", "task_type": "understanding", "prediction": "is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1195, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4014/Lab41-SRI-VOiCES-rm2-none-sp4014-ch186179-sg0001-mc01-stu-clo-dg090.wav", "answer": "it was that same day that the three boys from brighton were for the first time assigned to a regular unit of the signal corps also with a real thrill they learned that they were almost immediately to see war service for american troops were already in the trenches", "subset": "none", "task_type": "understanding", "prediction": "it was that same day that the three boys from brighton were for the first time assigned to a regular unit of the signal corps also with a real thrill they learned that they were almost immediately to see war service for american troops were already in the trenches", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1196, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4116/Lab41-SRI-VOiCES-rm2-none-sp4116-ch013256-sg0047-mc01-stu-clo-dg050.wav", "answer": "it is your home with me as long as you choose to remain but in this matter i must act as i fully believe jesus would in my place i am willing to bear all that society may say or do society is not my god by the side of this poor soul", "subset": "none", "task_type": "understanding", "prediction": "it is your home with me as long as you choose to remain but in this matter i must act as i fully believe jesus would in my place i am willing to bear all that society may say or do society is not my god by the side of this poor soul", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1197, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4160/Lab41-SRI-VOiCES-rm2-none-sp4160-ch014187-sg0021-mc02-lav-clo-dg120.wav", "answer": "quite replied thorndyke i have entertained it from the first and the new facts that you have gathered increase its probability you remember i said that four hypotheses were possible that the robbery was committed either by reuben by walter by john hornby or by some other person", "subset": "none", "task_type": "understanding", "prediction": "quite replied thorndyke i have entertained it from the first and the new facts that you have gathered increase its probability you remember i said that four hypotheses were possible that the robbery was committed either by reuben by walter by john hornby or by some other person", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1198, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-none-sp4427-ch012471-sg0015-mc02-lav-clo-dg070.wav", "answer": "though it come not immediately if it be present with them before they suffer any great misfortune that they ought to reason thus that god delays to assist them not because he has no regard to them but because he will first try their fortitude and the pleasure they take in their freedom", "subset": "none", "task_type": "understanding", "prediction": "though it come not immediately if it be present with them before they suffer any great misfortune that they ought to reason thus that god delays to assist them not because he has no regard to them but because he will first try their fortitude and the pleasure they take in their freedom", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1199, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-none-sp4427-ch020028-sg0002-mc02-lav-clo-dg180.wav", "answer": "no indeed we ran shivering through the long windy entries all wrapped in shawls and hugging ourselves to retain the friendly warmth of the fire as long as possible far from devising ways of letting in the air we tried hard to keep it out", "subset": "none", "task_type": "understanding", "prediction": "no indeed we ran shivering through the long windy entries all wrapped in shawls and hugging ourselves to retain the friendly warmth of the fire as long as possible far from devising ways of letting in the air we tried hard to keep it out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1200, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-none-sp4427-ch041933-sg0011-mc01-stu-clo-dg060.wav", "answer": "in a moment kostiei's words rushed into the king's mind and he began to weep bitterly to the surprise of everybody who had expected him nearly to die of joy at the sight of his son but try as he would and work as hard as he might", "subset": "none", "task_type": "understanding", "prediction": "in a moment codzi's words rushed into the king s mind and he began to weep bitterly to the surprise of everybody who had expected him nearly to die of joy at the sight of his son but try as he would and work as hard as he might", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1201, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm2-none-sp4438-ch048513-sg0013-mc02-lav-clo-dg170.wav", "answer": "when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her", "subset": "none", "task_type": "understanding", "prediction": "when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1202, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm2-none-sp4438-ch052195-sg0025-mc02-lav-clo-dg140.wav", "answer": "because of the years i put in on the sea if i'd put in the same years cow punching with my body young and pliable i wouldn't be rolling now but i'd be bow legged and so with that girl you noticed that her eyes were what i might call hard she has never been sheltered", "subset": "none", "task_type": "understanding", "prediction": "because of the years i put in on the sea if i put in the same years cow punching with my body young and pliable i wouldnt be rolling now but id be bowlegged and so with that girl you noticed that her eyes were what i might call hard she has never been sheltered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1203, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm2-none-sp4441-ch076250-sg0035-mc02-lav-clo-dg110.wav", "answer": "yes and another thing try to meet my brother find out all you can about his circumstances and friends make up to him worm yourself into his confidence the latter's an easy job become his friend tell him that i've cheated him", "subset": "none", "task_type": "understanding", "prediction": "yes and another thing try to meet my brother find out all you can about his circumstances and friends make up to him worm yourself into his confidence the latter is an easy job become his friend tell him that i have cheated him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1204, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-none-sp4535-ch279852-sg0008-mc01-stu-clo-dg120.wav", "answer": "i'll let a bullet go smack into the first man that makes a move he shouldn't here was a man they couldn't talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later", "subset": "none", "task_type": "understanding", "prediction": "i ll let a bullet go smack into the first man that makes a move he shouldn t here was a man they couldn t talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1205, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4586/Lab41-SRI-VOiCES-rm2-none-sp4586-ch061758-sg0003-mc02-lav-clo-dg100.wav", "answer": "as rapidly as if the injured limb no longer impeded him the hunter suspected his intent standing over six feet he saw the bloody knife blade lying along the cloak it was for that the mustanger was making", "subset": "none", "task_type": "understanding", "prediction": "as rapidly as if the injured limb no longer impeded him the hunter suspected his intent standing over six feet he saw the bloody knife blade lying along the cloak it was for that the mustanger was making", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1206, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4590/Lab41-SRI-VOiCES-rm2-none-sp4590-ch018005-sg0048-mc02-lav-clo-dg110.wav", "answer": "who nightly broke into our tents and took our fellow workers from our side in presenting you with this bowl we all add our prayers for your long life happiness and prosperity we shall ever remain sir your grateful servants", "subset": "none", "task_type": "understanding", "prediction": "who nightly broke into our tents and took our fellow workers from our side in presenting you with this bowl we all add our prayers for your long life happiness and prosperity we shall ever remain sir your grateful servants", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1207, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm2-none-sp4839-ch015307-sg0030-mc01-stu-clo-dg010.wav", "answer": "it needs not so much thought my lord send word to the emperor that we are all ready i am even now a weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of ymbercourt", "subset": "none", "task_type": "understanding", "prediction": "it needs not so much thought my lord send word to the emperor that we are all ready i am even now weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of umbacor", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1208, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm2-none-sp4848-ch028247-sg0043-mc01-stu-clo-dg150.wav", "answer": "vil villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion", "subset": "none", "task_type": "understanding", "prediction": "ville villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1209, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm2-none-sp4848-ch029108-sg0009-mc02-lav-clo-dg030.wav", "answer": "bigger child why what's two hundred thousand dollars pocket money mere pocket money look at the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along behind it", "subset": "none", "task_type": "understanding", "prediction": "bigger child why wants two hundred thousand dollars pocket money where pocket money look the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along behind it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1210, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4957/Lab41-SRI-VOiCES-rm2-none-sp4957-ch030119-sg0028-mc02-lav-clo-dg130.wav", "answer": "so it would be no wonder if he lost all sense of direction even had not the remarks of the girl at his side completely absorbed him beth drove slowly down the main street up a lane back by the lake road and along the street again and this programme was repeated several times", "subset": "none", "task_type": "understanding", "prediction": "so it would be no wonder if he lost all sense of direction even had not the remarks of the girl at his side completely absorbed him bat drove slowly down the main street up a lane back by the lake road and along the street again and this programme was repeated several times", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1211, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp4967/Lab41-SRI-VOiCES-rm2-none-sp4967-ch026553-sg0010-mc01-stu-clo-dg060.wav", "answer": "o little white hen may i go with you asked the river the little white hen told the river that he might go with her and asked him to ride in the little brown basket so the river climbed into the little brown basket", "subset": "none", "task_type": "understanding", "prediction": "oh little white hen may i go with you asked the river the little white hen told the river that he might go with her and asked him to ride in the little brown basket so the river climbed into the little brown basket", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1212, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5126/Lab41-SRI-VOiCES-rm2-none-sp5126-ch027504-sg0008-mc01-stu-clo-dg140.wav", "answer": "and falls backards and breaks his neck if he ain't watched whose business was it to have learned me better that i can't rightly say but it seemed it was the business of the government people to gaol me and iron me and flog me was that justice", "subset": "none", "task_type": "understanding", "prediction": "and falls backward and breaks his neck if he aint watched whose business was it to have learned me better that i can t rightly say but it seemed it was the business of the government people to gallow me and iron me and flog me was that justice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1213, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5126/Lab41-SRI-VOiCES-rm2-none-sp5126-ch027504-sg0031-mc02-lav-clo-dg060.wav", "answer": "there's no saying what mister knightley might do if his wife had been here thank god she's away at bathurst said starlight i hate seeing women put out besides everybody bows down to missus knightley she's as good as she's handsome i believe and", "subset": "none", "task_type": "understanding", "prediction": "there is no saying what mr knightley might do if his wife had been here thank god she is away at battersea said starlight i hate seeing women put out besides everybody bows down to mrs knightley she is as good as she is handsome i believe and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1214, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5157/Lab41-SRI-VOiCES-rm2-none-sp5157-ch047237-sg0019-mc01-stu-clo-dg000.wav", "answer": "persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from day break", "subset": "none", "task_type": "understanding", "prediction": "persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from daybreak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1215, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5157/Lab41-SRI-VOiCES-rm2-none-sp5157-ch047237-sg0019-mc02-lav-clo-dg000.wav", "answer": "persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from day break", "subset": "none", "task_type": "understanding", "prediction": "persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from daybreak", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1216, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm2-none-sp5189-ch037999-sg0002-mc01-stu-clo-dg130.wav", "answer": "this is of course mainly a parent's problem and is best solved by resorting to the following formula let a and b represent two young girls finishing schools in the east missus raleigh jones x from the west sends her daughter to a", "subset": "none", "task_type": "understanding", "prediction": "this is of course mainly a parent s problem and is best solved by resorting to the following formula let a and b represent two young girls finishing schools in the east mrs raleigh jones x from the west sends her daughter to a", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1217, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5319/Lab41-SRI-VOiCES-rm2-none-sp5319-ch042637-sg0003-mc02-lav-clo-dg120.wav", "answer": "it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position", "subset": "none", "task_type": "understanding", "prediction": "it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1218, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5319/Lab41-SRI-VOiCES-rm2-none-sp5319-ch084357-sg0034-mc02-lav-clo-dg020.wav", "answer": "the circumstantial evidence against the allegation that prince charles had left a legitimate child is so strong that no amount of romance of history could upset it in his latter days when separated from his wife the princess louisa", "subset": "none", "task_type": "understanding", "prediction": "the circumstantial evidence against the allegation that prince charles had left a legitimate child is so strong that no amount of romance of history could upset it in his latter days when separated from his wife the princess louisa", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1219, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5338/Lab41-SRI-VOiCES-rm2-none-sp5338-ch024640-sg0005-mc02-lav-clo-dg170.wav", "answer": "he certainly possesses talents beyond the rude sphere in which he moves and being neither destitute of ambition nor encumbered with scruples he will probably attempt by every means to distinguish himself during the period of these unhappy commotions", "subset": "none", "task_type": "understanding", "prediction": "He certainly possesses talents beyond the rude sphere in which he moves and being neither destitute of ambition nor encumbered with scruples. He will probably attempt, by every means. To distinguish himself during the period of these unhappy commotions.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1220, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5400/Lab41-SRI-VOiCES-rm2-none-sp5400-ch034479-sg0015-mc01-stu-clo-dg000.wav", "answer": "tit made room and levin started behind him the grass was short close to the road and levin who had not done any mowing for a long while and was disconcerted by the eyes fastened upon him cut badly for the first moments though he swung his scythe vigorously behind him he heard voices", "subset": "none", "task_type": "understanding", "prediction": "tit made room and levine started behind him the grass was short close to the road and levine who had not done any mowing for a long while and was disconcerted by the eyes fastened upon him cut badly for the first moments though he swung his scythe vigorously behind he heard voices", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1221, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5401/Lab41-SRI-VOiCES-rm2-none-sp5401-ch102526-sg0028-mc01-stu-clo-dg090.wav", "answer": "at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter", "subset": "none", "task_type": "understanding", "prediction": "at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1222, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5456/Lab41-SRI-VOiCES-rm2-none-sp5456-ch062014-sg0008-mc02-lav-clo-dg050.wav", "answer": "so de nex night de gal went off an comed back late wid de young man her mammy ax him in an gin him a seat by de fire an dar he sot all wrop up in his blinkit wid his haid turnt way f'um de light", "subset": "none", "task_type": "understanding", "prediction": "so the next night the gal went off and come back late with the young man her mammy ax him in and give him a seat by the fire and down he sat all wrapped up in his blanket with his head turned away from the light", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1223, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5583/Lab41-SRI-VOiCES-rm2-none-sp5583-ch041259-sg0043-mc01-stu-clo-dg180.wav", "answer": "and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain", "subset": "none", "task_type": "understanding", "prediction": "and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1224, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5635/Lab41-SRI-VOiCES-rm2-none-sp5635-ch058137-sg0014-mc02-lav-clo-dg060.wav", "answer": "with a party of friends mister jimmy hurrying out with a slate in his hand begged me to stop a moment and thus addressed me well mister carlton this algebra is a most powerful thing ain't it indeed it is mister jimmy have you been looking into it", "subset": "none", "task_type": "understanding", "prediction": "with a party of friends mr jimmy hurrying up with a slate in his hand begged me to stop a moment and thus addressed me well mr carlton this algebra is a most powerful thing ain t it indeed it is mr jimmy have you been looking into it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1225, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043301-sg0015-mc01-stu-clo-dg000.wav", "answer": "had been composed with both skill and ardour they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ's words themselves were quoted", "subset": "none", "task_type": "understanding", "prediction": "had been composed with both skill and ardor they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ s words themselves were quoted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1226, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043301-sg0026-mc01-stu-clo-dg160.wav", "answer": "and a storm of laughter rippled round the throng of heads she heard an indrawn hiss behind her chair and the next instant an exclamation from mabel what was that there was a sharp crack and the tiny gesticulating figure staggered back a step", "subset": "none", "task_type": "understanding", "prediction": "and a storm of laughter rippled around the throng of heads she heard an indrawn hiss behind her chair and the next instant an exclamation from mabel what was that there was a sharp crack and the tiny gesticulating figure staggered back a step", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1227, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043302-sg0005-mc02-lav-clo-dg150.wav", "answer": "she said then she broke off and sat back why did he shoot just then she asked oliver turned his eyes for an instant towards his mother but she was knitting tranquilly then he answered with a curious deliberateness", "subset": "none", "task_type": "understanding", "prediction": "she said then she broke off and sat back why did he shoot just then she asked oliver turned his eyes for an instant towards his mother but she was knitting tranquilly then he answered with a curious deliberateness", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1228, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5678/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043303-sg0015-mc01-stu-clo-dg070.wav", "answer": "mister phillips arrived the next morning as usual just as mabel had left the old lady's room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver's room", "subset": "none", "task_type": "understanding", "prediction": "mr phillips arrived the next morning as usual just as mabel had left the old lady s room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver s room", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1229, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm2-none-sp5717-ch100145-sg0017-mc01-stu-clo-dg070.wav", "answer": "of course obray count erskyll planetary proconsul of aditya didn't realize that he didn't even know what javasan meant just free them commodore vann shatrak couldn't see much of a problem either he would have answered", "subset": "none", "task_type": "understanding", "prediction": "of course obray count erskyll planetary proconsul of aditya didn't realize that he didn't even know what javasan meant just free them commodore van shatrak couldn't see much of a problem either he would have answered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1230, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5740/Lab41-SRI-VOiCES-rm2-none-sp5740-ch039910-sg0028-mc02-lav-clo-dg130.wav", "answer": "missus ralston went over to the christmas table and looked at the little gifts half tenderly and half pityingly they're not much like the contents of our basket are they she said as she touched the calendar jimmie had made for mollie out of cardboard and autumn leaves and grasses", "subset": "none", "task_type": "understanding", "prediction": "mrs ralston went over to the christmas table and looked at the little gifts half tenderly and half pityingly they are not much like the contents of our basket are they she said as she touched the calendar jimmy had made for molly out of cardboard and autumn leaves and grasses", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1231, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5740/Lab41-SRI-VOiCES-rm2-none-sp5740-ch097610-sg0031-mc01-stu-clo-dg110.wav", "answer": "for while rejoicings were still loud over the departure of the enemy there came a knock at missus tracy's door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier", "subset": "none", "task_type": "understanding", "prediction": "for while rejoicings were still loud over the departure of the enemy there came a knock at eces tracey s door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1232, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5789/Lab41-SRI-VOiCES-rm2-none-sp5789-ch070653-sg0003-mc02-lav-clo-dg110.wav", "answer": "and those who were to be called on to give evidence occupied chairs to one side of the table behind which the coroner sat while the jury in double row with plastered hair and a spurious ease of manner flanked him on the other side", "subset": "none", "task_type": "understanding", "prediction": "and those who were to be called on to give evidence occupied chairs to one side of the table behind which the coroner sat while the jury in double row with plastered hair and a spurious ease of manner flanked it on the other side", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1233, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-none-sp5935-ch043305-sg0009-mc02-lav-clo-dg150.wav", "answer": "again came the crying of voices again the signals and once more a car whirled past followed almost immediately by another there was a jerk a smooth movement percy staggered and fell into a seat", "subset": "none", "task_type": "understanding", "prediction": "again came the crying of voices again the signals and once more a car whirled past followed almost immediately by another there was a jerk a smooth movement percy staggered and fell into a seat", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1234, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-none-sp5935-ch055927-sg0018-mc02-lav-clo-dg050.wav", "answer": "thus while the screw outside of the hull is applying the force continuously the steam in the inside is driving the shafting with equal evenness and regularity the steam turbine does not appear to have by any means reached finality in its form", "subset": "none", "task_type": "understanding", "prediction": "thus while the screw outside of the hull is applying the force continuously the steam in the inside is driving the shafting with equal evenness and regularity the steam turbine does not appear to have by any means reached finality in its form", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1235, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm2-none-sp6147-ch034605-sg0030-mc01-stu-clo-dg160.wav", "answer": "it was a necessity doubtless but what a pity josiana appreciated lord david and showed him off there was between them a tacit agreement neither to conclude nor to break off the engagement they eluded each other this method of making love one step in advance and two back", "subset": "none", "task_type": "understanding", "prediction": "it was a necessity doubtless but what a pity josiana appreciated lord david and showed him off there was between them a tacit agreement neither to conclude nor to break off the engagement they eluded each other this method of making love one step in advance and two back", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1236, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6319/Lab41-SRI-VOiCES-rm2-none-sp6319-ch064726-sg0018-mc02-lav-clo-dg070.wav", "answer": "then the prince took the princess by the hand she was dressed in great splendour but he did not hint that she looked as he had seen pictures of his great grandmother look he thought her all the more charming for that", "subset": "none", "task_type": "understanding", "prediction": "then the prince took the princess by the hand she was dressed in great splendour but he did not hint that she looked as he had seen pictures of his great grandmother look he thought her all the more charming for that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1237, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6395/Lab41-SRI-VOiCES-rm2-none-sp6395-ch086708-sg0006-mc01-stu-clo-dg100.wav", "answer": "and yet dantes need not die death alone can separate them remarked fernand you talk like a noodle my friend said caderousse and here is danglars who is a wide awake clever deep fellow who will prove to you that you are wrong", "subset": "none", "task_type": "understanding", "prediction": "and yet dantes need not die death alone can separate them remarked fernand you talk like a noodle my friend said caderousse and here is danglars who is a wide awake clever deep fellow who will prove to you that you are wrong", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1238, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm2-none-sp6415-ch111615-sg0024-mc02-lav-clo-dg120.wav", "answer": "who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible", "subset": "none", "task_type": "understanding", "prediction": "who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1239, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm2-none-sp6454-ch093938-sg0016-mc02-lav-clo-dg080.wav", "answer": "i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business", "subset": "none", "task_type": "understanding", "prediction": "i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1240, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm2-none-sp6519-ch069411-sg0014-mc01-stu-clo-dg040.wav", "answer": "when that something else huddled in oozing blood on the floor beneath drew them unto itself with the irresistibleness of grim reality and he forgot all else in the horror of a sight for which his fears however great", "subset": "none", "task_type": "understanding", "prediction": "when that something else huddled in oozing blood on the floor beneath drew them unto itself with the irresistibleness of grim reality and he forgot all else in the horror of the sight for which his fears however great", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1241, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6519/Lab41-SRI-VOiCES-rm2-none-sp6519-ch231834-sg0020-mc02-lav-clo-dg170.wav", "answer": "but what grounds have you to believe him any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence", "subset": "none", "task_type": "understanding", "prediction": "but what grounds have you to believe in any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1242, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-none-sp6544-ch067863-sg0034-mc01-stu-clo-dg150.wav", "answer": "i am so glad i thought about it but it was really estralla she said if i was black we could come sylvia had replied then the boat swung clear and headed toward charleston i am not going to land at the big wharves said sylvia i am going to that wharf near miss patten's garden", "subset": "none", "task_type": "understanding", "prediction": "i am so glad i thought about it but it was really estralla she said if i was black we could come sylvia had replied then the boat swung clear and headed toward charleston i am not going to land at the big wharves said sylvia i am going to that wharf near miss patten s garden", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1243, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm2-none-sp6574-ch120583-sg0041-mc02-lav-clo-dg020.wav", "answer": "there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best", "subset": "none", "task_type": "understanding", "prediction": "there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1244, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6696/Lab41-SRI-VOiCES-rm2-none-sp6696-ch068773-sg0013-mc01-stu-clo-dg060.wav", "answer": "me mister forbes me yes tom i'll pay you twenty dollars a week to start with and more if you serve me faithfully and you'll board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself", "subset": "none", "task_type": "understanding", "prediction": "me mr forbes me yes tom i will pay you twenty dollars a week to start with and more if you serve me faithfully and you will board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1245, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6788/Lab41-SRI-VOiCES-rm2-none-sp6788-ch096241-sg0028-mc01-stu-clo-dg120.wav", "answer": "but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also", "subset": "none", "task_type": "understanding", "prediction": "but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1246, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6788/Lab41-SRI-VOiCES-rm2-none-sp6788-ch096241-sg0028-mc02-lav-clo-dg120.wav", "answer": "but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also", "subset": "none", "task_type": "understanding", "prediction": "but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1247, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6848/Lab41-SRI-VOiCES-rm2-none-sp6848-ch076049-sg0018-mc02-lav-clo-dg060.wav", "answer": "she had had no husband of the lord and master type so to speak but only a prince consort well in hand why shouldn't the grammont heiress dominate her male belonging if it came to that in the same fashion", "subset": "none", "task_type": "understanding", "prediction": "she had had no husband of a lord and master type so to speak but only a prince consort well in hand why shouldn t the grammont heiress dominate her male belonging if it came to that in the same fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1248, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6848/Lab41-SRI-VOiCES-rm2-none-sp6848-ch252322-sg0006-mc01-stu-clo-dg090.wav", "answer": "turning as he went to look back towards the bed and evidently going with reluctance is it fever asked the sick man in a faint but unfaltering accent it's a kind of cerebral congestion a matter of them membranes that's over the brain", "subset": "none", "task_type": "understanding", "prediction": "turning as he went to look back towards the bed and evidently going with reluctance is it fever asked the sick man in a faint but unfaltering accent it is a kind of cerebral congestion a matter of them membranes that is over the brain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1249, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm2-none-sp6895-ch092805-sg0031-mc02-lav-clo-dg010.wav", "answer": "oh i don't know says he and he begins to tell them about a cab driver at sixth avenue and broadway those ideas don't suit me i'm not tied down to anything that isn't eight thousand miles in diameter just put me down as e rushmore coglan citizen of the terrestrial sphere", "subset": "none", "task_type": "understanding", "prediction": "oh i don t know says he and he begins to tell them about a cab drive at sixth avenue and broadway those ideas don t suit me i m not tied down to anything that isn t eight thousand miles in diameter just put me down as eve rushmore coglan citizen of the terrestrial sphere", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1250, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm2-none-sp7000-ch083706-sg0015-mc02-lav-clo-dg000.wav", "answer": "if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mister hedges any objections which i might urge would appear quite trivial", "subset": "none", "task_type": "understanding", "prediction": "if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mr hedges any objections which i might urge would appear quite trivial", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1251, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm2-none-sp7095-ch088483-sg0007-mc02-lav-clo-dg130.wav", "answer": "just because he has said it for so long and so often the force of repetition is great it is in fact taken by a vast majority of men as the equivalent of proof most men have to accept their religions ready made", "subset": "none", "task_type": "understanding", "prediction": "just because he has said it for so long and so often the force of repetition is great it is in fact taken by a vast majority of men as the equivalent of proof most men have to accept their religions ready made", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1252, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm2-none-sp7095-ch088489-sg0000-mc01-stu-clo-dg020.wav", "answer": "when copernicus showed that the earth was not the center of the universe when darwin proved that man's origin was not the result of direct creation when freud explained that man was not the master of his own thoughts or actions", "subset": "none", "task_type": "understanding", "prediction": "when copernicus showed that the earth was not the center of the universe when darwin proved that man s origin was not the result of direct creation when freud explained that man was not the master of his own thoughts or actions", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1253, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-none-sp7148-ch007763-sg0027-mc01-stu-clo-dg160.wav", "answer": "were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connexions between things not dependent on our will and feelings natural laws by virtue of which in many cases", "subset": "none", "task_type": "understanding", "prediction": "were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connections between things not dependent on our will and feelings natural laws by virtue of which in many cases", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1254, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-none-sp7148-ch007763-sg0027-mc02-lav-clo-dg160.wav", "answer": "were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connexions between things not dependent on our will and feelings natural laws by virtue of which in many cases", "subset": "none", "task_type": "understanding", "prediction": "were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connections between things not dependent on our will and feelings natural laws by virtue of which in many cases", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1255, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7247/Lab41-SRI-VOiCES-rm2-none-sp7247-ch077778-sg0016-mc01-stu-clo-dg120.wav", "answer": "that was one instance two weeks later i went again this time to hear goetterdaemmerung the results were the same only the effect was instantaneous the curtain had hardly risen before i retired to the little ante room of the box our party occupied", "subset": "none", "task_type": "understanding", "prediction": "that was one instance two weeks later i went again this time to hear gotterdammerung the results were the same only the effect was instantaneous the curtain had hardly risen before i retired to the little anteroom of the box our party occupied", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1256, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7247/Lab41-SRI-VOiCES-rm2-none-sp7247-ch077778-sg0034-mc02-lav-clo-dg090.wav", "answer": "to be well shaken before taken will be an effective remedy for a torpid liver and the man or woman who suffers from lassitude will doubtless find in the lively airs of our two step composers an efficient tonic to bring their vitality up to a high standard of activity", "subset": "none", "task_type": "understanding", "prediction": "to be well shaken before taken will be an effective remedy for a torpid liver and the man or woman who suffers from lassitude will doubtless find in the lively airs of our two step composers an efficient tonic to bring their vitality up to a high standard of activity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1257, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7247/Lab41-SRI-VOiCES-rm2-none-sp7247-ch101864-sg0004-mc02-lav-clo-dg090.wav", "answer": "the farther away they could get from the oil that made the machinery of life run easily and noiselessly the better pleased they were the dining room looked particularly pleasant this july evening a gentle breeze stirred the curtains at the open windows", "subset": "none", "task_type": "understanding", "prediction": "the farther away they could get from the oil that made the machinery of life run easily and noiselessly the better pleased they were the dining room looked particularly pleasant this july evening a gentle breeze stirred the curtains at the open windows", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1258, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7276/Lab41-SRI-VOiCES-rm2-none-sp7276-ch090847-sg0045-mc02-lav-clo-dg030.wav", "answer": "and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen", "subset": "none", "task_type": "understanding", "prediction": "and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1259, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7276/Lab41-SRI-VOiCES-rm2-none-sp7276-ch284424-sg0042-mc01-stu-clo-dg130.wav", "answer": "what can the answer be trot looked the boy over carefully she didn't see any wings on him the only queer thing about him was his big umbrella oh she said suddenly clapping her hands together i know now", "subset": "none", "task_type": "understanding", "prediction": "what can the answer be trot looked the boy over carefully she didn t see any wings on him the only queer thing about him was his big umbrella oh she said suddenly clapping her hands together i know now", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1260, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm2-none-sp7498-ch099156-sg0013-mc01-stu-clo-dg000.wav", "answer": "we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time", "subset": "none", "task_type": "understanding", "prediction": "we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1261, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7688/Lab41-SRI-VOiCES-rm2-none-sp7688-ch105390-sg0042-mc02-lav-clo-dg110.wav", "answer": "rumour has it in france that your highness could an you would give the truest account of that enigmatical wayside flower he looked quickly and keenly at marguerite as he spoke but she betrayed no emotion and her eyes met his quite fearlessly", "subset": "none", "task_type": "understanding", "prediction": "Rumor has it in France that your highness could, and you would give the truest account of that enigmatical wayside flower. He looked quickly and keenly at Marguerite as he spoke, but she betrayed no emotion. And her eyes met his, quite fearlessly.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1262, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7688/Lab41-SRI-VOiCES-rm2-none-sp7688-ch109656-sg0020-mc02-lav-clo-dg180.wav", "answer": "there was a big lump in his throat as he thought of the cross words he had spoken to his wife surely it was hard enough for her to live in that horrible country without having to bear the burden of his abuse he cursed himself grimly and felt a sudden flush of shame that", "subset": "none", "task_type": "understanding", "prediction": "there was a big lump in his throat as he thought of the cross words he had spoken to his wife surely it was hard enough for her to live in that horrible country without having to bear the burden of his abuse he cursed himself grimly and felt a sudden flush of shame that", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1263, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-none-sp7850-ch281318-sg0009-mc02-lav-clo-dg120.wav", "answer": "so in a great company they came fluttering hopping twittering up to the elm tree where mother magpie nestled comfortably in her new house", "subset": "none", "task_type": "understanding", "prediction": "so in a great company they came fluttering hopping twittering up to the elm tree where mother magpie nestled comfortably in her new house", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1264, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-none-sp7850-ch281318-sg0010-mc02-lav-clo-dg110.wav", "answer": "o wise mother magpie dear mother magpie they cried teach us how to build our nests like yours for it is growing night and we are tired and sleepy", "subset": "none", "task_type": "understanding", "prediction": "oh wise mother magpie dear mother magpie they cried teach us how to build our nests like yours for it is growing night and we are tired and sleepy", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1265, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-none-sp7850-ch286674-sg0000-mc01-stu-clo-dg070.wav", "answer": "a person would think that after a family had lived so long in a place all the neighbors would be fond of them yet it is not so", "subset": "none", "task_type": "understanding", "prediction": "a person would think that after a family had lived so long in a place all the neighbors would be fond of them yet it is not so", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1266, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-none-sp7868-ch110706-sg0031-mc01-stu-clo-dg120.wav", "answer": "and long snake like shadows crept up along the mountain sides hans struggled on the sun was sinking but its descent seemed to bring no coolness the leaden weight of the dead air pressed upon his brow and heart but", "subset": "none", "task_type": "understanding", "prediction": "and long snake like shadows crept up along the mountain sides kahn struggled on the sun was sinking but its descent seemed to bring no coolness the leaden weight of the dead air pressed upon his brow and heart but", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1267, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-none-sp7868-ch110706-sg0035-mc01-stu-clo-dg040.wav", "answer": "and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball", "subset": "none", "task_type": "understanding", "prediction": "and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1268, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm2-none-sp7881-ch105574-sg0015-mc01-stu-clo-dg040.wav", "answer": "yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us", "subset": "none", "task_type": "understanding", "prediction": "yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1269, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm2-none-sp7881-ch105574-sg0034-mc01-stu-clo-dg060.wav", "answer": "i was always careful that this should not keep me away from the command when enduring hard marches or when engagements were coming on when in camp i kept my rifle in one of the ammunition wagons of several of which i had charge but if the alarm sounded my rifle was on my shoulder", "subset": "none", "task_type": "understanding", "prediction": "i was always careful that this should not keep me away from the command when enduring hard marches or when engagements were coming on when in camp i kept my rifle in one of the ammunition wagons of several of which i had charge but if the alarm sounded my rifle was on my shoulder", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1270, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm2-none-sp7881-ch109662-sg0027-mc01-stu-clo-dg180.wav", "answer": "and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet", "subset": "none", "task_type": "understanding", "prediction": "and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1271, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7910/Lab41-SRI-VOiCES-rm2-none-sp7910-ch080534-sg0007-mc02-lav-clo-dg180.wav", "answer": "eagles was absorbed in the study of a certain branch of political statistics the enthusiasm of his life was financial reform every budget presented to parliament he criticised with extraordinary thoroughness and in fact with an acumen", "subset": "none", "task_type": "understanding", "prediction": "eagles was absorbed in the study of a certain branch of political statistics the enthusiasm of his life was financial reform every budget presented to parliament he criticised with extraordinary thoroughness and in fact with an acumen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1272, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm2-none-sp7976-ch110523-sg0000-mc02-lav-clo-dg090.wav", "answer": "he had little enough to break or bite and once when there was a great famine in the land he could hardly procure even his daily bread and as he lay thinking in his bed one night he sighed and said to his wife what will become of us", "subset": "none", "task_type": "understanding", "prediction": "he had little enough to break or bite and once when there was a great famine in the land he could hardly procure even his daily bread and as he lay thinking in his bed one night he sighed and said to his wife what will become of us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1273, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm2-none-sp7981-ch112061-sg0025-mc01-stu-clo-dg020.wav", "answer": "justly indignant begged to be allowed to give the great lady a piece of his mind come on said vincent our business lies in another direction is it not strange he said smiling a few moments later as he tried to staunch the blood with his handkerchief", "subset": "none", "task_type": "understanding", "prediction": "justly indignant begged to be allowed to give the great lady a piece of his mind come on said vincent our business lies in another direction is it not strange he said smiling a few moments later as he tried to staunch the blood with his handkerchief", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1274, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm2-none-sp7995-ch276908-sg0012-mc01-stu-clo-dg070.wav", "answer": "of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature", "subset": "none", "task_type": "understanding", "prediction": "of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1275, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm2-none-sp7995-ch276908-sg0017-mc02-lav-clo-dg090.wav", "answer": "not of that monster man mister booth i am undone am revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech", "subset": "none", "task_type": "understanding", "prediction": "not of that monster man mr booth i am undone am revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1276, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm2-none-sp7995-ch280250-sg0028-mc01-stu-clo-dg040.wav", "answer": "hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it", "subset": "none", "task_type": "understanding", "prediction": "hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1277, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm2-none-sp7995-ch280250-sg0028-mc02-lav-clo-dg040.wav", "answer": "hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it", "subset": "none", "task_type": "understanding", "prediction": "hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1278, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm2-none-sp8108-ch280354-sg0017-mc02-lav-clo-dg040.wav", "answer": "he turned to gaze on his beloved dimly he saw her but for the last time for a power she could not resist drew her back orpheus stretched out his arms and tried to seize her but he only clasped the empty air", "subset": "none", "task_type": "understanding", "prediction": "he turned to gaze on his beloved dimly he saw her but for the last time for a power she could not resist drew her back orpheus stretched out his arms and tried to seize her but he only clasped the empty air", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1279, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm2-none-sp8108-ch280359-sg0006-mc01-stu-clo-dg100.wav", "answer": "sometimes he hid himself as one among a troop of timid reindeer sometimes he lay in the nest of a wood pigeon sometimes he swam a bright spotted fish in the sea but wherever he was among living creatures", "subset": "none", "task_type": "understanding", "prediction": "Sometimes he hid himself as one among a troop of timid reindeer. Sometimes he lay in the nest of a wood pigeon. Sometimes he swam a bright spotted fish in the sea. But wherever he was among living creatures.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1280, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm2-none-sp8225-ch274374-sg0019-mc02-lav-clo-dg140.wav", "answer": "son of lord say he himself as well as his father a great parliamentary leader was governor and commanded a garrison of two thousand five hundred foot and two regiments one of horse another of dragoons the fortifications not being complete or regular", "subset": "none", "task_type": "understanding", "prediction": "son of lord say he himself as well as his father a great parliamentary leader was governor and commanded a garrison of two thousand five hundred foot and two regiments one horse another of dragoons the fortifications not being complete or regular", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1281, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8225/Lab41-SRI-VOiCES-rm2-none-sp8225-ch274376-sg0002-mc01-stu-clo-dg060.wav", "answer": "than the english parliament in order to allure that nation into a close confederacy openly declared their wishes of ecclesiastical reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used", "subset": "none", "task_type": "understanding", "prediction": "then the english parliament in order to allure that nation into a close confederacy openly declared their wishes of ecclesiastical reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1282, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-none-sp8266-ch258262-sg0001-mc02-lav-clo-dg020.wav", "answer": "they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered", "subset": "none", "task_type": "understanding", "prediction": "they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1283, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-none-sp8266-ch258262-sg0012-mc02-lav-clo-dg050.wav", "answer": "and the land of the enchanted calf so called because its king al muzalzil had a pied calf which he had clad in housings brocaded with red gold and worshipped as a god one day the king and his people went in to the calf and found him trembling so the king said", "subset": "none", "task_type": "understanding", "prediction": "and the land of the enchanted calf so called because its king al murzazul had a piebald calf which he had clad in housings brocaded with red gold and worshipped as a god one day the king and his people went in to the calf and found him trembling so the king said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1284, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-none-sp8266-ch258263-sg0022-mc02-lav-clo-dg000.wav", "answer": "no but rejoice ye for king gharib hath returned to you so they rejoiced and gharib after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him", "subset": "none", "task_type": "understanding", "prediction": "no but rejoice ye for king gharib hath returned to you so they rejoiced and gharib after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1285, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8425/Lab41-SRI-VOiCES-rm2-none-sp8425-ch291444-sg0001-mc01-stu-clo-dg140.wav", "answer": "who serve as the tottering monuments of good old times will be gathered to their fathers their children engrossed by the empty pleasures or insignificant transactions of the present age will neglect to treasure up the recollections of the past", "subset": "none", "task_type": "understanding", "prediction": "who serve as the tottering monuments of good old times will be gathered to their fathers their children engrossed by the empty pleasures or insignificant transactions of the present age will neglect to treasure up the recollections of the past", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1286, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8575/Lab41-SRI-VOiCES-rm2-none-sp8575-ch290351-sg0028-mc01-stu-clo-dg140.wav", "answer": "on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small", "subset": "none", "task_type": "understanding", "prediction": "on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1287, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8605/Lab41-SRI-VOiCES-rm2-none-sp8605-ch276939-sg0024-mc01-stu-clo-dg170.wav", "answer": "and exulting with the thoughts of presently seeing her beloved friend she was answered at the door that the lady was not at home nor could she upon telling her name obtain any admission this considering the account she had received of the lady's cold greatly surprized her", "subset": "none", "task_type": "understanding", "prediction": "and exulting with the thoughts of presently seeing her beloved friend she was answered at the door that the lady was not at home nor could she upon telling her name obtain any admission this considering the account she had received of the lady s cold greatly surprised her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1288, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8605/Lab41-SRI-VOiCES-rm2-none-sp8605-ch291172-sg0006-mc02-lav-clo-dg070.wav", "answer": "and she intimated to me that it was only the baby girl with whom she intended to feed the little baby boy as he had not got fair play and so the majesty of justice was maintained cats are greatly sensible of the honour of maternity", "subset": "none", "task_type": "understanding", "prediction": "and she intimated to me that it was only the baby girl with whom she intended to feed the little baby boy as he had not got fair play and so the majesty of justice was maintained cats are greatly sensible of the honour of maternity", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1289, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8605/Lab41-SRI-VOiCES-rm2-none-sp8605-ch292138-sg0005-mc01-stu-clo-dg170.wav", "answer": "she greeted her two little playmates from the vicarage all three were bubbling over with glee at the prospect of an outing this bright june afternoon upon the river thames they were to go up stream to a pretty little nook in a quiet backwater", "subset": "none", "task_type": "understanding", "prediction": "she greeted her two little playmates from the vicarage all three were bubbling over with glee at the prospect of an outing this bright june afternoon upon the river thames they were to go up stream to a pretty little nook in a quiet backwater", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1290, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/none/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm2-none-sp8713-ch302111-sg0010-mc02-lav-clo-dg080.wav", "answer": "answered in the words which follow song of birds is idle chatter and the throstle's merely chirping as a child a daughter's treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seat thee", "subset": "none", "task_type": "understanding", "prediction": "answered in the words which follow song of birds is idle chatter and the thrushes merely chirping as a child a daughter is treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seek thee", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1291, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm2-tele-sp0122-ch129752-sg0041-mc02-lav-clo-dg040.wav", "answer": "sweetened and flavored with a few drops of vanilla put on the top cake and dust with powdered sugar date cake sift two cups of flour with four level teaspoons of baking powder one half level teaspoon of salt", "subset": "tele", "task_type": "understanding", "prediction": "Sweetened and flavored with a few drops of vanilla. Put on the top cake and dust with powdered sugar date cake. Sift 2 cups of flour with 4 level teaspoons of baking powder, one half level teaspoon of salt.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1292, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0159/Lab41-SRI-VOiCES-rm2-tele-sp0159-ch121902-sg0007-mc01-stu-clo-dg070.wav", "answer": "it was concluded that the whole aim of man's will though the means of pursuit vary is set intently upon happiness i do remember that this too was proved dost thou also call to mind how happiness is absolute good", "subset": "tele", "task_type": "understanding", "prediction": "it was concluded that the whole aim of man s will though the means of pursuit vary is set intently upon happiness i do remember that this too was proved dost thou also call to mind how happiness is absolutely good", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1293, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0159/Lab41-SRI-VOiCES-rm2-tele-sp0159-ch135897-sg0010-mc02-lav-clo-dg030.wav", "answer": "in a manner answerable to our condition but i added i rather believe you wish to marry again i shall feel much surprised if such be the case after the experience you have had of the little satisfaction there is in wedlock", "subset": "tele", "task_type": "understanding", "prediction": "in a manner answerable to our condition but i added i rather believe you wish to marry again i shall feel much surprised if such be the case after the experience you have had of the little satisfaction there is in redlack", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1294, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0188/Lab41-SRI-VOiCES-rm2-tele-sp0188-ch141613-sg0021-mc01-stu-clo-dg040.wav", "answer": "for who better than himself could understand the need of a child's presence for that matter pollyanna talked to everybody about jamie she assumed that everybody would be as interested as she herself was", "subset": "tele", "task_type": "understanding", "prediction": "for who better than himself could understand the need of a child's presence for that matter pollyanna talked to everybody about jamie she assumed that everybody would be as interested as she herself was", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1295, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0204/Lab41-SRI-VOiCES-rm2-tele-sp0204-ch148920-sg0003-mc01-stu-clo-dg050.wav", "answer": "relics of the days when the countrymen of julius caesar had settled there where have they not settled i for one would hardly be astonished if relics of the ancient romans should someday be found deep under the grass growing around the bunker hill monument", "subset": "tele", "task_type": "understanding", "prediction": "relics of the days when the countrymen of julius caesar had settled there where have they not settled i for one would hardly be astonished if relics of the ancient romans should some day be found deep under the grass growing around the bunker hill monument", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1296, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm2-tele-sp0205-ch123882-sg0030-mc01-stu-clo-dg080.wav", "answer": "and the new limited and the maritime express that holds the record of six hundred whirling miles from paris to marseilles but what are they to this this mad career this breakneck speed this thundering roar of the mariposa local driving hard to its home", "subset": "tele", "task_type": "understanding", "prediction": "and the new limited and the maritime express that holds the record of six hundred whirling miles from paris to marseilles but what are they to this this mad career this breakneck speed this thundering roar of the mariposa local driving hard to its home", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1297, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm2-tele-sp0208-ch126600-sg0011-mc02-lav-clo-dg090.wav", "answer": "freddie fisher fairly fussed when he came to eat his crust often on the floor he'd throw it hoping mother wouldn't know it goops all hate to eat the crust if you're told to then you must", "subset": "tele", "task_type": "understanding", "prediction": "Freddy Fisher fairly fussed when he came to eat his crust. Often on the floor, he d throw it, hoping mother wouldn t know it. Goofs all hate to eat the crust. If you re told to, then you must.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1298, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm2-tele-sp0208-ch126600-sg0030-mc01-stu-clo-dg170.wav", "answer": "just look at percival b sloop a most unpleasant sort of goop he pokes his fingers in his nose and wipes his hands upon his clothes he does a lot of things that you", "subset": "tele", "task_type": "understanding", "prediction": "just look at percival b slugh a most unpleasant sort of goop he pokes his fingers in his nose and wipes his hands upon his gloves he does a lot of things that you", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1299, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm2-tele-sp0209-ch004731-sg0002-mc02-lav-clo-dg030.wav", "answer": "comprehended many such not unfrequently through emma's persuasion he had some of the chosen and the best to dine with him but evening parties were what he preferred and unless he fancied himself at any time unequal to company", "subset": "tele", "task_type": "understanding", "prediction": "Comprehended many such, not unfrequently through Emma's persuasion. He had some of the chosen and the best to dine with him. But evening parties were what he preferred. And unless he fancied himself at any time, unequal to company.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1300, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0209/Lab41-SRI-VOiCES-rm2-tele-sp0209-ch157830-sg0016-mc02-lav-clo-dg050.wav", "answer": "it did not appear to him that sir walter could materially alter his style of living in a house which had such a character of hospitality and ancient dignity to support in any other place sir walter might judge for himself and would be looked up to as regulating the modes of life", "subset": "tele", "task_type": "understanding", "prediction": "it did not appear to him that sir walter could materially alter his style of living in a house which had such a character of hospitality and ancient dignity to support in any other place sir walter might judge for himself and would be looked up to as regulating the modes of life", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1301, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0240/Lab41-SRI-VOiCES-rm2-tele-sp0240-ch144999-sg0038-mc02-lav-clo-dg000.wav", "answer": "and by no means is it really necessary to a successful outing twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals", "subset": "tele", "task_type": "understanding", "prediction": "and by no means is it really necessary to a successful hunter twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1302, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0242/Lab41-SRI-VOiCES-rm2-tele-sp0242-ch126842-sg0035-mc01-stu-clo-dg010.wav", "answer": "peter no i don't want to hear about it said uncle alec sternly i don't care what you were fighting about but you must settle your quarrels in a different fashion remember my commands felix peter", "subset": "tele", "task_type": "understanding", "prediction": "Peter, no, I don't want to hear about it, said Uncle Alec sternly. I don't care what you were fighting about, but you must settle your quarrel in a different fashion. Remember my commands, Felix, Peter.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1303, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0288/Lab41-SRI-VOiCES-rm2-tele-sp0288-ch121741-sg0015-mc01-stu-clo-dg150.wav", "answer": "and enough likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god's making one would say", "subset": "tele", "task_type": "understanding", "prediction": "and enough likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god s making one would say", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1304, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm2-tele-sp0459-ch127521-sg0029-mc01-stu-clo-dg000.wav", "answer": "but silver from the other boat looked sharply over and called out to know if that were me and from that moment i began to regret what i had done the crews raced for the beach but the boat i was in having some start and being at once the lighter and the better manned", "subset": "tele", "task_type": "understanding", "prediction": "but silver from the other boat looked sharply over and called out to know if that were me and from that moment i began to regret what i had done the crews raced for the beach but the boat i was in having some start and being at once the lighter and the better manned", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1305, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0459/Lab41-SRI-VOiCES-rm2-tele-sp0459-ch127522-sg0003-mc01-stu-clo-dg120.wav", "answer": "another followed and soon over the whole surface of the marsh a great cloud of birds hung screaming and circling in the air i judged at once that some of my shipmates must be drawing near along the borders of the fen nor was i deceived", "subset": "tele", "task_type": "understanding", "prediction": "another followed and soon over the whole surface of the marsh a great cloud of birds hung screaming and circling in the air i judged at once that some of my shipmates must be drawing near along the borders of the fen nor was i deceived", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1306, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0472/Lab41-SRI-VOiCES-rm2-tele-sp0472-ch129983-sg0032-mc01-stu-clo-dg160.wav", "answer": "to which both of them submitted without any reluctance for nothing had been said on either side to make them dislike each other less than they had done before and elinor sat down to the card table with the melancholy persuasion that edward was not only without affection for the person who was to be his wife", "subset": "tele", "task_type": "understanding", "prediction": "to which both of them submitted without any reluctance for nothing had been said on either side to make them dislike each other less than they had done before and elinor sat down to the card table with the melancholy persuasion that edward was not only without affection for the person who was to be his wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1307, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0479/Lab41-SRI-VOiCES-rm2-tele-sp0479-ch107479-sg0005-mc02-lav-clo-dg150.wav", "answer": "and in order to quiet all suspicion of my real status in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and", "subset": "tele", "task_type": "understanding", "prediction": "and it required also special precautions in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1308, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm2-tele-sp0480-ch123176-sg0011-mc02-lav-clo-dg130.wav", "answer": "and season it with wine or lemon juice tapioca jelly wash the tapioca well and let it soak for several hours in cold water put it in a sauce pan with the same water and let it boil slowly till it is clear and thick", "subset": "tele", "task_type": "understanding", "prediction": "and season it with wine or lemon juice tapioca jelly wash the tapioca well and let it soak for several hours in cold water put it in a saucepan with the same water and let it boil slowly till it is clear and thick", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1309, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm2-tele-sp0480-ch126292-sg0029-mc02-lav-clo-dg070.wav", "answer": "partlet and having dug a grave for her he laid her in it and made a little hillock over her then he sat down by the grave and wept and mourned till at last he died too", "subset": "tele", "task_type": "understanding", "prediction": "having dug a grave for her he laid her in it down the hall and made a little hillock over her then he sat down by the grave and wept and mourned till at last he died too", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1310, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0480/Lab41-SRI-VOiCES-rm2-tele-sp0480-ch126336-sg0008-mc01-stu-clo-dg030.wav", "answer": "ah unlucky wretch that i am sighed she would that i had married king grisly beard next they came to some fine meadows whose are these beautiful green meadows said she", "subset": "tele", "task_type": "understanding", "prediction": "unlucky wretch that i am said she would that i had married king grizzly beard next they came to some fine meadows whose are these beautiful green meadows said she", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1311, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0492/Lab41-SRI-VOiCES-rm2-tele-sp0492-ch131882-sg0007-mc01-stu-clo-dg120.wav", "answer": "insects phileas fogg was a member of the reform and that was all the way in which he got admission to this exclusive club was simple enough he was recommended by the barings with whom he had an open credit", "subset": "tele", "task_type": "understanding", "prediction": "insects the late fog was a member of the reform and that was all the way in which he got admission to his exclusive club was simple enough he was recommended by the barings with whom he had an open credit", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1312, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch123163-sg0044-mc01-stu-clo-dg100.wav", "answer": "grated bread soaked in cream put in the omelet some think an improvement the dripping of a nice ham some persons use for omelet instead of butter to boil eggs have the water boiling and look at your watch as you put them in", "subset": "tele", "task_type": "understanding", "prediction": "Grated bread soaked in cream, put in the omelet. Some think an improvement. The dripping of a nice ham. Some persons use for omelet instead of butter to boil eggs. Have the water boiling and look at your watch as you put them in.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1313, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch128310-sg0034-mc01-stu-clo-dg080.wav", "answer": "looking silently on at the morning traffic in fleet street with their two heads as near to one another as the two eyes of each were bore a considerable resemblance to a pair of monkeys the resemblance was not lessened by the accidental circumstance that the mature jerry bit and spat out straw", "subset": "tele", "task_type": "understanding", "prediction": "looking silently on at the morning traffic in fleet street with their two heads as near to one another as the two eyes of each were bore a considerable resemblance to a pair of monkeys the resemblance was not lessened by the accidental circumstance that the mature jerry bit and spat out straw", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1314, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch128331-sg0002-mc02-lav-clo-dg180.wav", "answer": "had this work always ready for it now that it could strike the fingers of the knitting women were vicious with the experience that they could tear there was a change in the appearance of saint antoine the image had been hammering into this for hundreds of years", "subset": "tele", "task_type": "understanding", "prediction": "had this work always ready for it now that it could strike the fingers of the knitting women were vicious with the experience that they could tear there was a change in the appearance of saint antoine the image had been hammering into this for hundreds of years", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1315, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0636/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch128331-sg0021-mc01-stu-clo-dg150.wav", "answer": "and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth", "subset": "tele", "task_type": "understanding", "prediction": "and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1316, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0637/Lab41-SRI-VOiCES-rm2-tele-sp0637-ch127597-sg0003-mc01-stu-clo-dg010.wav", "answer": "his native valley and that he intended to return to it the same day at once it struck me that could i but reach that valley under his protection i might easily from thence reach nukuheva by water and animated by the prospect which this plan held out", "subset": "tele", "task_type": "understanding", "prediction": "his native valley and that he intended to return to it the same day at once it struck me that could i but reach that valley under his protection i might easily from thence reach nukuheva by water and animated by the prospect which this plan held out", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1317, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0770/Lab41-SRI-VOiCES-rm2-tele-sp0770-ch134592-sg0010-mc02-lav-clo-dg000.wav", "answer": "now he was just a blind breathing carcase nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there were something in these wise old dogs that did not perish utterly with death", "subset": "tele", "task_type": "understanding", "prediction": "now he was just a blind breathing carcass nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there were something in these wise old dogs that did not perish utterly with death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1318, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp0948/Lab41-SRI-VOiCES-rm2-tele-sp0948-ch132707-sg0018-mc01-stu-clo-dg010.wav", "answer": "their hand in ours and that night we knew that to hold the body of women in our arms is neither ugly nor shameful but the one ecstasy granted to the race of men", "subset": "tele", "task_type": "understanding", "prediction": "their hand in ours and that night we knew that to hold the body of a woman in our arms is neither ugly nor shameful but the one ecstasy granted to the race of men", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1319, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm2-tele-sp1050-ch134121-sg0013-mc01-stu-clo-dg120.wav", "answer": "but something was the matter she could not pull it up there was the dinner but she could not reach it all the family in turn went and tried all pulled together in vain the dinner could not be stirred", "subset": "tele", "task_type": "understanding", "prediction": "But something was the matter. She could not pull it up. There was the dinner, but she could not reach it all. The family, in turn, went and tried. All pulled together in vain. The dinner could not be stirred.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1320, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm2-tele-sp1050-ch134121-sg0023-mc01-stu-clo-dg070.wav", "answer": "yes said agamemnon they found there pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mister peterkin reached the carpenter's shop", "subset": "tele", "task_type": "understanding", "prediction": "yes said agamemnon they found their pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mr peterkin reached the carpenter shop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1321, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1050/Lab41-SRI-VOiCES-rm2-tele-sp1050-ch134121-sg0023-mc02-lav-clo-dg070.wav", "answer": "yes said agamemnon they found there pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mister peterkin reached the carpenter's shop", "subset": "tele", "task_type": "understanding", "prediction": "yes said agamemnon they found their pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mr peterkin reached the carpenter shop", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1322, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1052/Lab41-SRI-VOiCES-rm2-tele-sp1052-ch132776-sg0021-mc01-stu-clo-dg020.wav", "answer": "would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped", "subset": "tele", "task_type": "understanding", "prediction": "would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1323, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1052/Lab41-SRI-VOiCES-rm2-tele-sp1052-ch139308-sg0001-mc01-stu-clo-dg130.wav", "answer": "and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there", "subset": "tele", "task_type": "understanding", "prediction": "and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1324, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1066/Lab41-SRI-VOiCES-rm2-tele-sp1066-ch103481-sg0002-mc02-lav-clo-dg080.wav", "answer": "and hope looked out again from tired eyes down where the white point gardens drank the sun and rippled to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a taunt", "subset": "tele", "task_type": "understanding", "prediction": "and hope looked out again from tired eyes down where the white point gardens strike the sun and ripple to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a tod", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1325, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1112/Lab41-SRI-VOiCES-rm2-tele-sp1112-ch128136-sg0010-mc02-lav-clo-dg030.wav", "answer": "as if the bulk of twenty million whales were worth one pleading soul or all the laws that rule the lifeless suns could soothe the sense of outrage in a loving human heart sublime majestic", "subset": "tele", "task_type": "understanding", "prediction": "as if the bulk of twenty million whales were worth one pleading soul or all the laws that rule the lifeless suns could soothe the sense of outrage in a loving human heart sublime majestic", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1326, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1116/Lab41-SRI-VOiCES-rm2-tele-sp1116-ch137572-sg0003-mc02-lav-clo-dg060.wav", "answer": "when one has received the promise of something greatly desired but must wait awhile before its delivery the happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight", "subset": "tele", "task_type": "understanding", "prediction": "when one has received the promise of something greatly desired but must wait a while before its delivery happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1327, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1121/Lab41-SRI-VOiCES-rm2-tele-sp1121-ch135824-sg0002-mc01-stu-clo-dg160.wav", "answer": "began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny's cousins more closely related to him than to any other members of the mouse family", "subset": "tele", "task_type": "understanding", "prediction": "began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny s cousins more closely related to him than to any other members of the mouse family", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1328, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm2-tele-sp1160-ch139727-sg0010-mc01-stu-clo-dg040.wav", "answer": "unless their vast estates were in the same act expressly excused and they had even taken bonds of these deputies to observe such instructions the assemblies for three years held out against this injustice", "subset": "tele", "task_type": "understanding", "prediction": "unless their vast estates were in the same act expressly excused and they had even taken bonds of these deputies to observe such instructions the assemblies for three years bellowed out against this injustice", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1329, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1160/Lab41-SRI-VOiCES-rm2-tele-sp1160-ch139730-sg0007-mc01-stu-clo-dg000.wav", "answer": "should assist in comprehending the following he procur'd an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely form'd by instrument makers his lectures", "subset": "tele", "task_type": "understanding", "prediction": "should assist in comprehending the following he procured an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely formed by instrument makers his lectures", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1330, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_0032-1182/sp1182/Lab41-SRI-VOiCES-rm2-tele-sp1182-ch133396-sg0013-mc02-lav-clo-dg070.wav", "answer": "two days later a very stout little one eyed man clad in a leathern jerkin and wearing a round leathern cap upon his head came toiling up the path to the postern door of trutz drachen his back bowed under the burthen of a great peddler's pack it was our old friend the one eyed hans", "subset": "tele", "task_type": "understanding", "prediction": "two days later a very stout little one eyed man clad in a leathern jerkin and wearing a round leathern cap upon his head came toiling up the path to the postern door of trutz thal his back bowed under the burden of a great pedlar s pack it was our old friend the one eyed hans", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1331, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1235/Lab41-SRI-VOiCES-rm2-tele-sp1235-ch135883-sg0034-mc02-lav-clo-dg030.wav", "answer": "he then related what had passed betwixt him and the genie and informed her that he had given him his oath to return at the end of the year to receive death from his hands when they heard this afflicting intelligence they all began to lament in the most distressing manner", "subset": "tele", "task_type": "understanding", "prediction": "he then related what had passed betwixt him and the genie and informed her that he had given him his oath to return at the end of the year to receive death from his hands when they heard this afflicting intelligence they all began to lament in the most distressing manner", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1332, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm2-tele-sp1246-ch124548-sg0014-mc01-stu-clo-dg170.wav", "answer": "most of her red cross work ray still needed nursing she explained when carol saw him with his uniform off in a pepper and salt suit and a new gray felt hat she was disappointed he was not major wutherspoon he was raymie", "subset": "tele", "task_type": "understanding", "prediction": "most of her red cross work ray still needed nursing she explained when carol saw him with his uniform off in a pepper and salt suit and a new gray felt hat she was disappointed he was not major weatherspoon he was raymie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1333, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1246/Lab41-SRI-VOiCES-rm2-tele-sp1246-ch135815-sg0017-mc01-stu-clo-dg160.wav", "answer": "sometimes however if we cannot find a place that just suits us we go quite a distance are your babies born down in that little bedroom in the ground asked jumper the hare of course replied johnny chuck", "subset": "tele", "task_type": "understanding", "prediction": "sometimes however if we cannot find a place that just suits us we go quite a distance are your babies born down in that little bedroom in the ground asked jumper the hare of course replied johnny chuck", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1334, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1259/Lab41-SRI-VOiCES-rm2-tele-sp1259-ch027120-sg0000-mc02-lav-clo-dg040.wav", "answer": "chapter eight at five o'clock the two ladies retired to dress and at half past six elizabeth was summoned to dinner to the civil inquiries which then poured in and amongst which she had the pleasure of distinguishing the much superior solicitude of mister bingley's", "subset": "tele", "task_type": "understanding", "prediction": "chapter eight at five o clock the two ladies retired to dress and at half past six elizabeth was summoned to dinner to the civil inquiries which then poured in and amongst which she had the pleasure of distinguishing the much superior solicitude of mr bingley", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1335, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1271/Lab41-SRI-VOiCES-rm2-tele-sp1271-ch133279-sg0037-mc02-lav-clo-dg140.wav", "answer": "it constitutes a singular power so strangely composed of mingled good and evil that it is at the same time indispensable to the existence of freedom and nearly incompatible with the maintenance of public order", "subset": "tele", "task_type": "understanding", "prediction": "it constitutes a singular power that so strangely composed of mingled good and evil that it is at the same time indispensable to the existence of freedom and merely incompatible with the maintenance of public order", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1336, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm2-tele-sp1272-ch135031-sg0002-mc02-lav-clo-dg090.wav", "answer": "i have remained a prisoner only because i wished to be one and with this he stepped forward and burst the stout chains as easily as if they had been threads", "subset": "tele", "task_type": "understanding", "prediction": "i have remained a prisoner only because i wished to be one and with this he stepped forward and burst the stout chains as easily as if they had been threads", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1337, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1272/Lab41-SRI-VOiCES-rm2-tele-sp1272-ch141231-sg0023-mc02-lav-clo-dg160.wav", "answer": "the strength that enables someone in a trance to hold his body stiff and unsupported except at two points the head and heels", "subset": "tele", "task_type": "understanding", "prediction": "The strength that enables someone in a trance to hold his body stiff and unsupported. Except at two points, the head and heels.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1338, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch128226-sg0003-mc01-stu-clo-dg140.wav", "answer": "thus did the world once seem to me thus once on a time did i also cast my fancy beyond man like all backworldsmen beyond man forsooth ah ye brethren", "subset": "tele", "task_type": "understanding", "prediction": "thus did the world once seem to me thus once on a time did i also cast my fancy beyond man like all backworldsmen beyond man forsooth ah ye brethren", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1339, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch128240-sg0014-mc01-stu-clo-dg020.wav", "answer": "fain likewise would it play with the fire of the fagot and stake and be on thy guard also against the assaults of thy love too readily doth the recluse reach his hand to any one who meeteth him", "subset": "tele", "task_type": "understanding", "prediction": "fain likewise would it play with the fire of the faggot and stake and be on thy guard also against the assaults of thy love too readily doth the recluse reach his hand to any one who meeteth him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1340, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0001-mc02-lav-clo-dg120.wav", "answer": "is regarded as certain and conclusive nor does any man ever entertain a doubt where he sees a piece of iron that it will have weight and cohesion of parts as in all other instances which have ever fallen under his observation", "subset": "tele", "task_type": "understanding", "prediction": "is regarded as certain and conclusive nor does any man ever entertain a doubt where he sees a piece of iron that it will have weight and cohesion of parts as in all other instances which have ever fallen under his observation", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1341, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0018-mc01-stu-clo-dg180.wav", "answer": "be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to men it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one", "subset": "tele", "task_type": "understanding", "prediction": "be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to men it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1342, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0018-mc02-lav-clo-dg180.wav", "answer": "be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to men it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one", "subset": "tele", "task_type": "understanding", "prediction": "be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to man it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1343, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1392/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0021-mc02-lav-clo-dg010.wav", "answer": "is derived merely from custom it may be asked how it happens that men so much surpass animals in reasoning and one man so much surpasses another has not the same custom the same influence on all", "subset": "tele", "task_type": "understanding", "prediction": "is derived merely from custom it may be asked how it happens that men so much surpass animals in reason and one man so much surpasses another has not the same custom the same influence on all", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1344, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1472/Lab41-SRI-VOiCES-rm2-tele-sp1472-ch139797-sg0000-mc02-lav-clo-dg100.wav", "answer": "chapter thirteen a world of high medical knowledge i spent a long and profitable season in the vicinity of the great dipper witnessing the almost infinite variations of human life as found from world to world and looking upon the wild wastes of the many planets that are not inhabited", "subset": "tele", "task_type": "understanding", "prediction": "chapter thirteen a world of high medical knowledge i spent a long and profitable season in the vicinity of the great dipper witnessing the almost infinite variations of human life as found from world to world and looking upon the wild wastes of the many planets that are not inhabited", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1345, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1536/Lab41-SRI-VOiCES-rm2-tele-sp1536-ch137608-sg0016-mc01-stu-clo-dg100.wav", "answer": "and therewithal she turned her from the window and sir beaumains rode awayward from the castle making great dole and so he rode here and there and wist not where he rode till it was dark night and then it happened him to come to a poor man's house and there he was harboured all that night", "subset": "tele", "task_type": "understanding", "prediction": "and therewithal she turned her from the window and sir beaumains rode awayward from the castle making great dole and so he rode here and there and wist not where he rode till it was dark night and then it happened him to come to a poor man s house and there he was harboured all that night", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1346, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1841/Lab41-SRI-VOiCES-rm2-tele-sp1841-ch150351-sg0013-mc01-stu-clo-dg070.wav", "answer": "and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the indian came out and plunged into the cold water of a near by stream", "subset": "tele", "task_type": "understanding", "prediction": "and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the antaeon came out and plunged into the cold water of a nearby stream", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1347, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1867/Lab41-SRI-VOiCES-rm2-tele-sp1867-ch148436-sg0020-mc02-lav-clo-dg020.wav", "answer": "and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothin", "subset": "tele", "task_type": "understanding", "prediction": "and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1348, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm2-tele-sp1874-ch143361-sg0012-mc02-lav-clo-dg050.wav", "answer": "and his firm moderation was soon rewarded by a solid and honorable peace he maintained with a powerful hand the balance of the west till it was at length overthrown by the ambition of clovis and although unable to assist his rash and unfortunate kinsman", "subset": "tele", "task_type": "understanding", "prediction": "and his firm moderation was soon rewarded by a solid and honorable peace he maintained with a powerful hand the balance of the west till it was at length overthrown by the ambition of clovis and although unable to assist his rash and unfortunate kinsman", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1349, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1874/Lab41-SRI-VOiCES-rm2-tele-sp1874-ch165702-sg0018-mc01-stu-clo-dg100.wav", "answer": "emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four", "subset": "tele", "task_type": "understanding", "prediction": "emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1350, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1926/Lab41-SRI-VOiCES-rm2-tele-sp1926-ch147979-sg0036-mc02-lav-clo-dg160.wav", "answer": "several teachers experimented with him they found he had absolute pitch and a remarkable memory as a very young child he could repeat after a fashion any composition that was played for him no matter how many wrong notes he struck he never lost the intention of a passage", "subset": "tele", "task_type": "understanding", "prediction": "several teachers experimented with him they found he had absolute pitch and a remarkable memory as a very young child he could repeat after a fashion any composition that was played for him no matter how many wrong notes he struck he never lost the attention of the passage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1351, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm2-tele-sp1961-ch145733-sg0016-mc02-lav-clo-dg130.wav", "answer": "what does he say asked the princess i really hardly like to tell you answered the lady in waiting oh then you can whisper it to me he is disobliging said the princess and went away", "subset": "tele", "task_type": "understanding", "prediction": "what does he say asked the princess i really hardly like to tell you answered the lady in white and ear oh then you can whisper it to me and to supply to you said the princess and went away", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1352, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1961/Lab41-SRI-VOiCES-rm2-tele-sp1961-ch149739-sg0028-mc02-lav-clo-dg090.wav", "answer": "why of course exclaimed the angel haven't you come to my party didn't you get my invitation i sent you one by mail asked freckles yes said the angel i had to help with the preparations and i couldn't find time to drive out but i wrote you a letter", "subset": "tele", "task_type": "understanding", "prediction": "why of course exclaimed the angel havent you come to my party didn t you get my invitation i sent you one by mail asked freckles yes said the angel i had to help with the preparations and i could n t find time to drive up but i wrote you a letter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1353, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp1963/Lab41-SRI-VOiCES-rm2-tele-sp1963-ch147036-sg0034-mc02-lav-clo-dg050.wav", "answer": "milburgh had gone too far tarling saw his face lengthen and the look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath the confession of odette rider", "subset": "tele", "task_type": "understanding", "prediction": "milburgh had gone too far tarling saw his face lengthen and the look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath a confession of odette rider", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1354, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm2-tele-sp2012-ch139358-sg0006-mc01-stu-clo-dg030.wav", "answer": "nothing can be truer but while you have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency", "subset": "tele", "task_type": "understanding", "prediction": "nothing can be truer but why we have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1355, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2012/Lab41-SRI-VOiCES-rm2-tele-sp2012-ch139358-sg0007-mc02-lav-clo-dg080.wav", "answer": "what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words", "subset": "tele", "task_type": "understanding", "prediction": "what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1356, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2074/Lab41-SRI-VOiCES-rm2-tele-sp2074-ch147193-sg0010-mc02-lav-clo-dg000.wav", "answer": "then she took him by the hand and went into the temple and prayed and came down again with theseus to her home and when a full year was past she led theseus up again to the temple and bade him lift the stone", "subset": "tele", "task_type": "understanding", "prediction": "then she took him by the hand and went into the temple and prayed and came down again with theseus to her home and when a full year was passed she led theseus up again to the temple and bade him lift the stone", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1357, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2074/Lab41-SRI-VOiCES-rm2-tele-sp2074-ch147193-sg0015-mc02-lav-clo-dg050.wav", "answer": "till upon all the mountains there was no hunter so swift as theseus and he killed phaia the wild sow of crommyon which wasted all the land till all the people said surely the gods are with the lad", "subset": "tele", "task_type": "understanding", "prediction": "till upon all the mountains there was no hunter so swift as theseus and he killed phaia the wild sow of chromium which wasted all the land till all the people said surely the gods are with the lad", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1358, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2093/Lab41-SRI-VOiCES-rm2-tele-sp2093-ch143271-sg0025-mc01-stu-clo-dg120.wav", "answer": "at last he crept from me to speak to mister francis it is of no use to stay longer i'm afraid my lad he whispered unless we wait and see whether the hut is left empty when the expedition party comes back", "subset": "tele", "task_type": "understanding", "prediction": "At last, he crept from me to speak to Mr. Francis, it is of no use to stay longer, I am afraid, my lad, he whispered, unless we wait and see whether the hut is left empty. When the expedition party comes back.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1359, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2110/Lab41-SRI-VOiCES-rm2-tele-sp2110-ch161100-sg0026-mc01-stu-clo-dg180.wav", "answer": "it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing", "subset": "tele", "task_type": "understanding", "prediction": "it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1360, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2149/Lab41-SRI-VOiCES-rm2-tele-sp2149-ch007239-sg0011-mc01-stu-clo-dg110.wav", "answer": "god's firm foundation stands having this seal the lord knew those who are his and", "subset": "tele", "task_type": "understanding", "prediction": "Gods firm foundation stands. Having this seal, the Lord knew those who are his and.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1361, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm2-tele-sp2285-ch124595-sg0015-mc02-lav-clo-dg020.wav", "answer": "without seeking to probe further into matters in which he had no personal concern it was hardly to be supposed however that the local population would show equal forbearance curiosity was widespread", "subset": "tele", "task_type": "understanding", "prediction": "without seeking to probe further into matters in which he had no personal concern it was hardly to be supposed however that the local population would show equal forbearance curiosity was widespread", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1362, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2285/Lab41-SRI-VOiCES-rm2-tele-sp2285-ch163381-sg0000-mc01-stu-clo-dg040.wav", "answer": "by and by when we got up we turned over the truck the gang had stole off of the wreck and found boots and blankets and clothes and all sorts of other things and a lot of books and a spyglass", "subset": "tele", "task_type": "understanding", "prediction": "By and by, we got up. We turned over the truck. The gang had stole off of the wreck, found boots and blankets and clothes and all sorts of other things and a lot of books and a spyglass.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1363, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2294/Lab41-SRI-VOiCES-rm2-tele-sp2294-ch169656-sg0028-mc02-lav-clo-dg000.wav", "answer": "the moors then boarded the san antonio and took her in tow when close to the land the captain was rowed ashore and the pirates spent part of the night in unloading the cargo next morning the san antonio was seen drifting out to sea and the captain who was afraid of being put to death", "subset": "tele", "task_type": "understanding", "prediction": "the moors then boarded the san antonio and took her in tow when close to the land the captain was rowed ashore and the pirates spent part of the night in unloading the cargo next morning the san antonio was seen drifting out to sea and the captain who was afraid of being put to death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1364, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-tele-sp2412-ch153948-sg0001-mc02-lav-clo-dg130.wav", "answer": "it will be seen that i did not succeed in my design and that however much i may have met with that was new and strange i have been unable to reap any pecuniary advantage", "subset": "tele", "task_type": "understanding", "prediction": "it will be seen that i did not succeed in my design and that however much i may have met with that was new and strange i have been unable to reap any pecuniary advantage", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1365, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2412/Lab41-SRI-VOiCES-rm2-tele-sp2412-ch153954-sg0014-mc02-lav-clo-dg050.wav", "answer": "in about four hours of walking from the time we started and after passing two or three more villages we came upon a considerable town and my guides made many attempts to make me understand something but i gathered no inkling of their meaning except that i need be under no apprehension of danger", "subset": "tele", "task_type": "understanding", "prediction": "in about four hours of walking from the time we started and after passing two or three more villages we came upon a considerable town and my guides made many attempts to make me understand something but i gathered no inkling of their meaning except that i need be under no apprehension of danger", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1366, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2481/Lab41-SRI-VOiCES-rm2-tele-sp2481-ch012731-sg0012-mc02-lav-clo-dg060.wav", "answer": "stir them while boiling to keep them from spotting this dye will make a salmon or orange color according to the strength of it and the time the goods remain in drain them out of the dye and dry them quick in the shade when dry wash them in soft soap suds", "subset": "tele", "task_type": "understanding", "prediction": "stir them while boiling to keep them from spotting this dye will make a salmon or orange color according to the strength of it and the time the goods remain in drain them out of the dye and dry them quick in the shade when dry wash them in soft soap suds", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1367, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2691/Lab41-SRI-VOiCES-rm2-tele-sp2691-ch156755-sg0035-mc01-stu-clo-dg120.wav", "answer": "grandpa had the grave enclosed with a white paling and we children planted castilian rose bushes at the head and foot of the mound and carried water to them from the house and in time their branches met and the grave was a bed of fragrant blossoms", "subset": "tele", "task_type": "understanding", "prediction": "grandpa had the grave enclosed with white paling and we children planted castilian rose bushes at the head and foot of the mound and carried water to them from the house and in time their branches met and the grave was a bed of fragrant blossoms", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1368, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2758/Lab41-SRI-VOiCES-rm2-tele-sp2758-ch161217-sg0020-mc01-stu-clo-dg100.wav", "answer": "but though nemesis in her original character was the distributor of rewards as well as punishments the world was so full of sin that she found but little occupation in her first capacity and hence became finally regarded as the avenging goddess only", "subset": "tele", "task_type": "understanding", "prediction": "but though nemesis in her original character was the distributor of rewards as well as punishments the world was so full of sin that she found but little occupation in her first capacity and hence became finally regarded as the avenging goddess only", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1369, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2803/Lab41-SRI-VOiCES-rm2-tele-sp2803-ch154320-sg0000-mc01-stu-clo-dg080.wav", "answer": "fortunately will halley was not a man in a hurry and did not use a press of canvas or his masts would inevitably have come down", "subset": "tele", "task_type": "understanding", "prediction": "fortunately will halley was not a man in a hurry and did not use oppressive canvas or his mass would inevitably have come down", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1370, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm2-tele-sp2911-ch012359-sg0000-mc01-stu-clo-dg060.wav", "answer": "fit for drink a country without a fit drink for cheese has no cheese fit for drink greece was the first country to prove its epicurean fitness according to the old saying above for it had wine to tipple", "subset": "tele", "task_type": "understanding", "prediction": "fit for drink a country without a fit drink for cheese has no cheese fit for drink greece was the first country to approve its epicurean fitness according to the old saying above for it had wine to tipple", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1371, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp2911/Lab41-SRI-VOiCES-rm2-tele-sp2911-ch012359-sg0022-mc02-lav-clo-dg180.wav", "answer": "with any caraway seeded cheese or cream cheese with a handy saucer of caraway seeds in the section of france devoted to gin the juniper berries that flavor the drink also go into a local cheese fromage fort", "subset": "tele", "task_type": "understanding", "prediction": "With any caraway seeded cheese or cream cheese with a handy saucer of caraway seeds in the section of France devoted to gin, the juniper berries that flavor the drink also go into a local cheese, Formage Port.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1372, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp3368/Lab41-SRI-VOiCES-rm2-tele-sp3368-ch170950-sg0014-mc02-lav-clo-dg020.wav", "answer": "why he said are they not capable of defending themselves no i said not if we were right in the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success", "subset": "tele", "task_type": "understanding", "prediction": "why he said are they not capable of defending themselves no i said it is not if we were right that the principle which was acknowledged by all of us when we were framing this state the principle as you will remember was that one man cannot practise many arts with success", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1373, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-tele-sp3446-ch144019-sg0006-mc01-stu-clo-dg080.wav", "answer": "preceded beche de mer english beche de mer was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose beche de mer english is a splendid argument for the esperanto enthusiasts", "subset": "tele", "task_type": "understanding", "prediction": "preceded bechdeler english bechdeler was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose bechdeler english is a splendid argument for the esperanto enthusiasts", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1374, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp3446/Lab41-SRI-VOiCES-rm2-tele-sp3446-ch176270-sg0019-mc01-stu-clo-dg140.wav", "answer": "or submit to any terms that could violate their liberty they then made arrangements for the defense of the city in the meantime the florentine forces were not idle and after innumerable mischiefs done to the country", "subset": "tele", "task_type": "understanding", "prediction": "or submit to any terms that could violate their liberty they then made arrangements for the defence of the city in the meantime the florentine forces were not idle and after innumerable mischiefs done to the country", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1375, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_1212-3521/sp3483/Lab41-SRI-VOiCES-rm2-tele-sp3483-ch174132-sg0022-mc02-lav-clo-dg020.wav", "answer": "then for the last time i saw the earth an enduring globule of radiant blue swimming in an eternity of ether and there i a fragile flake of soul dust flickered silently across the void from the distant blue into the expanse of the unknown", "subset": "tele", "task_type": "understanding", "prediction": "then for the last time i saw the earth and a girding globule of radiant blue swimming in an eternity of ether and there i fragile flake of soul dust flickered silently across the void from the disc of blue into the expanse of the unknown", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1376, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp3549/Lab41-SRI-VOiCES-rm2-tele-sp3549-ch171171-sg0001-mc02-lav-clo-dg040.wav", "answer": "and so much of the wall as enclosed the city on the west side this wall was spared in order to afford a camp for such as were to lie in garrison as were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified", "subset": "tele", "task_type": "understanding", "prediction": "And so much of the wall as enclosed, the city on the west side, this wall was spared in order to afford a camp for such as were to lie in garrison. As were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1377, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp3923/Lab41-SRI-VOiCES-rm2-tele-sp3923-ch174992-sg0016-mc01-stu-clo-dg050.wav", "answer": "hoping that in spite of the sacrilege committed he might be able to face a world that would be ignorant of his crime as the vulpicide on the afternoon of the day of the deed went along the corridor to his room one maid servant whispered to another and the poor victim of an imperfect sight", "subset": "tele", "task_type": "understanding", "prediction": "hoping that in spite of the sacrilege committed he might be able to face a world that would be ignorant of his crime as the vulpo side on the afternoon of the day of the deed went along the corridor to his room one maid servant whispered to another and the poor victim of an imperfect sight", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1378, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp3972/Lab41-SRI-VOiCES-rm2-tele-sp3972-ch170212-sg0014-mc01-stu-clo-dg020.wav", "answer": "not unfrequently the shepherd was startled by the blare of trumpets and peering out beheld a cohort sometimes a legion in march and when the glittering crests were gone and the excitement incident to the intrusion over he bent himself to evolve the meaning of the eagles and gilded globes of the soldiery and the charm of a life so the opposite of his own yet these men rude and simple as they were had a knowledge and a wisdom of their own", "subset": "tele", "task_type": "understanding", "prediction": "not unfrequently the shepherd was startled by the blare of trumpets and peering out beheld a cohort sometimes a legion in march and when the glittering crests were gone and the excitement incident to the intrusion over he bent himself to evolve the meaning of the eagles and gilded globes of the soldiery and the charm of a life so the opposite of his own yet these men rude and simple as they were had a knowledge and a wisdom of their own", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1379, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp3994/Lab41-SRI-VOiCES-rm2-tele-sp3994-ch011512-sg0019-mc02-lav-clo-dg000.wav", "answer": "recently power commissioner of new york city and the most capable power engineer in north america who following benda by two or three months resigned his position and accepted what his letter termed the place of director of power in the science community", "subset": "tele", "task_type": "understanding", "prediction": "recently power commissioner of new york city and the most capable power engineer in north america who following benda by two or three months resigned his position and accepted what his letter termed the place of director of power in the science community", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1380, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4010/Lab41-SRI-VOiCES-rm2-tele-sp4010-ch010801-sg0016-mc02-lav-clo-dg000.wav", "answer": "is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne", "subset": "tele", "task_type": "understanding", "prediction": "is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1381, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm2-tele-sp4064-ch012118-sg0036-mc02-lav-clo-dg020.wav", "answer": "his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her", "subset": "tele", "task_type": "understanding", "prediction": "his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1382, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm2-tele-sp4064-ch019132-sg0034-mc01-stu-clo-dg060.wav", "answer": "nothing said the other she is simply ruining herself said oliver i've been trying to get reggie mann to have her introduced to missus devon but he says he wouldn't dare to take the risk no i presume not said montague", "subset": "tele", "task_type": "understanding", "prediction": "nothing said the other she is simply ruining herself said oliver i have been trying to get reggie mann to have her introduced to mrs devon but he says he wouldn't dare to take the risk no i presume not said montague", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1383, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4064/Lab41-SRI-VOiCES-rm2-tele-sp4064-ch077779-sg0032-mc02-lav-clo-dg090.wav", "answer": "don't ask me laughed the idiot i don't know yet i admire all the candidates personally very much but what are your politics republican or democratic asked the lawyer oh that's different said the idiot", "subset": "tele", "task_type": "understanding", "prediction": "don t ask me laughed the idiot i don t know yet i admire all the candidates personally very much but what are your politics republican or democratic asked the lawyer oh that s different said the idiot", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1384, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4145/Lab41-SRI-VOiCES-rm2-tele-sp4145-ch014013-sg0023-mc01-stu-clo-dg050.wav", "answer": "and the new byre you will think a prodigious improvement our dear little grand niece is in great health and much improved we reckon her extremely like our family particularly becky though she has a great look of bella at the same time then she laughs", "subset": "tele", "task_type": "understanding", "prediction": "and the new buyer you will think a prodigious improvement our dear little grand niece is in great health and much improved we reckon her extremely like our family particularly becky though she has a great look of bella at the same time then she laughs", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1385, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4331/Lab41-SRI-VOiCES-rm2-tele-sp4331-ch057179-sg0039-mc02-lav-clo-dg150.wav", "answer": "were at once obliterated from the duchess's bosom arabella with many expressions of thanks and a good humoured countenance left the room cursing the untowardness of her fate which would let nothing run smooth lord rufford was to come that at any rate was now almost certain", "subset": "tele", "task_type": "understanding", "prediction": "were at once obliterated from the duchess bosom arabella with many expressions of thanks and a good humoured countenance left the room cursing the untowardness of her fate which would let nothing run smooth lord rufford was to come that at any rate was now almost certain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1386, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4427/Lab41-SRI-VOiCES-rm2-tele-sp4427-ch020028-sg0015-mc02-lav-clo-dg030.wav", "answer": "and indisputably praiseworthy she was so good natured however and so happy in her delusion that i could not find it in my heart to remonstrate very vehemently except when she would make me listen to her interminable lectures upon the importance", "subset": "tele", "task_type": "understanding", "prediction": "and indisputably praiseworthy she was so good natured however and so happy in her delusion that i could not find it in my heart to remonstrate very vehemently except when she would make me listen to her interminable lectures upon the importance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1387, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4438/Lab41-SRI-VOiCES-rm2-tele-sp4438-ch048525-sg0015-mc01-stu-clo-dg120.wav", "answer": "then when he began to talk about the willows she found that such an idea as alterations hadn't entered his head she was to sleep in the very room that had been his and vera's in the very bed and positively", "subset": "tele", "task_type": "understanding", "prediction": "then when he began to talk about the willows she found that such an idea as alterations hadn t entered his head she was to sleep in the very room that had been his and vera s in the very bed and positively", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1388, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4441/Lab41-SRI-VOiCES-rm2-tele-sp4441-ch076262-sg0035-mc02-lav-clo-dg050.wav", "answer": "they went to the vaults and engaged a private room where breakfast was served to them has my hair turned grey asked rehnhjelm passing his hand over his hair which was damp and clung closely to his skull no old man that doesn't often happen even i'm not grey", "subset": "tele", "task_type": "understanding", "prediction": "they went to the vault and engaged a private room where breakfast was served to them has my hair turned grey asked wrenholme passing his hand over his hair which was damp and clung closely to his skull no old man that does not often happen even i am not grey", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1389, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4535/Lab41-SRI-VOiCES-rm2-tele-sp4535-ch279856-sg0025-mc01-stu-clo-dg050.wav", "answer": "star floated over the fence he had cleared it by a foot marjorie wheeled about dismounted and readjusted the stirrups there she said now now go i can never thank you he began don't please don't even try she interrupted", "subset": "tele", "task_type": "understanding", "prediction": "star floated over the fence he had cleared it by a foot marjorie wheeled about dismounted and readjusted the stirrups there she said now now go i can never thank you he began dont please dont even try she interrupted", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1390, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4586/Lab41-SRI-VOiCES-rm2-tele-sp4586-ch061758-sg0016-mc02-lav-clo-dg160.wav", "answer": "were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of head gear it was possible he might have seen fit to change the fashion", "subset": "tele", "task_type": "understanding", "prediction": "were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of headgear it was possible he might have seen fit to change the fashion", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1391, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4839/Lab41-SRI-VOiCES-rm2-tele-sp4839-ch015307-sg0029-mc02-lav-clo-dg130.wav", "answer": "everybody was sent out of the room save the captains to whom the lord of la palisse made known the emperor's letter which was read twice for the better understanding of it they all looked at one another laughing for to see who would speak first then said the lord of ymbercourt to the lord of la palisse", "subset": "tele", "task_type": "understanding", "prediction": "everybody was sent out of the room save the captains to whom the lord of la police made known the emperor s letter which was read twice for the better understanding of it they all looked at one another laughing for to see who would speak first then said the lord of imbuko to the lord of la police", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1392, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm2-tele-sp4848-ch029108-sg0009-mc02-lav-clo-dg030.wav", "answer": "bigger child why what's two hundred thousand dollars pocket money mere pocket money look at the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along behind it", "subset": "tele", "task_type": "understanding", "prediction": "bigger child why what's two hundred thousand dollars pocket money where pocket money look the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along they come to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1393, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp4848/Lab41-SRI-VOiCES-rm2-tele-sp4848-ch029108-sg0034-mc01-stu-clo-dg040.wav", "answer": "a spectacle of inconceivable sublimity so don't you see we've got the rail road to fall back on and in the meantime what are we worrying about that two hundred thousand dollars appropriation for that's all right", "subset": "tele", "task_type": "understanding", "prediction": "a spectacle of inconceivable solemnity so don t say we ve got the railroad to fall back on and in the meantime what are we worrying about that two hundred thousand dollar appropriation for that s all right", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1394, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5189/Lab41-SRI-VOiCES-rm2-tele-sp5189-ch059288-sg0037-mc01-stu-clo-dg060.wav", "answer": "combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting", "subset": "tele", "task_type": "understanding", "prediction": "combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1395, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5338/Lab41-SRI-VOiCES-rm2-tele-sp5338-ch024640-sg0001-mc02-lav-clo-dg020.wav", "answer": "mister morton replied that far from making any claim upon his good opinion his only wish and the sole purpose of his visit was to find out the means of deserving it", "subset": "tele", "task_type": "understanding", "prediction": "Mr. Morton replied that far from making any claim upon his good opinion, his only wish and the sole purpose of his visit was to find out the means of deserving it.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1396, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5338/Lab41-SRI-VOiCES-rm2-tele-sp5338-ch024640-sg0003-mc02-lav-clo-dg000.wav", "answer": "mister morton seemed particularly struck with the account of waverley's visit to donald bean lean", "subset": "tele", "task_type": "understanding", "prediction": "Mr. Morton seemed particularly struck with the account of Waverley S visit to Donald B. Wee.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1397, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5400/Lab41-SRI-VOiCES-rm2-tele-sp5400-ch003587-sg0006-mc01-stu-clo-dg120.wav", "answer": "p'raps he's been eating too much eating said polly oh mamsie he hasn't had anything and she pointed with shame and remorse to the seed cup with only a few dried husks in the very bottom oh polly began missus pepper but seeing the look on her face she changed her tone for one more cheerful", "subset": "tele", "task_type": "understanding", "prediction": "perhaps he has been eating too much eating said polly oh mamsie he hasn t had anything and she pointed with shame and remorse to the seed cup with only a few dried husks in the very bottom oh polly began mrs pepper but seeing the look on her face she changed her tone for one more cheerful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1398, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5400/Lab41-SRI-VOiCES-rm2-tele-sp5400-ch034478-sg0001-mc02-lav-clo-dg120.wav", "answer": "it's not right for you not to go to the meetings and altogether to keep out of the district business if decent people won't go into it of course it's bound to go all wrong we pay the money and it all goes in salaries and there are no schools nor district nurses nor midwives nor drugstores", "subset": "tele", "task_type": "understanding", "prediction": "it is not right for you not to go to the meetings and altogether to keep out of the district business if decent people don t go into it of course it s bound to go all wrong we pay the money and it all goes in salaries and there are no schools nor district nurses nor midwives nor drug stores", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1399, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5400/Lab41-SRI-VOiCES-rm2-tele-sp5400-ch034479-sg0006-mc01-stu-clo-dg040.wav", "answer": "it's splendid as exercise only you'll hardly be able to stand it said sergey ivanovitch without a shade of irony i've tried it it's hard work at first but you get into it i dare say i shall manage to keep it up really what an idea but tell me", "subset": "tele", "task_type": "understanding", "prediction": "it splendid as exercise only youll hardly be able to stand it said sergey ivanovitch without a shade of irony i have tried it it is hard work at first but you get into it i dare say i shall manage to keep it up really what an idea but tell me", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1400, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5583/Lab41-SRI-VOiCES-rm2-tele-sp5583-ch038026-sg0025-mc01-stu-clo-dg100.wav", "answer": "and as soon as ever he put on the wig of moss he became so ugly and pale and miserable to look at no one would have known him again then he went up to the king's palace and begged first for leave to be in the kitchen and bring in wood and water for the cook", "subset": "tele", "task_type": "understanding", "prediction": "and as soon as ever he put on the wig of moss he became so ugly and pale and miserable to look at no one would have known him again then he went up to the king s palace and begged first for leave to be in the kitchen and bring in wood and water for the cook", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1401, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5583/Lab41-SRI-VOiCES-rm2-tele-sp5583-ch041919-sg0006-mc01-stu-clo-dg110.wav", "answer": "laid it in the place where he usually slept and then hid himself in the night the draken came and each one hit the log a blow with his hatchet till it flew in pieces then they believed their object was gained and they lay down again", "subset": "tele", "task_type": "understanding", "prediction": "laid it in the place where he usually slept and then hid himself in the night the draken came and each one hit the log a blow with his hatchet till it flew in pieces then they believed their object was gained and they lay down again", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1402, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm2-tele-sp5717-ch094876-sg0004-mc02-lav-clo-dg120.wav", "answer": "so the hungry adventurers suddenly found themselves provided with plenty to eat and to drink they lost no time in picking the biggest strawberries and ripest oranges and soon had feasted to their hearts content", "subset": "tele", "task_type": "understanding", "prediction": "so the hungry adventurers suddenly found themselves provided with plenty to eat and to drink they lost no time in picking the biggest strawberries and ripest oranges and soon had feasted to their hearts content", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1403, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5717/Lab41-SRI-VOiCES-rm2-tele-sp5717-ch100145-sg0020-mc02-lav-clo-dg160.wav", "answer": "a few looked apprehensively at the ceiling as though expecting the hellburners and planet busters and nega matter bombs at any moment then one of the members among the benches rose we don't know how we are going to do it prince trevannion he said", "subset": "tele", "task_type": "understanding", "prediction": "a few looked apprehensively at the ceiling as though expecting to hell burners and planet busters and nega matter bombs at any moment then one of the members upon the benches rose we don t know how we are going to do it prince trevannion he said", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1404, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5789/Lab41-SRI-VOiCES-rm2-tele-sp5789-ch057195-sg0025-mc01-stu-clo-dg040.wav", "answer": "john morton might die and then who could tell whether lady ushant would ever return to cheltenham in this way the short lived peace soon came to an end especially as missus masters endeavoured to utilize for general family purposes", "subset": "tele", "task_type": "understanding", "prediction": "john morton might die and then he could tell whether lady ushant would ever return to cheltenham in this way their short lived peace soon came to an end especially as mrs masters endeavoured to utilise for general family purposes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1405, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5802/Lab41-SRI-VOiCES-rm2-tele-sp5802-ch066347-sg0015-mc02-lav-clo-dg110.wav", "answer": "i rubbed my eyes and looked about me it was true the great auditorium was empty and was gradually darkening i put on my hat and walked out refreshed having slept from five twenty until twelve or six hours and forty minutes straight that was one instance", "subset": "tele", "task_type": "understanding", "prediction": "i rubbed my eyes and looked about me it was true the great auditorium was empty and was gradually darkening i put on my hat and walked out in a daze having slept from five twenty until twelve or six hours and forty minutes straight that was one instance", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1406, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5802/Lab41-SRI-VOiCES-rm2-tele-sp5802-ch066347-sg0037-mc02-lav-clo-dg130.wav", "answer": "squills paregoric and other nasty tasting things they have now this alone will serve to popularize sickness and instead of being driven out of business their trade will pick up and the doctor and the doctor's gig and all the appurtenances of his profession", "subset": "tele", "task_type": "understanding", "prediction": "squeals berrigarrick and other nasty tasting things they have now this alone will serve to popularize sickness and instead of being driven out of business their trade will pick up and the doctor and the doctors gig and all the appurtenances of his profession", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1407, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5802/Lab41-SRI-VOiCES-rm2-tele-sp5802-ch076043-sg0024-mc02-lav-clo-dg150.wav", "answer": "he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burthen without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great gnomon of silbury", "subset": "tele", "task_type": "understanding", "prediction": "he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burden without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great gnomon of silbury", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1408, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5935/Lab41-SRI-VOiCES-rm2-tele-sp5935-ch043322-sg0019-mc01-stu-clo-dg020.wav", "answer": "after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not", "subset": "tele", "task_type": "understanding", "prediction": "after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1409, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp5968/Lab41-SRI-VOiCES-rm2-tele-sp5968-ch071320-sg0031-mc01-stu-clo-dg180.wav", "answer": "and paused for a continuance of the communication thus auspiciously commenced you are doctor parkes i take it for granted said marston in the same tone your most obedient humble servant sir replied he with the polite formality of the day and another grave bow doctor demanded marston", "subset": "tele", "task_type": "understanding", "prediction": "and paused for a continuance of the communication thus auspiciously commenced you are doctor parkes i take it for granted said marston in the same tone your most obedient humble servant sir replied he with the polite formality of the day and another grave bow doctor demanded marston", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1410, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp6099/Lab41-SRI-VOiCES-rm2-tele-sp6099-ch069550-sg0044-mc02-lav-clo-dg120.wav", "answer": "like an aureole above the head of yuki chan's mother as she knelt with clasped hands before the buddha on the shelf her moving lips had only one refrain the child the child", "subset": "tele", "task_type": "understanding", "prediction": "like an aureole above the head of yuki chan s mother as she knelt with clasped hands before the buddha on the shelf her moving lips had only one refrain the child the child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1411, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_3549-6147/sp6147/Lab41-SRI-VOiCES-rm2-tele-sp6147-ch034606-sg0018-mc01-stu-clo-dg090.wav", "answer": "the gentleman behind him chastised him for this by a prick of his sword which made him spring round another prick in the back warned the fellow that one of noble blood was behind him and so on each one wounding him in his turn when the man closed round by the circle of swords and covered with blood", "subset": "tele", "task_type": "understanding", "prediction": "the gentleman behind him chastised him for this by a prick of his sword which made him spring round another prick at the back warned the fellow that one of noble blood was behind him and so on each one wounding him in his turn when the man closed round by the circle of swords and covered with blood", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1412, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6241/Lab41-SRI-VOiCES-rm2-tele-sp6241-ch061946-sg0020-mc01-stu-clo-dg060.wav", "answer": "at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor's legs and left him standing with both feet on a separate stone like the colossus of rhodes", "subset": "tele", "task_type": "understanding", "prediction": "at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor s legs and left him standing with both feet on a separate stone like the colossus of rhodes", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1413, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6319/Lab41-SRI-VOiCES-rm2-tele-sp6319-ch057405-sg0001-mc02-lav-clo-dg100.wav", "answer": "after jupiter had bound prometheus on mount caucasus and had sent diseases and cares into the world men became very very wicked", "subset": "tele", "task_type": "understanding", "prediction": "after jupiter had bound prometheus on mount caucasus and had sent diseases and cares into the world men became very very wicked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1414, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6319/Lab41-SRI-VOiCES-rm2-tele-sp6319-ch275224-sg0006-mc02-lav-clo-dg020.wav", "answer": "then the wind took another frolic round the garden and made up to the large white lily into whose refined ear he whispered a doubt as to the necessity or advantage of her thick powerful stem being propped up against a stupid ugly stick", "subset": "tele", "task_type": "understanding", "prediction": "then the wind took another frolic round the garden and made up to the large white lily into whose refined ear he whispered a doubt as to the necessity or advantage of her thick powerful stem being propped up against a stupid ugly stick", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1415, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm2-tele-sp6385-ch034669-sg0006-mc02-lav-clo-dg140.wav", "answer": "as the simple instinct of a faithful animal an animal is a lucid somnambulist there are cases in which the dog feels that he should follow his master others in which he should precede him then the animal takes the direction of sense", "subset": "tele", "task_type": "understanding", "prediction": "as the simple instinct of a faithful animal an animal is a lucid synapheus there are cases in which the dog feels that he should follow his master others in which he should precede him then the animal takes the direction of sense", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1416, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6385/Lab41-SRI-VOiCES-rm2-tele-sp6385-ch220959-sg0005-mc02-lav-clo-dg150.wav", "answer": "on the contrary they are intellectual realities so love is a mental reality and not sensible for this reality the ear does not hear the eye does not see the smell does not perceive", "subset": "tele", "task_type": "understanding", "prediction": "on the contrary they are intellectual realities so love is a mental reality and not sensible for this reality the ear does not hear the eye does not see the smell does not perceive", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1417, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm2-tele-sp6415-ch111615-sg0011-mc01-stu-clo-dg170.wav", "answer": "came very near ending as a complete cynic though in what f p a would call his lastline he managed to wriggle into a more hopeful mood the first valuable discovery that the colyumist is likely to make is that all minds are very much the same", "subset": "tele", "task_type": "understanding", "prediction": "came very near ending as a complete cynic though in what fpa would call his last line he managed to wriggle into a more hopeful mood the first valuable discovery that the columnists is likely to make is that all minds are very much the same", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1418, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6415/Lab41-SRI-VOiCES-rm2-tele-sp6415-ch116629-sg0007-mc01-stu-clo-dg060.wav", "answer": "come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to", "subset": "tele", "task_type": "understanding", "prediction": "come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1419, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm2-tele-sp6454-ch093938-sg0016-mc01-stu-clo-dg080.wav", "answer": "i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business", "subset": "tele", "task_type": "understanding", "prediction": "i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1420, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm2-tele-sp6454-ch093938-sg0016-mc02-lav-clo-dg080.wav", "answer": "i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business", "subset": "tele", "task_type": "understanding", "prediction": "i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1421, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6454/Lab41-SRI-VOiCES-rm2-tele-sp6454-ch093938-sg0018-mc02-lav-clo-dg000.wav", "answer": "two hundred feet therefore brought me to the edge of the town and i wheeled my pony and rode down behind the rear of the buildings in turning i looked back and saw half a dozen mounted men already in pursuit", "subset": "tele", "task_type": "understanding", "prediction": "200 feet, therefore, brought me to the edge of the town. And I wheeled my pony and rode down behind the rear of the buildings. In turning, I looked back and saw half a dozen mounted men already in pursuit.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1422, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-tele-sp6544-ch067863-sg0004-mc02-lav-clo-dg050.wav", "answer": "and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had not come into the house he seemed much older to sylvia than he did on her visit to the plantation in october", "subset": "tele", "task_type": "understanding", "prediction": "and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had not come into the house he seemed much older to sylvia than he did on her visit to the plantation in october", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1423, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6544/Lab41-SRI-VOiCES-rm2-tele-sp6544-ch231862-sg0036-mc01-stu-clo-dg000.wav", "answer": "he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost", "subset": "tele", "task_type": "understanding", "prediction": "he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motionless stare lost lost he muttered all lost", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1424, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6574/Lab41-SRI-VOiCES-rm2-tele-sp6574-ch070756-sg0035-mc02-lav-clo-dg170.wav", "answer": "the labour of winding among the little paths of the mountain and fixing my feet firmly as i advanced perplexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the halfway resting place and seated myself beside the fountain", "subset": "tele", "task_type": "understanding", "prediction": "the labour of winding among the little paths of the mountain and fixing my feet firmly as i advanced vexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the half way resting place and seated myself beside the fountain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1425, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6848/Lab41-SRI-VOiCES-rm2-tele-sp6848-ch076049-sg0024-mc02-lav-clo-dg050.wav", "answer": "and it shall be happy for you all i ask all i ask protect guard cherish for to mister gunter lake it seemed there could be no lovelier thing in life than a wife", "subset": "tele", "task_type": "understanding", "prediction": "and it shall be happy for you all i ask all i ask protect guard cherish for to mr clinton lake it seemed there could be no lovelier thing in life than a wife", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1426, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6895/Lab41-SRI-VOiCES-rm2-tele-sp6895-ch092805-sg0017-mc01-stu-clo-dg110.wav", "answer": "and waved frantically his soft brimmed hat then he strayed through the smoke dropped into the vacant chair at our table and pulled out cigarettes the evening was at the period when reserve is thawed one of us mentioned three wuerzburgers to the waiter", "subset": "tele", "task_type": "understanding", "prediction": "and waved frantically his soft brimmed hat then he strayed through the smoke dropped into the vacant chair at our table and pulled out cigarettes the evening was at the period when reserve is thawed one of us mentioned three wurzburgers to the waiter", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1427, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm2-tele-sp6965-ch277898-sg0012-mc02-lav-clo-dg100.wav", "answer": "but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart's action was the doctor's verdict", "subset": "tele", "task_type": "understanding", "prediction": "but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart s action was the doctor s verdict", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1428, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp6965/Lab41-SRI-VOiCES-rm2-tele-sp6965-ch291718-sg0029-mc01-stu-clo-dg090.wav", "answer": "do you suppose it would do any good to shave the cat all over at this i could not resist the impulse to scream and your mother said i do believe the creature knows whenever we speak about her", "subset": "tele", "task_type": "understanding", "prediction": "do you suppose it would do any good to shave the cat all over at this i could not resist the impulse to scream and your mother said i do believe the creature knows whenever we speak about her", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1429, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7000/Lab41-SRI-VOiCES-rm2-tele-sp7000-ch083706-sg0015-mc02-lav-clo-dg000.wav", "answer": "if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mister hedges any objections which i might urge would appear quite trivial", "subset": "tele", "task_type": "understanding", "prediction": "if not considerable in height was great in girth it would certainly have turned the scale at sixteen a stone i felt that to cricketers who intended to play mr hedges any objections which i might urge would appear quite trivial", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1430, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7095/Lab41-SRI-VOiCES-rm2-tele-sp7095-ch088489-sg0002-mc02-lav-clo-dg120.wav", "answer": "instead of a steady progression of knowledge in this field there was a distinct retrogression according to the prevailing belief the earth was soon to be destroyed and the collecting of knowledge was futile and any study of its nature was vain", "subset": "tele", "task_type": "understanding", "prediction": "instead of a steady progression of knowledge in this field there was a distinct retrogression according to the prevailing belief the earth was soon to be destroyed and the collecting of knowledge was futile and any study of its nature was vain", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1431, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-tele-sp7148-ch059157-sg0015-mc02-lav-clo-dg050.wav", "answer": "she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny brawne", "subset": "tele", "task_type": "understanding", "prediction": "she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny brawne", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1432, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-tele-sp7148-ch059157-sg0037-mc01-stu-clo-dg150.wav", "answer": "his morbidness his mawkishness his fascination as by serpents on the other but in the resultant portrait it is a too respectable and virile keats that emerges keats was more virile as a man", "subset": "tele", "task_type": "understanding", "prediction": "his morbidness his mawkishness his fascination as by serpents on the other but in the resultant portrait it is a too respectable and virile keats that emerges keats was more virile as a man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1433, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7148/Lab41-SRI-VOiCES-rm2-tele-sp7148-ch082991-sg0013-mc02-lav-clo-dg170.wav", "answer": "are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king's highness said the tall man", "subset": "tele", "task_type": "understanding", "prediction": "are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addled pate with a vengeance the knave has been speaking treason of the king s highness said the tall man", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1434, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7276/Lab41-SRI-VOiCES-rm2-tele-sp7276-ch090847-sg0045-mc01-stu-clo-dg030.wav", "answer": "and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen", "subset": "tele", "task_type": "understanding", "prediction": "and it is thanks to him that i have returned in time with a storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1435, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7278/Lab41-SRI-VOiCES-rm2-tele-sp7278-ch104730-sg0015-mc02-lav-clo-dg180.wav", "answer": "but in a moment mister glascock of georgia moved that the petition be not received debate sprang up on a point of order and two days later before the question of reception was determined a resolution was offered by mister jarvis of maine", "subset": "tele", "task_type": "understanding", "prediction": "But in that moment, Mr. Glascock of Georgia moved that the petition be not received. Debate sprang up on a point of order. And two days later, before the question of reception was determined. A resolution was offered by Mr. Jarvis of Maine.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1436, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7498/Lab41-SRI-VOiCES-rm2-tele-sp7498-ch099156-sg0013-mc02-lav-clo-dg000.wav", "answer": "we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time", "subset": "tele", "task_type": "understanding", "prediction": "we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klumpstock came again to hamburg this he did a year after we had seen one another for the first time", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1437, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7517/Lab41-SRI-VOiCES-rm2-tele-sp7517-ch100437-sg0000-mc01-stu-clo-dg070.wav", "answer": "a household book once on a time i discovered samuel butler not the other two but the one who wrote the way of all flesh the second best novel in the english language", "subset": "tele", "task_type": "understanding", "prediction": "a household book once on a time i discovered samuel butler not the other two but the one who wrote the way of all flesh the second best novel in the english language", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1438, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm2-tele-sp7540-ch101258-sg0019-mc01-stu-clo-dg040.wav", "answer": "the poor whale has been lying three years across the strait and men and horses have nearly trampled his back into his ribs is he to lie there much longer i will remember said vassili and he went on he walked and walked", "subset": "tele", "task_type": "understanding", "prediction": "the poor well has been lying three years across a street and men and horses have nearly trampled his back into his ribs is he to lie there much longer i will remember said vassili and he went on he walked and walked", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1439, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm2-tele-sp7540-ch101258-sg0030-mc02-lav-clo-dg110.wav", "answer": "and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the whale had thrown up came sailing along and anchored close by", "subset": "tele", "task_type": "understanding", "prediction": "and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than you can mark the rich amount and now the twelve ships which the well had thrown up came sailing along and anchored close by", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1440, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7540/Lab41-SRI-VOiCES-rm2-tele-sp7540-ch101799-sg0011-mc01-stu-clo-dg180.wav", "answer": "had been tempted to put his hard earned money into certain projects that offering in their inception a too alluring promise of continuous prosperity and generous dividends had failed to withstand the test of time and the altered conditions of trade", "subset": "tele", "task_type": "understanding", "prediction": "had been tempted to put his hard earned money into certain projects that offering in their inception a too alluring promise of continuous prosperity and generous dividends had failed to withstand the test of time and the altered conditions of trade", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1441, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7688/Lab41-SRI-VOiCES-rm2-tele-sp7688-ch105390-sg0030-mc02-lav-clo-dg130.wav", "answer": "is mostly unbecoming to your charming sex madame madame la comtesse de tournay de basserive said lord grenville introducing the lady this is a pleasure madame my royal father as you know is ever glad to welcome those of your compatriots", "subset": "tele", "task_type": "understanding", "prediction": "is mostly unbecoming to your charming sex madame madame la comtesse de tournay de gasarit said lord grandbois introducing the lady this is a pleasure madame my royal father as you know is ever glad to welcome those of your compatriots", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1442, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7688/Lab41-SRI-VOiCES-rm2-tele-sp7688-ch109656-sg0016-mc01-stu-clo-dg080.wav", "answer": "it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing a meal or two and sleeping comfortably on your saddle blankets on a soft mattress of mesquite grass", "subset": "tele", "task_type": "understanding", "prediction": "it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing them a meal or two and sleeping comfortably on your saddle blankets in a soft mattress of mesquite grass", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1443, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-tele-sp7850-ch073752-sg0003-mc02-lav-clo-dg140.wav", "answer": "this violent and triumphant revolution in his prospects and his fortunes was hardly yet completely comprehended by our friend ferdinand armine and when he had left a note for the generous mirabel whose slumbers he would not disturb at this early hour even with good news he strolled along up charles street and to the park in one of those wild and joyous reveries in which we brood over coming bliss and create a thousand glorious consequences", "subset": "tele", "task_type": "understanding", "prediction": "this violent and triumphant revolution in his prospects and his fortunes was hardly yet completely comprehended by our friend ferdinand armine and when he had left a note for the generous mirabel whose slumbers he would not disturb at this early hour even with good news he strolled along up charles street and to the park in one of those wild and joyous reveries in which we brood over coming bliss and create a thousand glorious consequences", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1444, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-tele-sp7850-ch073752-sg0008-mc01-stu-clo-dg060.wav", "answer": "four and twenty hours ago and he deemed himself the most miserable and forlorn of human beings and now all the blessings of the world seemed showered at his feet", "subset": "tele", "task_type": "understanding", "prediction": "4 and 20 hours ago. And he deemed himself the most miserable and forlorn of human beings. And now, all the blessings of the world seemed showered at his feet.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1445, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7850/Lab41-SRI-VOiCES-rm2-tele-sp7850-ch111771-sg0002-mc01-stu-clo-dg080.wav", "answer": "grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field", "subset": "tele", "task_type": "understanding", "prediction": "grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1446, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7867/Lab41-SRI-VOiCES-rm2-tele-sp7867-ch275218-sg0023-mc01-stu-clo-dg000.wav", "answer": "still it went on snowing and thawing and freezing till the ice was a mile deep over wisconsin and the whole united states was one great skating rink so it kept on for about a million years until once", "subset": "tele", "task_type": "understanding", "prediction": "still it went on snowing and thawing and freezing till the ice was a mile deep over wisconsin and the whole united states was one great skating rink so it kept on for about a million years until once", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1447, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-tele-sp7868-ch110706-sg0013-mc02-lav-clo-dg030.wav", "answer": "which sprang from one of the lower and snowless elevations was now nearly in shadow all but the uppermost jets of spray which rose like slow smoke above the undulating line of the cataract and floated away in feeble wreaths upon the morning wind", "subset": "tele", "task_type": "understanding", "prediction": "which sprang from one of the lower and snowless elevations was now nearly in shadow all but the uppermost jet of spray which rose like slow smoke above the undulating line of cataract and floated away in feeble breaths upon the morning wind", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1448, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-tele-sp7868-ch246932-sg0004-mc01-stu-clo-dg090.wav", "answer": "but more air through the bars of its lungs i rose dressed and went out it was a still warm night no moon but plenty of star light the wind blowing as now gentle and sweet and cool", "subset": "tele", "task_type": "understanding", "prediction": "but more air through the bars of its lungs i rose dressed and went out it was a still warm night no moon but plenty of starlight the wind blowing as now gentle and sweet and cool", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1449, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7868/Lab41-SRI-VOiCES-rm2-tele-sp7868-ch246932-sg0006-mc01-stu-clo-dg080.wav", "answer": "so long as the stars remained unclouded i could find my way back when i pleased i had been out perhaps an hour when through the soft air came a cry apparently from far off there was something in the tone that seemed to me unusually frightful", "subset": "tele", "task_type": "understanding", "prediction": "so long as the stars remained unclouded i could find my way back when i pleased i had been out perhaps an hour when through the soft air came a cry apparently from far off there was something in the tone that seemed to me unusually frightful", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1450, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm2-tele-sp7881-ch105574-sg0015-mc02-lav-clo-dg040.wav", "answer": "yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us", "subset": "tele", "task_type": "understanding", "prediction": "yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1451, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7881/Lab41-SRI-VOiCES-rm2-tele-sp7881-ch105574-sg0017-mc01-stu-clo-dg080.wav", "answer": "in place of chasing murderers and guerrillas in missouri we entered new madrid one morning before daylight the enemy had left in awful haste i recall finding a dead rebel officer lying on a table in his tent in full uniform", "subset": "tele", "task_type": "understanding", "prediction": "in place of chasing murderers and guerrillas in missouri we entered new madrid one morning before daylight the enemy had left in awful haste i recall finding a dead rebel officer lying on a table in his tent in full uniform", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1452, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7932/Lab41-SRI-VOiCES-rm2-tele-sp7932-ch093470-sg0013-mc01-stu-clo-dg010.wav", "answer": "i think that crying last night meant something one way or the other well we shall see we shall see i will be off back again to my work now i feel all the better for having had this talk with you hesba's a good woman and she is fond of the child", "subset": "tele", "task_type": "understanding", "prediction": "i think that crying last night meant something one way or the other well we shall see we shall see i will be off back again to my work now i feel all the better for having had this talk with you hesba is a good woman she is fond of the child", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1453, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm2-tele-sp7976-ch105575-sg0029-mc02-lav-clo-dg050.wav", "answer": "a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war", "subset": "tele", "task_type": "understanding", "prediction": "a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1454, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7976/Lab41-SRI-VOiCES-rm2-tele-sp7976-ch110124-sg0001-mc02-lav-clo-dg010.wav", "answer": "every year at a certain day of a certain month he went away to a distant city to collect money on an account", "subset": "tele", "task_type": "understanding", "prediction": "every year at a certain day of a certain month he went away to a distant city to collect money on an account", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1455, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7981/Lab41-SRI-VOiCES-rm2-tele-sp7981-ch112061-sg0002-mc02-lav-clo-dg180.wav", "answer": "bishoprics and abbeys had been too often given to most unworthy persons in france the crown was almost supreme in such matters the queen therefore determined to appoint a council of conscience consisting of five members", "subset": "tele", "task_type": "understanding", "prediction": "bishoprics and abbeys had been too often given to most unworthy persons in france the crown was almost supreme in such matters the queen therefore determined to appoint a council of conscience consisting of five members", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1456, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm2-tele-sp7995-ch276907-sg0009-mc02-lav-clo-dg030.wav", "answer": "the first thing after redemption of the coat which mister booth hungry as he was thought of was to supply himself with snuff which he had long to his great sorrow been without on this occasion he presently missed that iron box", "subset": "tele", "task_type": "understanding", "prediction": "the first thing after redemption of the coat which mr booth hungry as he was thought of was to supply himself with snuff which he had long to his great sorrow been without on this occasion he presently missed that iron box", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1457, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp7995/Lab41-SRI-VOiCES-rm2-tele-sp7995-ch280250-sg0028-mc02-lav-clo-dg040.wav", "answer": "hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it", "subset": "tele", "task_type": "understanding", "prediction": "hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagined that they have found it", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1458, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8051/Lab41-SRI-VOiCES-rm2-tele-sp8051-ch118101-sg0026-mc02-lav-clo-dg180.wav", "answer": "though his stout and hearty appearance would have rendered him very desirable to a trader he fled from william wheeling of sandy hook maryland he spoke of his master as a pretty bad man who was always quarreling and would drink swear and lie", "subset": "tele", "task_type": "understanding", "prediction": "though his stout and hearty appearance would have rendered him very desirable to a trader he fled from william whealing of sandy hook maryland he spoke of his master as a pretty bad man who was always quarrelling and would drink swear and lie", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1459, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8057/Lab41-SRI-VOiCES-rm2-tele-sp8057-ch284428-sg0034-mc02-lav-clo-dg010.wav", "answer": "and the only thing i object to is electing the boolooroo for only three hundred years it ought to be for life my successor has already been elected but he can't reign for a hundred years to come i think three hundred years is plenty long enough", "subset": "tele", "task_type": "understanding", "prediction": "and the only thing i object to is electing the deliverer for only three hundred years it ought to be for life my successor has already been elected but he can reign for a hundred years to come i think three hundred years is plenty long enough", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1460, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8108/Lab41-SRI-VOiCES-rm2-tele-sp8108-ch280359-sg0013-mc02-lav-clo-dg150.wav", "answer": "by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death", "subset": "tele", "task_type": "understanding", "prediction": "by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1461, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8118/Lab41-SRI-VOiCES-rm2-tele-sp8118-ch114469-sg0033-mc01-stu-clo-dg050.wav", "answer": "and there were the broad shoulders of sergeant whitley and the figures of the others he rushed through the dripping forest and shouted in a tone that could be heard above the shriek of wind and rain colonel winchester recognized the voice but the light was so dim that he did not recognize him from whom it came", "subset": "tele", "task_type": "understanding", "prediction": "and there were the broad shoulders of sergeant whitley and the figures of the others he rushed through the dripping forest and shouted in a tone that could be heard above the shriek of wind and rain colonel winchester recognized the voice but the light was so dim that he did not recognize him from whom it came", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1462, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8222/Lab41-SRI-VOiCES-rm2-tele-sp8222-ch274379-sg0008-mc02-lav-clo-dg160.wav", "answer": "sir henry vane told the commons that if ever god appeared to them it was in the ordinances of yesterday that as he was credibly informed by many who had been present in different congregations the same lamentations and discourses which the godly preachers had made before them", "subset": "tele", "task_type": "understanding", "prediction": "sir henry bayne told the commons that if ever god appeared to them it was in the ordinances of yesterday that as he was credibly informed by many who had been present in different congregations the same lamentations and discourses which the godly creatures had made before them", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1463, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8222/Lab41-SRI-VOiCES-rm2-tele-sp8222-ch274379-sg0017-mc02-lav-clo-dg040.wav", "answer": "they would find it extremely difficult to supply the place of men now formed by experience to command and authority that the rank alone possessed by such as were members of either house prevented envy retained the army in obedience and gave weight to military orders", "subset": "tele", "task_type": "understanding", "prediction": "they would find it extremely difficult to supply the place of men now formed by experience to command and authority that the rank alone possessed by such as were members of either house prevented envy retained the army in obedience and gave weight to military orders", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1464, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-tele-sp8266-ch258263-sg0036-mc01-stu-clo-dg070.wav", "answer": "and said to her grieve not but take patience till thy son be grown a man when i will go to the land of the ajamis and strike off thy father's head from between his shoulders and seat thy son on the throne in his stead so she rose and kissed his hands and blessed him", "subset": "tele", "task_type": "understanding", "prediction": "and said to her grieve not but take patience till thy son be grown a man when i will go to the land of the ajamis and strike off thy father s head from between his shoulders and seat thy son on the throne in his stead so she rose and kissed his hands and blessed him", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1465, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8266/Lab41-SRI-VOiCES-rm2-tele-sp8266-ch279363-sg0024-mc02-lav-clo-dg100.wav", "answer": "they are in the nearer thickets cried the colonel and now they're climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest", "subset": "tele", "task_type": "understanding", "prediction": "they are in the nearer thickets cried the colonel and now they are climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
+{"index": 1466, "question": "Please transcribe the spoken content into written text.", "audio_path": "/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm2/tele/sp_6241-8713/sp8713/Lab41-SRI-VOiCES-rm2-tele-sp8713-ch296159-sg0014-mc01-stu-clo-dg020.wav", "answer": "his literary conscience allowed nothing to take the place of the experimental method the careful observation and arranging of minute facts intimate analytical study from the life no action was too small no emotion too insignificant", "subset": "tele", "task_type": "understanding", "prediction": "His literary conscience allowed nothing to take the place of the experimental method, the careful observation and arranging of minute facts. Intimate, analytical study from the life. No action was too small, no emotion, too insignificant.", "real_prompt": "You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks."}
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo_default_performance.json b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo_default_performance.json
new file mode 100644
index 0000000000000000000000000000000000000000..df58d0df83867c05c8d8c2052faa76c7cb8d4a79
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo_default_performance.json
@@ -0,0 +1,25 @@
+{
+ "task": "ASR",
+ "dataset": "voices_dev_clo",
+ "model": "Qwen2.5-Omni-7B-lora2",
+ "date": "2025-12-21 12:17:24.093810",
+ "performance": {
+ "babb": {
+ "wer": 3.79,
+ "total": 364
+ },
+ "musi": {
+ "wer": 3.13,
+ "total": 371
+ },
+ "none": {
+ "wer": 3.91,
+ "total": 380
+ },
+ "tele": {
+ "wer": 3.23,
+ "total": 351
+ }
+ },
+ "eval_method": "qwen2-audio-impl"
+}
\ No newline at end of file
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo_wer_details.jsonl b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo_wer_details.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..836f95227e86e35037ef28a5ec8edb3d22066fbc
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo_wer_details.jsonl
@@ -0,0 +1,1466 @@
+{"index":1,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm1-babb-sp0112-ch123215-sg0025-mc01-stu-clo-dg080.wav","answer":"of tolerant wonder anne despite her affection for rusty was not especially fond of cats but missus gardner's tone annoyed her inconsequently she remembered that missus john blythe was so fond of cats that she kept as many as her husband would allow","subset":"babb","task_type":"understanding","prediction":"of tolerant wonder ann despite her affection for rusty was not especially fond of cats but mrs gardiner s tone annoyed her inconsequently she remembered that mrs john blythe was so fond of cats that she kept as many as her husband would allow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":2,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm1-babb-sp0122-ch121729-sg0002-mc02-lav-clo-dg060.wav","answer":"magnus great and nator to swim a great swimmer maiden lady a term applied to an old maid by those who wish to avoid hurting her feelings malt","subset":"babb","task_type":"understanding","prediction":"magnus great and nator to swim a great swimmer maiden lady a term applied to an old maid by those who wish to avoid hurting her feelings malt","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":3,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm1-babb-sp0122-ch121730-sg0014-mc01-stu-clo-dg000.wav","answer":"one of the hardships of a minor's life pass a form of transportation issued free to those who are quite able to pay passenger one who does not travel on a pass antonym for deadhead","subset":"babb","task_type":"understanding","prediction":"one of the hardships of a miner's life pass a form of transportation issued free to those who are quite able to pay passenger one who does not travel on a pass antonym for deadhead","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":4,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0159\/Lab41-SRI-VOiCES-rm1-babb-sp0159-ch135897-sg0052-mc01-stu-clo-dg100.wav","answer":"that this solitary life is extremely irksome all these expressions and particularly the last greatly increased my love for him prince said i there is no doubt but providence has brought me into your port to afford you an opportunity","subset":"babb","task_type":"understanding","prediction":"that this solitary life is extremely irksome all these expressions and particularly the last greatly increased my love for him prince said i there is no doubt but providence has brought me into your port to afford you an opportunity","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":5,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0174\/Lab41-SRI-VOiCES-rm1-babb-sp0174-ch084280-sg0013-mc02-lav-clo-dg010.wav","answer":"in mary it seems to me i found both womanhood and fellowship i found what many have dreamt of love and friendship freely given and i could do nothing but clutch at her to make her my possession","subset":"babb","task_type":"understanding","prediction":"in mary it seems to me i found both womanhood and fellowship i found what many have travelled after love and friendship free and yet i could do nothing but clutch at her to make her my possession","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":6,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0188\/Lab41-SRI-VOiCES-rm1-babb-sp0188-ch135249-sg0029-mc01-stu-clo-dg170.wav","answer":"but were now tall ivory columns in a fairy palace of twilight and stars in their shadows anne and gilbert talked in lover fashion of their new home and their new life together i've found a nest for us anne oh where","subset":"babb","task_type":"understanding","prediction":"but were now tall ivory columns in a fairy palace of twilight and stars in their shadows anne and gilbert talked in lover fashion of their new home and their new life together i ve found a nest for us anne oh where","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":7,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm1-babb-sp0205-ch159056-sg0032-mc01-stu-clo-dg020.wav","answer":"could not be improvised in this hurried though disastrously slow preparation for a war the ship in which wolfe was to sail had been lying idle for years and her pestilential bilge water soon began to make the sailors and soldiers sicken and die","subset":"babb","task_type":"understanding","prediction":"could not be improved at this hurried though disastrously slow preparation for a war the ship in which wolfe was to sail had been lying idle for years and her pestilential bilge water soon began to make the sailors and soldiers sicken and die","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":8,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0208\/Lab41-SRI-VOiCES-rm1-babb-sp0208-ch126851-sg0011-mc02-lav-clo-dg070.wav","answer":"now the farmers and the old ladies are afraid to send their animals to you just as we were beginning to be well off again now we shall be ruined entirely this is the last straw i will no longer be housekeeper for you if you don't send away that alligator","subset":"babb","task_type":"understanding","prediction":"now the farmers and the old ladies are afraid to send their animals feed just as we were beginning to be well off again now we shall be ruined entirely this is the last straw i will no longer be housekeeper for you if you dont send away that alligator","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":9,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm1-babb-sp0209-ch004731-sg0033-mc02-lav-clo-dg050.wav","answer":"that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware","subset":"babb","task_type":"understanding","prediction":"that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":10,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm1-babb-sp0209-ch004733-sg0009-mc01-stu-clo-dg120.wav","answer":"you never could persuade her to read half so much as you wished you know you could not i dare say replied missus weston smiling that i thought so then but since we have parted i can never remember emma's omitting to do any thing i wished","subset":"babb","task_type":"understanding","prediction":"you never could persuade her to read half so much as you wished you know you could not i dare say replied mrs weston smiling that i thought so then but since we have parted i can never remember emma s omitting to do anything i wished","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":11,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm1-babb-sp0209-ch004733-sg0009-mc02-lav-clo-dg120.wav","answer":"you never could persuade her to read half so much as you wished you know you could not i dare say replied missus weston smiling that i thought so then but since we have parted i can never remember emma's omitting to do any thing i wished","subset":"babb","task_type":"understanding","prediction":"you never could persuade her to read half so much as you wished you know you could not i dare say replied mrs weston smiling that i thought so then but since we have parted i can never remember emma s omitting to do any thing i wished","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":12,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0224\/Lab41-SRI-VOiCES-rm1-babb-sp0224-ch128660-sg0019-mc02-lav-clo-dg060.wav","answer":"beware of that man be he friend or brother whose hair is one color and moustache another portland me one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of one's future husband","subset":"babb","task_type":"understanding","prediction":"beware of that man be he friend or brother whose hair is one color and mustache another portland may one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of ones future husband","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":13,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0240\/Lab41-SRI-VOiCES-rm1-babb-sp0240-ch160593-sg0000-mc01-stu-clo-dg100.wav","answer":"mine by the right of the white election mine by the royal seal mine by the sign in the scarlet prison bars cannot conceal mine here in vision and in veto mine by the grave's repeal titled confirmed delirious charter","subset":"babb","task_type":"understanding","prediction":"mine by the right of the white election mine by the royal seal mine by the sign the scarlet prison bars cannot conceal mine here in vision and in veto mine by the grave s repeal titled confirmed delirious charter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":14,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-babb-sp0242-ch122626-sg0030-mc02-lav-clo-dg170.wav","answer":"did she say that to me did you hear her eliza and georgiana won't i tell mama but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing","subset":"babb","task_type":"understanding","prediction":"did she say that to me do you hear her eliza and georgiana won t i tell mamma but first he ran headlong at me i felt him grasp my hair and my shoulder thea closed with a desperate thing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":15,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0288\/Lab41-SRI-VOiCES-rm1-babb-sp0288-ch121741-sg0007-mc01-stu-clo-dg000.wav","answer":"by their very nature be about something amiss i have occasionally wondered how she would have behaved to a girl on reflection i think a little better but the girl would have been worse off because she could not have escaped from her as we did","subset":"babb","task_type":"understanding","prediction":"by their very nature he had done something amiss i have occasionally wondered how she would have behaved to a girl on reflection i think a little better but the girl would have been in worse odds because she could not escape from paris as we did","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":16,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm1-babb-sp0472-ch129979-sg0009-mc01-stu-clo-dg180.wav","answer":"perhaps be a little soured by finding like many others of his sex that through some unaccountable bias in favour of beauty he was the husband of a very silly woman but she knew that this kind of blunder was too common for any sensible man to be lastingly hurt by it","subset":"babb","task_type":"understanding","prediction":"perhaps be a little sour by finding like many others of his sex that through some unaccountable bias in favor of beauty he was the husband of a very silly woman but he knew that this kind of blunder was too common for any sensible man to be lastingly hurt by it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":17,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm1-babb-sp0472-ch129979-sg0011-mc02-lav-clo-dg010.wav","answer":"it will be quite delightful my love applying to her husband don't you long to have the miss dashwoods come to cleveland certainly he replied with a sneer i came into devonshire with no other view","subset":"babb","task_type":"understanding","prediction":"it will be quite delightful my love applied her husband don t you long to have the moustache once come to cleveland certainly he replied with a serene mien i came into debenture with no idea","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":11}
+{"index":18,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm1-babb-sp0479-ch107480-sg0016-mc01-stu-clo-dg100.wav","answer":"to twenty five hundred and i am to land a yard or two of the stuff for you in some mysterious way i demanded how is it to be by kidnapping the lady the snatch and run game or how sarcasm does not suit your complexion bunny retorted henriette","subset":"babb","task_type":"understanding","prediction":"twenty five hundred and i am to land a yard or two of the stuff for you in some mysterious way i demanded how is it to be by kidnapping the lady the snatcher and robber game or how sarcasm does not suit your complexion bunny retorted henrietta","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":19,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm1-babb-sp0479-ch134717-sg0056-mc02-lav-clo-dg050.wav","answer":"weapons and each with musing soul retire to celebrate our dear commander's death no more for him life's stormy conflicts nor victory nor defeat no more time's dark events charging like ceaseless clouds across the sky but sing poet in our name","subset":"babb","task_type":"understanding","prediction":"weapons in each music soul retire to celebrate our dear commander s death no more for him life s stormy conflicts nor victory nor defeat no more time s dark events charging like ceaseless clouds across the sky but sing poet in our name","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":20,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-babb-sp0480-ch126336-sg0008-mc02-lav-clo-dg030.wav","answer":"ah unlucky wretch that i am sighed she would that i had married king grisly beard next they came to some fine meadows whose are these beautiful green meadows said she","subset":"babb","task_type":"understanding","prediction":"unlucky wretch that i am said she would that i had married king grizzly bear next they came to some fine meadows whose are these beautiful green meadows said she","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":21,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm1-babb-sp0492-ch131882-sg0007-mc02-lav-clo-dg120.wav","answer":"insects phileas fogg was a member of the reform and that was all the way in which he got admission to this exclusive club was simple enough he was recommended by the barings with whom he had an open credit","subset":"babb","task_type":"understanding","prediction":"insects joey spugg was a member of the reform and that was all the way in which he got admission to his exclusive club was simple enough he was recommended by the bearings with whom he had an open credit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":22,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0597\/Lab41-SRI-VOiCES-rm1-babb-sp0597-ch134789-sg0007-mc01-stu-clo-dg000.wav","answer":"somewhat disturbed by intrigues but still retaining on their faces something of the serenity of toil and in their souls that flower of honesty which survives the first fall in woman one of the four was called the young because she was the youngest of them","subset":"babb","task_type":"understanding","prediction":"somewhat disturbed by intrigues but still retaining on their faces something of the serenity of toil and in their souls that flower of honesty which survives the first fall in woman one of the four was called the young because she was the youngest of them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":23,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm1-babb-sp0636-ch123163-sg0044-mc01-stu-clo-dg100.wav","answer":"grated bread soaked in cream put in the omelet some think an improvement the dripping of a nice ham some persons use for omelet instead of butter to boil eggs have the water boiling and look at your watch as you put them in","subset":"babb","task_type":"understanding","prediction":"grated bread soaked in cream put in the omelet some think an improvement the dripping of a nice ham some persons use for omelet instead of butter to boil eggs have the water boiling and look at your watch as you put them in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":24,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm1-babb-sp0637-ch127579-sg0004-mc02-lav-clo-dg040.wav","answer":"i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat","subset":"babb","task_type":"understanding","prediction":"i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":25,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0652\/Lab41-SRI-VOiCES-rm1-babb-sp0652-ch130737-sg0000-mc02-lav-clo-dg040.wav","answer":"never drink any hard liquors such as whisky brandy gin or cocktails with oysters or clams as it is liable to upset you for the rest of the evening","subset":"babb","task_type":"understanding","prediction":"Never drink any hard liquors such as whiskey. Brandy, gin or cocktails with oysters or clams as it is liable to upset you for the rest of the evening.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":26,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0868\/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0001-mc01-stu-clo-dg180.wav","answer":"for long the instrument was treasured by the emperor of china but all in vain were the efforts of those who in turn tried to draw melody from its strings in response to their utmost strivings there came from the harp but harsh notes of disdain","subset":"babb","task_type":"understanding","prediction":"For long, the instrument was treasured by the emperor of China. But all in vain were the efforts of those who, in turn, tried to draw melody from its strings in response to their utmost strivings. There came from the harp, but harsh notes of disdain.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":27,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0868\/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0001-mc02-lav-clo-dg180.wav","answer":"for long the instrument was treasured by the emperor of china but all in vain were the efforts of those who in turn tried to draw melody from its strings in response to their utmost strivings there came from the harp but harsh notes of disdain","subset":"babb","task_type":"understanding","prediction":"For long, the instrument was treasured by the emperor of China. But all in vain were the efforts of those who, in turn, tried to draw melody from its strings in response to their utmost strivings. There came from the harp, but harsh notes of disdain.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":28,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0868\/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0002-mc02-lav-clo-dg070.wav","answer":"once more the sweet breath of spring played amidst its branches the young cataracts as they danced down the ravine laughed to the budding flowers anon were heard the dreamy voices of summer with its myriad insects the gentle pattering of rain","subset":"babb","task_type":"understanding","prediction":"Once more, the sweet breath of spring played amidst its branches. The young cataracts, as they danced down the ravine, laughed to the budding flowers anon. Were heard the dreamy voices of summer with its myriad insects. The gentle patterning of rain.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":29,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0868\/Lab41-SRI-VOiCES-rm1-babb-sp0868-ch131294-sg0017-mc02-lav-clo-dg130.wav","answer":"he sings only of himself his works may be nearer science but are further from humanity we have an old saying in japan that a woman cannot love a man who is truly vain for their is no crevice in his heart for love to enter and fill up","subset":"babb","task_type":"understanding","prediction":"he sings only of himself his works may be nearer science but are further from humanity we have an old saying in japan that a woman cannot love a man who is truly vain for there is no crevice in his heart for love to enter and fill up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":30,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0882\/Lab41-SRI-VOiCES-rm1-babb-sp0882-ch123266-sg0029-mc02-lav-clo-dg000.wav","answer":"i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay","subset":"babb","task_type":"understanding","prediction":"i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":31,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0948\/Lab41-SRI-VOiCES-rm1-babb-sp0948-ch132705-sg0009-mc02-lav-clo-dg090.wav","answer":"a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said","subset":"babb","task_type":"understanding","prediction":"a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":32,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm1-babb-sp0949-ch162667-sg0001-mc02-lav-clo-dg030.wav","answer":"angles give the name to england attila king of the huns in italy genseric takes rome the lombards the people who inhabit the northern parts beyond the rhine and the danube","subset":"babb","task_type":"understanding","prediction":"angles give the name to england attila king of the huns in italy genseric takes rome the lombards the people who inhabit the northern parts beyond the rhine and the danube","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":33,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm1-babb-sp0949-ch162667-sg0034-mc01-stu-clo-dg020.wav","answer":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","subset":"babb","task_type":"understanding","prediction":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":34,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm1-babb-sp1050-ch134119-sg0020-mc01-stu-clo-dg060.wav","answer":"he packed up his bottles in a leather case and went back with them all first he looked at the coffee and then stirred it then he put in a little chlorate of potassium and the family tried it all round but it tasted no better","subset":"babb","task_type":"understanding","prediction":"he packed up his bottles in a leather case and went back with them all first he looked at the coffee and then stirred it then he put in a little chlorate of potassium and the family tried it all round but it tasted no better","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":35,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm1-babb-sp1050-ch134121-sg0014-mc01-stu-clo-dg110.wav","answer":"no dinner exclaimed agamemnon i am quite hungry said solomon john at last mister peterkin said i am not proud i am willing to dine in the kitchen this room was below the dining room all consented to this","subset":"babb","task_type":"understanding","prediction":"no dinner exclaimed agamemnon i am quite hungry said solomon john at last mr peterkin said i am not proud i am willing to dine in the kitchen this room was below the dining room all consented to this","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":36,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp1052\/Lab41-SRI-VOiCES-rm1-babb-sp1052-ch132776-sg0021-mc01-stu-clo-dg020.wav","answer":"would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped","subset":"babb","task_type":"understanding","prediction":"would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":37,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm1-babb-sp1066-ch004479-sg0015-mc01-stu-clo-dg000.wav","answer":"i should suffer more from comparison a gentleman's family is all that i should condition for i know you i know you you would take up with any thing but i shall be a little more nice and i am sure the good campbells will be quite on my side","subset":"babb","task_type":"understanding","prediction":"i should suffer more from comparison a gentleman's family is all that i should condition for i know you i know you you will take up with anything but i shall be a little more nice and i am sure the good campbells will be quite on my side","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":38,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm1-babb-sp1112-ch128136-sg0031-mc02-lav-clo-dg170.wav","answer":"are two strong simple verses and indeed the spirit of the whole poem is dignified and stately the rest of the volume however is disappointing ordinary theology has long since converted its gold into lead","subset":"babb","task_type":"understanding","prediction":"Are two strong, simple verses, and indeed. The spirit of the whole poem is dignified and stately. The rest of the volume, however, is disappointing. Ordinary theology has long since converted its gold into lead.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":39,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm1-babb-sp1160-ch139727-sg0014-mc01-stu-clo-dg030.wav","answer":"and therefore i propos'd that the orders should be payable in a year and to bear an interest of five per cent with these orders i suppos'd the provisions might easily be purchas'd the assembly with very little hesitation adopted the proposal the orders were immediately printed","subset":"babb","task_type":"understanding","prediction":"and therefore i proposed that the orders should be payable in a year and to bear an interest of five per cent with these orders i supposed the provisions might easily be purchased the assembly with very little hesitation adopted the proposal the orders were immediately printed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":40,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm1-babb-sp1160-ch139730-sg0019-mc02-lav-clo-dg050.wav","answer":"undertook to repeat what he called the philadelphia experiments and after they were performed before the king and court all the curious of paris flocked to see them i will not swell this narrative with an account of that capital experiment","subset":"babb","task_type":"understanding","prediction":"Undertook to repeat what he called the Philadelphia experiments. And after they were performed before the king and court, all the curious of Paris flocked to see them. I will not swell this narrative with an account of that capital experiment.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":41,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1271\/Lab41-SRI-VOiCES-rm1-babb-sp1271-ch136861-sg0014-mc02-lav-clo-dg020.wav","answer":"did not endeavour to depress me with threats of censure from the publick or with objections learned from those who had learned them from my own preface your's is the only letter of goodwill that i have received","subset":"babb","task_type":"understanding","prediction":"did not endeavor to depress me with threats of censure from the public or with objections learned from those who had learned them from my own preface yours is the only letter of good will that i have received","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":42,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm1-babb-sp1335-ch163935-sg0018-mc02-lav-clo-dg150.wav","answer":"put a little bag of mixed spices such as are used in making pickles on to cook with the fowl while the fowl is cooking take about a pound of rice and fry it with a few sliced onions and a little butter or crisco","subset":"babb","task_type":"understanding","prediction":"Put a little bag of mixed spices. Such as are used in making pickles on to cook with the fowl while the fowl is cooking. Take about a pound of rice and fry it with a few sliced onions and a little butter, or Crisco.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":43,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm1-babb-sp1335-ch163935-sg0022-mc01-stu-clo-dg110.wav","answer":"beef or mutton pullao very delicious pullao may be made from the cheapest cuts of beef and mutton get about two pounds of beef or mutton cut in bits cook until it is very tender","subset":"babb","task_type":"understanding","prediction":"beef or mutton pulao very delicious pulao may be made from the cheapest cuts of beef and mutton get about two pounds of beef or mutton cut in bits cook until it is very tender","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":44,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1425\/Lab41-SRI-VOiCES-rm1-babb-sp1425-ch139297-sg0036-mc01-stu-clo-dg120.wav","answer":"for during this interval a great change had taken place in master hugh and his once kind and affectionate wife the influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both","subset":"babb","task_type":"understanding","prediction":"For during this interval, a great change had taken place in Master Hugh and his once kind and affectionate wife. The influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":45,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-babb-sp1472-ch285314-sg0011-mc01-stu-clo-dg040.wav","answer":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up","subset":"babb","task_type":"understanding","prediction":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":46,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1536\/Lab41-SRI-VOiCES-rm1-babb-sp1536-ch138488-sg0027-mc01-stu-clo-dg090.wav","answer":"mary being not merely queen consort but also queen regnant was inaugurated in all things like a king was girt with the sword lifted up into the throne and presented with the bible the spurs and the orb of the temporal grandees of the realm and of their wives and daughters","subset":"babb","task_type":"understanding","prediction":"Mary, being not merely queen consort, but also queen regnant, was inaugurated in all things like a king, was girt with the sword, lifted up into the throne and presented with the Bible. The spurs and the orb of the temporal grandees of the realm and of their wives and daughters.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":47,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1737\/Lab41-SRI-VOiCES-rm1-babb-sp1737-ch142397-sg0008-mc01-stu-clo-dg100.wav","answer":"to pass along busy streets of your own building for ever ringing an imaginary bell and offering airy muffins of your own make to a bustling thronging crowd of your own creation there were points about the game it cannot be denied though it seemed scarce in harmony with this radiant wind swept morning","subset":"babb","task_type":"understanding","prediction":"to pass along busy streets of your own building forever ringing an imaginary bell and offering airy muffins of your own make to a bustling thronging crowd of your own creation there were points about the game it cannot be denied though it seemed scarce in harmony with this radiant wind swept morning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":48,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm1-babb-sp1867-ch154071-sg0043-mc02-lav-clo-dg170.wav","answer":"you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i'll smash every bone in his ugly head","subset":"babb","task_type":"understanding","prediction":"you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i ll smash every bone in his ugly head","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":49,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1926\/Lab41-SRI-VOiCES-rm1-babb-sp1926-ch143879-sg0024-mc01-stu-clo-dg100.wav","answer":"was in direct proportion to the frequency with which he occupied her thoughts as this happened very often it sometimes appeared to missus ludlow that she had lost her courage so uncanny a result of so exhilarating an incident as inheriting a fortune","subset":"babb","task_type":"understanding","prediction":"was in direct proportion to the frequency with which he occupied her thoughts as this happened very often it sometimes appeared to mrs ludlow that she had lost her courage so uncanny a result of so exhilarating an incident as inheriting a fortune","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":50,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm1-babb-sp1961-ch145733-sg0000-mc01-stu-clo-dg170.wav","answer":"there was once a poor prince he possessed a kingdom which though small was yet large enough for him to marry on and married he wished to be now it was certainly a little audacious of him to venture to say to the emperor's daughter will you marry me but he did venture to say so","subset":"babb","task_type":"understanding","prediction":"there was once a poor prince he possessed a kingdom which though small was yet large enough for him to marry on and married he wished to be now it was certainly a little audacious of him to venture to say to the emperor s daughter will you marry me but he did venture to say so","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":51,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1963\/Lab41-SRI-VOiCES-rm1-babb-sp1963-ch142393-sg0048-mc02-lav-clo-dg100.wav","answer":"lest he should startle her too much yet he thought she's not one to be overstartled she's always so calm and quiet as if she was prepared for anything what was she thinking of as she wound up the hill","subset":"babb","task_type":"understanding","prediction":"lest he should startle her too much yet he thought she is not one to be over startled she is always so calm and quiet as if she was prepared for anything what was she thinking of as she wound up the hill","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":52,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm1-babb-sp1970-ch028415-sg0004-mc01-stu-clo-dg120.wav","answer":"hosanna in the highest the city was crowded with travelers from all over palestine and from foreign countries too they were the pilgrims who had come for the passover feast the crowds saw the procession coming they saw the donkey","subset":"babb","task_type":"understanding","prediction":"hosanna in the highest the city was crowded with travelers from all over palestine and from foreign countries too they were the pilgrims who had come for the passover feast the crowd saw the procession coming they saw the donkey","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":53,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm1-babb-sp2012-ch139356-sg0000-mc01-stu-clo-dg160.wav","answer":"the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon","subset":"babb","task_type":"understanding","prediction":"the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":54,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm1-babb-sp2110-ch161101-sg0016-mc02-lav-clo-dg040.wav","answer":"could do the same thing at once that is true art he also has a beautiful round tone not a note is missing one hears everything everything is well marked he has a fine staccato bow","subset":"babb","task_type":"understanding","prediction":"could do the same thing at once that is true art he also has a beautiful round tone not a note is missing one hears everything everything is well marked he has a fine staccato bow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":55,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2149\/Lab41-SRI-VOiCES-rm1-babb-sp2149-ch008912-sg0013-mc02-lav-clo-dg150.wav","answer":"she will soon see you now i am just going up to tell her you are here what haven't you told her before said melbury oh no said the other you see you came so very early at last the bell rang missus charmond could see him","subset":"babb","task_type":"understanding","prediction":"she will soon see you now i am just going up to tell her you are here what haven t you told her before said melbury oh no said the other you see you came so very early at last the bell rang mrs charmond could see him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":56,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm1-babb-sp2156-ch017942-sg0029-mc01-stu-clo-dg080.wav","answer":"now she will despise me and forget me it is better that she should think me a brute than that i should be always haunted by those pleading eyes the door of the distant church house opened and closed","subset":"babb","task_type":"understanding","prediction":"now she will despise me and forget me it is better that she should think me a brute than that i should be always haunted by those pleading eyes the door of the distant church house opened and closed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":57,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2162\/Lab41-SRI-VOiCES-rm1-babb-sp2162-ch164461-sg0006-mc02-lav-clo-dg140.wav","answer":"since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves","subset":"babb","task_type":"understanding","prediction":"since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":58,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm1-babb-sp2289-ch152257-sg0026-mc02-lav-clo-dg020.wav","answer":"justinian also did a great deal of good by establishing a number of manufactures in constantinople it was he who first brought silk worms into europe to the last year of his life justinian was strong and active","subset":"babb","task_type":"understanding","prediction":"justinian also did a great deal of good by establishing a number of manufactures in constantinople it was he who first brought silkworms into europe to the last year of his life justinian was strong and active","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":59,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm1-babb-sp2289-ch152258-sg0007-mc01-stu-clo-dg160.wav","answer":"and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work intrusted to him and","subset":"babb","task_type":"understanding","prediction":"and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work entrusted to him and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":60,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2294\/Lab41-SRI-VOiCES-rm1-babb-sp2294-ch169656-sg0015-mc01-stu-clo-dg070.wav","answer":"and the pirates boarded the schooner without further opposition the vessel was at once ransacked even the clothes of the crew being taken the ship's own boat was lowered and into this the marauders put their booty and took it ashore also carrying the captain and one of the crew with them","subset":"babb","task_type":"understanding","prediction":"and the pirates boarded the schooner without further opposition the vessel was at once ransacked even the clothes of the crew being taken the ship s own boat was lowered and into this the marauders put their booty and took it ashore also carrying the captain and one of the crew with them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":61,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2294\/Lab41-SRI-VOiCES-rm1-babb-sp2294-ch169656-sg0022-mc02-lav-clo-dg070.wav","answer":"an arrangement was afterwards made with the pirates to release the captains of the fiducia and the portuguese barque rosita faro a much earlier capture and some members of both crews in exchange for the riffians captured by the spanish steamer sevilla and a ransom of three thousand dollars","subset":"babb","task_type":"understanding","prediction":"an arrangement was afterwards made with the pirates to release the captains of the foudia and the portuguese bark rosita de peru a much earlier capture and some members of both crews in exchange for the riffians captured by the spanish steamer sevilla and a ransom of three thousand dollars","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":62,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm1-babb-sp2412-ch153948-sg0001-mc02-lav-clo-dg130.wav","answer":"it will be seen that i did not succeed in my design and that however much i may have met with that was new and strange i have been unable to reap any pecuniary advantage","subset":"babb","task_type":"understanding","prediction":"It will be seen that I did not succeed in my design and that, however much I may have met with. That was new and strange. I have been unable to reap any pecuniary advantage.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":63,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2532\/Lab41-SRI-VOiCES-rm1-babb-sp2532-ch157475-sg0013-mc02-lav-clo-dg130.wav","answer":"the folks will never find him down there for we can not tell them where he is and they will never guess it the dolls were all very sad they stayed out upon the shiny new tin gutter until it began raining and hoped and hoped that raggedy andy could get back up to them","subset":"babb","task_type":"understanding","prediction":"the folks will never find him down there for we cannot tell them where he is and they will never guess it the dolls were all very sad they stayed out upon the shiny new tin gutter until it began raining and hoped and hoped that raggedy andy could get back up to them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":64,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2573\/Lab41-SRI-VOiCES-rm1-babb-sp2573-ch178449-sg0023-mc01-stu-clo-dg080.wav","answer":"you feeding a strip of zinc into a machine nine hours a day no wonder she broke off and then after a keen glance at his face she said i should think you would have been a bad hand at it he laughed ruefully","subset":"babb","task_type":"understanding","prediction":"you feeding a strip of zinc into a machine nine hours a day no wonder she broke off and then after a keen glance at his face she said i should think you would have been a bad hand at it he laughed ruefully","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":65,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2673\/Lab41-SRI-VOiCES-rm1-babb-sp2673-ch156474-sg0006-mc01-stu-clo-dg030.wav","answer":"but before it could be executed circumstances intervened effectually to thwart that object while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress","subset":"babb","task_type":"understanding","prediction":"but before it could be executed circumstances intervened effectually to thwart that object while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":66,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2673\/Lab41-SRI-VOiCES-rm1-babb-sp2673-ch162130-sg0014-mc01-stu-clo-dg020.wav","answer":"it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution","subset":"babb","task_type":"understanding","prediction":"it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":67,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2691\/Lab41-SRI-VOiCES-rm1-babb-sp2691-ch156750-sg0014-mc01-stu-clo-dg130.wav","answer":"for she knew that we were nimbler footed when she started us off in happy mood each cow wore a bell of different tone and knew her own name yet it was not an easy task even in pleasant weather to collect the various strings and get them home on time","subset":"babb","task_type":"understanding","prediction":"for she knew that we were nimbler footed when she started us off in a happy mood each cow wore a bell of different tone and knew her own name yet it was not an easy task even in pleasant weather to collect the various strings and get them home on time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":68,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm1-babb-sp2758-ch086588-sg0001-mc02-lav-clo-dg160.wav","answer":"he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth","subset":"babb","task_type":"understanding","prediction":"he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":69,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm1-babb-sp2764-ch036617-sg0028-mc02-lav-clo-dg070.wav","answer":"the abraham lincoln reached an average speed of eighteen point three miles per hour a considerable speed but still not enough to cope with our gigantic cetacean the frigate's interior accommodations complemented its nautical virtues i was well satisfied with my cabin","subset":"babb","task_type":"understanding","prediction":"the abraham lincoln reached an average speed of eighteen point three miles per hour a considerable speed but still not enough to cope with our gigantic cetacean the frigate s interior accommodations complemented its nautical virtues i was well satisfied with my cabin","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":70,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm1-babb-sp2803-ch154320-sg0000-mc01-stu-clo-dg080.wav","answer":"fortunately will halley was not a man in a hurry and did not use a press of canvas or his masts would inevitably have come down","subset":"babb","task_type":"understanding","prediction":"fortunately will halley was not a man in a hurry and did not use oppressive canvas or his mass would inevitably have come down","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":71,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm1-babb-sp3368-ch170950-sg0006-mc02-lav-clo-dg080.wav","answer":"and dine off tables and they should have sauces and sweets in the modern style yes i said now i understand the question which you would have me consider is not only how a state but how a luxurious state is created and possibly there is no harm in this","subset":"babb","task_type":"understanding","prediction":"and dine off tables and they should have sauces and sweets in the modern style yes i said now i understand the question which you would have me consider is not only how a state but how a luxurious state is created and possibly there is no harm in this","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":72,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm1-babb-sp3483-ch119637-sg0028-mc01-stu-clo-dg040.wav","answer":"this creature his most prized possession san lan with the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil arts had i not seen the naked horror of her soul","subset":"babb","task_type":"understanding","prediction":"this creature his most prized possession san lawn with the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil art had i not seen the naked horror of her soul","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":73,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp3521\/Lab41-SRI-VOiCES-rm1-babb-sp3521-ch007591-sg0016-mc01-stu-clo-dg020.wav","answer":"and thus the waltzers perforce ceased their evolutions and there was a brief disconcert of the whole gay company and while the chimes of the clock yet rang it was observed that the giddiest grew pale and the more aged and sedate passed their hands over their brows as if in confused reverie or meditation","subset":"babb","task_type":"understanding","prediction":"unless the waltzers perforce ceased their evolutions and there was a brief disconcert of the whole gay company and while the chimes of the clock yet rang it was observed that the giddiest grew pale and the more aged and sedate passed their hands over their brows as if in confused reverie or meditation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":74,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_1212-3521\/sp3521\/Lab41-SRI-VOiCES-rm1-babb-sp3521-ch175962-sg0016-mc01-stu-clo-dg020.wav","answer":"then my brother toby cried my father clapping his two hands together shall go with us let my old tye wig quoth my uncle toby and my laced regimentals be hung to the fire all night trim page numbering skips ten pages","subset":"babb","task_type":"understanding","prediction":"then my brother toby cried my father clapping his two hands together shall go with us let my old tie wig quoth my uncle toby and my laced regimentals be hung to the fire all night trim page numbering skips ten pages","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":75,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm1-babb-sp3549-ch009203-sg0006-mc01-stu-clo-dg150.wav","answer":"approaching the shuddering rabbi addressed him as follows my son rejoice your trials here below are about to end if in the presence of such obstinacy i was forced to permit with deep regret","subset":"babb","task_type":"understanding","prediction":"approaching the shuddering rabbi addressed him as follows my son rejoice your trials here below are about to end if in the presence of such obstinacy i was forced to permit with deep regret","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":76,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3645\/Lab41-SRI-VOiCES-rm1-babb-sp3645-ch039840-sg0010-mc01-stu-clo-dg010.wav","answer":"opened his hands caught the moth and resumed his former attitude before beginning to speak of my business said alexey alexandrovitch following the lawyer's movements with wondering eyes i ought to observe that the business about which i have to speak to you is to be strictly private","subset":"babb","task_type":"understanding","prediction":"opened his hands caught the moth and resumed his former attitude before beginning to speak of my business said alexey alexandrovitch following the lawyer s movements with wondering eyes i ought to observe that the business about which i have to speak to you is to be strictly private","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":77,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3645\/Lab41-SRI-VOiCES-rm1-babb-sp3645-ch039840-sg0032-mc02-lav-clo-dg010.wav","answer":"if one wants the result one must admit the means if it is so alexey alexandrovitch began suddenly turning white but at that moment the lawyer rose and again went to the door to speak to the intruding clerk","subset":"babb","task_type":"understanding","prediction":"if one wants the result one must admit the means if it is so alexey alexandrovitch began suddenly turning white but at that moment the lawyer rose and again went to the door to speak to the intruding clerk","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":78,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm1-babb-sp3835-ch178028-sg0016-mc01-stu-clo-dg110.wav","answer":"that it was impossible to expect anything else from a blind and depraved old man i only wonder that the fate of russia could have been entrusted to such a man as long as this news remained unofficial it was possible to doubt it but the next day the following communication was received from count rostopchin","subset":"babb","task_type":"understanding","prediction":"that it was impossible to expect anything else from a blind and depraved old man i only wonder that the fate of russia could have been entrusted to such a man as long as the news remained unofficial it was possible to doubt it but the next day the following communication was received from count rostopchin","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":79,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm1-babb-sp3923-ch153309-sg0039-mc02-lav-clo-dg060.wav","answer":"and manufactures his own concoctions in a house he has rented here on a lonely road some half mile out of town wellgood does the man named wellgood mister grey exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town","subset":"babb","task_type":"understanding","prediction":"and manufactures his own concoctions in a house he has rented here on the longview road some half mile of town wellgood does many wellgood mr gregg exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":80,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm1-babb-sp3923-ch181420-sg0021-mc01-stu-clo-dg110.wav","answer":"and his athletics served to strengthen his appeals to the london boys whom he enrolled in the brigades he founded the inter hospital rowing club at putney and rowed in the first inter hospital race he played on the varsity football team and won the throwing the hammer at the sports","subset":"babb","task_type":"understanding","prediction":"and his athletics served to strengthen his appeals to the london boys whom he enrolled in the brigades he founded the inter hospital rowing club at putney and rowed in the first inter hospital race he played on the varsity football team and won the throwing the hammer at the sports","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":81,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3972\/Lab41-SRI-VOiCES-rm1-babb-sp3972-ch005791-sg0010-mc01-stu-clo-dg130.wav","answer":"when remonstrances were sent to london he neither punished nor reprimanded the delinquents but marched an armed force into our country to compel us to be trampled on it was not an alexander nor a charlemagne coming in his strength to subdue ancient enemies or to aggrandize his name","subset":"babb","task_type":"understanding","prediction":"when remonstrances were sent to london he neither punished nor reprimanded the delinquents but marched an armed force into our country to compel us to be trampled on it was not an alexander nor charlemagne coming in his strength to subdue ancient enemies or to aggrandize his name","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":82,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3989\/Lab41-SRI-VOiCES-rm1-babb-sp3989-ch182402-sg0004-mc01-stu-clo-dg160.wav","answer":"hi spotty he shouted where do you live spotty slowly turned his head and looked up at peter there was a twinkle in his eyes though peter didn't see it right here in the smiling pool where else should i live he replied","subset":"babb","task_type":"understanding","prediction":"hi spotty he shouted where do you live spotty slowly turned his head and looked up at peter there was a twinkle in his eyes though peter didn't see it right here on the smiling pool where else should i live he replied","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":83,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp3994\/Lab41-SRI-VOiCES-rm1-babb-sp3994-ch149798-sg0017-mc01-stu-clo-dg110.wav","answer":"added the scarecrow but how asked uncle henry in a grave voice for he could not bear to think of his dear niece dorothy being out there under water how shall we do it leave that to glinda","subset":"babb","task_type":"understanding","prediction":"added the scarecrow but how asked uncle henry in a grave voice for he could not bear to think of his dear niece dorothy being out there under water how shall we do it leave that to glinda","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":84,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-babb-sp4014-ch186175-sg0019-mc01-stu-clo-dg180.wav","answer":"and he started down the passageway toward a narrow stairs leading to a still lower chamber in the vessel three turns two to the right and one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock","subset":"babb","task_type":"understanding","prediction":"and he started down the passageway towards a narrow stairs leading to a still lower chamber in the vessel three turns two to the right one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":85,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-babb-sp4014-ch186183-sg0024-mc01-stu-clo-dg170.wav","answer":"he pointed her nose downward toward the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer's place in the taube was making desperate signals","subset":"babb","task_type":"understanding","prediction":"he pointed her nose downward towards the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer s place in the top was making desperate signals","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":86,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4057\/Lab41-SRI-VOiCES-rm1-babb-sp4057-ch183239-sg0007-mc01-stu-clo-dg130.wav","answer":"is not devoid of sense but why this custom designed for that excellent mortal the t atkins who walked out with nurse maids and was none too busy between whiles should be forced upon a totally different if no less estimable","subset":"babb","task_type":"understanding","prediction":"is not devoid of sense but why this custom designed for that excellent mortal the t atkins who walked out with nursemaids and was none too busy between whiles should be forced upon a totally different if no less estimable","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":87,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm1-babb-sp4064-ch012118-sg0002-mc02-lav-clo-dg150.wav","answer":"they had waited but a few moments when mister underwood's carriage stopped before this entrance and an instant later kate heard her father's voice directing the coachman to call for him in about an hour as the key turned in the lock she heard walcott's voice also","subset":"babb","task_type":"understanding","prediction":"they had waited but a few moments when mr underwood's carriage stopped before this entrance and an instant later kate heard her father's voice directing the coachman to call for him in about an hour as the key turned in the lock she heard walcott's voice also","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":88,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4116\/Lab41-SRI-VOiCES-rm1-babb-sp4116-ch013265-sg0006-mc02-lav-clo-dg090.wav","answer":"you are always doing some queer thing or other felicia said the older girl as the carriage whirled on past the great residences already brilliantly lighted am i what have i done that is queer now rose asked the other looking up suddenly and turning her head towards her sister","subset":"babb","task_type":"understanding","prediction":"you always doing some queer thing or other felicia said the older girl as the carriage whirled on past the great residences already brilliantly lighted am i what have i done that is queer now rose asked the other looking up suddenly and turning her head towards her sister","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":89,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4145\/Lab41-SRI-VOiCES-rm1-babb-sp4145-ch014013-sg0001-mc01-stu-clo-dg180.wav","answer":"her grace had issued cards for a concert and after mature deliberation it was decided that her rival should strike out something new and announce a christening for the same night the first intimation douglas had of the honour intended him by this arrangement","subset":"babb","task_type":"understanding","prediction":"her grace had issued cards for a concert and after mature deliberation it was decided that her rival should strike out something new and announce a christening for the same night the first intimation douglas had of the honour intended him by this arrangement","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":90,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4145\/Lab41-SRI-VOiCES-rm1-babb-sp4145-ch104606-sg0005-mc02-lav-clo-dg030.wav","answer":"this went on jack airily is a friend of mine bruce graham graham this is miss brodie madge acknowledged the introduction with an inclination of the head which was so faint as to be almost imperceptible","subset":"babb","task_type":"understanding","prediction":"this went on jack airily is a friend of mine bruce graham graham this is miss prody madge acknowledged the introduction with an inclination of the head which was so faint as to be almost imperceptible","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":91,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4160\/Lab41-SRI-VOiCES-rm1-babb-sp4160-ch011549-sg0020-mc01-stu-clo-dg120.wav","answer":"she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin's wishes in the matter of military balls and blue satin slippers","subset":"babb","task_type":"understanding","prediction":"she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin s wishes in the matter of military balls and blue satin slippers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":92,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4160\/Lab41-SRI-VOiCES-rm1-babb-sp4160-ch011550-sg0027-mc01-stu-clo-dg050.wav","answer":"that her pronoun was almost an interjection i thought perhaps said priscilla quietly that a message from you would gratify him if you had one to send theo took up her gloves and began to draw them on a sudden feeling of pain or discomfort striking her","subset":"babb","task_type":"understanding","prediction":"that her pronoun was almost an interjection i thought perhaps said priscilla quietly that a message from you would gratify him if you had one to send theo took up her gloves and began to draw them on a sudden feeling of pain or discomfort striking her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":93,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4160\/Lab41-SRI-VOiCES-rm1-babb-sp4160-ch014187-sg0005-mc01-stu-clo-dg040.wav","answer":"a queer affair jervis a very odd affair indeed i was coming up from the borough picking my way mighty carefully across the road on account of the greasy slippery mud and had just reached the foot of london bridge when i heard a heavy lorry coming down the slope a good deal too fast","subset":"babb","task_type":"understanding","prediction":"a queer affair jervis a very odd affair indeed i was coming up from the borough picking my way mighty carefully across the road on account of the greasy slippery mud and had just reached the foot of london bridge when i heard a heavy lorry coming down the slope a good deal too fast","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":94,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4331\/Lab41-SRI-VOiCES-rm1-babb-sp4331-ch057180-sg0021-mc02-lav-clo-dg110.wav","answer":"an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said up stairs they could not have talked as they were then talking","subset":"babb","task_type":"understanding","prediction":"an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said upstairs they could not have talked as they were then talking","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":95,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm1-babb-sp4427-ch020028-sg0010-mc01-stu-clo-dg060.wav","answer":"i ride in the omnibus and am almost choked with my bonnet strings such a furious draught meets me in the face and when with infinite pains i have secured the only tolerably warm corner my next neighbor becomes very faint and must have the window open","subset":"babb","task_type":"understanding","prediction":"arrive in the omnibus and am almost choked with my bonnet strings such a furious draught meets me in the face and when with infinite pains i have secured the only tolerably warm corner my next neighbour becomes very faint and must have the window open","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":96,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm1-babb-sp4438-ch048513-sg0023-mc01-stu-clo-dg110.wav","answer":"and no man could say more but judging from what well what people had said to him it hadn't been much of a success sometimes and often and often he had been hurt deeply hurt by being misunderstood and lucy said","subset":"babb","task_type":"understanding","prediction":"and no man could say more but judging from what well what people had said to him it hadn't been much of a success sometimes and often and often he had been hurt deeply hurt by being misunderstood and lucy said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":97,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm1-babb-sp4438-ch048525-sg0023-mc02-lav-clo-dg040.wav","answer":"she sat like a beggar in patient distress waiting for him to emerge and be kind to her of course as far as the minor wishes and preferences of every day went it was all quite easy once she had grasped the right answer to the question","subset":"babb","task_type":"understanding","prediction":"she sat like a beggar in patient distress waiting for him to emerge and be kind to her of course as far as the minor wishes and preferences of every day went it was all quite easy once she had grasped the right answer to the question","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":98,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm1-babb-sp4441-ch076262-sg0010-mc02-lav-clo-dg060.wav","answer":"and he declared that many so called unbearable situations could be borne quite easily if only one did not exaggerate their importance the time passed slowly but at last it struck ten a gentle double rap at the door relieved the tension","subset":"babb","task_type":"understanding","prediction":"Annie declared that many so called unbearable situations could be borne quite easily if only one did not exaggerate their importance. The time passed slowly, but at last, it struck 10. A gentle double rap at the door, relieved the tension.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":99,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4744\/Lab41-SRI-VOiCES-rm1-babb-sp4744-ch004158-sg0009-mc01-stu-clo-dg110.wav","answer":"all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims","subset":"babb","task_type":"understanding","prediction":"all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":100,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4744\/Lab41-SRI-VOiCES-rm1-babb-sp4744-ch083616-sg0012-mc02-lav-clo-dg130.wav","answer":"he it was they thought who produced the thunder and the lightning by hurling stones with his sling and the thunderbolts that fall said they are his children few villages were willing to be without one or more of these they were in appearance small round smooth stones","subset":"babb","task_type":"understanding","prediction":"he it was they thought who produced the thunder and the lightning by hurling stones with his sling and the thunderbolts that fall said they are his children few villages were willing to be without one or more of these they were in appearance small round smooth stones","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":101,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4859\/Lab41-SRI-VOiCES-rm1-babb-sp4859-ch022176-sg0005-mc01-stu-clo-dg090.wav","answer":"that princess mary was in moscow the death sufferings and last days of prince andrew had often occupied pierre's thoughts and now recurred to him with fresh vividness having heard at dinner that princess mary was in moscow and living in her house","subset":"babb","task_type":"understanding","prediction":"that princess mary was in moscow the death sufferings and last days of prince andrew had often occupied pierre s thoughts and now recurred to him with fresh vividness having heard at dinner that princess mary was in moscow and living in her house","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":102,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4859\/Lab41-SRI-VOiCES-rm1-babb-sp4859-ch022176-sg0016-mc02-lav-clo-dg070.wav","answer":"she again glanced rapidly from pierre's face to that of the lady in the black dress and said do you really not recognize her pierre looked again at the companion's pale delicate face with its black eyes and peculiar mouth and something near to him long forgotten and more than sweet","subset":"babb","task_type":"understanding","prediction":"she again glanced rapidly from pierre s face to that of the lady in the black dress and said do you really not recognize her pierre looked again at the companion s pale delicate face with its black eyes and peculiar mouth and something near to him long forgotten and more than sweet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":103,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp4967\/Lab41-SRI-VOiCES-rm1-babb-sp4967-ch026520-sg0009-mc02-lav-clo-dg180.wav","answer":"king nebuchadnezzar saw a wonderful dream the accomplishment of which god showed him in his sleep but when he arose out of his bed he forgot the accomplishment so he sent for the chaldeans and magicians and the prophets and told them that he had seen a dream","subset":"babb","task_type":"understanding","prediction":"king nebuchadnezzar saw a wonderful dream the accomplishment of which god showed him in his sleep but when he rose out of his bed he forgot the accomplishment so he sent for the chaldeans and magicians and the prophets and told them that he had seen a dream","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":104,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm1-babb-sp5154-ch026558-sg0022-mc01-stu-clo-dg150.wav","answer":"the monkey was at last able to pull out one of his hands the sun poured down more of his hottest rays and soon the monkey was able to pull out his two hands then he could pull out one foot then another and in a little while his body too","subset":"babb","task_type":"understanding","prediction":"The monkey was at last able to pull out one of his hands. The sun poured down more of his hottest rays. And soon, the monkey was able to pull out his two hands. Then he could pull out 1 ft. Then another. And in a little while, his body, too.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":105,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm1-babb-sp5154-ch026559-sg0021-mc02-lav-clo-dg080.wav","answer":"this is not the monkey's leg it is just a dry stick he said as he made a wry face then he fished the empty cocoanut shell out of the pot that is not the monkey's head he said as he tasted it","subset":"babb","task_type":"understanding","prediction":"This is not the monkey's leg. It is just a dry stick, he said, as he made a wry face. Then he fished the empty cocoanut shell out of the pot. That is not the monkey's head, he said, as he tested it.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":106,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm1-babb-sp5189-ch037999-sg0001-mc01-stu-clo-dg030.wav","answer":"for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries to the trip east together with minute instructions as to the journey itself selecting a proper school","subset":"babb","task_type":"understanding","prediction":"for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries of the trip east together with minute instructions as to the journey itself selecting a proper school","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":107,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm1-babb-sp5189-ch056574-sg0007-mc02-lav-clo-dg120.wav","answer":"sich a magnificent chance to make it manifest try yoor self particularly on custer tho after all continyood he in a musin abstracted sort a way wich he's fallen into lately the fellow is sich a triflin bein","subset":"babb","task_type":"understanding","prediction":"such a magnificent chance to make it manifest try yourself particularly on custer though after all continued he in a musing abstracted sort of way which he has fallen into lately the fellow is such a trifling being","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":12}
+{"index":108,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5319\/Lab41-SRI-VOiCES-rm1-babb-sp5319-ch042637-sg0002-mc02-lav-clo-dg010.wav","answer":"districts and counties black men would be supported and elected to office because they were black and white men would be opposed and defeated because they were white taking mississippi for purposes of illustration","subset":"babb","task_type":"understanding","prediction":"districts and counties black men would be supported and elected to office because they were black and white men would be opposed and defeated because they were white taking mississippi for purposes of illustration","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":109,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5319\/Lab41-SRI-VOiCES-rm1-babb-sp5319-ch042637-sg0003-mc01-stu-clo-dg120.wav","answer":"it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position","subset":"babb","task_type":"understanding","prediction":"it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":110,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5338\/Lab41-SRI-VOiCES-rm1-babb-sp5338-ch024640-sg0009-mc01-stu-clo-dg080.wav","answer":"since that time their numbers have gradually diminished but a good many are still to be found in the western counties and several with a better temper than in seventeen o seven have now taken arms for government","subset":"babb","task_type":"understanding","prediction":"since that time their numbers have gradually diminished but a good many are still to be found in the western counties and several with a better temper than in seventeen o seven have now taken arms for government","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":111,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5386\/Lab41-SRI-VOiCES-rm1-babb-sp5386-ch008684-sg0033-mc01-stu-clo-dg140.wav","answer":"the son had a rope ready to cast round its horns and throw it to the ground but the ox was stronger than the rope and soon tore it in pieces then it dashed away to the wood the youth following over hedges and ditches they both went till they reached the rocky pass which bordered the herdsman's land","subset":"babb","task_type":"understanding","prediction":"the sun had a rope ready to cast round its horns and throw it to the ground but the ox was stronger than the rope and soon tore it in pieces then it dashed away to the wood the youth following over hedges and ditches they both went till they reached the rocky pass which bordered the herdsman s land","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":112,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm1-babb-sp5456-ch062043-sg0003-mc01-stu-clo-dg080.wav","answer":"she must have had a time of it it was my fate to take passage in this boat the captain was a good natured easy going man careful of the comfort of his passengers and exceedingly fond of the game of brag we had been out a little more than five days","subset":"babb","task_type":"understanding","prediction":"she must have had a time of it it was my fate to take passage in this boat the captain was a good natured easy going man careful of the comfort of his passengers and exceedingly fond of the game of brag we had been out a little more than five days","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":113,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5583\/Lab41-SRI-VOiCES-rm1-babb-sp5583-ch041259-sg0000-mc01-stu-clo-dg100.wav","answer":"in the perusal of the following pages your sensibility will be most severely tried ah what were the misfortunes i had before experienced and which i have already related to you to the one i am now going to inform you of","subset":"babb","task_type":"understanding","prediction":"in the perusal of the following pages your sensibility will be most severely tried ah what were the misfortunes i had before experienced and which i have already related to you to the one i am now going to inform you of","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":114,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5583\/Lab41-SRI-VOiCES-rm1-babb-sp5583-ch041259-sg0043-mc02-lav-clo-dg180.wav","answer":"and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain","subset":"babb","task_type":"understanding","prediction":"and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":115,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm1-babb-sp5678-ch043301-sg0011-mc02-lav-clo-dg100.wav","answer":"the murmurs of talk rose into cheering old lord pemberton came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily","subset":"babb","task_type":"understanding","prediction":"the murmurs of talk rose into cheering old lord pemberdon came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":116,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5802\/Lab41-SRI-VOiCES-rm1-babb-sp5802-ch066347-sg0012-mc02-lav-clo-dg010.wav","answer":"for example said the doctor of course we don't doubt your word but when a man makes a statement based upon personal observation it is profitable to ask him what his precise experience has been merely for the purpose of adding to our own knowledge","subset":"babb","task_type":"understanding","prediction":"for example said the doctor of course we do not doubt your word but when a man makes a statement based upon personal observation it is profitable to ask him what his precise experience has been merely for the purpose of adding to our own knowledge","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":117,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm1-babb-sp5868-ch055088-sg0015-mc02-lav-clo-dg050.wav","answer":"and the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth is whirled through europe without gaining a single idea worth crossing the street for","subset":"babb","task_type":"understanding","prediction":"and the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth has whirled through europe without gaining a single idea worth crossing the straits for","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":118,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp6099\/Lab41-SRI-VOiCES-rm1-babb-sp6099-ch069550-sg0012-mc02-lav-clo-dg160.wav","answer":"and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful","subset":"babb","task_type":"understanding","prediction":"and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":119,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm1-babb-sp6147-ch034605-sg0039-mc01-stu-clo-dg170.wav","answer":"she wore great dresses of velvet satin or moire some composed of fifteen or sixteen yards of material with embroideries of gold and silver and round her waist many knots of pearls alternating with other precious stones she was extravagant in gold lace","subset":"babb","task_type":"understanding","prediction":"she wore great dresses of velvet satin or moire some composed of fifteen or sixteen yards of material with embroideries of gold and silver and round her waist many knots of pearls alternating with other precious stones she was extravagant in gold lace","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":120,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm1-babb-sp6147-ch034607-sg0031-mc02-lav-clo-dg080.wav","answer":"in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher wren is a very passable mansard somers is as good as lamoignon anne has a racine in dryden","subset":"babb","task_type":"understanding","prediction":"in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher rand is a very passable mazarin somers is as good as lemoignon anne has a racine in dryden","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":121,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm1-babb-sp6241-ch061946-sg0006-mc01-stu-clo-dg130.wav","answer":"i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur","subset":"babb","task_type":"understanding","prediction":"i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":122,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm1-babb-sp6395-ch087997-sg0045-mc02-lav-clo-dg090.wav","answer":"but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive","subset":"babb","task_type":"understanding","prediction":"but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":123,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm1-babb-sp6415-ch100596-sg0002-mc02-lav-clo-dg070.wav","answer":"georgie stopped to examine some loose sheets of paper which were impaled upon the door what's this patty oh that's the registration list for the german club priscilla's secretary you know and every one who wants to join comes here","subset":"babb","task_type":"understanding","prediction":"georgie stopped to examine some loose sheets of paper which were impaled upon the door what s this paddy oh that s the registration list for the german club priscilla s secretary you know and everybody who wants to join comes here","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":124,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm1-babb-sp6415-ch111615-sg0024-mc01-stu-clo-dg120.wav","answer":"who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible","subset":"babb","task_type":"understanding","prediction":"who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":125,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm1-babb-sp6519-ch069412-sg0034-mc02-lav-clo-dg170.wav","answer":"the proprietor's name is yardley we have nothing against him the place is highly respectable but it harbours a boarder a permanent one i believe who has occasioned no little comment no one has ever seen her face unless it is the landlord's wife","subset":"babb","task_type":"understanding","prediction":"the proprietor s name is yardley we have nothing against him the place is highly respectable but it harbors a boarder an incipient one i believe who has occasioned no little comment no one has ever seen her face unless it is the landlord s wife","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":126,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm1-babb-sp6519-ch231834-sg0004-mc02-lav-clo-dg080.wav","answer":"close at hand various artifices aided her to pass for thirty and it was only in the solitude of her own room that her real age was apparent never did woman wage a more resolute fight with time than did miss greeb","subset":"babb","task_type":"understanding","prediction":"close at hand various artifices aided her to pass for thirty and it was only in the solitude of her own room that her real age was apparent never did woman wage a more resolute fight with time than did miss gree","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":127,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm1-babb-sp6519-ch231834-sg0020-mc01-stu-clo-dg170.wav","answer":"but what grounds have you to believe him any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence","subset":"babb","task_type":"understanding","prediction":"but what grounds have you to believe in any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":128,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6696\/Lab41-SRI-VOiCES-rm1-babb-sp6696-ch068773-sg0000-mc01-stu-clo-dg020.wav","answer":"lucy's ghost kenneth had sent word to tom gates asking the young man to come to elmhurst but it was not until two days after the lawn party that tom appeared and asked permission to see mister forbes beth and louise were with kenneth at the time","subset":"babb","task_type":"understanding","prediction":"lucy s ghost kenneth had sent word to tom gates asking the young man to come to elmhurst but it was not until two days after the lawn party that tom appeared and asked permission to see mr forbes beth and louise were with kenneth at the time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":129,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-babb-sp6895-ch092805-sg0008-mc01-stu-clo-dg040.wav","answer":"the local note of the mere globe trotter but his opinions never fluttered or drooped he was as impartial to cities countries and continents as the winds or gravitation and as e rushmore coglan prattled of this little planet i thought with glee","subset":"babb","task_type":"understanding","prediction":"the local note of the mere globe trotter but his opinions never fluttered or drooped he was as impartial to cities countries and continents as the wind or gravitation and as e rushmore coburn prattled of this little planet i thought with glee","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":130,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-babb-sp6895-ch092805-sg0008-mc02-lav-clo-dg040.wav","answer":"the local note of the mere globe trotter but his opinions never fluttered or drooped he was as impartial to cities countries and continents as the winds or gravitation and as e rushmore coglan prattled of this little planet i thought with glee","subset":"babb","task_type":"understanding","prediction":"the local note of the mere globe trotter but his opinions never fluttered or drew he was impartial to cities countries and continents as the wind or gravitation and as eve rushmore cokely prattled of this little planet i thought with glee","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":131,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-babb-sp6895-ch092806-sg0009-mc02-lav-clo-dg180.wav","answer":"there was something in her manner that warned mister mc caskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware pig's face is it said missus mc caskey and hurled a stewpan full of bacon and turnips at her lord","subset":"babb","task_type":"understanding","prediction":"there was something in her manner that warned mr maccaskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware pig's face is it said mrs maccaskey and hurled a stew pan full of bacon and turnips at her lord","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":132,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm1-babb-sp6965-ch277899-sg0013-mc02-lav-clo-dg180.wav","answer":"brown with a darkish tail norah changed colour does it live in a tree and eat nuts she asked hoping that the use of the adjective large might be an exaggeration vladimir laughed","subset":"babb","task_type":"understanding","prediction":"brown with a darkish tail norah changed colour does it live in a tree and eat nuts she asked hoping that the use of the adjective large might be an exaggeration vladimir laughed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":133,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm1-babb-sp7000-ch083696-sg0027-mc01-stu-clo-dg000.wav","answer":"well he said it's a pity it should be wasted i'll eat it myself which he did and me standing in the rain there looking on that did put my back up mister evans i said short and sharp i wish you a good day i am going","subset":"babb","task_type":"understanding","prediction":"well he said it is a pity it should be wasted i ll leave it myself which he did and me standing in the rain there looking on that did put my back up mr evans i said short and sharp i wish you a good day i am going","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":134,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm1-babb-sp7095-ch088489-sg0021-mc01-stu-clo-dg170.wav","answer":"the great orthodox body of religiosa dementia fell back upon the remainder of the theory that the hebrew language was the first of all languages which was spoken by the almighty given by him to adam","subset":"babb","task_type":"understanding","prediction":"the great orthodox body of religiosa dementia fell back upon the remainder of the theory that the hebrew language was the first of all languages which was spoken by the almighty given by him to adam","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":135,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm1-babb-sp7148-ch007763-sg0001-mc01-stu-clo-dg130.wav","answer":"it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing","subset":"babb","task_type":"understanding","prediction":"it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":136,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm1-babb-sp7148-ch082991-sg0013-mc02-lav-clo-dg170.wav","answer":"are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king's highness said the tall man","subset":"babb","task_type":"understanding","prediction":"are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king s highness said the tall man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":137,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7264\/Lab41-SRI-VOiCES-rm1-babb-sp7264-ch092316-sg0028-mc02-lav-clo-dg060.wav","answer":"no one of them is in any sense general or really national the free press gives you the truth but only in disjointed sections for it is disparate and it is particularist it is marked with isolation and it is so marked because its origin lay in various and most diverse propaganda","subset":"babb","task_type":"understanding","prediction":"no one of them is in any sense general or really national the free press gives you the truth but only in disjointed sections for it is disparate and it is particularist it is marked with isolation and it is so marked because it is originally in various and most diverse propaganda","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":138,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7276\/Lab41-SRI-VOiCES-rm1-babb-sp7276-ch090847-sg0006-mc01-stu-clo-dg060.wav","answer":"alas what are we to do i can not take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing","subset":"babb","task_type":"understanding","prediction":"alas what are we to do i cannot take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":139,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7276\/Lab41-SRI-VOiCES-rm1-babb-sp7276-ch090847-sg0045-mc02-lav-clo-dg030.wav","answer":"and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen","subset":"babb","task_type":"understanding","prediction":"and it is thanks to him that i have returned in time with the storm at my heels you mariana are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":140,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm1-babb-sp7278-ch246956-sg0032-mc02-lav-clo-dg110.wav","answer":"let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves","subset":"babb","task_type":"understanding","prediction":"let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":141,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm1-babb-sp7445-ch094523-sg0020-mc01-stu-clo-dg180.wav","answer":"that the parliament while it sits must first proceed upon the king's business and that this assembly cannot without his consent impeach any of his ministers and judges even according to our present strict maxims with regard to law and the royal prerogative","subset":"babb","task_type":"understanding","prediction":"That the Parliament, while it sits, must first proceed upon the king's business and that this Assembly cannot, without his consent. Impeach any of his ministers and judges. Even according to our present strict maxims. With regard to the law and the royal prerogative.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":142,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099124-sg0010-mc01-stu-clo-dg040.wav","answer":"humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former","subset":"babb","task_type":"understanding","prediction":"humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":143,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099156-sg0024-mc01-stu-clo-dg050.wav","answer":"dated twenty sixth august in which she informs him that she has a prospect of being a mother in the month of november and of thus attaining what has been her only wish ungratified for these four years she writes from hamburg where she was on a visit to her family","subset":"babb","task_type":"understanding","prediction":"dated twenty sixth august in which she informs him that she has a prospect of being a mother in the month of november and of thus attaining what has been her only wish ungratified for these four years she writes from hamburg where she was on a visit to her family","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":144,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099157-sg0011-mc02-lav-clo-dg000.wav","answer":"having submitted her first drawings to sir hans sloane and doctor mead these eminent physicians encouraged her to proceed with the work she also received the kindest countenance from mister philip miller a well known writer on horticulture","subset":"babb","task_type":"understanding","prediction":"having submitted her first drawings to sir hans sloane and dr mead these eminent physicians encouraged her to proceed with the work she also received the kindest countenance from mr philip miller a well known writer on horticulture","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":145,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm1-babb-sp7498-ch099157-sg0017-mc02-lav-clo-dg040.wav","answer":"he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on agriculture he went there leaving his wife in england he was received with honour at the court of stockholm","subset":"babb","task_type":"understanding","prediction":"he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on aquaculture he went there leaving his wife in england he was received with honour at the court of stockholm","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":146,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm1-babb-sp7540-ch101262-sg0041-mc01-stu-clo-dg000.wav","answer":"come to me o mare of the mountain witch the prince did as he was bid and as the hair touched his fingers the wolf changed back into a mare with the foal beside her and when he had mounted and ridden her home the old woman was on the steps to receive them","subset":"babb","task_type":"understanding","prediction":"come to me o mare of the mountain witch prince did as he was bid and as the hair touched his fingers the wolf changed back into a mare with the foal beside her and when he had mounted and ridden her home the old woman was on the steps to receive them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":147,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7704\/Lab41-SRI-VOiCES-rm1-babb-sp7704-ch106965-sg0012-mc01-stu-clo-dg120.wav","answer":"who is she asked teddy as tired and exhausted by his recital he threw himself on the grass to rest one of the bigger boys answered him i seed her come yesterday in a cab from the town to old sol at the turnpike she and her mother i reckon","subset":"babb","task_type":"understanding","prediction":"who is she asked teddy as tired and exhausted by his recital he threw himself on the grass to rest one of the bigger boys answered him i seed her come yesterday in a cab from the town to old sol at the turnpike she and her mother i reckon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":148,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm1-babb-sp7868-ch110705-sg0018-mc01-stu-clo-dg040.wav","answer":"something like that of a kettle on the boil gluck looked out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment","subset":"babb","task_type":"understanding","prediction":"something like that of a kettle on the boil luck looked out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":149,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm1-babb-sp7881-ch109662-sg0030-mc01-stu-clo-dg040.wav","answer":"merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her","subset":"babb","task_type":"understanding","prediction":"merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":150,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7910\/Lab41-SRI-VOiCES-rm1-babb-sp7910-ch105673-sg0041-mc02-lav-clo-dg130.wav","answer":"there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries","subset":"babb","task_type":"understanding","prediction":"there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":151,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm1-babb-sp7932-ch093470-sg0011-mc02-lav-clo-dg120.wav","answer":"i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruth's own wish that it should be told to others","subset":"babb","task_type":"understanding","prediction":"i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruths own wish that it should be told to others","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":152,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-babb-sp7976-ch110124-sg0013-mc02-lav-clo-dg020.wav","answer":"the two eldest ate their apples but the youngest could not eat that night she threw the apple away","subset":"babb","task_type":"understanding","prediction":"The two eldest ate their apples, but the youngest could not eat that night. She threw the apple away.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":153,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-babb-sp7976-ch110124-sg0018-mc02-lav-clo-dg040.wav","answer":"the merchant's daughter at first did not answer but as he kept on calling to her she finally asked him what it was that he wanted","subset":"babb","task_type":"understanding","prediction":"The merchant's daughter at first did not answer, but as he kept on calling to her, she finally asked him what it was that he wanted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":154,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-babb-sp7981-ch112058-sg0001-mc02-lav-clo-dg010.wav","answer":"to endow a band of priests who would devote their lives to evangelizing the peasantry on her estates vincent was delighted but considering himself unfit to undertake the management of such an enterprise he proposed that it should be put into the hands of the jesuits or the oratorians","subset":"babb","task_type":"understanding","prediction":"they would now a band of priests who would devote their lives to evangelizing the peasantry on her estates vincent was delighted but considering himself unfit to undertake the management of such an enterprise he proposed that it should be put into the hands of the jesuits or the oratorians","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":155,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm1-babb-sp7995-ch276908-sg0029-mc02-lav-clo-dg060.wav","answer":"in which on the lovely tenth of june under a serene sky the amorous jacobite kissing the odoriferous zephyr's breath gathers a nosegay of white roses to deck the whiter breast of celia","subset":"babb","task_type":"understanding","prediction":"in which on the lovely tenth of june under a serene sky the amorous gigolite kissing the odoriferous zephyr s breath gathers a nosegay of white roses to deck the whiter breast of celia","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":156,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8051\/Lab41-SRI-VOiCES-rm1-babb-sp8051-ch119902-sg0019-mc02-lav-clo-dg000.wav","answer":"and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits","subset":"babb","task_type":"understanding","prediction":"and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":157,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm1-babb-sp8108-ch280359-sg0013-mc02-lav-clo-dg150.wav","answer":"by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death","subset":"babb","task_type":"understanding","prediction":"by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":158,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8118\/Lab41-SRI-VOiCES-rm1-babb-sp8118-ch114469-sg0018-mc01-stu-clo-dg090.wav","answer":"then the wind shifted and drove the sheets of rain sprinkled with hail directly in his face he was compelled to stop a while and take refuge behind a big oak while he shivered in the shelter of the tree the only things that he thought of spontaneously were dry clothes hot food a fire and a warm bed","subset":"babb","task_type":"understanding","prediction":"then the wind shifted and drove the sheets of rain sprinkled with hail directly in his face he was compelled to stop a while and take refuge behind a big oak while he shivered in the shelter of the tree the only things that he thought of spontaneously were dry clothes hot food a fire and a warm bed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":159,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm1-babb-sp8225-ch274375-sg0023-mc01-stu-clo-dg030.wav","answer":"the necessities of the garrison were extreme one barrel of powder was their whole stock of ammunition remaining and their other provisions were in the same proportion essex had brought with him military stores and the neighboring country abundantly supplied him with victuals of every kind","subset":"babb","task_type":"understanding","prediction":"the necessities of the garrison were extreme one barrel of powder was their whole stock of ammunition remaining and their other provisions were in the same proportion essex had brought with him military stores and the neighboring country abundantly supplied him with victuals of every kind","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":160,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm1-babb-sp8225-ch274376-sg0000-mc02-lav-clo-dg120.wav","answer":"the establishment of presbyterian discipline in their own country they were not satisfied but indulged still in an ardent passion for propagating by all methods that mode of religion in the neighboring kingdoms having flattered themselves in the fervor of their zeal","subset":"babb","task_type":"understanding","prediction":"the establishment of presbyterian discipline in their own country they were not satisfied but indulged still in an ardent passion for propagating by all methods that mode of religion in the neighbouring kingdoms having flattered themselves in the fervour of their zeal","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":161,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm1-babb-sp8266-ch279363-sg0024-mc01-stu-clo-dg100.wav","answer":"they are in the nearer thickets cried the colonel and now they're climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest","subset":"babb","task_type":"understanding","prediction":"they are in the nearer thickets cried the colonel and now they are climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":162,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-babb-sp8425-ch291444-sg0013-mc01-stu-clo-dg150.wav","answer":"the infant years of our city to introduce a thousand pleasing fictions but i have scrupulously discarded many a pithy tale and marvelous adventure whereby the drowsy ear of summer indolence might be enthralled","subset":"babb","task_type":"understanding","prediction":"the infant years of our city to introduce a thousand pleasing fictions but i have scrupulously discarded many a pithy tale and marvellous adventure whereby the drowsy ear of summer indolence might be enthralled","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":163,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-babb-sp8425-ch292520-sg0004-mc01-stu-clo-dg030.wav","answer":"and dinning market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare's light into one sacred rhythm for the devil's spite a woman's thin raucous voice carries the tune bids men rejoice","subset":"babb","task_type":"understanding","prediction":"the dinny market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare s light into one sacred rhythm for the devil s fight a woman s thin raucous voice carries the tune bids men rejoice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":164,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-babb-sp8425-ch292520-sg0013-mc02-lav-clo-dg040.wav","answer":"light green in the deeps like your eyes in sunshine winds the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel","subset":"babb","task_type":"understanding","prediction":"light green in the deeps like your eyes in sunshine why is the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":165,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8575\/Lab41-SRI-VOiCES-rm1-babb-sp8575-ch290350-sg0016-mc02-lav-clo-dg080.wav","answer":"which we apply to all parts of time whose lengths we would consider yet there may be other parts of the universe where they no more use these measures of ours than in japan they do our inches feet or miles but yet something analogous to them there must be for without some regular periodical returns","subset":"babb","task_type":"understanding","prediction":"which we apply to all parts of time whose lengths we would consider yet there may be other parts of the universe where they no more use these measures of ours than in japan they do our inches feet or miles but yet something analogous to them there must be for without some regular periodical returns","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":166,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8575\/Lab41-SRI-VOiCES-rm1-babb-sp8575-ch290351-sg0021-mc01-stu-clo-dg010.wav","answer":"and thus likewise we sometimes speak of place distance or bulk in the great inane beyond the confines of the world when we consider so much of that space as is equal to or capable to receive a body of any assigned dimensions as a cubic foot or do suppose a point in it","subset":"babb","task_type":"understanding","prediction":"and thus likewise we sometimes speak of place distance or bulk in the great innate beyond the confines of the world when we consider so much of that space as is equal to or capable to receive a body of any assigned dimensions as a cubic foot or do you suppose a point in it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":167,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8635\/Lab41-SRI-VOiCES-rm1-babb-sp8635-ch295756-sg0013-mc02-lav-clo-dg170.wav","answer":"they came to the house where they were to be fed and lodged the wood men went to bed with their clothes on but george took his off and as he turned in he found his bed was of loose straw with not a thing on it but the thread bare blank et he was to wrap him self in","subset":"babb","task_type":"understanding","prediction":"they came to the house where they were to be fed and lodged the woodmen went to bed with their clothes on but george took his off and as he turned in he found his bed was of loose straw with not a thing on it but the threadbare blanket he was to wrap himself in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":168,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8635\/Lab41-SRI-VOiCES-rm1-babb-sp8635-ch295756-sg0026-mc02-lav-clo-dg040.wav","answer":"a doub loon is a gold coin of spain worth not quite sixteen dol lars a pis tole is a small gold coin of spain worth not quite four dol lars this rough kind of life though he did not know it was to fit him for the toils and ills of war","subset":"babb","task_type":"understanding","prediction":"a doubloon is a gold coin of spain worth not quite sixteen dollars a pistole is a small gold coin of spain worth not quite four dollars this rough kind of life though he did not know it was to fit him for the toils and ills of war","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":169,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8677\/Lab41-SRI-VOiCES-rm1-babb-sp8677-ch246948-sg0037-mc02-lav-clo-dg160.wav","answer":"then will he forgive and endure and pour out his soul for the beloved who yet grope their way in doubt and passion then every man will be dear and precious to him even the worst for in him also lies an unknown yearning after the same peace wherein he rests and loves","subset":"babb","task_type":"understanding","prediction":"Then will he forgive and endure and pour out his soul for the beloved. Who yet grope their way in doubt and passion. Then every man will be dear and precious to him, even the worst for in him also lies an unknown yearning after the same peace wherein he rests and loves.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":170,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8677\/Lab41-SRI-VOiCES-rm1-babb-sp8677-ch291953-sg0010-mc02-lav-clo-dg060.wav","answer":"brave urien sleeps upon his craggy bed mountains ye mourn in vain modred whose magic song made huge plinlimmon bow his cloud topt head on dreary arvon's shore they lie smear'd with gore and ghastly pale","subset":"babb","task_type":"understanding","prediction":"brave urien sleeps upon his craggy bed mountain she mourning vain modred whose magic song made huge glendower bow his cloud topped head on dreary arvon shore they lie smeared with gore and ghastly pale","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":171,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8677\/Lab41-SRI-VOiCES-rm1-babb-sp8677-ch296078-sg0009-mc02-lav-clo-dg160.wav","answer":"when these things happened aunt florence was called in as a matter of course and she set the fractures and salved the burns and stopped the flow of sawdust and proved herself in every way a most skillful nursery surgeon and physician","subset":"babb","task_type":"understanding","prediction":"when these things happened aunt florence was called in as a matter of course and she set the fractures and salved the burns and stopped the flow of sawdust and proved herself in every way a most skillful nursery surgeon and physician","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":172,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/babb\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm1-babb-sp8713-ch296159-sg0005-mc01-stu-clo-dg010.wav","answer":"for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling","subset":"babb","task_type":"understanding","prediction":"for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":173,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0093\/Lab41-SRI-VOiCES-rm1-musi-sp0093-ch123172-sg0024-mc02-lav-clo-dg020.wav","answer":"put more on in two days keep it in a cold place in three or four days it will do to stretch on sticks hang it up in a dry cool place with as much salt as will stick to it when quite dry put it in a paper bag and hang it up","subset":"musi","task_type":"understanding","prediction":"put more on in two days keep it in a cold place in three or four days will do to stretch on sticks hang it up in a dry cool place with as much salt as will stick to it when quite dry put it in a paper bag and hang it up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":174,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm1-musi-sp0112-ch121671-sg0019-mc01-stu-clo-dg000.wav","answer":"asked the grandmother who was sitting upon her doorsteps engaged in mending sixteen pairs of stockings at your house the stranger replied it looks for all the world like a big shoe a shoe she said in surprise why yes","subset":"musi","task_type":"understanding","prediction":"asked the grandmother who was sitting upon her doorstep engaged in mending sixteen pairs of stockings that s your house the stranger replied it looks for all the world like a big shoe a shoe she said in surprise why yes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":175,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm1-musi-sp0112-ch123215-sg0025-mc01-stu-clo-dg080.wav","answer":"of tolerant wonder anne despite her affection for rusty was not especially fond of cats but missus gardner's tone annoyed her inconsequently she remembered that missus john blythe was so fond of cats that she kept as many as her husband would allow","subset":"musi","task_type":"understanding","prediction":"of tolerant wonder anne despite her affection for rusty was not especially fond of cats but mrs gardiner s tone annoyed her inconsequently she remembered that mrs john blythe was so fond of cats that she kept as many as her husband would allow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":176,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm1-musi-sp0122-ch121729-sg0022-mc02-lav-clo-dg070.wav","answer":"and devoted to the rubber industry negro one who votes your way nigger one who doesn't neighbor one who knows more about your affairs than yourself","subset":"musi","task_type":"understanding","prediction":"and devoted to the rubber industry negro one who votes your way nigger one who doesn t neighbor one who knows more about your affairs than yourself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":177,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm1-musi-sp0122-ch121730-sg0018-mc01-stu-clo-dg000.wav","answer":"pawnbroker a mercenary man to whom money is the one redeeming quality peace a mythical condition of tranquillity frequently reported from the phillipines peach a popular synonym for fair woman","subset":"musi","task_type":"understanding","prediction":"pawnbroker a mercenary man to whom money is the one redeeming quality peace a mythical condition of tranquility frequently reported from the philippines peach a popular synonym for fair woman","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":178,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0159\/Lab41-SRI-VOiCES-rm1-musi-sp0159-ch121891-sg0012-mc02-lav-clo-dg040.wav","answer":"for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature","subset":"musi","task_type":"understanding","prediction":"for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":179,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0174\/Lab41-SRI-VOiCES-rm1-musi-sp0174-ch168635-sg0002-mc01-stu-clo-dg030.wav","answer":"his sister and his sister's children had left him only a vague and far off memory which had finally almost completely vanished he had made every effort to find them and not having been able to find them he had forgotten them","subset":"musi","task_type":"understanding","prediction":"his sister and his sister's children had left him only a vague and far off memory which had finally almost completely vanished he had made every effort to find them and not having been able to find them he had forgotten them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":180,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm1-musi-sp0205-ch123882-sg0036-mc01-stu-clo-dg020.wav","answer":"bill and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely as the great swamp just this side of the bridge over the ossawippi","subset":"musi","task_type":"understanding","prediction":"bill and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely is the great swamp just this side of the bridge over the ossolipi","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":181,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm1-musi-sp0205-ch157088-sg0010-mc02-lav-clo-dg150.wav","answer":"and sat watching olaf as he mothered the half baked bannock loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range","subset":"musi","task_type":"understanding","prediction":"and sat watching olaf essie mother the half baked bannock loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":182,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0208\/Lab41-SRI-VOiCES-rm1-musi-sp0208-ch126851-sg0026-mc01-stu-clo-dg070.wav","answer":"so long as the hens lay eggs and the cow gives milk we can have omelettes and junket and there are plenty of vegetables left in the garden the winter is still a long way off don't fuss that was the trouble with sarah she would fuss","subset":"musi","task_type":"understanding","prediction":"so long as the hens lay eggs and the cow gives milk we can have omelets and junket and there are plenty of vegetables left in the garden the winter is still a long way off dont fuss that was the trouble with sarah she would fuss","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":183,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0224\/Lab41-SRI-VOiCES-rm1-musi-sp0224-ch129790-sg0006-mc02-lav-clo-dg040.wav","answer":"his mind went back over the adventure of yesterday if of yesterday it was he was clear on the matter of the easily successful raid upon the island of barbados every detail stood vividly in his memory up to the moment at which","subset":"musi","task_type":"understanding","prediction":"his mind went back over the adventure of yesterday if of yesterday it was he was clear of the matter of the easily successful raid upon the island of barbados every detail stood vividly in his memory up to the moment at which","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":184,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-musi-sp0242-ch122625-sg0006-mc01-stu-clo-dg070.wav","answer":"men too often confound them they should not be confounded appearance should not be mistaken for truth narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of christ","subset":"musi","task_type":"understanding","prediction":"Men too often confound them. They should not be confounded. Appearance should not be mistaken for truth. Narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of Christ.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":185,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0296\/Lab41-SRI-VOiCES-rm1-musi-sp0296-ch141721-sg0027-mc02-lav-clo-dg120.wav","answer":"and gave him an honourable military post in his army with a farther promise of promotion to the highest dignity but upon this express condition that he would act for the future as a soldier of honour but assur'd him at the same time","subset":"musi","task_type":"understanding","prediction":"and give him an honourable military post in his army with a farther promise of promotion to the highest dignity but upon this express condition that he would act for the future as a soldier of honour but assured him at the same time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":186,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm1-musi-sp0459-ch127521-sg0016-mc02-lav-clo-dg150.wav","answer":"hung over us like a thunder cloud and it was not only we of the cabin party who perceived the danger long john was hard at work going from group to group spending himself in good advice and as for example no man could have shown a better","subset":"musi","task_type":"understanding","prediction":"hung over us like a thundercloud and it was not only we of the cabin party who perceived the danger long john was hard at work going from group to group spending himself in good advice and as for example no man could have shown a better","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":187,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm1-musi-sp0459-ch127521-sg0018-mc01-stu-clo-dg140.wav","answer":"appeared the worst we held a council in the cabin sir said the captain if i risk another order the whole ship'll come about our ears by the run you see sir here it is i get a rough answer do i not","subset":"musi","task_type":"understanding","prediction":"appeared the worst we held a council in the cabin sir said the captain if i risk another order the whole ship will come about our ears by the run you see sir here it ends i get a rough answer do i not","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":188,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm1-musi-sp0459-ch127522-sg0016-mc01-stu-clo-dg020.wav","answer":"the rocks of the spy glass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain","subset":"musi","task_type":"understanding","prediction":"The rocks of the spyglass reechoed it a score of times. The whole troop of marsh birds rose again, darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":189,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-musi-sp0480-ch123176-sg0003-mc01-stu-clo-dg130.wav","answer":"if the room is kept perfectly still boiled custard beat an egg with a heaped tea spoonful of sugar stir it into a tea cupful of boiling milk and stir till it is thick","subset":"musi","task_type":"understanding","prediction":"if the room is kept perfectly still boiled custard beat an egg with a heaped teaspoonful of sugar stir it into a teacup full of boiling milk and stir till it is thick","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":190,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-musi-sp0480-ch126292-sg0012-mc01-stu-clo-dg020.wav","answer":"so chanticleer built a handsome carriage with four red wheels and harnessed six mice to it and then he and partlet got into the carriage and away they drove soon afterwards a cat met them and said where are you going","subset":"musi","task_type":"understanding","prediction":"so chanticleer built a handsome carriage with four red wheels and harnessed six mice to it and then he and partlick got into the carriage and away they drove soon afterwards a cat met them and said where are you going","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":191,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-musi-sp0480-ch127525-sg0009-mc01-stu-clo-dg180.wav","answer":"returned the captain we must keep upstream you see sir he went on if once we dropped to leeward of the landing place it's hard to say where we should get ashore","subset":"musi","task_type":"understanding","prediction":"returned the captain we must keep up stream you see sir he went on if once we drop to the leeward of the landing place it is hard to say where we should get ashore","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":192,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm1-musi-sp0492-ch131899-sg0008-mc01-stu-clo-dg010.wav","answer":"he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation","subset":"musi","task_type":"understanding","prediction":"he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":193,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm1-musi-sp0636-ch128310-sg0029-mc02-lav-clo-dg120.wav","answer":"growling over it like any four footed inmate of a menagerie towards nine o'clock he smoothed his ruffled aspect and presenting as respectable and business like an exterior as he could overlay his natural self with issued forth to the occupation of the day","subset":"musi","task_type":"understanding","prediction":"growling over it like any four footed inmate of a menagerie towards nine o clock he smoothed his ruffled aspect and presenting as respectable and business like an exterior as he could overlay his natural self with issued forth to the occupation of the day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":194,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm1-musi-sp0636-ch128331-sg0021-mc01-stu-clo-dg150.wav","answer":"and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth","subset":"musi","task_type":"understanding","prediction":"and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":195,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm1-musi-sp0637-ch127579-sg0010-mc02-lav-clo-dg070.wav","answer":"induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object","subset":"musi","task_type":"understanding","prediction":"induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":196,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm1-musi-sp0637-ch127595-sg0003-mc02-lav-clo-dg140.wav","answer":"would commence a low dismal and monotonous chant accompanying the voice with the instrumental melody produced by two small half rotten sticks tapped slowly together a pair of which were held in the hands of each person present","subset":"musi","task_type":"understanding","prediction":"would commence a low dismal and monotonous chant accompanying the voice with the instrumental melody produced by two small half rotten sticks tapped slowly together a pair of which were held in the hands of each person present","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":197,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0652\/Lab41-SRI-VOiCES-rm1-musi-sp0652-ch129742-sg0015-mc02-lav-clo-dg170.wav","answer":"put the pulp into a basin with two ounces of melted butter two tablespoonfuls of lemon juice half a pound of chestnuts boiled and grated and seasoning of salt and white pepper to taste","subset":"musi","task_type":"understanding","prediction":"put the pulp into a basin with two ounces of melted butter two tablespoonfuls of lemon juice half a pound of chestnuts boiled and grated and seasoning of salt and white pepper to taste","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":198,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0882\/Lab41-SRI-VOiCES-rm1-musi-sp0882-ch123266-sg0029-mc02-lav-clo-dg000.wav","answer":"i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay","subset":"musi","task_type":"understanding","prediction":"i felt melancholy under this savage aspect of nature and my thoughts went away to the cheerful scenes i had left in the far south we had to cross a few narrow fiords and at last quite a wide gulf the tide then high allowed us to pass over without delay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":199,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0948\/Lab41-SRI-VOiCES-rm1-musi-sp0948-ch132705-sg0009-mc01-stu-clo-dg090.wav","answer":"a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said","subset":"musi","task_type":"understanding","prediction":"a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":200,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm1-musi-sp0949-ch134657-sg0022-mc02-lav-clo-dg000.wav","answer":"who labored to disguise the truths of facts and to pervert the sense of the laws he sometimes forgot the gravity of his station asked indiscreet or unseasonable questions and betrayed by the loudness of his voice and the agitation of his body the earnest vehemence","subset":"musi","task_type":"understanding","prediction":"who labored to disguise the truth of facts and to pervert the sense of the laws he sometimes forgot the grabby of a station asked indiscreet or unseasonable questions and betrayed by the loudness of his voice and the agitation of his body the earnest venoms","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":201,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm1-musi-sp0949-ch138545-sg0032-mc02-lav-clo-dg120.wav","answer":"this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown","subset":"musi","task_type":"understanding","prediction":"this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":202,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm1-musi-sp0949-ch162667-sg0034-mc02-lav-clo-dg020.wav","answer":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","subset":"musi","task_type":"understanding","prediction":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":203,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1052\/Lab41-SRI-VOiCES-rm1-musi-sp1052-ch139307-sg0027-mc01-stu-clo-dg160.wav","answer":"he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what council could it be that gathered there","subset":"musi","task_type":"understanding","prediction":"he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what counsel could it be that gathered there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":204,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm1-musi-sp1066-ch005330-sg0006-mc02-lav-clo-dg110.wav","answer":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune","subset":"musi","task_type":"understanding","prediction":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":205,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm1-musi-sp1066-ch103481-sg0002-mc01-stu-clo-dg080.wav","answer":"and hope looked out again from tired eyes down where the white point gardens drank the sun and rippled to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a taunt","subset":"musi","task_type":"understanding","prediction":"and hope looked out again from tired eyes down where the white point gardens strike the sun and ripple to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a taunt","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":206,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm1-musi-sp1112-ch001043-sg0000-mc02-lav-clo-dg010.wav","answer":"chapter seven a sprained ankle i was panic stricken as i ran along the corridor i was confident that the mysterious intruder and probable murderer had been found and that he lay dead or dying at the foot of the chute i got down the staircase somehow and through the kitchen to the basement stairs","subset":"musi","task_type":"understanding","prediction":"chapter seven a sprained ankle i was panic stricken as i ran along the corridor i was confident that the mysterious intruder and probable murderer had been found and that he lay dead or dying at the foot of the chute i got down the staircase somehow and through the kitchen to the basement stairs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":207,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm1-musi-sp1112-ch001043-sg0006-mc02-lav-clo-dg070.wav","answer":"but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cozy","subset":"musi","task_type":"understanding","prediction":"but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cosy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":208,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm1-musi-sp1112-ch128138-sg0000-mc01-stu-clo-dg120.wav","answer":"mister ian hamilton's ballad of hadji is undeniably clever hadji is a wonderful arab horse that a reckless hunter rides to death in the pursuit of a wild boar and the moral of the poem for there is a moral","subset":"musi","task_type":"understanding","prediction":"Mr. Ian Hamiltons Ballad of Hadji is undeniably clever. Hadji is a wonderful Arab horse that a reckless hunter rides to death in the pursuit of a wild boar. And the moral of the poem for there is a moral.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":209,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm1-musi-sp1116-ch132851-sg0021-mc01-stu-clo-dg020.wav","answer":"while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her","subset":"musi","task_type":"understanding","prediction":"while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":210,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm1-musi-sp1116-ch137572-sg0003-mc01-stu-clo-dg060.wav","answer":"when one has received the promise of something greatly desired but must wait awhile before its delivery the happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight","subset":"musi","task_type":"understanding","prediction":"when one has received the promise of something greatly desired but must wait a while before its delivery the happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":211,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm1-musi-sp1116-ch137572-sg0048-mc01-stu-clo-dg070.wav","answer":"but instead a complete trust in each other one who prides himself or herself on having to be handled with gloves has a great deal of growing up to do in order to be able to be an active partner in the marriage cry babying is no more helpful in marriage than in business or social life","subset":"musi","task_type":"understanding","prediction":"but instead a complete trust in each other one who prides himself or herself on having to be handled with gloves has a great deal of growing up to do in order to be able to be an active partner in the marriage pry babying is no more helpful in marriage than in business or social life","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":212,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1121\/Lab41-SRI-VOiCES-rm1-musi-sp1121-ch176698-sg0034-mc02-lav-clo-dg100.wav","answer":"and tossed her head indignantly but slowly as they went they came within sight of the house at last with its quaint gables and many latticed windows and the blue smoke curling up from its twisted chimneys","subset":"musi","task_type":"understanding","prediction":"and tossed her head indignantly but slowly as they wept they came within sight of the house at last with its quaint gables and many lacquered windows and the blue smoke curling up from its twisted chimneys","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":213,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm1-musi-sp1160-ch134674-sg0003-mc01-stu-clo-dg110.wav","answer":"and dejected countenances and without daring to complain of the murder of their king they affirmed with solemn oaths that the late invasion was the crime of some irregular robbers which the public council of the nation condemned and abhorred","subset":"musi","task_type":"understanding","prediction":"and dejected countenances and without daring to complain of the murder of their king they affirmed with solemn oaths that the late invasion was the crime of some irregular robbers which the public council of the nation condemned and abhorred","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":214,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm1-musi-sp1160-ch139727-sg0005-mc01-stu-clo-dg090.wav","answer":"which would be of more use to them we parted he going to philadelphia and i to boston in returning i met at new york with the votes of the assembly by which it appear'd that notwithstanding his promise to me he and the house were already in high contention","subset":"musi","task_type":"understanding","prediction":"which would be of more use to them we parted he going to philadelphia and i to boston in returning i met at new york with the votes of the assembly by which it appeared that notwithstanding his promise to me he and the house were already in high contention","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":215,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm1-musi-sp1160-ch139730-sg0007-mc02-lav-clo-dg000.wav","answer":"should assist in comprehending the following he procur'd an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely form'd by instrument makers his lectures","subset":"musi","task_type":"understanding","prediction":"should assist in comprehending the following he procured an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely formed by instrument makers his lectures","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":216,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1259\/Lab41-SRI-VOiCES-rm1-musi-sp1259-ch027120-sg0012-mc01-stu-clo-dg000.wav","answer":"and indulged their mirth for some time at the expense of their dear friend's vulgar relations with a renewal of tenderness however they returned to her room on leaving the dining parlour and sat with her till summoned to coffee she was still very poorly and elizabeth would not quit her at all","subset":"musi","task_type":"understanding","prediction":"and indulged their mirth for some time at the expense of their dear friend s wild dilations with a renewal of tenderness however they returned to her room on leaving the dining parlor and sat with her till summoned to coffee she was still very poorly and elizabeth would not question her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":217,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1271\/Lab41-SRI-VOiCES-rm1-musi-sp1271-ch133279-sg0006-mc01-stu-clo-dg150.wav","answer":"which things that are supremely good in their very nature are wont to excite in the mind and i approve of it more from a recollection of the evils it prevents than from a consideration of the advantages it ensures","subset":"musi","task_type":"understanding","prediction":"which things that are supremely good in their very nature are wont to excite in the mind and i approve of it more from a recollection of the evils it prevents than from a consideration of the advantages it ensures","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":218,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm1-musi-sp1272-ch141231-sg0012-mc01-stu-clo-dg050.wav","answer":"i'm here because the matter is of utmost importance and brandd is the one i must see now stand aside","subset":"musi","task_type":"understanding","prediction":"i am here because the matter is of utmost importance and brand is the one i must see now stand aside","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":219,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm1-musi-sp1272-ch141231-sg0023-mc02-lav-clo-dg160.wav","answer":"the strength that enables someone in a trance to hold his body stiff and unsupported except at two points the head and heels","subset":"musi","task_type":"understanding","prediction":"The strength that enables someone in a trance to hold his body stiff and unsupported. Except at two points. The head and heels.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":220,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm1-musi-sp1335-ch163935-sg0005-mc02-lav-clo-dg110.wav","answer":"then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander","subset":"musi","task_type":"understanding","prediction":"then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":221,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm1-musi-sp1383-ch130532-sg0018-mc01-stu-clo-dg020.wav","answer":"i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions","subset":"musi","task_type":"understanding","prediction":"i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":222,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm1-musi-sp1383-ch130532-sg0027-mc02-lav-clo-dg010.wav","answer":"i speak the secret feeling of this company i speak what i know when i say i speak wholly without authority i speak with feeling upon this point","subset":"musi","task_type":"understanding","prediction":"i speak the secret feeling of this company i speak what i know when i say i speak wholly without authority i speak with feeling upon this point","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":223,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm1-musi-sp1392-ch140654-sg0008-mc02-lav-clo-dg160.wav","answer":"company with fools as with an enemy is always painful company with the wise is pleasure","subset":"musi","task_type":"understanding","prediction":"company with fools as with an enemy is always painful company with the wise is pleasure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":224,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-musi-sp1472-ch142848-sg0010-mc01-stu-clo-dg160.wav","answer":"each labourer is able to gather from four to ten or fifteen pounds a day when the trees attain to six or seven years of age the produce becomes so inferior that they are removed to make room for a fresh succession or they are cut down to allow of numerous young shoots","subset":"musi","task_type":"understanding","prediction":"each labourer is able to gather from four to ten or fifteen pounds a day when the trees attain to six or seven years of age the produce becomes so inferior that they are removed to make room for a fresh succession for they are cut down to allow of numerous young shoots","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":225,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-musi-sp1472-ch285314-sg0011-mc01-stu-clo-dg040.wav","answer":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up","subset":"musi","task_type":"understanding","prediction":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":226,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-musi-sp1472-ch285314-sg0011-mc02-lav-clo-dg040.wav","answer":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up","subset":"musi","task_type":"understanding","prediction":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":227,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1607\/Lab41-SRI-VOiCES-rm1-musi-sp1607-ch149245-sg0016-mc01-stu-clo-dg100.wav","answer":"which respect for his immense power prevented them from fully expressing after repeatedly vowing fidelity to both parties and repeatedly betraying both he began to think that he should best provide for his safety","subset":"musi","task_type":"understanding","prediction":"which respect for his immense power prevented them from fully expressing after repeatedly vowing fidelity to both parties and repeatedly betraying both he began to think that he should best provide for his safety","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":228,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1841\/Lab41-SRI-VOiCES-rm1-musi-sp1841-ch179183-sg0017-mc01-stu-clo-dg110.wav","answer":"now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful","subset":"musi","task_type":"understanding","prediction":"now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":229,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1851\/Lab41-SRI-VOiCES-rm1-musi-sp1851-ch151817-sg0017-mc01-stu-clo-dg120.wav","answer":"was there anything so very absurd in his method of reasoning or of drawing a deduction still that exaltation did not prevent uncle phaeton from taking all essential precautions and it was only when an especially secure landing place was sighted","subset":"musi","task_type":"understanding","prediction":"was there anything so very absurd in his method of reasoning or of drawing a deduction still that exultation did not prevent uncle phaeton from taking all essential precautions and it was only when an especially secure landing place was sighted","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":230,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm1-musi-sp1867-ch154071-sg0011-mc01-stu-clo-dg120.wav","answer":"peering through the slit between the drawn curtains which sheltered him from being observed at his spying when he called out softly the sound brought gregg with one long leap out of the chair where he was sleeping to the window there could be no shadow of a doubt about it","subset":"musi","task_type":"understanding","prediction":"peering through the slit between the drawn curtains which sheltered him from being observed at his spying when he called out softly the sound brought gregg with one long leap out of the chair where he was sleeping to the window there could be no shadow of a doubt about it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":231,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm1-musi-sp1874-ch089898-sg0006-mc01-stu-clo-dg010.wav","answer":"whom wilfrid as his clerk attended to the place where he was to be beheaded being very desirous though the bishop strongly opposed it to die with him but the executioners understanding that he was a stranger and of the english nation spared him and would not put him to death with his bishop","subset":"musi","task_type":"understanding","prediction":"and wilfrid as his clerk attended to the place where he was to be beheaded being very desirous though the bishop strongly opposed it to die with him but the executioners understanding that he was a stranger and of the english nation spared him and would not put him to death with his bishop","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":232,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm1-musi-sp1961-ch149739-sg0018-mc02-lav-clo-dg070.wav","answer":"he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor","subset":"musi","task_type":"understanding","prediction":"he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":233,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1963\/Lab41-SRI-VOiCES-rm1-musi-sp1963-ch142776-sg0013-mc02-lav-clo-dg060.wav","answer":"a little nutmeg one teaspoonful of flour one pint of cream one pint of milk forcemeat balls mace salt and pepper to taste bread crumbs one egg two quarts of water mode","subset":"musi","task_type":"understanding","prediction":"a little nutmeg one teaspoonful of flour one pint of cream one pint of milk forcemeat balls mace salt and pepper to taste bread crumbs one egg two quarts of water melt","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":234,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1963\/Lab41-SRI-VOiCES-rm1-musi-sp1963-ch147036-sg0034-mc02-lav-clo-dg050.wav","answer":"milburgh had gone too far tarling saw his face lengthen and the look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath the confession of odette rider","subset":"musi","task_type":"understanding","prediction":"milburgh had gone too far tarling saw his face lengthen and a look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath the confession of odad rider","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":235,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm1-musi-sp1970-ch010594-sg0035-mc01-stu-clo-dg140.wav","answer":"but i heard her voice it was a lady's voice and what she wore beautiful jewels jewels you said she was poor so she declared herself but she had on her neck under her coat","subset":"musi","task_type":"understanding","prediction":"but i heard her voice it was a lady's voice and what she wore beautiful jewels jewels you said she was poor so she declared herself but she had on her neck under her coat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":236,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139355-sg0027-mc02-lav-clo-dg180.wav","answer":"but after all why not these indians are no longer the indians of days gone by instead of being clothed in the national fashion with a frontlet of macaw feathers bow and blow tube have they not adopted the american costume of white cotton trousers","subset":"musi","task_type":"understanding","prediction":"but after all why not these indians are no longer the indians of days gone by instead of being clothed in the national fashion with a frontlet of macaw feathers bow and blow tube have they not adopted the american costume of white cotton trousers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":237,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139355-sg0028-mc01-stu-clo-dg120.wav","answer":"at present the capital of the upper amazon it began as a simple mission founded by the portuguese carmelites about sixteen ninety two and afterward acquired by the jesuit missionaries from the beginning","subset":"musi","task_type":"understanding","prediction":"at present the capital of the upper amazon it began as a simple mission founded by the portuguese carmelites about sixteen ninety two and afterward acquired by the jesuit missionaries from the beginning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":238,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139356-sg0000-mc01-stu-clo-dg160.wav","answer":"the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon","subset":"musi","task_type":"understanding","prediction":"the continued descent on the evening of the fifth of july the atmosphere had been oppressive since the morning and threatened approaching storms large bats of ruddy color skimmed with their huge wings the current of the amazon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":239,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm1-musi-sp2012-ch139358-sg0018-mc02-lav-clo-dg130.wav","answer":"it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries","subset":"musi","task_type":"understanding","prediction":"it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":240,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2060\/Lab41-SRI-VOiCES-rm1-musi-sp2060-ch147963-sg0002-mc01-stu-clo-dg020.wav","answer":"ambrosch come along by the cornfield yesterday where i was at work and showed me three prairie dogs he'd shot he asked me if they was good to eat i spit and made a face and took on to scare him but he just looked like he was smarter'n me and put em back in his sack and walked off","subset":"musi","task_type":"understanding","prediction":"ambrose come on by the cornfield yesterday where i was at work he showed me three prairie dogs he d shot he asked me if they was good to eat i spit and made a face and took on to scare him but he just looked like he was smarter i mean and put em back in his sack and walked off","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":241,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2060\/Lab41-SRI-VOiCES-rm1-musi-sp2060-ch150855-sg0011-mc02-lav-clo-dg130.wav","answer":"there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie's bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy","subset":"musi","task_type":"understanding","prediction":"there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie s bewilderment was now a member of dubwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":242,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2060\/Lab41-SRI-VOiCES-rm1-musi-sp2060-ch150855-sg0029-mc02-lav-clo-dg010.wav","answer":"it's just the kind of thing poor mister ansell would say well i'm brutal i believe it does varden good to have his ears pulled now and then and i don't care whether they pull them in play or not boys ought to rough it or they never grow up into men and your mother would have agreed with me","subset":"musi","task_type":"understanding","prediction":"its just the kind of thing poor mr ansell would say well i am brutal i believe it does a boy good to have his ears pulled now and then and i don't care whether they pull them in play or not boys ought to rough it or they never grow up into men and your mother would have agreed with me","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":243,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2093\/Lab41-SRI-VOiCES-rm1-musi-sp2093-ch143271-sg0020-mc01-stu-clo-dg040.wav","answer":"we'll go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply","subset":"musi","task_type":"understanding","prediction":"we will go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":244,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm1-musi-sp2110-ch161100-sg0030-mc01-stu-clo-dg110.wav","answer":"he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died","subset":"musi","task_type":"understanding","prediction":"he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":245,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm1-musi-sp2110-ch161101-sg0013-mc02-lav-clo-dg080.wav","answer":"no expression neither piano nor forte but goes on always the same but all that signifies nothing to me the organ is nevertheless the king of instruments augsburg october seventeenth","subset":"musi","task_type":"understanding","prediction":"no expression neither piano nor forte but goes on always the same but all that signifies nothing to me the organ is nevertheless the king of instruments augsburg october seventeen","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":246,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2149\/Lab41-SRI-VOiCES-rm1-musi-sp2149-ch036146-sg0008-mc01-stu-clo-dg070.wav","answer":"what life and action and heroism there was to him in the multitudinous roar of the forest and what an eternity of existence in the monologue of the river which brawled far far below him over its wide stony bed how the river sparkled and danced and went on","subset":"musi","task_type":"understanding","prediction":"what life and action and heroism there was to him in the multitudinous roar of the forest and what an eternity of existence in the monologue of the river which brawled far far below him over its white stony bed how the river sparkled and danced and went on","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":247,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm1-musi-sp2156-ch082458-sg0026-mc02-lav-clo-dg000.wav","answer":"now bell ran out of the door and received a bullet from his own pistol the body of bell tumbled down the back stairs falling on the jailer a german by the name of geiss who was sitting at the foot of the stairs","subset":"musi","task_type":"understanding","prediction":"Now, Bell ran out of the door and received a bullet from his own pistol. The body of Bell tumbled down the back stairs, falling on the jailer, a German by the name of Geiss, who was sitting at the foot of the stairs.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":248,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2269\/Lab41-SRI-VOiCES-rm1-musi-sp2269-ch088761-sg0004-mc01-stu-clo-dg100.wav","answer":"and i wanted to observe him more closely and hear what he talked about but i received orders to attend evensong at the parish church and to haunt the mind of lena houghton as we passed down the high street","subset":"musi","task_type":"understanding","prediction":"and i wanted to observe him more closely and hear what he talked about but i received orders to attend evensong at the parish church and to haunt the mind of lena houghton as we passed down the high street","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":249,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2269\/Lab41-SRI-VOiCES-rm1-musi-sp2269-ch088761-sg0014-mc02-lav-clo-dg000.wav","answer":"though she stood and sat and knelt and curtseyed and articulated words her thoughts were entirely absorbed in me i crowded out the magnificat with a picture of zaluski and gertrude morley","subset":"musi","task_type":"understanding","prediction":"though she stood and sat and knelt and curtseyed and articulated words her thoughts were entirely absorbed in me i crowded out the magnificat with a picture of zaluski and gertrude morley","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":250,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm1-musi-sp2289-ch152254-sg0005-mc02-lav-clo-dg010.wav","answer":"but genseric sternly refused never he said shall i go back to spain until i am master of africa then cried boniface i will drive you back soon afterwards there was a battle between the romans and vandals and the romans were defeated","subset":"musi","task_type":"understanding","prediction":"but genseric sternly refused never he said shall i go back to spain until i am master of africa then cried longface i will drive you back soon after there was a battle between romans and vandals and the romans were defeated","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":251,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm1-musi-sp2289-ch152257-sg0001-mc01-stu-clo-dg130.wav","answer":"but he was determined to go even though he should have to walk every step of the road and live on fruits that he could gather by the way he was a bright clever boy who had spent his life hitherto in a village but was now eager to go out into the world","subset":"musi","task_type":"understanding","prediction":"but he was determined to go even though he should have to walk every step of the road and live on fruits that he could gather by the way he was a bright clever boy who had spent his life hitherto in a village but was now eager to go out into the world","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":252,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm1-musi-sp2289-ch152258-sg0007-mc02-lav-clo-dg160.wav","answer":"and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work intrusted to him and","subset":"musi","task_type":"understanding","prediction":"and faithfully paid over to the owners of the goods the money he had received mohammed had no school education he could neither read nor write but he was not ignorant he knew well how to do the work entrusted to him and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":253,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm1-musi-sp2412-ch153948-sg0006-mc02-lav-clo-dg100.wav","answer":"i was to see the sheep not necessarily close at hand nor to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet","subset":"musi","task_type":"understanding","prediction":"i was to see the sheep not necessarily close at hand or to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":254,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2532\/Lab41-SRI-VOiCES-rm1-musi-sp2532-ch163402-sg0000-mc02-lav-clo-dg000.wav","answer":"because tom said we got to have some light to see how to dig by and a lantern makes too much and might get us into trouble what we must have was a lot of them rotten chunks that's called fox fire and just makes a soft kind of a glow when you lay them in a dark place","subset":"musi","task_type":"understanding","prediction":"because tom said we got to have some light to see how to dig by and a lantern makes too much and might get us into trouble what we must have was a lot of them rock chunks that is called fox fire and just makes a soft kind of a glow when you lay them in a dark place","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":255,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm1-musi-sp2758-ch086039-sg0011-mc01-stu-clo-dg020.wav","answer":"and after she had cleaned her house and fed her chickens and put everything in its place again she bent over the kitchen table and the sound of her big scissors might be heard snip snap as far as the garden her husband could not see anything to snip at","subset":"musi","task_type":"understanding","prediction":"and after she had cleaned her house and fed her chickens and put everything in its place again she bent over the kitchen table and the sound of her big scissors might be heard snip snap as far as the garden her husband could not see anything to snip at","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":256,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm1-musi-sp2758-ch161217-sg0015-mc01-stu-clo-dg100.wav","answer":"aged hideous and also lame which is evidently meant to indicate the slow and halting march of destiny which they controlled painters and sculptors on the other hand depicted them as beautiful maidens of a grave but kindly aspect","subset":"musi","task_type":"understanding","prediction":"Aged, hideous, and also lame, which is evidently meant to indicate the slow and halting march of destiny, which they control painters and sculptors, on the other hand, depicted them as beautiful maidens of a grave but kindly aspect","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":257,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm1-musi-sp2803-ch154320-sg0003-mc01-stu-clo-dg060.wav","answer":"their minds were so distracted at this change of route as to be quite unhinged","subset":"musi","task_type":"understanding","prediction":"their minds were so distracted at this change of route as to be quite unhinged","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":258,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm1-musi-sp2911-ch015045-sg0022-mc01-stu-clo-dg110.wav","answer":"and as the voyager passed some wooded point or thicket covered island the whistling of a stone headed arrow proclaimed perhaps the presence of these fierce marauders at montreal there was no human life save during a brief space in early summer","subset":"musi","task_type":"understanding","prediction":"and as the voyager passed some wooded point or thicket covered island the whistling of a stone headed arrow proclaimed perhaps the presence of these fierce marauders at montreal there was no human life saved during a brief space in early summer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":259,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm1-musi-sp3446-ch144019-sg0006-mc01-stu-clo-dg080.wav","answer":"preceded beche de mer english beche de mer was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose beche de mer english is a splendid argument for the esperanto enthusiasts","subset":"musi","task_type":"understanding","prediction":"preceded bestumair english bestumair was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose bestumair english is a splendid argument for the esperanto enthusiasts","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":260,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm1-musi-sp3483-ch174132-sg0004-mc01-stu-clo-dg120.wav","answer":"by writing down an account of them to the best of my ability though should this my diary ever be read when i am gone the readers will but shake their heads and be the more convinced that i was mad this house how ancient it is","subset":"musi","task_type":"understanding","prediction":"by writing down an account of them to the best of my ability though should this my diary ever be read when i am gone the readers will but shake their heads and be the more convinced that i was mad this house how ancient it is","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":261,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm1-musi-sp3483-ch174132-sg0010-mc01-stu-clo-dg000.wav","answer":"but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study","subset":"musi","task_type":"understanding","prediction":"but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":262,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm1-musi-sp3549-ch171171-sg0024-mc02-lav-clo-dg080.wav","answer":"and this in hopes that they should be able to proceed so far as to rise from under ground in a safe place and by that means escape but when they came to make the experiment they were disappointed of their hope for the miners could make but small progress","subset":"musi","task_type":"understanding","prediction":"and this in hopes that they should be able to proceed so far as to rise from under ground in a safe place and by that means escape but when they came to make the experiment they were disappointed of their hope for the miners could make but small progress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":263,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm1-musi-sp3549-ch173591-sg0001-mc01-stu-clo-dg090.wav","answer":"but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots","subset":"musi","task_type":"understanding","prediction":"but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":264,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm1-musi-sp3835-ch178028-sg0013-mc02-lav-clo-dg120.wav","answer":"had suddenly taken a very large dose of the drug and had died in agony before assistance could be rendered her it was said that prince vasili and the old count had turned upon the italian but the latter had produced such letters from the unfortunate deceased that they had immediately let the matter drop","subset":"musi","task_type":"understanding","prediction":"had suddenly taken a very large dose of the drug and had died in agony before assistance could be rendered her it was said that prince vasili and the old count had turned upon the italian but the latter had produced such letters from the unfortunate deceased that they had immediately let the matter drop","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":265,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm1-musi-sp3835-ch178029-sg0008-mc02-lav-clo-dg060.wav","answer":"which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire","subset":"musi","task_type":"understanding","prediction":"which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked gaining time colonel i always require it replied danver conceal nothing from me i wish to know absolutely how things are sire","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":266,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp3989\/Lab41-SRI-VOiCES-rm1-musi-sp3989-ch182389-sg0005-mc02-lav-clo-dg150.wav","answer":"gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mister rabbit the grandfather a thousand times removed of peter rabbit was always getting into trouble yes sir old mister rabbit was always getting into trouble","subset":"musi","task_type":"understanding","prediction":"gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mr rabbit the grandfather a thousand times removed of peter rabbit was always getting in the trouble yes sir old mr rabbit was always getting in the trouble","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":267,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp3994\/Lab41-SRI-VOiCES-rm1-musi-sp3994-ch011512-sg0017-mc02-lav-clo-dg130.wav","answer":"the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved","subset":"musi","task_type":"understanding","prediction":"the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":268,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4010\/Lab41-SRI-VOiCES-rm1-musi-sp4010-ch010801-sg0011-mc02-lav-clo-dg070.wav","answer":"and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operations of the spiritual as of the physical world are simply a turning again to the source","subset":"musi","task_type":"understanding","prediction":"and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operation of the spiritual as of the physical world are simply a turning again to the source","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":269,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-musi-sp4014-ch186176-sg0020-mc02-lav-clo-dg140.wav","answer":"well i'll cover the battery room said slim ignoring jerry's remark let's see lieutenant mackinson then suggested joe and they went to find the young officer who was convalescing from his encounter with the spy when he had approved the plan they got the o k of the captain","subset":"musi","task_type":"understanding","prediction":"well i ll come in the band room said slant ignoring jerry s remark let s see lieutenant mackinson then suggested joe and they want to find the young officer who is convalescing from his encounter with the spy when he had approved the plan they got the o k of the captain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":270,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4110\/Lab41-SRI-VOiCES-rm1-musi-sp4110-ch011535-sg0002-mc01-stu-clo-dg130.wav","answer":"as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming","subset":"musi","task_type":"understanding","prediction":"as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":271,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4116\/Lab41-SRI-VOiCES-rm1-musi-sp4116-ch003582-sg0023-mc01-stu-clo-dg070.wav","answer":"how could you don't mind it polly whispered jasper twasn't her fault phronsie said missus whitney smilingly stooping over the child would you like to see a little pussy i have for you but the chubby face didn't look up brightly as usual","subset":"musi","task_type":"understanding","prediction":"how could you dont mind it polly whispered jasper twasn t her fault phronsie said mrs whitney smilingly stooping over the child would you like to see a little pussy i have for you but the chubby face did n t look up brightly as usual","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":272,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4116\/Lab41-SRI-VOiCES-rm1-musi-sp4116-ch013256-sg0010-mc02-lav-clo-dg020.wav","answer":"the girls in the carriage were smitten into helpless astonishment the saloon keeper had come to the door of the saloon and was standing there looking on with his hands on his hips and the rectangle from its windows its saloon steps its filthy sidewalk gutter and roadway paused","subset":"musi","task_type":"understanding","prediction":"the girls in the carriage were smitten into helpless astonishment the saloon keeper had come to the door of the saloon and was standing there looking on with his hands on his hips and the rectangle from its windows its saloon steps its filthy sidewalk gutter and roadway paused","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":273,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4160\/Lab41-SRI-VOiCES-rm1-musi-sp4160-ch011549-sg0006-mc02-lav-clo-dg000.wav","answer":"he came to the window and looked in at her are you coming to see priscilla he said lady throckmorton said i might she answered the warmth in her face chilled by his unenthusiastic though kindly tone she did not know what a struggle it cost him to face her thus carelessly all at once","subset":"musi","task_type":"understanding","prediction":"he came to the window and looked in at her are you coming to see priscilla he said lady throckmorton said i might she answered the warmth in her face chilled by his unenthusiastic though kindly tone she did not know what a struggle it cost him to face her thus carelessly all at once","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":274,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4331\/Lab41-SRI-VOiCES-rm1-musi-sp4331-ch057180-sg0006-mc02-lav-clo-dg020.wav","answer":"i haven't got any pastors and masters the duchess suggested lord rufford i thought all that kind of nonsense was over said arabella i believe a great deal is over you can do many things that your mother and grandmother couldn't do but absolute freedom","subset":"musi","task_type":"understanding","prediction":"i haven got any pastors and masters the duchess suggested lord rufford i thought all that kind of nonsense was over said arabella i believe a great deal is over you can do many things that your mother and grandmother couldnt do but absolute freedom","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":275,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm1-musi-sp4438-ch052195-sg0014-mc01-stu-clo-dg090.wav","answer":"and whether it had filtered down from above and was all right it wouldn't do any harm to try it he decided by the time they had reached the sidewalk and he swung behind ruth and took up his station on the outside then the other problem presented itself","subset":"musi","task_type":"understanding","prediction":"and whether it had filtered down from above and was all right it wouldn't do any harm to try it he decided by the time they had reached the sidewalk and he swung behind ruth and took up his station on the outside then the other problem presented itself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":276,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm1-musi-sp4535-ch279852-sg0008-mc01-stu-clo-dg120.wav","answer":"i'll let a bullet go smack into the first man that makes a move he shouldn't here was a man they couldn't talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later","subset":"musi","task_type":"understanding","prediction":"i ll let a bullet go smack into the first man that makes a move he shouldn t here was a man they couldn t talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":277,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm1-musi-sp4535-ch279856-sg0032-mc02-lav-clo-dg100.wav","answer":"through each settlement he walked star quietly but always ready to throw himself forward dig his heels into the horse's flanks and race away an hour passed two hours three hours they pressed northward steadily sometimes at a walk but usually at a comfortable steady trot","subset":"musi","task_type":"understanding","prediction":"Through each settlement, he walked stark, quietly. But always ready to throw himself forward. Dig his heels into the horse's flanks and race away. An hour passed,2 hours,3 hours. They pressed northward steadily, sometimes at a walk, usually at a comfortable, steady trot.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":278,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4590\/Lab41-SRI-VOiCES-rm1-musi-sp4590-ch018005-sg0052-mc02-lav-clo-dg120.wav","answer":"at last the labourers entirely declined to go on unless they were guarded by an iron entrenchment of course it is difficult to work a railway under these conditions and until we found an enthusiastic sportsman to get rid of these lions our enterprise was seriously hindered","subset":"musi","task_type":"understanding","prediction":"at last the laborers entirely declined to go on unless they were guarded by an iron entrenchment of course it is difficult to work a railway under these conditions and until we found an enthusiastic sportsman to get rid of these lions our enterprise was seriously hindered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":279,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4744\/Lab41-SRI-VOiCES-rm1-musi-sp4744-ch004158-sg0009-mc02-lav-clo-dg110.wav","answer":"all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims","subset":"musi","task_type":"understanding","prediction":"all remedies were useless this was the yellow fever the disorder spread alarm and confusion throughout the city on an average more than four hundred died daily in the midst of disorder and confusion death heaped victims on victims","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":280,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm1-musi-sp4839-ch015307-sg0003-mc01-stu-clo-dg050.wav","answer":"and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at treviso when emperor maximilian's commissioner presented himself in order to take possession of it","subset":"musi","task_type":"understanding","prediction":"and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor vanyadello and his allies of cambrai but at trevisa when emperor maximilian s commissioner presented himself in order to take possession of it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":281,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm1-musi-sp4848-ch029108-sg0034-mc02-lav-clo-dg040.wav","answer":"a spectacle of inconceivable sublimity so don't you see we've got the rail road to fall back on and in the meantime what are we worrying about that two hundred thousand dollars appropriation for that's all right","subset":"musi","task_type":"understanding","prediction":"the spectacle of inconceivable solemnity so don t see we ve got the railroad to fall back on and in the meantime what are we worrying about that two hundred thousand dollar appropriation for that s all right","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":282,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm1-musi-sp4848-ch101836-sg0017-mc01-stu-clo-dg060.wav","answer":"the kindness you showed me on a former day so mvoo laana sat down simba kongway went away but soon returned with some game he had caught and then he brought some fire and the young man cooked the game and ate it","subset":"musi","task_type":"understanding","prediction":"the kindness you showed me on a former day so magoulanes sat down simba conway went away but soon returned with some game he had caught and then he brought some fire and the young man cooked the game and ate it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":283,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4859\/Lab41-SRI-VOiCES-rm1-musi-sp4859-ch022176-sg0008-mc02-lav-clo-dg110.wav","answer":"and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman","subset":"musi","task_type":"understanding","prediction":"and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":284,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4957\/Lab41-SRI-VOiCES-rm1-musi-sp4957-ch023295-sg0011-mc01-stu-clo-dg120.wav","answer":"without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sandford interrupted the menace prepared for utterance saying and you still mean i suppose to make mister rushbrook your heir","subset":"musi","task_type":"understanding","prediction":"without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sanford interrupted the menace prepared for utterance saying and you still mean i suppose to make mr rushbrook your heir","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":285,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp4957\/Lab41-SRI-VOiCES-rm1-musi-sp4957-ch023295-sg0026-mc01-stu-clo-dg130.wav","answer":"it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you","subset":"musi","task_type":"understanding","prediction":"it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":286,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5126\/Lab41-SRI-VOiCES-rm1-musi-sp5126-ch034483-sg0013-mc02-lav-clo-dg130.wav","answer":"the sensation produced by her children and her the children were not only beautiful to look at in their smart little dresses but they were charming in the way they behaved aliosha it is true did not stand quite correctly","subset":"musi","task_type":"understanding","prediction":"the sensation produced by her children and her the children were not only beautiful to look at in their smart little dresses but they were charming in the way they behaved elisha it is true did not stand quite correctly","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":287,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5319\/Lab41-SRI-VOiCES-rm1-musi-sp5319-ch064075-sg0017-mc02-lav-clo-dg150.wav","answer":"the next morning when we were about ready to start out on the trap line i asked pard what he intended to do with pont he said that he would tie him to a tree that stood against the shanty close to the door we were going to take different lines of traps","subset":"musi","task_type":"understanding","prediction":"the next morning when we were about ready to start out on the trap line i asked pard what he intended to do with pont he said that he would tie him to a tree that stood against the shanty close to the door we were going to take different lines of traps","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":288,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5386\/Lab41-SRI-VOiCES-rm1-musi-sp5386-ch028384-sg0027-mc02-lav-clo-dg060.wav","answer":"who were free and of age the bride who had taken care to bathe herself the night before appeared in all her splendor but veiled in imitation of rebecca who veiled herself when she came in sight of isaac she was then given to the bridegroom by her parents in words to this purpose","subset":"musi","task_type":"understanding","prediction":"who were free and of age the bride who had taken care to bathe herself the night before appeared in all her splendor but veiled in imitation of rebecca who veiled herself when she came in sight of isaac she was then given to the bridegroom by her parents in words to this purpose","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":289,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5400\/Lab41-SRI-VOiCES-rm1-musi-sp5400-ch034479-sg0026-mc01-stu-clo-dg060.wav","answer":"the crescent shaped curve of the cut grass the grass and flower heads slowly and rhythmically falling before the blade of his scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came","subset":"musi","task_type":"understanding","prediction":"the crescent shaped curve of the cut grass the grass and flower head slowly and rhythmically falling before the blade of his scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":290,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm1-musi-sp5456-ch058161-sg0009-mc01-stu-clo-dg020.wav","answer":"his was the rental of half havana and all matanzas and santa anna rich as he was could hardly hold a candle to light the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers","subset":"musi","task_type":"understanding","prediction":"his was the rental of half a van and all matanzas and santa anna rich as he was could hardly hold a candle to like the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":291,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5583\/Lab41-SRI-VOiCES-rm1-musi-sp5583-ch038026-sg0017-mc01-stu-clo-dg100.wav","answer":"and then we'll be off as fast as we can so when the lad had got on the horse off they went at such a rate he couldn't at all tell how they went but when he had ridden awhile the horse said i think i hear a noise look round can you see anything yes","subset":"musi","task_type":"understanding","prediction":"and then we ll be off as fast as we can so when the lad had got on the horse off they went at such a rate he couldn t at all tell how they went but when he had ridden a while the horse said i think i hear a noise look round can you see anything yes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":292,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm1-musi-sp5635-ch053458-sg0027-mc02-lav-clo-dg080.wav","answer":"although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a black bird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion","subset":"musi","task_type":"understanding","prediction":"although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a black bird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":293,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm1-musi-sp5635-ch058137-sg0021-mc01-stu-clo-dg180.wav","answer":"or the duties more onerous than had been anticipated that a man ought to resign and try another naturally therefore mister rapid thought he would like to sit in our chair of languages or have some employment in the state college and hence he called for that purpose on doctor sylvan who","subset":"musi","task_type":"understanding","prediction":"or the duties more onerous than had been anticipated that a man ought to resign and try another naturally therefore mr rapid thought that he would like to sit in our chair of languages or have some employment in the state college and hence he called for that purpose on dr sylvan who","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":294,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm1-musi-sp5678-ch043301-sg0011-mc01-stu-clo-dg100.wav","answer":"the murmurs of talk rose into cheering old lord pemberton came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily","subset":"musi","task_type":"understanding","prediction":"the murmurs of talk rose into cheering old lord pamperdon came first a grey haired upright man whose father had been active in denouncing the house of which he was a member on the occasion of its fall over seventy years ago and his son had succeeded him worthily","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":295,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm1-musi-sp5678-ch043301-sg0015-mc02-lav-clo-dg000.wav","answer":"had been composed with both skill and ardour they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ's words themselves were quoted","subset":"musi","task_type":"understanding","prediction":"had been composed with both skill and ardor they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ s words themselves were quoted","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":296,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm1-musi-sp5717-ch061421-sg0010-mc02-lav-clo-dg150.wav","answer":"as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and you'll forget there was no answer billy and you'll forget bertram's voice was insistent reproachful","subset":"musi","task_type":"understanding","prediction":"as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and youll forget there was no answer billy and youll forget bertram s voice was insistent reproachful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":297,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5789\/Lab41-SRI-VOiCES-rm1-musi-sp5789-ch057158-sg0004-mc02-lav-clo-dg100.wav","answer":"she wants you to go to her at cheltenham for a month oh mister morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me","subset":"musi","task_type":"understanding","prediction":"she wants you to go to her at cheltenham for a month oh mr morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":298,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm1-musi-sp5868-ch055088-sg0035-mc02-lav-clo-dg100.wav","answer":"and the best prayer i can offer for you is perhaps that you should never need to understand me but if that sore need should come and that poison should begin to spread its mist over your brains and hearts then you will be proof against it just in proportion","subset":"musi","task_type":"understanding","prediction":"And the best prayer I can offer for you is perhaps that you should never need to understand me. But if that sore need should come and that poison should begin to spread its mist over your brains and hearts. Then you will be proof against it, just in proportion.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":299,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm1-musi-sp5868-ch066166-sg0005-mc01-stu-clo-dg160.wav","answer":"and a fringe of gray hair circling his head like a crown as he took off his tarpaulin i observed that the top of his head was quite smooth and flat as if somebody had sat down on him when he was very young there was something noticeably hearty in this man's bronzed face","subset":"musi","task_type":"understanding","prediction":"and a fringe of gray hair circling his head like a crown as he took off his tarpaulin i observed that the top of his head was quite smooth and flat as if somebody had sat down on him when he was very young there was something noticeably haughty in this man s bronzed face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":300,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm1-musi-sp5935-ch043322-sg0015-mc02-lav-clo-dg170.wav","answer":"will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure","subset":"musi","task_type":"understanding","prediction":"will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":301,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm1-musi-sp5935-ch043322-sg0019-mc01-stu-clo-dg020.wav","answer":"after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not","subset":"musi","task_type":"understanding","prediction":"after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":302,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061943-sg0027-mc01-stu-clo-dg070.wav","answer":"the men appeared robust but heavy fair haired like germans but of pensive mien exiles of a higher scale in the ladder of humanity than the eskimos but i thought much more unhappy since with superior perceptions they are compelled to live within the limits of the polar circle","subset":"musi","task_type":"understanding","prediction":"The men appeared robust, but heavy, fair haired like Germans, but of pensive mien exiles of a higher scale in the ladder of humanity than the Esquimos. But I thought much more unhappy since with superior perceptions, they are compelled to live within the limits of the polar circle.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":303,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061946-sg0003-mc01-stu-clo-dg120.wav","answer":"geographers have divided it into four parts and we had to cross the southwest quarter which in the vernacular is called sudvestr fjordungr","subset":"musi","task_type":"understanding","prediction":"geographers have divided it into four parts and we had to cross the southwest quarter which in the vernacular is called suedvest fjordinger","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":304,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061946-sg0022-mc01-stu-clo-dg180.wav","answer":"i thoroughly understood and appreciated the necessity for waiting before crossing the fjord for that moment when the sea at its highest point is in a state of slack water","subset":"musi","task_type":"understanding","prediction":"i thoroughly understood and appreciated the necessity for waiting before crossing the fjord or that moment when the sea at its highest point is in a state of slack water","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":305,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm1-musi-sp6241-ch061946-sg0023-mc02-lav-clo-dg040.wav","answer":"accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion","subset":"musi","task_type":"understanding","prediction":"accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":306,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6319\/Lab41-SRI-VOiCES-rm1-musi-sp6319-ch057405-sg0001-mc02-lav-clo-dg100.wav","answer":"after jupiter had bound prometheus on mount caucasus and had sent diseases and cares into the world men became very very wicked","subset":"musi","task_type":"understanding","prediction":"after jupiter had bound prometheus on mount carpathus and had sent diseases and cares into the world men became very very wicked","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":307,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm1-musi-sp6385-ch034655-sg0015-mc01-stu-clo-dg040.wav","answer":"the maze of passages and alcoves with secret and bewildering doors checked and retarded his progress he strove to run he was obliged to wander he thought that he had but one door to thrust open while he had a skein of doors to unravel","subset":"musi","task_type":"understanding","prediction":"the maze of passages and alcoves with secret and bewildering doors checked and retarded his progress he strove to run he was obliged to wander he thought that he had but one door to thrust open while he had a skein of doors to unravel","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":308,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm1-musi-sp6395-ch087997-sg0045-mc02-lav-clo-dg090.wav","answer":"but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive","subset":"musi","task_type":"understanding","prediction":"but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":309,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm1-musi-sp6454-ch107462-sg0036-mc01-stu-clo-dg100.wav","answer":"let you get up and cut its throat says he and then we will be shut of the domned screechin thing then you got the knife ma'am prompted deasey it was the bread knife she answered with the ugly notches in the blade","subset":"musi","task_type":"understanding","prediction":"let you get up and cut its throat says he and then we will be shut of that darned screeching thing then you got a knife maam professed b c it was a bread knife she answered with the ugly notches in the blade","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":310,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm1-musi-sp6454-ch120342-sg0005-mc02-lav-clo-dg050.wav","answer":"and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people in the very lowest bolgie being ill natured enough to grieve","subset":"musi","task_type":"understanding","prediction":"and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people in the very lowest foggy being ill natured enough to grieve","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":311,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm1-musi-sp6544-ch071420-sg0002-mc02-lav-clo-dg160.wav","answer":"you are going to hand me over to the the authorities never come i won't hurt you he led the way through the woods across a small stream and past a spot where some wild berries grew then they struck a trail leading up a hillside the place was new to her","subset":"musi","task_type":"understanding","prediction":"you are going to hand me over to the the authorities never come i won t hurt you he led the way through the woods across a small stream and past a spot where some wild berries grew then they struck a trail leading up a hillside the place was new to her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":312,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm1-musi-sp6574-ch120583-sg0009-mc02-lav-clo-dg120.wav","answer":"but we knew how to stop them our brothers we said we matter not nor our transgression it is only our brother men who matter give no thought to us for we are nothing but listen to our words","subset":"musi","task_type":"understanding","prediction":"but we knew how to stop them our brothers we said we matter not nor our transgression it is only our brother men who matter give no thought to us for we are nothing but listen to our words","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":313,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm1-musi-sp6574-ch120583-sg0011-mc01-stu-clo-dg100.wav","answer":"we spoke of it and of our long quest and of our tunnel and of our escape from the palace of corrective detention not a hand moved in that hall as we spoke nor an eye then we put the wires to the box and they all bent forward and sat still watching","subset":"musi","task_type":"understanding","prediction":"we spoke of it and of our long quest and of our tunnel and of our escape from the palace of corrective detention not a hand moved in that hall as we spoke nor an eye then we put the wires to the box and they all bent forward and sat still watching","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":314,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm1-musi-sp6574-ch120583-sg0041-mc01-stu-clo-dg020.wav","answer":"there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best","subset":"musi","task_type":"understanding","prediction":"there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":315,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6696\/Lab41-SRI-VOiCES-rm1-musi-sp6696-ch073296-sg0020-mc02-lav-clo-dg180.wav","answer":"turning her eyes with affectionate anxiety toward her husband middling my dear i cannot compliment you i think mister john knightley very far from looking well what is the matter sir did you speak to me cried mister john knightley hearing his own name","subset":"musi","task_type":"understanding","prediction":"turning her eyes with affectionate anxiety toward her husband middling my dear i cannot compliment you i think mr john knightley very far from looking well what is the matter sir did you speak to me cried mr john knightley hearing his own name","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":316,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-musi-sp6895-ch092806-sg0025-mc02-lav-clo-dg050.wav","answer":"oh wailed missus murphy twas yisterday or maybe four hours ago i dunno but it's lost he is me little boy mike he was playin on the sidewalk only this mornin' or was it wednesday i'm that busy with work tis hard to keep up with dates","subset":"musi","task_type":"understanding","prediction":"oh wailed mrs murphy twas yesterday or maybe four hours ago i don know but it s lost he is me little boy mike he was playing on the sidewalk only this morning or was it wednesday i m that busy with work tis hard to keep up with dates","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":317,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-musi-sp6895-ch092806-sg0035-mc02-lav-clo-dg060.wav","answer":"we never did said mister mc caskey lingering with the fact but if we had jawn think what sorrow would be in our hearts this night with our little phelan run away and stolen in the city nowheres at all ye talk foolishness said mister mc caskey tis pat he would be named","subset":"musi","task_type":"understanding","prediction":"we never did said mr maccaskey lingering with the fact but if we had john think what sorrow would be in our hearts tis night with our little phelan run away and stolen in the city nowheres at all ye talk foolishness said mr maccaskey tis pat he would be named","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":318,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm1-musi-sp6965-ch277898-sg0012-mc01-stu-clo-dg100.wav","answer":"but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart's action was the doctor's verdict","subset":"musi","task_type":"understanding","prediction":"but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart s action was the doctor s verdict","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":319,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm1-musi-sp6965-ch277899-sg0035-mc02-lav-clo-dg110.wav","answer":"and in a few seconds missus hoopington's shrill monotone had the field to itself but after the major's display her best efforts at vocal violence missed their full effect it was as though one had come straight out from a wagner opera","subset":"musi","task_type":"understanding","prediction":"and in a few seconds mrs hoopingtons shrill monotone had the field to itself but after the major s display her best efforts at vocal violence missed their full effect it was as though one had come straight out from a wagner opera","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":320,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm1-musi-sp7000-ch083708-sg0021-mc01-stu-clo-dg120.wav","answer":"i've got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy","subset":"musi","task_type":"understanding","prediction":"i have got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":321,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm1-musi-sp7095-ch088484-sg0023-mc02-lav-clo-dg100.wav","answer":"and the glory of the morning hills science does not justify by faith but by works it is the living denial of that age long acceptance which we accord to the mystery as such","subset":"musi","task_type":"understanding","prediction":"and the glory of the morning hills science does not justify by faith but by works it is the living denial of that age long acceptance which we accord to the mystery as such","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":322,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm1-musi-sp7148-ch059157-sg0007-mc01-stu-clo-dg060.wav","answer":"she was a person of unbridled temperament and that in her later years she fell into loose ways and was no credit to the family that she had other qualities besides those mentioned by the tea dealer is shown by the passionate affection","subset":"musi","task_type":"understanding","prediction":"she was a person of unbridled temperament and that in her later years she fell into loose ways and was no credit to the family that she had other qualities besides those mentioned by the tea dealer is shown by the passionate affection","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":323,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm1-musi-sp7148-ch082991-sg0013-mc01-stu-clo-dg170.wav","answer":"are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king's highness said the tall man","subset":"musi","task_type":"understanding","prediction":"are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addled pate with a vengeance the knave has been speaking treason of the king s highness said the tall man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":324,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm1-musi-sp7278-ch246956-sg0029-mc01-stu-clo-dg080.wav","answer":"occasion to the dishonest to cavil and condemn imagine saint paul having a prevision of how he would be misunderstood and heeding it what would then have become of all those his most magnificent outbursts and would any amount of","subset":"musi","task_type":"understanding","prediction":"occasion to the dishonest to cavil and condemn imagine st paul having a prevision of how he would be misunderstood and heeding it what would then have become of all those his most magnificent outbursts and would any amount of","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":325,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm1-musi-sp7445-ch094522-sg0037-mc02-lav-clo-dg160.wav","answer":"the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country","subset":"musi","task_type":"understanding","prediction":"the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":326,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm1-musi-sp7445-ch094526-sg0027-mc01-stu-clo-dg020.wav","answer":"england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vicar of christ","subset":"musi","task_type":"understanding","prediction":"england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vicar of christ","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":327,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm1-musi-sp7498-ch099157-sg0008-mc01-stu-clo-dg000.wav","answer":"she resolved by an unexampled labour for a woman to effect the delivery of her husband she had in her girlish days practised the drawing and colouring of flowers a suitable and amiable accomplishment of her sex","subset":"musi","task_type":"understanding","prediction":"she resolved by an unexampled labor for a woman to effect the delivery of her husband she had in her girlish days practiced the drawing and coloring of flowers a suitable and amiable accomplishment of her sex","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":328,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm1-musi-sp7498-ch099157-sg0017-mc01-stu-clo-dg040.wav","answer":"he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on agriculture he went there leaving his wife in england he was received with honour at the court of stockholm","subset":"musi","task_type":"understanding","prediction":"he obtained for some time a lucrative employment from the duke of chandos he was subsequently invited to sweden on account of a work he had published on agriculture he went there leaving his wife in england he was received with honour at the court of stockholm","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":329,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7704\/Lab41-SRI-VOiCES-rm1-musi-sp7704-ch106965-sg0028-mc01-stu-clo-dg050.wav","answer":"mother would give me leave to fight him just once in a way don't you think that would be nice fightin ain't the only grand thing in this world peace is grander was the slow response to this appeal that's what mother says she made me learn this morning","subset":"musi","task_type":"understanding","prediction":"mother would give me leave to fight him just once in a way dont you think that would be nice fightin ain't the only grand thing in this world peace is grander was the slow response to this appeal that is what mother says she made me learn this morning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":330,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm1-musi-sp7850-ch281318-sg0006-mc02-lav-clo-dg050.wav","answer":"she popped into her new house and sat there comfortably peering out through the window slits with her sharp little eyes","subset":"musi","task_type":"understanding","prediction":"She popped into her new house and SAT there comfortably, peering out through the window slits with her sharp little eyes.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":331,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm1-musi-sp7850-ch286674-sg0005-mc02-lav-clo-dg140.wav","answer":"they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies","subset":"musi","task_type":"understanding","prediction":"They did not breathe it into their mouths or through gills. But took it in through some openings in the back part of their bodies.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":332,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm1-musi-sp7881-ch109662-sg0027-mc01-stu-clo-dg180.wav","answer":"and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet","subset":"musi","task_type":"understanding","prediction":"and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":333,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm1-musi-sp7881-ch109662-sg0030-mc02-lav-clo-dg040.wav","answer":"merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her","subset":"musi","task_type":"understanding","prediction":"merely a tag upon the plant bearing a barbarous foreign or botanical name he waited until night but her answer did not come his large pride and hurt vanity kept him from seeking her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":334,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm1-musi-sp7932-ch278228-sg0004-mc02-lav-clo-dg010.wav","answer":"whose chiefs were eager to secure the well known cashier of messrs dunbar dunbar and balderby's establishment poor clement could not go into the world yet his disappointment had been too bitter and he had no heart to go out amongst hard men of business and begin life again","subset":"musi","task_type":"understanding","prediction":"whose chiefs were eager to secure the well known cashier of messrs dunbar dunbar and balderby's establishment poor leman could not go into the world yet his disappointment had been too bitter and he had no heart to go out amongst hard men of business and begin life again","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":335,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm1-musi-sp7932-ch278228-sg0023-mc02-lav-clo-dg050.wav","answer":"and the decided expression of his thin lips and prominent chin the detective business happened to be rather dull just now there was nothing stirring but a bank of england forgery case and mister carter informed clement that there were more cats in scotland yard than could find mice to kill","subset":"musi","task_type":"understanding","prediction":"and the decided expression of his thin lips and prominent chin the detective business happened to be rather dull just now there was nothing stirring but a bank of england forgery case and mr carter informed clement that there were more cats in scotland yard than could find mice to kill","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":336,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-musi-sp7976-ch110124-sg0018-mc01-stu-clo-dg040.wav","answer":"the merchant's daughter at first did not answer but as he kept on calling to her she finally asked him what it was that he wanted","subset":"musi","task_type":"understanding","prediction":"The merchant's daughter at first did not answer, but as he kept on calling to her, she finally asked him what it was that he wanted.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":337,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-musi-sp7976-ch110523-sg0017-mc02-lav-clo-dg020.wav","answer":"creep in said the witch and see if it is hot enough and then we will put in the bread but she intended when grethel got in to shut up the oven and let her bake so that she might eat her as well as hansel","subset":"musi","task_type":"understanding","prediction":"pre then said the witch and see if it is hot enough and then we will put in the bread which she intended but gretel got in to shut up the oven and let her bake so that she might eat her as well as hansel","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":338,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-musi-sp7981-ch112056-sg0007-mc02-lav-clo-dg060.wav","answer":"and that as he was evidently destined to do great work for god it would be to his advantage to have powerful and influential friends although the prospect of such a post filled the humble parish priest with consternation","subset":"musi","task_type":"understanding","prediction":"and that as he was evidently destined to do great work for god it would be to his advantage to have powerful and influential friends although the prospect of such a post filled the humble parish priest with consternation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":339,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-musi-sp7981-ch112057-sg0035-mc01-stu-clo-dg030.wav","answer":"this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns taking marseilles as his first station here where the conditions were perhaps even worse than in paris","subset":"musi","task_type":"understanding","prediction":"this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns picking marseilles as his first station here where the conditions were perhaps even worse than in paris","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":340,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-musi-sp7981-ch112058-sg0024-mc02-lav-clo-dg070.wav","answer":"and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries","subset":"musi","task_type":"understanding","prediction":"and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of st lazare alone were at the head of sixty such seminaries","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":341,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm1-musi-sp7995-ch276908-sg0017-mc01-stu-clo-dg090.wav","answer":"not of that monster man mister booth i am undone am revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech","subset":"musi","task_type":"understanding","prediction":"not of that monster man mr booth i am undone and revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":342,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8051\/Lab41-SRI-VOiCES-rm1-musi-sp8051-ch295385-sg0030-mc01-stu-clo-dg010.wav","answer":"and sorely would he swell when from the ramparts of fort casimir he beheld the flag of their high mightinesses struck to the rival fortress to heighten his vexation governor printz who as has been shown was a huge trencherman","subset":"musi","task_type":"understanding","prediction":"and sorely would he swell when from the ramparts of fort casimir he beheld the flag of their high mightinesses struck to the rival fortress to heighten his vexation governor printz who as has been shown was a huge trencherman","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":343,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8057\/Lab41-SRI-VOiCES-rm1-musi-sp8057-ch284428-sg0011-mc02-lav-clo-dg080.wav","answer":"said the boolooroo nodding his funny head go ahead then and eat your lunch he retreated a little way to a marble seat beside the fountain but watched the strangers carefully cap'n bill feeling sure he had won the argument whispered to the boy and girl","subset":"musi","task_type":"understanding","prediction":"Said the Boolooroo nodding his funny head. Go ahead then, and eat your lunch. He retreated a little way to a marble seat beside the fountain, but watched the strangers carefully. Cap'n Bill feeling sure he had won the argument, whispered to the boy and girl.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":344,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm1-musi-sp8108-ch274318-sg0029-mc01-stu-clo-dg170.wav","answer":"and power and confidence came with them he began to breathe deeply and regularly and at the same time to absorb into himself the forces opposed to him and to turn them to his own account","subset":"musi","task_type":"understanding","prediction":"And power and confidence came with them. He began to breathe deeply and regularly. And at the same time, to absorb into himself the forces opposed to him and to turn them to his own account.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":345,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm1-musi-sp8108-ch280354-sg0022-mc02-lav-clo-dg160.wav","answer":"oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus's lyre","subset":"musi","task_type":"understanding","prediction":"oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus lyre","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":346,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8118\/Lab41-SRI-VOiCES-rm1-musi-sp8118-ch268287-sg0020-mc01-stu-clo-dg090.wav","answer":"will no depth of grief no length of time no visitation from him who is over us all ever bend your adamant and implacable will i heard with some surprise his allusion to the great being whom he was not wont to recognise","subset":"musi","task_type":"understanding","prediction":"will no depth of grief no length of time no visitation from him who is over us all ever bend your adamant and implacable will i heard with some surprise his allusion to the great being whom he was not wont to recognize","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":347,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8152\/Lab41-SRI-VOiCES-rm1-musi-sp8152-ch258974-sg0046-mc01-stu-clo-dg050.wav","answer":"yet the slight reflection given to the choice of an occupation by most young people gives to this statement a very practical bearing the world is filled with industrial misfits round men in square holes good carpenters spoiled to make poor doctors","subset":"musi","task_type":"understanding","prediction":"yet the slight reflection given to the choice of an occupation by most young people gives to this statement a very practical bearing the world is filled with industrial misfits round men in square holes good carpenters spoiled to make poor doctors","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":348,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-musi-sp8425-ch292520-sg0004-mc02-lav-clo-dg030.wav","answer":"and dinning market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare's light into one sacred rhythm for the devil's spite a woman's thin raucous voice carries the tune bids men rejoice","subset":"musi","task_type":"understanding","prediction":"the dimmy market stalls where women shout their wares and meat hangs out grotesque distorted by the gas flare's light into one sacred rhythm for the devil's spite a woman's thin raucous voice carries the tune bids men rejoice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":349,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8575\/Lab41-SRI-VOiCES-rm1-musi-sp8575-ch290351-sg0028-mc01-stu-clo-dg140.wav","answer":"on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small","subset":"musi","task_type":"understanding","prediction":"on the other side the ordinary smallest measure we have of either is looked on as a unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":350,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8575\/Lab41-SRI-VOiCES-rm1-musi-sp8575-ch290351-sg0028-mc02-lav-clo-dg140.wav","answer":"on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small","subset":"musi","task_type":"understanding","prediction":"on the other side the ordinary smallest measure we have of either is looked on as a unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":351,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8605\/Lab41-SRI-VOiCES-rm1-musi-sp8605-ch292138-sg0019-mc02-lav-clo-dg150.wav","answer":"a miniature bay quite apart from the main river this is called a backwater catching hold of a tree with the hook on the end of her pole miss green brought the punt up against the bank under the overhanging willows","subset":"musi","task_type":"understanding","prediction":"a miniature bay quite apart from the main river this is called a backwater catching hold of a tree with the hook on the end of her pole miss green brought the punt up against the bank under the overhanging willows","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":352,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm1-musi-sp8713-ch296159-sg0045-mc02-lav-clo-dg110.wav","answer":"and know what reaction it was capable of in a word to experimentalise in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use","subset":"musi","task_type":"understanding","prediction":"and know what reaction it was capable of in a word to experimentalize in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":353,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/musi\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm1-musi-sp8713-ch302111-sg0012-mc01-stu-clo-dg010.wav","answer":"with a knife completely pointless and an egg in knots he twisted yet no knot was seen upon it then again he asked the maiden in the sledge to sit beside him but the maid gave crafty answer i perchance at length may join you","subset":"musi","task_type":"understanding","prediction":"with a knife completely pointless and an egg in knots he twisted yet no nub is seen upon it then again he asked the maiden in the sledge to sit beside him but the maid gave crafty answer i perchance at length may join you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":354,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0093\/Lab41-SRI-VOiCES-rm1-none-sp0093-ch123172-sg0007-mc01-stu-clo-dg180.wav","answer":"when the cream will be thick and rich and churns easier if the weather is very cold and the cream has been chilled have a large pot of water over the fire set in the bucket when it is near boiling heat and keep stirring till it is milk warm have the churn scalded and put it in","subset":"none","task_type":"understanding","prediction":"when the cream will be thick and rich and churned easier if the weather is very cold and the cream has been chilled have a large pot of water over the fire set in the bucket when it is near boiling heat and keep stirring till it is milk warm have the churn scalded and put it in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":355,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0093\/Lab41-SRI-VOiCES-rm1-none-sp0093-ch126209-sg0023-mc01-stu-clo-dg080.wav","answer":"but capable of passing as such at a little distance despite some coarseness of skin and fibre she had a round and prominent bosom full lips perfect teeth and the rich complexion of a cochin hen's egg she was a complete and substantial female animal","subset":"none","task_type":"understanding","prediction":"but capable of passing as such at a little distance despite some coarseness of skin and fibre she had a round and prominent bosom full lips perfect teeth and the rich complexion of a cochin hen s egg she was a complete and substantial female animal","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":356,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm1-none-sp0112-ch123215-sg0025-mc01-stu-clo-dg080.wav","answer":"of tolerant wonder anne despite her affection for rusty was not especially fond of cats but missus gardner's tone annoyed her inconsequently she remembered that missus john blythe was so fond of cats that she kept as many as her husband would allow","subset":"none","task_type":"understanding","prediction":"of tolerant wonder ann despite her affection for rusty was not especially fond of cats but mrs gardiner s tone annoyed her inconsequently she remembered that mrs john blythe was so fond of cats that she kept as many as her husband would allow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":357,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm1-none-sp0112-ch123216-sg0003-mc02-lav-clo-dg030.wav","answer":"said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can't said anne sorrowfully","subset":"none","task_type":"understanding","prediction":"said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can t said anne sorrowfully","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":358,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0188\/Lab41-SRI-VOiCES-rm1-none-sp0188-ch141613-sg0017-mc02-lav-clo-dg150.wav","answer":"bridled the little girl aggrievedly as the man began to laugh and anyway i don't understand why some folks should have such a lot and other folks shouldn't have anything and i don't like it","subset":"none","task_type":"understanding","prediction":"bridled the little girl aggrievedly as the man began to laugh and anyway i don t understand why some folks should have such a lot and other folks shouldn t have anything and i don t like it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":359,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm1-none-sp0204-ch162375-sg0020-mc01-stu-clo-dg030.wav","answer":"that is the house of shaws she cried blood built it blood stopped the building of it blood shall bring it down see here she cried again i spit upon the ground and crack my thumb at it black be its fall","subset":"none","task_type":"understanding","prediction":"that is the house of shaws she cried blood built it blood stopped the building of it blood shall bring it down see here she cried again i spit upon the ground and crack my thumb at it black be its fall","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":360,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm1-none-sp0205-ch123882-sg0034-mc02-lav-clo-dg180.wav","answer":"that dull reserve that seemed to hold the passengers in the electric suburban has clean vanished and gone they are talking listen of the harvest and the late election and of how the local member is mentioned for the cabinet and all the old familiar topics of the sort","subset":"none","task_type":"understanding","prediction":"that dull reserve that seemed to hold the passengers in the electric suburban has clean vanished and gone they are talking listening of the harvest and the late election and of how the local member is mentioned for the cabinet and all the old familiar topics of the sort","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":361,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm1-none-sp0205-ch157088-sg0010-mc02-lav-clo-dg150.wav","answer":"and sat watching olaf as he mothered the half baked bannock loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range","subset":"none","task_type":"understanding","prediction":"and sat watching olaf as he mothered the half baked bannack loaf it made him think of his father a thousand times the two must have camped like this in the days when alaska was new and there were no maps to tell them what lay beyond the next range","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":362,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm1-none-sp0205-ch159056-sg0010-mc02-lav-clo-dg120.wav","answer":"when he was a colonel and had been through the wars and at court he still believed she was a match for all the beauties he was not lucky enough to take after her in looks except in her one weak feature a cutaway chin his body indeed","subset":"none","task_type":"understanding","prediction":"when he was a colonel and had been through the wars and at court he still believed she was a match for all the beauties he was not lucky enough to take after her in looks except in her one weak feature a cutaway chin his body indeed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":363,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm1-none-sp0209-ch157830-sg0013-mc02-lav-clo-dg180.wav","answer":"what every comfort of life knocked off journeys london servants horses table contractions and restrictions every where to live no longer with the decencies even of a private gentleman no","subset":"none","task_type":"understanding","prediction":"what every comfort of life knocked off journeys london servants horses table contractions and restrictions everywhere to live no longer with the decencies even of a private gentleman no","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":364,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0240\/Lab41-SRI-VOiCES-rm1-none-sp0240-ch160593-sg0021-mc02-lav-clo-dg060.wav","answer":"it would be life and life is over there behind the shelf the sexton keeps the key to putting up our life his porcelain like a cup discarded of the housewife quaint or broken a newer sevres pleases old ones crack i could not die with you","subset":"none","task_type":"understanding","prediction":"it would be life and life is over there behind the shelf the sexton keeps the key to putting up our life his porcelain like a cup discarded of the housewife quaint or broken a newer sever's pleases old ones crack i could not die with you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":365,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-none-sp0242-ch122626-sg0001-mc02-lav-clo-dg050.wav","answer":"and humbled by the consciousness of my physical inferiority to eliza john and georgiana reed the said eliza john and georgiana were now clustered round their mama in the drawing room she lay reclined on a sofa by the fireside","subset":"none","task_type":"understanding","prediction":"and humbled by the consciousness of my physical infirmity to eliza john and georgina reed the said eliza john and georgina were now clustered round their mamma in the drawing room she lay reclined on a sofa by the fireside","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":366,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-none-sp0242-ch126842-sg0018-mc01-stu-clo-dg000.wav","answer":"after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cecily desperately drawing lots is wickeder that fighting said dan","subset":"none","task_type":"understanding","prediction":"after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cicely desperately drawing lots is wickeder than fighting said dan","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":367,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0288\/Lab41-SRI-VOiCES-rm1-none-sp0288-ch130994-sg0033-mc02-lav-clo-dg060.wav","answer":"may serve as a standard the state of agriculture and the populousness of a country have been considered as nearly connected with each other and as a rule for the purpose intended numbers in the view of simplicity and certainty are entitled to a preference","subset":"none","task_type":"understanding","prediction":"may serve as a standard the state of agriculture and the populousness of a country have been considered as nearly connected with each other and as a rule for the purpose intended numbers in the view of simplicity and certainty are entitled to a preference","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":368,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0296\/Lab41-SRI-VOiCES-rm1-none-sp0296-ch129659-sg0002-mc01-stu-clo-dg150.wav","answer":"to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding","subset":"none","task_type":"understanding","prediction":"to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":369,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0296\/Lab41-SRI-VOiCES-rm1-none-sp0296-ch141721-sg0022-mc02-lav-clo-dg030.wav","answer":"of his pompous helmet his superb cuirass his rich bracelets his brilliant cuisses or armour for his thighs and other martial accoutrements when zadig had equipp'd himself cap a pee in his now recover'd armour","subset":"none","task_type":"understanding","prediction":"of his pompous helmet his superb cuirass his rich bracelets his brilliant cuisses or armour for his thighs and other martial accoutrements when zany had equipped himself cap a pie in his now recovered armour","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":370,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm1-none-sp0459-ch123443-sg0034-mc02-lav-clo-dg010.wav","answer":"and just as i was thinking i should be free of them at last they must needs come wriggling down from the sky ugh serpent but i'm not a serpent i tell you said alice i'm a i'm a well what are you said the pigeon","subset":"none","task_type":"understanding","prediction":"and just as i was thinking i should be free of them at last they must needs come wriggling down from the sky ah serpent but i am not a serpent i tell you said alice i am a i am a well what are you said the pigeon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":371,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm1-none-sp0472-ch130755-sg0009-mc02-lav-clo-dg070.wav","answer":"would be hardly less painful than of both and so on through the whole list of lady russell's too gentle reductions how anne's more rigid requisitions might have been taken is of little consequence lady russell's had no success at all","subset":"none","task_type":"understanding","prediction":"would be hardly less painful than of both and so on through the whole list of lady russell's too gentle reductions how anne's more rigid requisitions might have been taken is of little consequence lady russell's had no success at all","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":372,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm1-none-sp0479-ch107479-sg0004-mc02-lav-clo-dg170.wav","answer":"and still retain the prejudice against inferior associations which an english gentleman whatever the vicissitudes of his career can never quite rid himself of i had to join their club an exclusive organization of butlers and gentlemen's gentlemen otherwise valets","subset":"none","task_type":"understanding","prediction":"that still retain the prejudice against inferior associations which an english gentleman whatever the vicissitudes of his career can never quite rid himself of i had to join their club an exclusive organization of butlers and gentlemen s gentlemen otherwise valets","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":373,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm1-none-sp0479-ch126480-sg0027-mc01-stu-clo-dg030.wav","answer":"little tin patty pan duchess drew a long breath then i must have been eating mouse no wonder i feel ill but perhaps i should feel worse if i had really swallowed a patty pan duchess reflected what a very awkward thing to have to explain to ribby","subset":"none","task_type":"understanding","prediction":"little tin patty pan duchess drew a long breath then it must have been eating mouse no wonder i feel ill but perhaps i should feel worse if i had really swallowed a patty pan duchess reflected what a very awkward thing to have to explain to ribby","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":374,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-none-sp0480-ch126292-sg0014-mc02-lav-clo-dg110.wav","answer":"with all my heart get up behind and be sure you do not fall off take care of this handsome coach of mine nor dirty my pretty red wheels so fine now mice be ready and wheels run steady for we are going a visit to pay","subset":"none","task_type":"understanding","prediction":"with all my heart get up behind and be sure you do not fall off take care of this handsome coach of mine nor dirty my pretty red wheels so fine now mice be ready and wheels run steady for we are going a visit to pay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":375,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-none-sp0480-ch127525-sg0006-mc02-lav-clo-dg120.wav","answer":"two fresh men were at the oars the tide keeps washing her down could you pull a little stronger not without swamping the boat said he you must bear up sir","subset":"none","task_type":"understanding","prediction":"two fresh men were at the oars the tide keeps washing her down could you pull a little stronger not without swamping the boat said he you must bear up sir","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":376,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm1-none-sp0492-ch131899-sg0008-mc01-stu-clo-dg010.wav","answer":"he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation","subset":"none","task_type":"understanding","prediction":"he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":377,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0597\/Lab41-SRI-VOiCES-rm1-none-sp0597-ch127694-sg0014-mc01-stu-clo-dg110.wav","answer":"nevertheless the little douglas squirrel can open them indians climb the trees like bears and beat off the cones or recklessly cut off the more fruitful branches with hatchets while the squaws gather and roast them until the scales open sufficiently","subset":"none","task_type":"understanding","prediction":"nevertheless the little douglas squirrel can open them indians climb the trees like bears and beat off the cones or recklessly cut off the more fruitful branches with hatchets while the squaws gather and roast them until the scales open sufficiently","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":378,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0597\/Lab41-SRI-VOiCES-rm1-none-sp0597-ch134789-sg0036-mc01-stu-clo-dg050.wav","answer":"they are forever talking about it to us to me in particular just as the old women in naples cry to saint januarius faccia gialluta fa o miracolo yellow face perform thy miracle so our beauties say to me incessantly","subset":"none","task_type":"understanding","prediction":"they are forever talking about it to us to me in particular just as the old women in naples cry to saint januarius facciocioluto fa un miracolo yellow face perform thy miracle so our beauties say to me incessantly","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":379,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm1-none-sp0636-ch128331-sg0015-mc01-stu-clo-dg090.wav","answer":"with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building","subset":"none","task_type":"understanding","prediction":"with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":380,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0652\/Lab41-SRI-VOiCES-rm1-none-sp0652-ch129742-sg0012-mc02-lav-clo-dg080.wav","answer":"salad two cups of apples cut into small pieces one cup celery cut into small pieces one cup english walnuts","subset":"none","task_type":"understanding","prediction":"salad two cups of apples cut into small pieces one cup celery cut into small pieces one cup english walnuts","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":381,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0652\/Lab41-SRI-VOiCES-rm1-none-sp0652-ch130737-sg0010-mc02-lav-clo-dg060.wav","answer":"sauterne is a white bordeaux a strong luscious wine the best known varieties being","subset":"none","task_type":"understanding","prediction":"Sauvignon is a white Bordeaux, a strong. Luscious wine, the best known varieties being.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":382,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm1-none-sp0949-ch162667-sg0034-mc01-stu-clo-dg020.wav","answer":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","subset":"none","task_type":"understanding","prediction":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":383,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm1-none-sp1050-ch134121-sg0015-mc02-lav-clo-dg010.wav","answer":"each one went down taking a napkin the cook laid the kitchen table put on it her best table cloth and the family sat down amanda went to the dumb waiter for the dinner but she could not move it down the family were all in dismay","subset":"none","task_type":"understanding","prediction":"each one went down taking a napkin the cook laid the kitchen table put on it her best tablecloth and the family sat down amanda went to the dumb waiter for the dinner but she could not move it down the family were all in dismay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":384,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1052\/Lab41-SRI-VOiCES-rm1-none-sp1052-ch139308-sg0001-mc02-lav-clo-dg130.wav","answer":"and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there","subset":"none","task_type":"understanding","prediction":"and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":385,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm1-none-sp1066-ch005330-sg0006-mc01-stu-clo-dg110.wav","answer":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune","subset":"none","task_type":"understanding","prediction":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":386,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm1-none-sp1112-ch128136-sg0019-mc01-stu-clo-dg090.wav","answer":"are excessively tedious but when mister rodd leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed","subset":"none","task_type":"understanding","prediction":"are excessively tedious but when mr rod leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":387,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm1-none-sp1116-ch132847-sg0029-mc01-stu-clo-dg050.wav","answer":"the swallow is less swift than the wind the wind is less swift than the lightning but you my horse if you love me must be swifter than them all for there is a part of my heart that suffers the best part of my heart that is in danger and the horse heard her","subset":"none","task_type":"understanding","prediction":"The swallow is less swift than the wind. The wind is less swift than the lightning. But you, my horse, if you love me, must be swifter than them all for there is a part of my heart that suffers the best part of my heart that is in danger. And the horse heard her.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":388,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm1-none-sp1116-ch132851-sg0015-mc01-stu-clo-dg070.wav","answer":"and six new pieces of silver in the pocket of her apron and she believed that all this was owing to jegu and she could no longer do without him even in her thoughts when things had reached this pass the brownie told the young man that he had better ask barbaik to marry him","subset":"none","task_type":"understanding","prediction":"and six new pieces of silver in the pocket of her apron and she believed that all this was owing to jegu and she could no longer do without him even in her thoughts when things had reached this pass the brownie told the young man that he had better ask barbe to marry him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":389,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm1-none-sp1160-ch134674-sg0015-mc01-stu-clo-dg000.wav","answer":"as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps","subset":"none","task_type":"understanding","prediction":"as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":390,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1182\/Lab41-SRI-VOiCES-rm1-none-sp1182-ch133396-sg0014-mc02-lav-clo-dg150.wav","answer":"he waited for a while and then knocked again rap tap tap presently with a click a little square wicket that pierced the door was opened and a woman's face peered out through the iron bars the one eyed hans whipped off his leathern cap","subset":"none","task_type":"understanding","prediction":"he waited for a while and then knocked again rap tap tap presently with a click a little square wicket that pierced the door was opened and a woman s face peered out through the iron bars the one eyed hans whipped off his leather cap","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":391,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_0032-1182\/sp1182\/Lab41-SRI-VOiCES-rm1-none-sp1182-ch134316-sg0027-mc01-stu-clo-dg040.wav","answer":"she examined the room carefully at the farthermost end was another door and this she pushed gently at first and then vigorously without producing the slightest impression she still had her bag a small affair of black moire which hung from her belt","subset":"none","task_type":"understanding","prediction":"she examined the room carefully at the farthermost end was another door and this she pushed gently at first and then vigorously without producing the slightest impression she still had her bag a small affair of black moire which hung from her belt","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":392,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1235\/Lab41-SRI-VOiCES-rm1-none-sp1235-ch135883-sg0020-mc02-lav-clo-dg070.wav","answer":"he was agreeably surprised when he found the prince entered the council chamber without giving him the fatal orders he expected the sultan according to his custom spent the day in regulating his affairs and when the night had closed in retired with scheherazade","subset":"none","task_type":"understanding","prediction":"he was agreeably surprised when he found the prince enter the council chamber without giving him the fatal orders he expected the sultan according to his custom spent the day in regulating his affairs and when the night closed in retired to shahrazad","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":393,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1235\/Lab41-SRI-VOiCES-rm1-none-sp1235-ch135887-sg0026-mc02-lav-clo-dg130.wav","answer":"if he had had a design upon my life why did he save me then he needed only to have left me to my disease i could not have escaped it as life was fast decaying forbear then to fill me with unjust suspicions","subset":"none","task_type":"understanding","prediction":"if he had had a design upon my life why did he save me then he needed only to have left me to my disease i could not have escaped it as life was fast decaying forbear then to fill me with unjust suspicions","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":394,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm1-none-sp1246-ch135815-sg0012-mc02-lav-clo-dg000.wav","answer":"peter was delighted to air his knowledge the last one i was in said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it","subset":"none","task_type":"understanding","prediction":"peter was delighted to air his knowledge the last one i was in he said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":395,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm1-none-sp1272-ch135031-sg0000-mc01-stu-clo-dg090.wav","answer":"because you were sleeping instead of conquering the lovely rose princess has become a fiddle without a bow while poor shaggy sits there a cooing dove","subset":"none","task_type":"understanding","prediction":"because you are sleeping instead of conquering the lovely rose princess has become a fiddle without a bow while poor shaggy sits there a cooing dove","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":396,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm1-none-sp1383-ch130489-sg0016-mc02-lav-clo-dg150.wav","answer":"her heart fluttered with a vague terror her heart pounded in her throat her heart was full of speechless sorrow her hurrying thoughts clamored for utterance her imagination recoiled her interest flagged","subset":"none","task_type":"understanding","prediction":"her heart fluttered with a vague terror her heart pounded in her throat her heart was full of speechless sorrow her hurrying thoughts clamored for utterance her imagination recoiled her interest flagged","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":397,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm1-none-sp1383-ch130489-sg0018-mc02-lav-clo-dg130.wav","answer":"her mood was unaccountably chilled her musings took a sudden and arbitrary twist her scarlet lip curled cruelly her smile was faintly depreciatory her smile was linked with a sigh","subset":"none","task_type":"understanding","prediction":"her mood was unaccountably chilled her musings took a sudden and arbitrary twist her scarlet lip curled cruelly her smile was faintly depreciatory her smile was linked with a sigh","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":398,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-none-sp1472-ch142848-sg0009-mc01-stu-clo-dg160.wav","answer":"the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves one selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation","subset":"none","task_type":"understanding","prediction":"the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves when selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":399,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-none-sp1472-ch285314-sg0037-mc02-lav-clo-dg170.wav","answer":"mister skeelty stared at him a moment then he laughed they're mostly foreigners mister merrick who haven't yet fully mastered the english language but he added thoughtfully a few among them might subscribe if your country sheet contains any news of interest at all","subset":"none","task_type":"understanding","prediction":"mr skeelty stared at him a moment then he laughed they are mostly foreigners mr merrick who haven t yet fully mastered the english language but he added thoughtfully a few among them might subscribe if your country sheet contains any news of interest at all","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":400,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1851\/Lab41-SRI-VOiCES-rm1-none-sp1851-ch148312-sg0008-mc02-lav-clo-dg100.wav","answer":"he said quietly and still protested with many compliments that he would marry none but her when baptista came back he asked at once how speed you with my daughter how should i speed but well replied petruchio how but well","subset":"none","task_type":"understanding","prediction":"he said quietly and still protested with many compliments that he would marry none but her when baptista came back he asked at once how speed you with my daughter how should i speed but well replied petruchio how but well","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":401,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1851\/Lab41-SRI-VOiCES-rm1-none-sp1851-ch151817-sg0036-mc02-lav-clo-dg150.wav","answer":"or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course they must be totally ignorant of all such things as flying machines and the like","subset":"none","task_type":"understanding","prediction":"or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course it must be totally ignorant of all such things as flying machines and the like","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":402,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm1-none-sp1867-ch154075-sg0008-mc01-stu-clo-dg140.wav","answer":"had the clever devil guessed at the truth so easily had he sent his follower away merely to avoid having it known that a man had taken shelter in the room of the girl he loved go on the leader was repeating let me hear the whole truth","subset":"none","task_type":"understanding","prediction":"had the clever devil guessed at the truth so easily had he sent his follower away merely to avoid having it known that a man had taken shelter in the room of the girl he loved go on the leader was repeating let me hear the whole truth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":403,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm1-none-sp1867-ch154075-sg0018-mc02-lav-clo-dg130.wav","answer":"as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance","subset":"none","task_type":"understanding","prediction":"as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":404,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm1-none-sp1874-ch165702-sg0018-mc01-stu-clo-dg100.wav","answer":"emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four","subset":"none","task_type":"understanding","prediction":"emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":405,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm1-none-sp1874-ch165702-sg0020-mc02-lav-clo-dg150.wav","answer":"april fourteenth assassinated in ford's theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett","subset":"none","task_type":"understanding","prediction":"april fourteenth assassinated in ford s theatre washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":406,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1926\/Lab41-SRI-VOiCES-rm1-none-sp1926-ch147987-sg0012-mc02-lav-clo-dg030.wav","answer":"when i got home i climbed in at the kitchen window i was covered with blood from my nose and lip but i was too sick to do anything about it i found a shawl and an overcoat on the hatrack lay down on the parlor sofa and in spite of my hurts went to sleep","subset":"none","task_type":"understanding","prediction":"when i got home i climbed in at the kitchen window i was covered with blood from my nose and lip but i was too sick to do anything about it i found a shawl and an overcoat on the hat rack lay down on the parlor sofa and in spite of my hurts went to sleep","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":407,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm1-none-sp1970-ch026100-sg0035-mc01-stu-clo-dg110.wav","answer":"oh his alibi is good of course because he was around the club all that evening i guess he was here and i don't remember it i shook hands with him and left far out on the golf links the coroner was bending over examining something on the ground","subset":"none","task_type":"understanding","prediction":"oh his alibi is good of course because he was around the club all that evening i guess he was here and i don t remember it i shook hands with him and left far out on the golf links the coroner was bending over examining something on the ground","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":408,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm1-none-sp2012-ch139358-sg0018-mc01-stu-clo-dg130.wav","answer":"it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries","subset":"none","task_type":"understanding","prediction":"it is said that by negligence or bad management the number of these trees is decreasing in the basin of the amazon but the forests of seringueira trees are still very considerable on the banks of the madeira purus and other tributaries","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":409,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2074\/Lab41-SRI-VOiCES-rm1-none-sp2074-ch147193-sg0032-mc01-stu-clo-dg000.wav","answer":"king of athens who lives on pallas hill and say to him the stone is lifted but whose is the pledge beneath it then show him the sword and the sandals and take what the gods shall send","subset":"none","task_type":"understanding","prediction":"king of athens who lives on palace hill and say to him the stone is lifted but whose is the pledge beneath it then show him the sword and the sandals and take what the gods shall send","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":410,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2149\/Lab41-SRI-VOiCES-rm1-none-sp2149-ch007239-sg0015-mc02-lav-clo-dg070.wav","answer":"boasters proud blasphemers disobedient to parents unthankful","subset":"none","task_type":"understanding","prediction":"boasters proud blasphemers disobedient to parents unthankful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":411,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm1-none-sp2156-ch025563-sg0042-mc01-stu-clo-dg120.wav","answer":"the buttons on phelan's coat were fairly undulating with the emotions that stirred within him in his seething gray matter there stirred the remembrance that bateato had told him that women were robbing the house you mean the women","subset":"none","task_type":"understanding","prediction":"the buttons on phelan s coat were fairly undulating with the emotions that stirred within him in his seething gray matter there stirred the remembrance that bateato had told him that women were robbing the house you mean the women","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":412,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2162\/Lab41-SRI-VOiCES-rm1-none-sp2162-ch164461-sg0006-mc01-stu-clo-dg140.wav","answer":"since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves","subset":"none","task_type":"understanding","prediction":"since we have nothing to compare it with religion prefers to think of it as quick for religion the flowers shoot up suddenly like rockets for religion the mountains are lifted up suddenly like waves","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":413,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2162\/Lab41-SRI-VOiCES-rm1-none-sp2162-ch164461-sg0026-mc02-lav-clo-dg110.wav","answer":"or go off on something different altogether this crucial point in his life is marked by nicholas nickleby it must be remembered that before this issue of nicholas nickleby his work successful as it was","subset":"none","task_type":"understanding","prediction":"or go off on something different altogether this crucial point in his life is marked by nicholas nickleby it must be remembered that before this issue of nicholas nickleby his work successful as it was","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":414,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm1-none-sp2285-ch149890-sg0024-mc02-lav-clo-dg070.wav","answer":"where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mister hurstwood came from the first individual recognised glad to see you said the latter grasping his hand lightly","subset":"none","task_type":"understanding","prediction":"where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mr hurstwood came from the first individual recognized glad to see you said the latter grasping his hand lightly","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":415,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm1-none-sp2285-ch163380-sg0014-mc01-stu-clo-dg110.wav","answer":"after a long time the rain let up but the clouds stayed and the lightning kept whimpering and by and by a flash showed us a black thing ahead floating and we made for it it was the raft and mighty glad was we to get aboard of it again","subset":"none","task_type":"understanding","prediction":"after a long time the rain let up but the clouds stayed and the lightning kept whimpering and by and by a flash showed us a black thing ahead floating and we made for it it was the raft and mighty glad was we to get aboard of it again","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":416,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm1-none-sp2285-ch163380-sg0034-mc02-lav-clo-dg050.wav","answer":"for helping these rapscallions because rapscallions and dead beats is the kind the widow and good people takes the most interest in well before long here comes the wreck dim and dusky sliding along down a kind of","subset":"none","task_type":"understanding","prediction":"for helping these rapscallions cause rapscallions and deadbeats is the kind a widow and good people take the most interest in well before long here comes the wreck dim and dusky sliding along down a kind of","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":417,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm1-none-sp2285-ch163381-sg0034-mc01-stu-clo-dg020.wav","answer":"does a cat talk like a cow or a cow talk like a cat no dey don't it's natural and right for em to talk different from each other ain't it course and ain't it natural and right","subset":"none","task_type":"understanding","prediction":"Does a cat talk like a cow or a cow talk like a cat, No, they don't. It's natural and right for em to talk different from each other, ain't it. Course, and ain't it natural and right.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":418,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm1-none-sp2289-ch152258-sg0005-mc01-stu-clo-dg030.wav","answer":"that people gave him the name of el amin which means the truthful at this time he was only sixteen years of age but the rich traders had so much confidence in him that they gave him important business to attend to and trusted him with large sums of money","subset":"none","task_type":"understanding","prediction":"that people gave him the name of el amin which means the truthful at this time he was only sixteen years of age but the rich traders had so much confidence in him that they gave him important business to attend to and trusted him with large sums of money","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":419,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm1-none-sp2412-ch153948-sg0000-mc02-lav-clo-dg080.wav","answer":"if the reader will excuse me i will say nothing of my antecedents nor of the circumstances which led me to leave my native country the narrative would be tedious to him and painful to myself","subset":"none","task_type":"understanding","prediction":"if the reader will excuse me i will say nothing of my antecedents nor of the circumstances which led me to leave my native country the narrative would be tedious to him and painful to myself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":420,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2573\/Lab41-SRI-VOiCES-rm1-none-sp2573-ch178450-sg0027-mc01-stu-clo-dg150.wav","answer":"aren't you ever goin to bed sheridan halted all right mamma he said with a vast sigh let's go up and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising lopsidedly in her drowsiness","subset":"none","task_type":"understanding","prediction":"arent you ever going to bed sheridan halted all right mamma he said with a vast sigh lets go up and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising lopsidedly in her drowsiness","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":421,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2691\/Lab41-SRI-VOiCES-rm1-none-sp2691-ch156745-sg0027-mc01-stu-clo-dg160.wav","answer":"merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances","subset":"none","task_type":"understanding","prediction":"merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":422,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm1-none-sp2764-ch036616-sg0038-mc02-lav-clo-dg110.wav","answer":"not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day's delay would have been unforgivable","subset":"none","task_type":"understanding","prediction":"not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day s delay would have been unforgivable","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":423,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm1-none-sp2764-ch036617-sg0016-mc01-stu-clo-dg130.wav","answer":"don't bother counting just squeeze it all in and hurry what about master's collections conseil ventured to observe we'll deal with them later what the archaeotherium hyracotherium oreodonts cheiropotamus and master's other fossil skeletons","subset":"none","task_type":"understanding","prediction":"dont bother counting just squeeze it all in and hurry what about masters collections conseil ventured to observe we will deal with them later what the archaeotherium hyracotherium oreodonts carpothermus and masters other fossil skeletons","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":424,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm1-none-sp2803-ch154320-sg0004-mc02-lav-clo-dg150.wav","answer":"much as they had been interested in his dissertation on the pampas or australia his lectures on new zealand fell on cold and indifferent ears","subset":"none","task_type":"understanding","prediction":"Much as they had been interested in his dissertation on the Pampas or Australia, his lectures on New Zealand fell on cold and indifferent ears","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":425,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm1-none-sp2803-ch154328-sg0018-mc02-lav-clo-dg120.wav","answer":"their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sounds that only a thin layer of earth prevented immediate communication","subset":"none","task_type":"understanding","prediction":"their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sounds that only a thin layer of earth prevented immediate communication","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":426,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm1-none-sp2911-ch015045-sg0011-mc02-lav-clo-dg170.wav","answer":"or prowling warrior we have said that this group of tribes was relatively very populous yet it is more than doubtful whether all of them united had union been possible could have mustered eight thousand fighting men to speak further of them is needless","subset":"none","task_type":"understanding","prediction":"or prowling warrior we have said that this group of tribes was relatively very populous yet it is more than doubtful whether all of them united had union been possible could have mustered eight thousand fighting men to speak further of them is needless","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":427,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm1-none-sp2911-ch015084-sg0007-mc02-lav-clo-dg070.wav","answer":"not by a depleted antagonist still feeble from the exhaustion of a starved and persecuted infancy but by an athletic champion of the principles of richelieu and of loyola liberty may thank the iroquois that by their insensate fury","subset":"none","task_type":"understanding","prediction":"not by a depleted antagonist still feeble from the exhaustion of a starved and persecuted infancy but by an athletic champion of the principles of richelieu and of boyola liberty may thank the iroquois that by their incessant fury","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":428,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3235\/Lab41-SRI-VOiCES-rm1-none-sp3235-ch011599-sg0012-mc02-lav-clo-dg010.wav","answer":"into several constituent groups the principal compound measures are four beat and six beat both being referred to as compound duple measures five beat seven beat nine beat and twelve beat measures","subset":"none","task_type":"understanding","prediction":"in a several constituent groups the principal compound measures are four beat and six beat both being referred to as compound duple measures five beat seven beat nine beat and twelve beat measures","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":429,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3235\/Lab41-SRI-VOiCES-rm1-none-sp3235-ch028433-sg0007-mc02-lav-clo-dg150.wav","answer":"and crowded to the utmost capacity for comfort every stateroom was full each seat at the tables occupied not a foot of space above or below decks was left unused but provision was made for all","subset":"none","task_type":"understanding","prediction":"and crowded to the utmost capacity for comfort every state room was full each seat at the tables occupied not a foot of space above or below decks was left unused but provision was made for all","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":430,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm1-none-sp3368-ch170950-sg0014-mc02-lav-clo-dg020.wav","answer":"why he said are they not capable of defending themselves no i said not if we were right in the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success","subset":"none","task_type":"understanding","prediction":"why he said are they not capable of defending themselves no i said not if we were right that the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":431,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm1-none-sp3368-ch170951-sg0047-mc01-stu-clo-dg010.wav","answer":"he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a chorus neither shall we allow teachers to make use of them in the instruction of the young meaning","subset":"none","task_type":"understanding","prediction":"he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a corpse neither shall we allow teachers to make use of them in the instruction of the young meaning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":432,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm1-none-sp3368-ch170952-sg0041-mc02-lav-clo-dg140.wav","answer":"any more than i can allow our citizens to believe that he the wise cheiron's pupil the son of a goddess and of peleus who was the gentlest of men and third in descent from zeus was so disordered in his wits as to be at one time the slave of two seemingly inconsistent passions","subset":"none","task_type":"understanding","prediction":"any more than i can allow our citizens to believe that he the wise charon s pupil the son of a goddess and of pelias who was the gentlest of men and third in descent from zeus was so disordered in his wits as to be at one time the slave of two seemingly inconsistent passions","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":433,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm1-none-sp3483-ch115968-sg0003-mc01-stu-clo-dg090.wav","answer":"and laid out new camp locations scattering them farther to the south and avoiding ground which had been seared by the han beams and the immediate locations of the han wrecks during this period a sharp check was kept upon han messages","subset":"none","task_type":"understanding","prediction":"and laid out new camp locations scattering them farther to the south and avoiding ground which had been seared by the han beams and the immediate locations of the han wrecks during this period a sharp check was kept upon han messages","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":434,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm1-none-sp3483-ch174132-sg0010-mc01-stu-clo-dg000.wav","answer":"but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study","subset":"none","task_type":"understanding","prediction":"but this is a true record of my own experiences and i would not put pen to paper to amuse anyone no it was after midnight on the morning of the twenty first day of january i was sitting reading as is often my custom in my study","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":435,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_1212-3521\/sp3521\/Lab41-SRI-VOiCES-rm1-none-sp3521-ch007591-sg0036-mc01-stu-clo-dg050.wav","answer":"but in the next his brow reddened with rage who dares he demanded hoarsely of the courtiers who stood near him who dares insult us with this blasphemous mockery seize him and unmask him that we may know whom we have to hang at sunrise from the battlements","subset":"none","task_type":"understanding","prediction":"but in the next his brow reddened with rage who dares he demanded hoarsely of the courtiers who stood near him who dares insult us with this blasphemous mockery seize him and unmask him that we may know whom we have to hang at sunrise from the battlements","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":436,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm1-none-sp3835-ch178030-sg0013-mc02-lav-clo-dg170.wav","answer":"nicholas rostov took a close and prolonged part in the defense of his country but did so casually without any aim at self sacrifice and he therefore looked at what was going on in russia without despair and without dismally racking his brains over it","subset":"none","task_type":"understanding","prediction":"nicholas rostov took a close and prolonged part in the defense of his country but did so casually without any aim at self sacrifice and he therefore looked at what was going on in russia without despair and without dismally racking his brains over it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":437,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm1-none-sp3923-ch181420-sg0027-mc01-stu-clo-dg080.wav","answer":"pious and god fearing most of them but largely at the mercy of the local traders who took their pay in fish for the bare necessities of living with a large account always on the trader's side with such medical aid and ministration as came only occasionally by the infrequent mail boat","subset":"none","task_type":"understanding","prediction":"pious and god fearing most of them but largely at the mercy of the local traders who took their pay in fish for the bare necessities of living with a large account always on the traders side with such medical aid and ministration as came only occasionally by the infrequent mail boat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":438,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp3994\/Lab41-SRI-VOiCES-rm1-none-sp3994-ch149798-sg0002-mc02-lav-clo-dg020.wav","answer":"raise the sunken island and save our friends and the imprisoned skeezers afterward we can visit the mountain and punish the cruel magician of the flatheads that is sensible approved the shaggy man i quite agree with you","subset":"none","task_type":"understanding","prediction":"raise the sunken island and save our friends and the imprisoned skeezers afterward we can visit the mountain and punish the cruel magician of the flatheads that is sensible approved the shaggy man i quite agree with you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":439,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-none-sp4014-ch186175-sg0019-mc01-stu-clo-dg180.wav","answer":"and he started down the passageway toward a narrow stairs leading to a still lower chamber in the vessel three turns two to the right and one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock","subset":"none","task_type":"understanding","prediction":"and he started down the passageway towards a narrow stairway leading to a still lower chamber in the vessel three turns two to the right and one to the left and the captain stopped again to listen seemingly from within the wall right at their elbows there came a feeble knock","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":440,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-none-sp4014-ch186176-sg0004-mc02-lav-clo-dg140.wav","answer":"evidently also from the boiler or engine room brushed by us he had disappeared when the sailor said to me i think that was the fellow the one that just went by not wanting to arouse his suspicions i ended the conversation with a casual remark and then strolled away until i was out of the sailor's sight","subset":"none","task_type":"understanding","prediction":"And gently, also from the boiler or engine room, brushed by us. He had disappeared. The sailor said to me, I think that was the fellow. The one that just went by not wanting to rouse his suspicions. I entered the conversation with a casual remark and then strolled away until I was out of the sailor sight.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":441,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-none-sp4014-ch186183-sg0024-mc01-stu-clo-dg170.wav","answer":"he pointed her nose downward toward the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer's place in the taube was making desperate signals","subset":"none","task_type":"understanding","prediction":"he pointed her nose downward towards the american lines four american planes sailed off and upward to meet the oncoming german air armada but from the ground it could be seen that the man in the observer s place in the top was making desperate signals","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":442,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4057\/Lab41-SRI-VOiCES-rm1-none-sp4057-ch012085-sg0006-mc02-lav-clo-dg150.wav","answer":"hand out your valuables a man of medium height wearing a mask and full beard stood over him darrell quietly handed over his watch and purse noting as he did so the man's hands white well formed well kept","subset":"none","task_type":"understanding","prediction":"hand out your valuables a man of medium height wearing a mask and full beard stood over him darrell quietly handed over his watch and purse noting as he did so the man s hands white well formed well kept","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":443,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm1-none-sp4064-ch019132-sg0011-mc02-lav-clo-dg010.wav","answer":"mister gamble proposed that they visit one of the theatres he had a box all ready it seemed and oliver accepted for alice before montague could say a word for her he spoke for himself however he had important work to do and must be excused","subset":"none","task_type":"understanding","prediction":"mr gamble proposed that they visit one of the theatres he had a box all ready it seemed and oliver accepted for alice before montague could say a word for her he spoke for himself however he had important work to do and must be excused","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":444,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm1-none-sp4064-ch019132-sg0034-mc01-stu-clo-dg060.wav","answer":"nothing said the other she is simply ruining herself said oliver i've been trying to get reggie mann to have her introduced to missus devon but he says he wouldn't dare to take the risk no i presume not said montague","subset":"none","task_type":"understanding","prediction":"nothing said the other she is simply ruining herself said oliver i have been trying to get reggie mann to have her introduced to mrs devon but he says he wouldn't dare to take the risk no i presume not said montague","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":445,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm1-none-sp4064-ch077779-sg0014-mc02-lav-clo-dg010.wav","answer":"and provokes a great deal of innocent mirth you don't yourself believe that last yarn about the prohibition candidate do you i haven't heard any yarn about him said the bibliomaniac that he is the owner of a brewery up in rochester","subset":"none","task_type":"understanding","prediction":"and provokes a great deal of innocent mirth you dont yourself believe that last yarn about the prohibition candidate do you i haven t heard any yarn about him said the bibliomaniac that he is the owner of a brewery up in rochester","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":446,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm1-none-sp4064-ch077779-sg0028-mc01-stu-clo-dg170.wav","answer":"can have no private life then you approve of these stories of candidates cousins the prattling anecdotes of their grandchildren these paragraphs narrating the doings of their uncles in law and all that sneered the bibliomaniac","subset":"none","task_type":"understanding","prediction":"can have no private life then you approve of these stories of candidates cousins the prattling anecdotes of their grandchildren these paragraphs narrating the doings of their uncles in law and all that sneered the bibliomaniac","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":447,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4110\/Lab41-SRI-VOiCES-rm1-none-sp4110-ch011533-sg0018-mc01-stu-clo-dg150.wav","answer":"he hoped also to see from above something of the result of the strange aerial bombardment of which his father had spoken in their flight which had been to them a flight through the glories of a super heavenly universe they had lost all count of time","subset":"none","task_type":"understanding","prediction":"he hoped also to see from above something of the result of the strange aerial bombardment of which his father had spoken in their flight which had been to them a flight through the glories of a super heavenly universe they had lost all count of time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":448,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4116\/Lab41-SRI-VOiCES-rm1-none-sp4116-ch003582-sg0035-mc02-lav-clo-dg140.wav","answer":"for we should never get the child here again if we let her go now and i talked well i had to talk some but well the upshot is i did get her and i did bring her and here she is and the old gentleman was so delighted with his success","subset":"none","task_type":"understanding","prediction":"for we should never get the child here again if we let her go now and i talked well i had to talk some but well the upshot is i did get her and i did bring her and here she is and the old gentleman was so delighted with his success","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":449,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4116\/Lab41-SRI-VOiCES-rm1-none-sp4116-ch013256-sg0021-mc02-lav-clo-dg020.wav","answer":"the devil is waiting for me see him she exclaimed hoarsely she turned and pointed with a shaking finger at the saloon keeper the crowd laughed virginia stepped up to her and put her arm about her loreen she said firmly come with me","subset":"none","task_type":"understanding","prediction":"the devil is waiting for me see him she exclaimed hoarsely she turned and pointed with a shaking finger at the saloon keeper the crowd laughed virginia stepped up to her and put her arm about her laurine she said firmly come with me","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":450,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4116\/Lab41-SRI-VOiCES-rm1-none-sp4116-ch013265-sg0019-mc02-lav-clo-dg010.wav","answer":"people can't live at that concert pitch all the time you see if rachel doesn't give it up soon it's a great pity she doesn't come to chicago and sing in the auditorium concerts she has received an offer i'm going to write and urge her to come i'm just dying to hear her sing felicia","subset":"none","task_type":"understanding","prediction":"people can live at that concert pitch all the time you see if rachel doesn't give it up soon it is a great pity she doesn't come to chicago and sing in the auditorium concerts she has received an offer i am going to write and urge her to come i am just dying to hear her sing valasia","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":451,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4145\/Lab41-SRI-VOiCES-rm1-none-sp4145-ch104606-sg0003-mc02-lav-clo-dg050.wav","answer":"in her astonishment she all but knocked the lamp over jack laughed i believe he said you two have met before madge continued speechless she passed her hand before her eyes as if to make sure she was not dreaming","subset":"none","task_type":"understanding","prediction":"in her astonishment she all but knocked the lamp over jack laughed i believe he said you two have met before madge continued speechless she passed her hand before her eyes as if to make sure she was not dreaming","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":452,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4331\/Lab41-SRI-VOiCES-rm1-none-sp4331-ch057179-sg0037-mc01-stu-clo-dg040.wav","answer":"to the duchess condemnation from lady augustus almost amounted to praise she felt sure that mister morton was a worthy man who would not probably behave badly and though she could not unravel the mystery and certainly had no suspicion in regard to lord rufford","subset":"none","task_type":"understanding","prediction":"to the duchess condemnation from lady augustus almost amounted to praise she felt sure that mr morton was a worthy man who had not probably behaved badly and though she could not unravel the mystery and certainly had no suspicion in regard to lord rufford","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":453,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4331\/Lab41-SRI-VOiCES-rm1-none-sp4331-ch057180-sg0021-mc02-lav-clo-dg110.wav","answer":"an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said up stairs they could not have talked as they were then talking","subset":"none","task_type":"understanding","prediction":"an arrangement which her grace had thought safe with reference to the rights of the minister to patagonia the duchess though she was at some distance down the table had seen that her niece and lord rufford were intimate and remembered immediately what had been said upstairs they could not have talked as they were then talking","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":454,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm1-none-sp4427-ch041933-sg0034-mc01-stu-clo-dg020.wav","answer":"and were feeling quite happy when suddenly they heard the sound of a gallop far behind them the prince sprang from the saddle and laid his ear to the ground they are pursuing us he said then there is no time to be lost answered the princess","subset":"none","task_type":"understanding","prediction":"and were feeling quite happy when suddenly they heard the sound of a gallop far behind them the prince sprang from the saddle and laid his ear to the ground they are pursuing us he said then there is no time to be lost answered the princess","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":455,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm1-none-sp4438-ch048525-sg0011-mc01-stu-clo-dg080.wav","answer":"the kindest and gentlest of men hadn't been kind and gentle but unjust by explaining well that was at the very beginning she soon learned that a doubt in her mind was better kept there","subset":"none","task_type":"understanding","prediction":"the kindest and gentlest of men hadnt been kind and gentle but unjust by explaining well that was at the very beginning she soon learned that a doubt in her mind was better kept there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":456,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm1-none-sp4441-ch076250-sg0004-mc01-stu-clo-dg050.wav","answer":"vex you old man you expect me to keep my vexations to myself but you lie lay old girl i say lie your burdens on my shoulders too was that what you promised me when we got married","subset":"none","task_type":"understanding","prediction":"vex you old man you expect me to keep my vexation to myself but you lie lay old girl i said lie your burden is on my shoulders too was that what you promised me when we got married","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":457,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm1-none-sp4441-ch076262-sg0018-mc01-stu-clo-dg030.wav","answer":"as if he wanted to force his thoughts into another groove it's my birthday and i want you to have breakfast with me agnes who had seen the train rushing straight at her felt relieved she burst into merry laughter and embraced falander but as breakfast has been ordered for eleven we'll have to wait a while","subset":"none","task_type":"understanding","prediction":"as if he wanted to force his thoughts into another groove it is my birthday and i want you to have breakfast with me agnes who had seen the train rushing straight at her felt relieved she burst into merry laughter and embraced philander but as breakfast has been ordered for eleven we will have to wait a while","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":458,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm1-none-sp4535-ch279849-sg0019-mc01-stu-clo-dg030.wav","answer":"brown took the throttle and pushed the general onward toward green's station tom put the last of the fuel in the fire and leaned wearily against the cab drops of rain carried by the wind splashed upon him and ran down his body streaking the soot which covered his chest and stomach","subset":"none","task_type":"understanding","prediction":"brown took the throttle and pushed the gentle onward toward green station tom put the last of the fuel in the fire and leaned wearily against the cab drops of rain carried by the wind splashed upon him and ran down his body streaking the soot which covered his chest and stomach","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":459,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm1-none-sp4535-ch279856-sg0001-mc02-lav-clo-dg170.wav","answer":"she answered crying i won't let you here joe and sam put those things down and stay here oh tom they'll surely catch you if you try it she clutched his arm as though to hold him from running into the woods but marjorie there's nothing we can do he protested please go back","subset":"none","task_type":"understanding","prediction":"she answered crying i won t let you here joe and sam put those things down and stay here oh tom they ll surely catch you if you try it she clutched his arm as though to hold him from running into the woods but marjorie there s nothing we can do he protested please go back","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":460,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm1-none-sp4839-ch015307-sg0016-mc02-lav-clo-dg060.wav","answer":"to save it who would refuse to risk his own life and that of his children if the defence of padua is the pledge for the salvation of venice who would hesitate to go and defend it and though the forces already there were sufficient is not our honor also concerned therein","subset":"none","task_type":"understanding","prediction":"to save it who would refuse to risk his own life and that of his children if the defence of padua is the pledge for the salvation of venice who would hesitate to go and defend it and though the forces already there were sufficient is not our honour also concerned therein","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":461,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm1-none-sp4839-ch015307-sg0030-mc01-stu-clo-dg010.wav","answer":"it needs not so much thought my lord send word to the emperor that we are all ready i am even now a weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of ymbercourt","subset":"none","task_type":"understanding","prediction":"it needs not so much thought my lord send word to the emperor that we are all ready i am even now weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of imbocor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":462,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm1-none-sp4848-ch029108-sg0006-mc01-stu-clo-dg050.wav","answer":"the nearer it grows to the time when it will start same as every day you live brings you nearer to nearer the grave well no not that exactly but you can't understand these things","subset":"none","task_type":"understanding","prediction":"the nearer it grows to the time when it will start same as every day you live brings you nearer to nearer the grave well no not that exactly but you cannot understand these things","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":463,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm1-none-sp4848-ch101836-sg0026-mc01-stu-clo-dg170.wav","answer":"the man who was released from the trap persuaded the people that some evil would come out of it and affect the children of the sultan and the children of the vizir then the people became excited and tied the hands of mvoo laana behind him","subset":"none","task_type":"understanding","prediction":"the man who was released from the trap persuaded the people that some evil would come out of it and affect the children of the sultan and the children of the vizier then the people became excited and tied the hands of mvoo laana behind him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":464,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4859\/Lab41-SRI-VOiCES-rm1-none-sp4859-ch029340-sg0018-mc01-stu-clo-dg080.wav","answer":"fichte chateaubriand and others the historian evidently decomposes alexander's power into the components talleyrand chateaubriand and the rest but the sum of the components that is the interactions of chateaubriand","subset":"none","task_type":"understanding","prediction":"fichte chateaubriand and others the historian evidently decomposes alexander s power into the components talleyrand chateaubriand and the rest but the sum of the components that is the interactions of chateaubriand","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":465,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp4957\/Lab41-SRI-VOiCES-rm1-none-sp4957-ch023295-sg0030-mc02-lav-clo-dg120.wav","answer":"not entirely replied matilda and since it is granted i am careless but she told me her letter concerned none but me to explain perfectly to matilda lady elmwood's letter and that she might perfectly understand upon what terms she was admitted into elmwood castle","subset":"none","task_type":"understanding","prediction":"not entirely replied matilda and since it is granted i am careless but she told me her letter concerned not but me to explain perfectly to matilda lady elmwood's letter and that she might perfectly understand upon what terms she was admitted into elmwood castle","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":466,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5126\/Lab41-SRI-VOiCES-rm1-none-sp5126-ch027504-sg0008-mc02-lav-clo-dg140.wav","answer":"and falls backards and breaks his neck if he ain't watched whose business was it to have learned me better that i can't rightly say but it seemed it was the business of the government people to gaol me and iron me and flog me was that justice","subset":"none","task_type":"understanding","prediction":"and falls backward and breaks his neck if he ain t watched whose business was it to have learned me better that i can t rightly say but it seemed it was the business of the government people to gall me and iron me and flog me was that justice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":467,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5126\/Lab41-SRI-VOiCES-rm1-none-sp5126-ch034483-sg0012-mc02-lav-clo-dg170.wav","answer":"but nice for the object which she now had in view in the church there was no one but the peasants the servants and their women folk but darya alexandrovna saw or fancied she saw","subset":"none","task_type":"understanding","prediction":"but nice for the object which he now had in view in the church there was no one but the peasants the servants and their women folk but darya alexandrovna saw or fancied she saw","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":468,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm1-none-sp5154-ch006174-sg0005-mc01-stu-clo-dg180.wav","answer":"although they were many she could only play with one at a time and that indeed troubled her a little or live lambs that were not all wool or the sheep dogs which were very friendly with her and the best of playfellows as she thought for she had no human ones to compare them with","subset":"none","task_type":"understanding","prediction":"although there were many she could only play with one at a time and that indeed troubled her a little or live lambs that were not all wool or the sheep dogs which were very friendly with her and the best of playfellows as she thought for she had no human ones to compare them with","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":469,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm1-none-sp5154-ch006174-sg0028-mc01-stu-clo-dg100.wav","answer":"was not so terrible or dangerous as the wrathful one the conceited one however was sometimes very angry and then her anger was more spiteful than the other's and again the wrathful one was often very conceited too","subset":"none","task_type":"understanding","prediction":"was not so terrible or dangerous as the wrathful one the conceited one however was sometimes very angry and then her anger was more spiteful than the others and again the wrathful one was often very conceited too","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":470,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm1-none-sp5154-ch026559-sg0010-mc02-lav-clo-dg080.wav","answer":"when the little boy was rubbing his eyes to get the dirt out of them the monkey made a sudden dash out of the cave and escaped to the tree tops when the man returned the little boy did not dare to tell him that the monkey had escaped the man waited and waited and waited","subset":"none","task_type":"understanding","prediction":"when the little boy was rubbing his eyes to get the dirt out of them the monkey made a sudden dash out of the cave and escaped to the tree tops when the man returned the little boy did not dare to tell him that the monkey had escaped the man waited and waited and waited","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":471,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm1-none-sp5154-ch026559-sg0016-mc02-lav-clo-dg160.wav","answer":"so they let the monkey fill the pot as he liked he put into it some little dry sticks and an empty cocoanut shell then he said o children o children i cannot dance any more it is so hot here in this room the children","subset":"none","task_type":"understanding","prediction":"so they let the monkey fill the pot as he liked he put into it some little dry sticks and an empty cocoanut shell then he said oh children oh children i cannot dance any more it is so hot here in this room the children","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":472,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5157\/Lab41-SRI-VOiCES-rm1-none-sp5157-ch047238-sg0003-mc02-lav-clo-dg170.wav","answer":"which should join you as soon as the weather would permit at present indeed it is not very encouraging for row boats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry","subset":"none","task_type":"understanding","prediction":"would should join you as soon as the weather would permit at present indeed it is not very encouraging for rowboats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":473,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm1-none-sp5189-ch037999-sg0001-mc01-stu-clo-dg030.wav","answer":"for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries to the trip east together with minute instructions as to the journey itself selecting a proper school","subset":"none","task_type":"understanding","prediction":"for the benefit of those who are making this trip for the first time we outline a few of the more important points in connection with the preliminaries of the trip east together with minute instructions as to the journey itself selecting a proper school","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":474,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5386\/Lab41-SRI-VOiCES-rm1-none-sp5386-ch004145-sg0012-mc02-lav-clo-dg110.wav","answer":"should do our utmost to extirpate slavery from the land for my own part i shall do all i can when the redeemer was about to ascend to the bosom of the father and resume the glory which he had with him before the world was he promised his disciples that the power of the holy ghost should come upon them","subset":"none","task_type":"understanding","prediction":"should do our utmost to extirpate slavery from the land for my own part i shall do all i can when the redeemer was about to ascend to the bosom of the father and resume the glory which he had with him before the world was he promised his disciples that the power of the holy ghost should come upon them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":475,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm1-none-sp5401-ch039508-sg0007-mc01-stu-clo-dg150.wav","answer":"and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly play a very important part which will be more strongly altered","subset":"none","task_type":"understanding","prediction":"and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly played a very important part which will be more strongly altered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":476,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm1-none-sp5456-ch062014-sg0000-mc02-lav-clo-dg180.wav","answer":"the woman who married an owl by anne virginia culbertson when the children got home from the nutting expedition and had eaten supper they sat around discontentedly wishing every few minutes that their mother had returned i wish mamma would come back","subset":"none","task_type":"understanding","prediction":"the woman who married an owl by ann virginia culbertson when the children got home from the nutting expedition and had eaten supper they sat around discontentedly wishing every few minutes that their mother had returned i wish mamma would come back","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":477,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm1-none-sp5635-ch044582-sg0022-mc01-stu-clo-dg080.wav","answer":"such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration","subset":"none","task_type":"understanding","prediction":"such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":478,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm1-none-sp5717-ch061421-sg0010-mc01-stu-clo-dg150.wav","answer":"as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and you'll forget there was no answer billy and you'll forget bertram's voice was insistent reproachful","subset":"none","task_type":"understanding","prediction":"as he followed her into the kitchen after the sorry meal was over why yes dear yes sighed billy trying to smile and youll forget there was no answer billy and youll forget bertram's voice was insistent reproachful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":479,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm1-none-sp5717-ch100145-sg0019-mc02-lav-clo-dg030.wav","answer":"that is the problem of the adityan mastership they are your slaves we have neither the intention nor the right to free them but let me remind you that slavery is specifically prohibited by the imperial constitution","subset":"none","task_type":"understanding","prediction":"that is the problem of the addykin mastership they are your slaves we have neither the intention nor the right to free them but let me remind you that slavery is specifically prohibited by the imperial constitution","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":480,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5740\/Lab41-SRI-VOiCES-rm1-none-sp5740-ch097610-sg0039-mc02-lav-clo-dg160.wav","answer":"for a christmas present pretty little fido said kitty taking the soft curly creature in her arms i think it's the best present in the world and to morrow is to be real christmas because you are home papa and we'll eat the turkey said harry","subset":"none","task_type":"understanding","prediction":"for a christmas present pretty little fido said kitty taking the soft curly creature in her arms i think it is the best present in the world and to morrow is to be real christmas because you are home papa and we will eat the turkey said harry","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":481,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5789\/Lab41-SRI-VOiCES-rm1-none-sp5789-ch057158-sg0008-mc01-stu-clo-dg080.wav","answer":"and missus masters had more than once said that that kind of thing must be all over meaning that mary was to drop her intimacy with high born people that were of no real use and then there was mister twentyman and his suit","subset":"none","task_type":"understanding","prediction":"and mrs masters had more than once said that that kind of thing must be all over meaning that mary was to drop her intimacy with high born people that were of no real use and then there was mr twentyman and his suit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":482,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5802\/Lab41-SRI-VOiCES-rm1-none-sp5802-ch076043-sg0024-mc02-lav-clo-dg150.wav","answer":"he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burthen without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great gnomon of silbury","subset":"none","task_type":"understanding","prediction":"he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burden without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great knoll of silbury","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":483,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm1-none-sp5868-ch066166-sg0027-mc01-stu-clo-dg120.wav","answer":"according to his own account he must have been shipwrecked at least twice a year ever since his birth he had served under decatur when that gallant officer peppered the algerines and made them promise not to sell their prisoners of war into slavery he had worked a gun at the bombardment of vera cruz in the mexican war","subset":"none","task_type":"understanding","prediction":"according to his own account he must have been shipwrecked at least twice a year ever since his birth he had served under decatur when that gallant officer peppered the algerines and made them promise not to sell their prisoners of war into slavery he had worked a gun at the bombardment of vera cruz in the mexican war","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":484,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp6099\/Lab41-SRI-VOiCES-rm1-none-sp6099-ch069550-sg0029-mc01-stu-clo-dg170.wav","answer":"there was jimmu tenno the first real emperor his hair was done in a curious fashion and his dress was of a wonderful brocade while his hands clasped two fierce looking swords","subset":"none","task_type":"understanding","prediction":"there was jiboutenno the first real emperor his hair was done in a curious fashion and his dress was of a wonderful brocade while his hands clasped two fierce looking swords","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":485,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm1-none-sp6147-ch034605-sg0025-mc01-stu-clo-dg020.wav","answer":"to whom it was said he had sold his sister miss churchill bolingbroke was in his meridian and richelieu in his dawn gallantry found its convenience in a certain medley of ranks men were equalized by the same vices as they were later on perhaps by the same ideas","subset":"none","task_type":"understanding","prediction":"to whom it was said he had sold his sister miss churchill bolingbroke was in his meridian and richelieu in his dawn gallantry found its convenience in a certain medley of ranks men were equalized by the same vices as they were later on perhaps by the same ideas","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":486,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm1-none-sp6241-ch066616-sg0011-mc02-lav-clo-dg010.wav","answer":"consequently both mother and father began their education at the post they were sent to the factor's school and two winters were passed in port arthur that they might have the advantage of thoroughly equipped schools","subset":"none","task_type":"understanding","prediction":"consequently both mother and father began their education at the post they were sent to the factor school and two winters were passed in port arthur that they might have the advantage of thoroughly equipped schools","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":487,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6319\/Lab41-SRI-VOiCES-rm1-none-sp6319-ch275224-sg0005-mc02-lav-clo-dg130.wav","answer":"still the rose tree stood out that there must be some great advantages in a gardener's care for she could not pretend to be ignorant of her own superiority to all her wild relations in the woods","subset":"none","task_type":"understanding","prediction":"still the rose tree stood out that there must be some great advantages in a gardener s care for she could not pretend to be ignorant of her own superiority to all her wild relations in the woods","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":488,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm1-none-sp6385-ch034655-sg0022-mc01-stu-clo-dg170.wav","answer":"representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners","subset":"none","task_type":"understanding","prediction":"representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":489,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm1-none-sp6395-ch087997-sg0045-mc02-lav-clo-dg090.wav","answer":"but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive","subset":"none","task_type":"understanding","prediction":"but which is so often accompanied with frivolous and superficial qualities was in him certainly attended with the most severe application the most extensive learning the greatest depth of thought and a capacity in every respect the most comprehensive","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":490,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm1-none-sp6395-ch087997-sg0046-mc01-stu-clo-dg000.wav","answer":"upon the whole i have always considered him both in his lifetime and since his death as approaching as nearly to the idea of a perfectly wise and virtuous man as perhaps the nature of human frailty will permit i ever am dear sir","subset":"none","task_type":"understanding","prediction":"upon the whole i have always considered him both in his lifetime and since his death as approaching as nearly to the idea of a perfectly wise and virtuous man as perhaps the nature of human frailty will permit i ever am dear sir","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":491,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm1-none-sp6415-ch111615-sg0011-mc02-lav-clo-dg170.wav","answer":"came very near ending as a complete cynic though in what f p a would call his lastline he managed to wriggle into a more hopeful mood the first valuable discovery that the colyumist is likely to make is that all minds are very much the same","subset":"none","task_type":"understanding","prediction":"came very near ending as a complete cynic though in what fpa would call his last line he managed to wriggle into a more hopeful mood the first valuable discovery that the columnists is likely to make is that all minds are very much the same","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":492,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm1-none-sp6415-ch116629-sg0007-mc01-stu-clo-dg060.wav","answer":"come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to","subset":"none","task_type":"understanding","prediction":"come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":493,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm1-none-sp6454-ch093938-sg0018-mc02-lav-clo-dg000.wav","answer":"two hundred feet therefore brought me to the edge of the town and i wheeled my pony and rode down behind the rear of the buildings in turning i looked back and saw half a dozen mounted men already in pursuit","subset":"none","task_type":"understanding","prediction":"two hundred feet therefore brought me to the edge of the town and i wheeled my pony and rode down behind the rear of the buildings in turning i looked back and saw half a dozen mounted men already in pursuit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":494,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm1-none-sp6454-ch107462-sg0008-mc02-lav-clo-dg140.wav","answer":"and setting the whisky bottle betwixt his customer and himself with a nod which said help yourself he would lean forward with the soft indulgent grin of the human man of the world and begin now","subset":"none","task_type":"understanding","prediction":"and setting the whiskey bottle betwixt his customer and himself with a nod which said help yourself he would lean forward with the soft indulgent grin of the human man of the world and begin now","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":495,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm1-none-sp6454-ch107462-sg0013-mc02-lav-clo-dg120.wav","answer":"deasey would make reply but twas from a certain person whom perhaps we need not name then the whiskey bottle would move forward like a pawn in chess and the next soothing words would be","subset":"none","task_type":"understanding","prediction":"d c would make reply but twas from a certain person whom perhaps we need not name then the whiskey bottle would move forward like a pawn in chess and the next soothing words would be","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":496,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm1-none-sp6519-ch231834-sg0033-mc01-stu-clo-dg080.wav","answer":"tossing her head and gliding towards the door it ain't for me to say what i think i am the last person in the world to meddle with what don't concern me that i am and thus ending the conversation miss greeb vanished with significant look and pursed up lips","subset":"none","task_type":"understanding","prediction":"tossing her head and gliding toward the door it ain't for me to say what i think i am the last person in the world to meddle with what don't concern me that i am and thus ending the conversation miss screeb vanished with significant look and pursed up lips","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":497,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm1-none-sp6544-ch067863-sg0023-mc02-lav-clo-dg110.wav","answer":"and aunt connie rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with missus carleton a little while before supper and told her of what uncle peter had said that ships from the north were on the way to the aid of fort sumter","subset":"none","task_type":"understanding","prediction":"and aunt conny rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with mrs carlton a little while before supper and told her of what uncle peter had said that ships from the north were on their way to the aid of fort sumter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":498,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm1-none-sp6544-ch231862-sg0011-mc01-stu-clo-dg020.wav","answer":"and as link was the moving spirit in the matter his vanity was sufficiently gratified as to make him quite amiable we've got him this time mister denzil he said with enthusiasm you and i and a couple of policemen will go down to that house in geneva square by the front sir by the front","subset":"none","task_type":"understanding","prediction":"and as link was the moving spirit in the matter his vanity was sufficiently gratified as to make him quite amiable we have got him this time mr denzil he said with enthusiasm you and i and a couple of policemen will go down to that house in geneva square by the front sir by the front","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":499,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6696\/Lab41-SRI-VOiCES-rm1-none-sp6696-ch068773-sg0018-mc01-stu-clo-dg070.wav","answer":"he was not yet thoroughly rested but night was approaching and he reflected that he could obtain all the sleep that he needed then so greatly refreshed and in a quieter mood than he had been for days the young man dressed and entered the hall to find his way downstairs","subset":"none","task_type":"understanding","prediction":"he was not yet thoroughly rested but night was approaching and he reflected that he could obtain all the sleep that he needed then so greatly refreshed and in a quieter mood than he had been for days the young man dressed and entered the hall to find his way downstairs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":500,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-none-sp6895-ch092805-sg0034-mc01-stu-clo-dg020.wav","answer":"but cling to their cities hem as a child to the mother's gown not so e rushmore coglan with the whole world for his my meditations were interrupted by a tremendous noise and conflict in another part of the cafe i saw above the heads of the seated patrons","subset":"none","task_type":"understanding","prediction":"but cling to their citys hem as a child to the mothers gown not so e rushmore coblen with the whole world for his my meditations were interrupted by a tremendous noise and conflict in another part of the cafe i saw above the heads of the seated patrons","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":501,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm1-none-sp7000-ch083708-sg0020-mc01-stu-clo-dg130.wav","answer":"he drew one out and threw it up to me my second ball was a colourable imitation of my first only this time it was wide to leg to long leg mister benyon sent it flying put down tom benyon another six he cried i do like your bowling mister","subset":"none","task_type":"understanding","prediction":"he drew one out and threw it up to me my second ball was a colourable imitation of my first only this time it was wide to leg to long leg mr benyon sent it flying put down tom benyon another six he cried i do like your bowling mister","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":502,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm1-none-sp7148-ch007763-sg0001-mc02-lav-clo-dg130.wav","answer":"it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing","subset":"none","task_type":"understanding","prediction":"it was of no common importance to me at this period to be able to digest and mature my thoughts for my own mind only without any immediate call for giving them out in print had i gone on writing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":503,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7247\/Lab41-SRI-VOiCES-rm1-none-sp7247-ch077778-sg0026-mc02-lav-clo-dg050.wav","answer":"the awful pain that was gradually gnawing away at his vitals seemed to lose its poignancy in the face of the greater suffering and physical relief was instant as the musician proceeded the internal disorder yielded gradually to the external and finally passed away","subset":"none","task_type":"understanding","prediction":"the awful pain that was gradually gnawing away at his vitals seemed to lose its poignancy in the face of the greater suffering and physical relief was instant as the musician proceeded the internal disorder yielded gradually to the external and finally passed away","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":504,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7247\/Lab41-SRI-VOiCES-rm1-none-sp7247-ch094108-sg0022-mc02-lav-clo-dg020.wav","answer":"while upon the left bank surmounting a high rock strewn beach is the dilapidated frame house of a west virginia cracker through whose garden patch the line takes its way unobserved and unthought of by pigs chickens and children which in hopeless promiscuity swarm the interstate premises","subset":"none","task_type":"understanding","prediction":"while upon the left bank surrounding a high rock strewn beach is the dilapidated frame house of a west virginia cracker through whose garden patch the line takes its way unobserved and unthought of by pigs chickens and children which in hopeless promiscuity swarm the interstate premises","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":505,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7264\/Lab41-SRI-VOiCES-rm1-none-sp7264-ch092310-sg0003-mc01-stu-clo-dg140.wav","answer":"where a great daily paper is concerned he was compelled then to respect his advertisers as his paymasters to that extent therefore his power of giving true news and of printing sound opinion was limited even though his own inclinations should lean towards such news and such opinion","subset":"none","task_type":"understanding","prediction":"where a great daily paper is concerned he was compelled then to respect his advertisers as his paymasters to that extent therefore his power of giving true news and of printing sound opinion was limited even though his own inclinations should lean towards such news and such opinion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":506,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm1-none-sp7278-ch091083-sg0018-mc01-stu-clo-dg120.wav","answer":"as a publisher but the prize that he had set out to win was to own the public ledger the opportunity came in december eighteen sixty four but his paper was losing money his friends advised against taking such a burden he would surely fail","subset":"none","task_type":"understanding","prediction":"as a publisher but the prize that he had set out to win was to own the public ledger the opportunity came in december eighteen sixty four but his paper was losing money his friends advised against taking such a burden he would surely fail","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":507,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm1-none-sp7278-ch104730-sg0026-mc01-stu-clo-dg060.wav","answer":"as then made up the house of representatives wore hardly even upon the iron temper and inflexible disposition of mister adams the most insignificant error of conduct in me at this time he writes in april","subset":"none","task_type":"understanding","prediction":"as then made up the house of representatives were hardly even upon the iron temper and inflexible disposition of mr. ames the most insignificant error of conduct in may at this time he writes in april","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":508,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm1-none-sp7278-ch104730-sg0039-mc01-stu-clo-dg090.wav","answer":"i said that in another part of the capitol it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence' here a loud cry of order order burst forth in which the speaker yelled the loudest","subset":"none","task_type":"understanding","prediction":"i said that in another part of the capitol it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence here a loud cry of order order burst forth in which the speaker yelled the loudest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":509,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm1-none-sp7278-ch246956-sg0032-mc01-stu-clo-dg110.wav","answer":"let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves","subset":"none","task_type":"understanding","prediction":"let him preach again to enforce the truth for which he is jealous and if it should seem to any that the two utterances need reconciling let those who would have them consistent reconcile them for themselves","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":510,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7517\/Lab41-SRI-VOiCES-rm1-none-sp7517-ch100442-sg0005-mc01-stu-clo-dg110.wav","answer":"we grocers only put the currants out for show and so that we may run our fingers through them luxuriously when business is slack i have a good line in shortbreads madam if i can find the box","subset":"none","task_type":"understanding","prediction":"we grocers only put the currants out for show and so that we may run our fingers through them luxuriously when business is slack i have a good line in shortbreads madam if i can find the box","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":511,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm1-none-sp7850-ch111771-sg0007-mc01-stu-clo-dg160.wav","answer":"time wore away and on the ninth of april eighteen sixty five grant captured the confederate army under lee thus virtually ending the war","subset":"none","task_type":"understanding","prediction":"time wore away and on the ninth of april eighteen sixty five grant captured the confederate army under lee thus virtually ending the war","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":512,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm1-none-sp7850-ch286674-sg0005-mc01-stu-clo-dg140.wav","answer":"they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies","subset":"none","task_type":"understanding","prediction":"They did not breathe it into their mouths or through gills. But took it in through some openings in the back part of their bodies.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":513,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm1-none-sp7850-ch286674-sg0005-mc02-lav-clo-dg140.wav","answer":"they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies","subset":"none","task_type":"understanding","prediction":"they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":514,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7867\/Lab41-SRI-VOiCES-rm1-none-sp7867-ch275218-sg0001-mc01-stu-clo-dg150.wav","answer":"when the gulf of mexico rolled its warm and shallow waters as far north as escanaba and eau claire in fact an immensely long time ago there lived somewhere in oconto county wisconsin a little jelly fish","subset":"none","task_type":"understanding","prediction":"When the Gulf of Mexico rolled its warm and shallow waters as far north as Escanaba and Eau Claire, in fact. An immensely long time ago, there lived somewhere in Oconto County, Wisconsin, a little jellyfish.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":515,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm1-none-sp7868-ch110705-sg0018-mc02-lav-clo-dg040.wav","answer":"something like that of a kettle on the boil gluck looked out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment","subset":"none","task_type":"understanding","prediction":"something like that of a kettle on the boil luck was out of the window no it was certainly in the house upstairs and downstairs no it was certainly in that very room coming in quicker time and clearer notes every moment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":516,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm1-none-sp7881-ch105574-sg0015-mc01-stu-clo-dg040.wav","answer":"yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us","subset":"none","task_type":"understanding","prediction":"yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":517,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm1-none-sp7881-ch109662-sg0027-mc02-lav-clo-dg180.wav","answer":"and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet","subset":"none","task_type":"understanding","prediction":"and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":518,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm1-none-sp7932-ch110056-sg0022-mc01-stu-clo-dg180.wav","answer":"and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by","subset":"none","task_type":"understanding","prediction":"and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":519,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-none-sp7976-ch105575-sg0013-mc02-lav-clo-dg010.wav","answer":"when morning came the firing opened and for all that day the battle raged fiercely at the left and center left we getting the worst of it too","subset":"none","task_type":"understanding","prediction":"when morning came the firing opened and for all that day the battle raged fiercely at the left and center left we getting the worst of it too","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":520,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-none-sp7976-ch105575-sg0029-mc01-stu-clo-dg050.wav","answer":"a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war","subset":"none","task_type":"understanding","prediction":"a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":521,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-none-sp7976-ch110124-sg0006-mc02-lav-clo-dg110.wav","answer":"it's surely a terrible storm outside said the merchant's eldest daughter as the wind rattled the tiles of the roof and the rain beat in torrents against the doors and windows","subset":"none","task_type":"understanding","prediction":"it is surely a terrible storm outside said the merchant s eldest daughter as the wind rattled the tiles of the roof and the rain beat in torrents against the doors and windows","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":522,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm1-none-sp7976-ch110523-sg0010-mc02-lav-clo-dg110.wav","answer":"hansel thought the roof tasted very nice and so he tore off a great piece while grethel broke a large round pane out of the window and sat down quite contentedly","subset":"none","task_type":"understanding","prediction":"hansel thought the roof tasted very nice and so he tore off a great piece while grethel broke a large round pane out of the window and sat down quite contentedly","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":523,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-none-sp7981-ch112057-sg0025-mc02-lav-clo-dg170.wav","answer":"madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money","subset":"none","task_type":"understanding","prediction":"madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":524,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-none-sp7981-ch112057-sg0035-mc01-stu-clo-dg030.wav","answer":"this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns taking marseilles as his first station here where the conditions were perhaps even worse than in paris","subset":"none","task_type":"understanding","prediction":"this enabled vincent to carry his mission farther afield and he determined to visit all the convict prisons in the seaport towns picking marseilles as his first station here where the conditions were perhaps even worse than in paris","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":525,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-none-sp7981-ch112058-sg0024-mc01-stu-clo-dg070.wav","answer":"and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries","subset":"none","task_type":"understanding","prediction":"and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":526,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8051\/Lab41-SRI-VOiCES-rm1-none-sp8051-ch118101-sg0035-mc02-lav-clo-dg090.wav","answer":"rather smart black well made and well calculated for a canadian he was prompted to escape purely from the desire to be free he fled from a very insulting man by the name of edward schriner from the neighborhood of sairsville mills","subset":"none","task_type":"understanding","prediction":"rather smart black well made and well calculated for a canadian he was prompted to escape purely from the desire to be free he fled from a very insulting man by the name of edward schreiner from the neighborhood of sairsville mills","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":527,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8057\/Lab41-SRI-VOiCES-rm1-none-sp8057-ch284428-sg0034-mc02-lav-clo-dg010.wav","answer":"and the only thing i object to is electing the boolooroo for only three hundred years it ought to be for life my successor has already been elected but he can't reign for a hundred years to come i think three hundred years is plenty long enough","subset":"none","task_type":"understanding","prediction":"and the only thing i object to is electing the boolooroo for only three hundred years it ought to be for life my successor has already been elected but he can t reign for a hundred years to come i think three hundred years is plenty long enough","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":528,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm1-none-sp8108-ch274318-sg0046-mc02-lav-clo-dg130.wav","answer":"and uttering little soft sounds of affection in his throat the doctor lit the candle and brought it over he saw the collie lying on its side against the wall it was utterly exhausted and foam still hung about its jaws its tail and eyes responded to the sound of its name","subset":"none","task_type":"understanding","prediction":"and uttering little soft sounds of affection in his throat the doctor lit the candle and brought it over he saw the collie lying on its side against the wall it was utterly exhausted and foam still hung about its jaws its tail and eyes responded to the sound of its name","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":529,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm1-none-sp8108-ch280359-sg0017-mc01-stu-clo-dg010.wav","answer":"and drag out whatever living thing they could find there it was done as he desired thor held one end of the net and all the rest of the gods drew the other through the water when they pulled it up the first time however it was empty and they would have gone away disappointed","subset":"none","task_type":"understanding","prediction":"and drag out whatever living thing they could find there it was done as he desired thor held one end of the net and all the rest of the gods drew the other through the water when they pulled it up the first time however it was empty and they would have gone away disappointed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":530,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8118\/Lab41-SRI-VOiCES-rm1-none-sp8118-ch114469-sg0032-mc01-stu-clo-dg160.wav","answer":"a mile or two further and in the swish of the storm he heard hoofbeats again looking forth from the bushes he saw another line of horsemen but now they were going in the direction of pope's army dick recognized these figures shapeless as he might appear on his horse that was colonel winchester","subset":"none","task_type":"understanding","prediction":"a mile or two further and in the swish of the storm he heard hoof beats again looking forth from the bushes he saw another line of horsemen but now they were going in the direction of polk s army dick recognized these figures shapeless as he might appear on his horse that was colonel winchester","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":531,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8222\/Lab41-SRI-VOiCES-rm1-none-sp8222-ch274380-sg0015-mc02-lav-clo-dg060.wav","answer":"whether if unlimited power were intrusted to the parliament during so long a period it would not be easy for them to frame the subsequent bill in the manner most agreeable to themselves and keep forever possession of the sword as well as of every article of civil power and jurisdiction","subset":"none","task_type":"understanding","prediction":"whether if unlimited power were intrusted to the parliament during so long a period it would not be easy for them to frame the subsequent bill in the manner most agreeable to themselves and keep for ever possession of the sword as well as of every article of civil power and jurisdiction","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":532,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm1-none-sp8225-ch274375-sg0001-mc02-lav-clo-dg110.wav","answer":"those parliamentary leaders it must be owned who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity","subset":"none","task_type":"understanding","prediction":"those parliamentary leaders it must be owned who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":533,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-none-sp8425-ch246962-sg0025-mc02-lav-clo-dg130.wav","answer":"yea all grand discovery for things must be foreseen ere they can be realized apprehended ere they be comprehended this much he could say for himself and no more that he was ready to lay down his life for the mere chance","subset":"none","task_type":"understanding","prediction":"yea all grand discovery for things must be foreseen ere they can be realized apprehended ere they be comprehended this much he could say for himself and no more that he was ready to lay down his life for the mere chance","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":534,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-none-sp8425-ch287387-sg0003-mc01-stu-clo-dg130.wav","answer":"and ancient art a museum for his dreaming spirit already as a child as a boy he had felt that passion for antiquity developing he learnt how to rummage through the stocks of old jewish dealers","subset":"none","task_type":"understanding","prediction":"and ancient art a museum for his dreaming spirit already as a child as a boy he had felt that passion for antiquity developing he learnt how to rummage through the stocks of old jewish dealers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":535,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-none-sp8425-ch292520-sg0014-mc01-stu-clo-dg120.wav","answer":"and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wave and solemnly sway to the wash and swell of our passing","subset":"none","task_type":"understanding","prediction":"and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wave and solemnly sway to the wash and swell of our passing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":536,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/none\/sp_6241-8713\/sp8605\/Lab41-SRI-VOiCES-rm1-none-sp8605-ch291172-sg0007-mc02-lav-clo-dg150.wav","answer":"and when deprived of their kittens feel very wretched indeed under these circumstances they will nurse and suckle almost any creature cats rearing dogs a cat of mine a few years ago suckled and reared a beautiful pomeranian dog","subset":"none","task_type":"understanding","prediction":"and when deprived of their kittens feel very wretched indeed under these circumstances they will nurse and suckle almost any creature cats rearing dogs a cat of mine a few years ago suckled and reared a beautiful pomeranian dog","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":537,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm1-tele-sp0112-ch123216-sg0003-mc02-lav-clo-dg030.wav","answer":"said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can't said anne sorrowfully","subset":"tele","task_type":"understanding","prediction":"said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can t said anne sorrowfully","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":538,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm1-tele-sp0112-ch123216-sg0022-mc02-lav-clo-dg000.wav","answer":"gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written him a nice little note of thanks but she had never worn the trinket tonight she fastened it about her white throat with a dreamy smile she and phil walked to redmond together","subset":"tele","task_type":"understanding","prediction":"gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written him a nice little note of thanks but she had never worn the trinket tonight she fastened it around her white throat with a dreamy smile she and phil walked to redmond together","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":539,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm1-tele-sp0122-ch121730-sg0019-mc02-lav-clo-dg150.wav","answer":"probably because the peach is largely a skin and stony at heart pearl a small round product manufactured by an oyster bought by a lobster and worn by a butterfly penitent from pen meaning to write and","subset":"tele","task_type":"understanding","prediction":"probably because the peach is largely skin and stony at heart pearl a small round product manufactured by an oyster bought by a lobster and worn by a butterfly penitent from pen meaning to write and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":540,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm1-tele-sp0122-ch121734-sg0016-mc02-lav-clo-dg160.wav","answer":"yellow fever a passion for reading the hearst newspapers yolk the legacy of the hen and the burden of its lay yoke the inheritance of the hen pecked and the burden of the married","subset":"tele","task_type":"understanding","prediction":"yellow fever a passion for reading the hearst newspapers yolk the legacy of the hen and the burden of its lay yoke the inheritance of the hen pecked and the burden of the merry","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":541,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm1-tele-sp0122-ch129752-sg0022-mc01-stu-clo-dg180.wav","answer":"sift three and one half cups of flour with five level teaspoons of baking powder and add to the first mixture stir well and fold in the beaten whites of two eggs beat in layer cake tins and spread the following mixture between","subset":"tele","task_type":"understanding","prediction":"sift three and one half cups of flour with five level teaspoons of baking powder and add to the first mixture stir well and fold in the beaten whites of two eggs beat in layer cake tins and spread the following mixture between","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":542,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0159\/Lab41-SRI-VOiCES-rm1-tele-sp0159-ch121891-sg0012-mc01-stu-clo-dg040.wav","answer":"for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature","subset":"tele","task_type":"understanding","prediction":"for if this ever gaping ever craving want is glutted by wealth it needs must be that the want itself which can be so glutted still remains i do not speak of how very little suffices for nature","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":543,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0174\/Lab41-SRI-VOiCES-rm1-tele-sp0174-ch050561-sg0008-mc01-stu-clo-dg160.wav","answer":"but if i play you a roundel lady get me a gift from the emperor's daughter her finger ring for my finger bring though she's pledged a thousand leagues over the water lady lady my fair lady o my rose white lady","subset":"tele","task_type":"understanding","prediction":"but if i play you around o lady get me a gift from the emperor s daughter her finger ring for my finger bring though she s pledged a thousand leagues over the water lady lady my fair lady o my rose white lady","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":544,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0174\/Lab41-SRI-VOiCES-rm1-tele-sp0174-ch168635-sg0018-mc02-lav-clo-dg040.wav","answer":"he had returned to prison this time for having done right he had quaffed fresh bitterness disgust and lassitude were overpowering him even the memory of the bishop probably suffered a temporary eclipse though sure to reappear later on luminous and triumphant but after all that sacred memory was growing dim","subset":"tele","task_type":"understanding","prediction":"he had returned to prison this time for having done right he had quaffed fresh vigor this disgust and lassitude were overpowering him even the memory of the bishop probably suffered a temporary eclipse so sure to reappear later on luminous since triumphant but after all that sacred memory was growing dim","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":545,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm1-tele-sp0204-ch148920-sg0022-mc01-stu-clo-dg070.wav","answer":"interested them for a while and ben had to be almost pulled away from the dingy old portrait of van der werf the town hall as well as the egyptian museum is on the breedstraat the longest and finest street in leyden","subset":"tele","task_type":"understanding","prediction":"interested them for a while and ben had to be almost pulled away from the dingy old portrait of van der kroos the town hall as well as the egyptian museum is on the breedstraat the longest and finest street in leyden","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":546,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm1-tele-sp0204-ch287139-sg0033-mc02-lav-clo-dg050.wav","answer":"so it was no great matter for surprise that when they got down to the hole the lugger was already under way though still close in he hailed her a voice replied telling him to keep out of the moonlight or he would get some lead in him","subset":"tele","task_type":"understanding","prediction":"so it was no great matter for surprise that when they got down to the hole the lugger was already under way though still close in he hailed her a voice replied telling him to keep out of the moonlight or he would get some lead in him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":547,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm1-tele-sp0204-ch287139-sg0037-mc01-stu-clo-dg070.wav","answer":"and to tell you the truth i should like to get it put in safety to be sure boy quite right said he i'll take it if you like i thought perhaps doctor livesey i began perfectly right","subset":"tele","task_type":"understanding","prediction":"and to tell you the truth i should like to get it put in safety to be sure boy quite right said he i ll take it if you like i thought perhaps dr livesey i began perfectly right","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":548,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm1-tele-sp0205-ch159056-sg0036-mc02-lav-clo-dg000.wav","answer":"when the squire handed him his first commission and there it is to day and on it are the verses ending this spot so sacred will forever claim a proud alliance with its hero's name wolfe was at last an officer","subset":"tele","task_type":"understanding","prediction":"when the squire handed him his first commission and there it is to day and on it are the verses ending this spot so sacred will forever claim a proud alliance with its hero s name wolfe was at last an officer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":549,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm1-tele-sp0209-ch004731-sg0000-mc02-lav-clo-dg160.wav","answer":"from his fortune his house and his daughter he could command the visits of his own little circle in a great measure as he liked he had not much intercourse with any families beyond that circle his horror of late hours and large dinner parties","subset":"tele","task_type":"understanding","prediction":"From his fortune, his house and his daughter, he could command the visits of his own little circle in great measure as he liked. He had not much intercourse with any families beyond that circle. His horror of late hours and large dinner parties.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":550,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0224\/Lab41-SRI-VOiCES-rm1-tele-sp0224-ch129790-sg0054-mc01-stu-clo-dg080.wav","answer":"we desire to make for the dutch settlement of curacao as straightly as possible will you pledge me your honour if i release you upon parole that you will navigate us thither if so we will release you and your surviving men upon arrival there","subset":"tele","task_type":"understanding","prediction":"we desire to make for the dutch settlement of curacoa as straightly as possible will you pledge me your honor if i release you upon parole that you will navigate us thither if so we will release you and your surviving men upon arrival there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":551,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch122625-sg0006-mc02-lav-clo-dg070.wav","answer":"men too often confound them they should not be confounded appearance should not be mistaken for truth narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of christ","subset":"tele","task_type":"understanding","prediction":"Men too often confound them. They should not be confounded. Appearance should not be mistaken for truth. Narrow human doctrines that only tend to elate and magnify a few should not be substituted for the world redeeming creed of Christ.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":552,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch122625-sg0009-mc02-lav-clo-dg090.wav","answer":"as the very master of that working corps who would restore to rectitude the warped system of things because i think no commentator on his writings has yet found the comparison that suits him the terms which rightly characterise his talent","subset":"tele","task_type":"understanding","prediction":"as the very master of that working corps who would restore to rectitude the warped system of things because i think no commentator on his writings has yet found the comparison that suits him the terms which rightly characterize his talent","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":553,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch122626-sg0030-mc01-stu-clo-dg170.wav","answer":"did she say that to me did you hear her eliza and georgiana won't i tell mama but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing","subset":"tele","task_type":"understanding","prediction":"did she say that to me do you hear her eliza and georgiana wont i tell mamma but first he ran headlong at me i felt him grasp my hair and my shoulder he it closed with a desperate thing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":554,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch126842-sg0018-mc01-stu-clo-dg000.wav","answer":"after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cecily desperately drawing lots is wickeder that fighting said dan","subset":"tele","task_type":"understanding","prediction":"after that no moral force on earth could have prevented felix from fighting he would have faced an army with banners you might settle it by drawing lots said cicely desperately drawing lots is wickeder than fighting said dan","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":555,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm1-tele-sp0242-ch126842-sg0034-mc01-stu-clo-dg110.wav","answer":"uncle alec walked around the corner of the granary with cecily behind him he was not angry there was a quizzical look in his eyes but he took the combatants by their shirt collars and dragged them apart this stops right here boys","subset":"tele","task_type":"understanding","prediction":"uncle alec walked around the corner of the granary with cicely behind him he was not angry there was a quizzical look in his eyes but he took the combatants by their shirt collars and dragged them apart this stops right here boys","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":556,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm1-tele-sp0459-ch127522-sg0016-mc02-lav-clo-dg020.wav","answer":"the rocks of the spy glass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain","subset":"tele","task_type":"understanding","prediction":"the rocks of the spyglass reechoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":557,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm1-tele-sp0472-ch129983-sg0005-mc02-lav-clo-dg070.wav","answer":"with almost every other man in the world it would be an alarming prospect but edward's affection and constancy nothing can deprive me of i know that conviction must be every thing to you and he is undoubtedly supported by the same trust in your's","subset":"tele","task_type":"understanding","prediction":"with almost every other man in the world it would be an alarming prospect but edward's affection and constancy nothing can deprive me of i know that conviction must be everything to you and he is undoubtedly supported by the same trust in yours","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":558,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm1-tele-sp0479-ch107479-sg0005-mc01-stu-clo-dg150.wav","answer":"and in order to quiet all suspicion of my real status in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and","subset":"tele","task_type":"understanding","prediction":"and in order to quiet all suspicion of my real status in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":559,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm1-tele-sp0479-ch134717-sg0035-mc02-lav-clo-dg010.wav","answer":"as i held as if by their hands my comrades in the night and the voice of my spirit tallied the song of the bird come lovely and soothing death undulate round the world serenely arriving arriving in the day in the night to all to each","subset":"tele","task_type":"understanding","prediction":"as i held as if by their hands my comrades in the night and the voice of my spirit tallied the song of the girl to come lovely and soothing death undulate round the world serenely arriving arriving in the day and the night to all to each","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":560,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-tele-sp0480-ch123176-sg0039-mc02-lav-clo-dg150.wav","answer":"pat a tea spoonful in a pot that will hold about two cups and pour boiling water on it let it set by the fire to draw five or ten minutes rye mush this is a nourishing and light diet for the sick","subset":"tele","task_type":"understanding","prediction":"Pat a tea spoonful in a pot that will hold about 2 cups and pour boiling water on it. Let it set by the fire to draw 5 or 10 minutes. Rye mush. This is a nourishing and light diet for the sick.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":561,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm1-tele-sp0480-ch126336-sg0017-mc01-stu-clo-dg170.wav","answer":"and broke all her goods into a thousand pieces then she began to cry and knew not what to do ah what will become of me said she what will my husband say","subset":"tele","task_type":"understanding","prediction":"and broke all her goods into a thousand pieces then she began to cry and knew not what to do ah what will become of me said she what will my husband say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":562,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm1-tele-sp0492-ch131890-sg0031-mc02-lav-clo-dg140.wav","answer":"on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the roadstead and was soon once more on the indian ocean","subset":"tele","task_type":"understanding","prediction":"on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the rogestead and was soon once more on the indian ocean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":563,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm1-tele-sp0510-ch130101-sg0012-mc02-lav-clo-dg180.wav","answer":"the youth cried out to him hysterically i ll take care of yeh jim i ll take care of yeh i swear t gawd i will sure will yeh henry the tall soldier beseeched yes yes i tell yeh i'll take care of yeh jim protested the youth","subset":"tele","task_type":"understanding","prediction":"the youth cried out to him hysterically i ll take care of you jim i ll take care of you i swear to god i will sure will you henry the tall soldier besieged yes yes i tell you i ll take care of you jim protested the youth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":564,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm1-tele-sp0510-ch130103-sg0027-mc01-stu-clo-dg010.wav","answer":"as he was at last compelled to pay attention to them his capacity for self hate was multiplied in despair he declared that he was not like those others he now conceded it to be impossible that he should ever become a hero","subset":"tele","task_type":"understanding","prediction":"as he was at last compelled to pay attention to them his capacity for self hate was multiplied in despair he declared that he was not like those others he now conceded it to be impossible that he should ever become a hero","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":565,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm1-tele-sp0510-ch130103-sg0047-mc02-lav-clo-dg180.wav","answer":"then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled","subset":"tele","task_type":"understanding","prediction":"then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":566,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm1-tele-sp0636-ch123163-sg0006-mc02-lav-clo-dg160.wav","answer":"fresh shad is better to be sprinkled with salt an hour before it is put to broil put a plate over the top to keep the heat in in broiling shad or other fresh fish you should dust them with corn meal before you put them down to bake a fresh shad","subset":"tele","task_type":"understanding","prediction":"fresh shad is better to be sprinkled with salt an hour before it is put to broil put a plate over the top to keep the heat in in broiling shad or other fresh fish you should dust them with corn meal before you put them down to bake a fresh shad","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":567,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm1-tele-sp0637-ch127597-sg0016-mc01-stu-clo-dg050.wav","answer":"it was also by night alone that i could hope to accomplish my object and then only by adopting the utmost precaution the entrance to marheyo's habitation was through a low narrow opening in its wicker work front","subset":"tele","task_type":"understanding","prediction":"it was also by night alone that i could hope to accomplish my object and then only by adopting the utmost precaution the entrance to marheyo s habitation was through a low narrow opening in its wickerwork front","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":568,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0652\/Lab41-SRI-VOiCES-rm1-tele-sp0652-ch130737-sg0009-mc02-lav-clo-dg120.wav","answer":"lacrima christi a still wine of excellent flavor and bouquet","subset":"tele","task_type":"understanding","prediction":"macrimacristi a still wine of excellent flavour and bouquet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":569,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0770\/Lab41-SRI-VOiCES-rm1-tele-sp0770-ch134592-sg0013-mc01-stu-clo-dg120.wav","answer":"there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcotes and aclands and many other newer names that she had forgotten","subset":"tele","task_type":"understanding","prediction":"there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcoats and athlens and many other newer names that she had forgotten","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":570,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp0882\/Lab41-SRI-VOiCES-rm1-tele-sp0882-ch123268-sg0033-mc01-stu-clo-dg090.wav","answer":"this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour","subset":"tele","task_type":"understanding","prediction":"this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":571,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm1-tele-sp1050-ch134120-sg0029-mc02-lav-clo-dg150.wav","answer":"missus peterkin wishes to go to drive one morning missus peterkin was feeling very tired as she had been having a great many things to think of and she said to mister peterkin i believe i shall take a ride this morning","subset":"tele","task_type":"understanding","prediction":"mrs peterkin wishes to go to drive one morning mrs peterkin was feeling very tired as she had been having a great many things to think of and she said to mr peterkin i believe i shall take a ride this morning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":572,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp1052\/Lab41-SRI-VOiCES-rm1-tele-sp1052-ch139307-sg0007-mc02-lav-clo-dg010.wav","answer":"about fourteen i don't understand very probably not our social order will probably seem very complex to you to tell you the truth i don't understand it myself very clearly nobody does you will perhaps bye and bye","subset":"tele","task_type":"understanding","prediction":"About 14. I don't understand. Very probably not. Our social order will probably seem very complex to you. To tell you the truth, I don't understand it myself very clearly. Nobody does. You will, perhaps, by and by.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":573,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm1-tele-sp1066-ch005330-sg0006-mc01-stu-clo-dg110.wav","answer":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune","subset":"tele","task_type":"understanding","prediction":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":574,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm1-tele-sp1066-ch103481-sg0026-mc01-stu-clo-dg080.wav","answer":"each huddled dumbly to each but eyes could not lift from the sea only hands touched in the dawn he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream","subset":"tele","task_type":"understanding","prediction":"each huddled dumbly to each but eyes could not lift from the sea only hands touched in the dawn he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":575,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm1-tele-sp1116-ch132851-sg0021-mc01-stu-clo-dg020.wav","answer":"while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her","subset":"tele","task_type":"understanding","prediction":"while now i can receive no presents except from my husband i can never dance except with my husband oh you wretched dwarf i will never never forgive you in spite of her fierce words no one knew better than barbaik how to put her pride in her pocket when it suited her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":576,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp1121\/Lab41-SRI-VOiCES-rm1-tele-sp1121-ch176698-sg0035-mc02-lav-clo-dg010.wav","answer":"smiling and placid as though in all this great world there were no such thing to be found as an auctioneer's hammer and presently they swung into the drive and drew up in the courtyard and there was adam","subset":"tele","task_type":"understanding","prediction":"smiling and placid as though in all this great world there were no such thing to be found as an auctioneer s hammer and presently they swung to the drive and drew up in the courtyard and there was adam","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":577,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm1-tele-sp1160-ch139730-sg0002-mc02-lav-clo-dg020.wav","answer":"a present of a glass tube with some account of the use of it in making such experiments i eagerly seized the opportunity of repeating what i had seen at boston","subset":"tele","task_type":"understanding","prediction":"a present of a glass tube with some account of the use of it in making such experiments i eagerly seized the opportunity of repeating what i had seen at boston","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":578,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1212\/Lab41-SRI-VOiCES-rm1-tele-sp1212-ch014653-sg0000-mc02-lav-clo-dg070.wav","answer":"he started as though he couldn't believe his eyes when he saw me the lord hath delivered mine enemy into my hand shone in his evil little face why mister tausig i cried before he could get his breath how odd to","subset":"tele","task_type":"understanding","prediction":"he started as though he couldn believe his eyes when he saw me the lord hath delivered mine enemy into my hand shown in his evil little face why mr tausig i cried before he could get his breath how odd","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":579,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1212\/Lab41-SRI-VOiCES-rm1-tele-sp1212-ch075242-sg0029-mc02-lav-clo-dg160.wav","answer":"and several people were talking all at once he made bold to open the door and step in what he saw you already know as by this time the children had started to bathe zip the doctor was told to go right upstairs","subset":"tele","task_type":"understanding","prediction":"and several people were talking all at once he made bold to open the door and step in what he saw you already know as by this time the children had started to bang zip the doctor was told to go right upstairs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":580,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1212\/Lab41-SRI-VOiCES-rm1-tele-sp1212-ch185485-sg0025-mc01-stu-clo-dg130.wav","answer":"and introduced myself without ceremony i told him my experiences he was delighted i next heartily indorsed every word stated in his advertisements he was not surprised for he knew the effects of his pills were such as i described","subset":"tele","task_type":"understanding","prediction":"and introduced myself without ceremony i told him my experiences he was delighted i next heartily endorsed every word stated in his advertisements he was not surprised for he knew the effects of his pills were such as i described","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":581,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1259\/Lab41-SRI-VOiCES-rm1-tele-sp1259-ch137770-sg0029-mc01-stu-clo-dg030.wav","answer":"no sooner did i sign the agreement than she got engaged poor little girl she was so keen on it all and wouldn't even wait to make proper inquiries about the shooting afraid it would get snapped up just like all of your sex well no harm's done","subset":"tele","task_type":"understanding","prediction":"no sooner did i sign the agreement than she got engaged poor little girl she was so keen on it all and wouldn't even wait to make proper inquiries about the shooting afraid it would get snapped up just like all of your sex well no harm done","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":582,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm1-tele-sp1335-ch160602-sg0013-mc01-stu-clo-dg160.wav","answer":"deep in its quiet mossy bed sheltered from sun and shower the grateful worm spun its winter tomb in the shadow of the flower and clover guarded well its rest till autumn's leaves were sere","subset":"tele","task_type":"understanding","prediction":"deep in its quiet mossy bed sheltered from sun and shower the grateful worm spun its winter tomb in the shadow of the flower and clover guarded well its rest till autumn leaves were sere","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":583,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm1-tele-sp1392-ch128226-sg0016-mc02-lav-clo-dg090.wav","answer":"they now fancied themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport to their body and this earth gentle is zarathustra to the sickly verily","subset":"tele","task_type":"understanding","prediction":"they now fancied themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport to their bodies and this earth gentle is zarathustra to the sickly verily","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":584,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm1-tele-sp1392-ch140654-sg0011-mc02-lav-clo-dg000.wav","answer":"and does not give himself to meditation forgetting the real aim of life and grasping at pleasure will in time envy him","subset":"tele","task_type":"understanding","prediction":"and does not give himself to meditation forgetting the real aim of life and grasping at pleasure will in time envy him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":585,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1417\/Lab41-SRI-VOiCES-rm1-tele-sp1417-ch001536-sg0003-mc02-lav-clo-dg010.wav","answer":"ha i am observed he murmured the words broke the spell instantly the five visitors burst simultaneously into speech are you the acting editor of this paper i wish to have a word with you sir mister windsor i presume","subset":"tele","task_type":"understanding","prediction":"ha i am observed he had murmured the words broke the spell instantly the five visitors burst simultaneously into speech are you the acting editor of this paper i wish to have a word with you sir mr windsor i presume","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":586,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1425\/Lab41-SRI-VOiCES-rm1-tele-sp1425-ch139291-sg0034-mc01-stu-clo-dg120.wav","answer":"the songs of the slave represent the sorrows of his heart and he is relieved by them only as an aching heart is relieved by its tears at least such is my experience i have often sung to drown my sorrow but seldom to express my happiness","subset":"tele","task_type":"understanding","prediction":"the songs of the slave represent the sorrows of his heart and he is relieved by them only as an aching heart is relieved by its tears at least such is my experience i have often sung to drown my sorrow but seldom to express my happiness","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":587,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1425\/Lab41-SRI-VOiCES-rm1-tele-sp1425-ch139297-sg0013-mc02-lav-clo-dg170.wav","answer":"would be our inevitable condition a condition held by us all in the utmost horror and dread i suffered more anxiety than most of my fellow slaves i had known what it was to be kindly treated they had known nothing of the kind","subset":"tele","task_type":"understanding","prediction":"would be our inevitable condition a condition held by us all in the utmost horror and dread i suffered more anxiety than most of my fellow slaves i had known what it was to be kindly treated they had known nothing of the kind","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":588,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-tele-sp1472-ch142848-sg0009-mc02-lav-clo-dg160.wav","answer":"the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves one selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation","subset":"tele","task_type":"understanding","prediction":"the shrub is pruned so as not to exceed the height of from two to three feet much in the same manner as the vine is treated in france they pluck the leaves when selecting them according to the kinds of tea required and notwithstanding the tediousness of the operation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":589,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm1-tele-sp1472-ch285314-sg0011-mc01-stu-clo-dg040.wav","answer":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up","subset":"tele","task_type":"understanding","prediction":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i s'pose he is there now very good i ll hunt him up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":590,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1536\/Lab41-SRI-VOiCES-rm1-tele-sp1536-ch137608-sg0013-mc01-stu-clo-dg020.wav","answer":"i have not deserved that ye should show me this strangeness and i had weened that i should have right good cheer with you and unto my power i have deserved thank and well i am sure i have bought your love with part of the best blood within my body fair courteous knight said dame lionesse","subset":"tele","task_type":"understanding","prediction":"i have not deserved that ye should show me this strangeness and i had weened that i should have reft good cheer with you and unto my power i have deserved thank and well i am sure i have bought your love with part of the best blood within my body fair courteous knight said dame lyones","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":591,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1536\/Lab41-SRI-VOiCES-rm1-tele-sp1536-ch138488-sg0025-mc02-lav-clo-dg090.wav","answer":"two generations of public men have since laboured with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment","subset":"tele","task_type":"understanding","prediction":"two generations of public men have since labored with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":592,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1737\/Lab41-SRI-VOiCES-rm1-tele-sp1737-ch142396-sg0008-mc01-stu-clo-dg130.wav","answer":"there was an exception in the curate who would receive unblenching the information that the meadow beyond the orchard was a prairie studded with herds of buffalo which it was our delight moccasined and tomahawked to ride down with those whoops that announce the scenting of blood","subset":"tele","task_type":"understanding","prediction":"there was an exception in the curate who would receive unblenchingly information that the meadow beyond the orchard was a prairie studded with herds of buffalo which it was our delight moccasined and tomahawked to ride down with those whoops that announced the scenting of blood","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":593,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1737\/Lab41-SRI-VOiCES-rm1-tele-sp1737-ch146161-sg0002-mc02-lav-clo-dg150.wav","answer":"knit two together knit two fourth row seamed making one at the beginning fifth row make one knit two knit two together knit one make one","subset":"tele","task_type":"understanding","prediction":"knit two together knit two fourth row seam making one at the beginning fifth row make one knit two knit two together knit one make one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":594,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm1-tele-sp1867-ch154071-sg0043-mc01-stu-clo-dg170.wav","answer":"you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i'll smash every bone in his ugly head","subset":"tele","task_type":"understanding","prediction":"you got to get that gent i seen grinning from the window grinning asked bill gregg grinding his teeth and starting from his chair was the skunk laughing at me sure every minute bill gregg groaned i ll smash every bone in his ugly head","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":595,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm1-tele-sp1867-ch154075-sg0018-mc02-lav-clo-dg130.wav","answer":"as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance","subset":"tele","task_type":"understanding","prediction":"as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":596,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm1-tele-sp1874-ch089898-sg0022-mc01-stu-clo-dg050.wav","answer":"this being heard the pope and all the rest said that a man of so great authority who had held the office of a bishop for nearly forty years ought by no means to be condemned but being altogether cleared of the faults laid to his charge should return home with honour","subset":"tele","task_type":"understanding","prediction":"this being heard the pope and all the rest said that a man of so great authority who had held the office of a bishop for nearly forty years ought by no means to be condemned but being altogether cleared of the false late to his charge should return home with honour","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":597,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm1-tele-sp1874-ch089898-sg0027-mc01-stu-clo-dg050.wav","answer":"but be ready for i will return and visit you at the end of four years and when you come into your country you shall recover the greater part of the possessions that have been taken from you and shall end your days in peace and quiet the bishop accordingly recovered","subset":"tele","task_type":"understanding","prediction":"but be ready for i will return and visit you at the end of four years and when you come into your country you shall recover the greater part of the possessions that have been taken from you and shall end your days in peace and quiet the bishop accordingly recovered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":598,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm1-tele-sp1874-ch165702-sg0020-mc02-lav-clo-dg150.wav","answer":"april fourteenth assassinated in ford's theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett","subset":"tele","task_type":"understanding","prediction":"april fourteenth assassinated in ford s theater washington by a mad actor wilkes booth april nineteenth body laid in state at washington april twenty sixth booth slain in resisting arrest by sergeant boscan corbett","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":599,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1926\/Lab41-SRI-VOiCES-rm1-tele-sp1926-ch143879-sg0015-mc01-stu-clo-dg010.wav","answer":"missus ludlow sacrificed as i say to paris yet had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations","subset":"tele","task_type":"understanding","prediction":"mrs ludlow sacrificed as i say to paris yet had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":600,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm1-tele-sp1961-ch149738-sg0036-mc01-stu-clo-dg100.wav","answer":"some of his specimens were so rare that she was unfamiliar with them and with the flower book between them they knelt studying the different varieties she wandered the length of the cathedral aisle with him and it was at her suggestion that he lighted his altar with a row of flaming foxfire","subset":"tele","task_type":"understanding","prediction":"some of his specimens were so rare that she was unfamiliar with them and with the flower book between them they knelt studying the different varieties she wandered the length of the cathedral aisle with him and it was at her suggestion that he lighted his altar with a row of flaming foxfire","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":601,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm1-tele-sp1970-ch028415-sg0006-mc01-stu-clo-dg050.wav","answer":"some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another","subset":"tele","task_type":"understanding","prediction":"some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":602,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm1-tele-sp2012-ch139358-sg0007-mc01-stu-clo-dg080.wav","answer":"what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words","subset":"tele","task_type":"understanding","prediction":"what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":603,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2060\/Lab41-SRI-VOiCES-rm1-tele-sp2060-ch150855-sg0011-mc02-lav-clo-dg130.wav","answer":"there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie's bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy","subset":"tele","task_type":"understanding","prediction":"there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie s bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":604,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2074\/Lab41-SRI-VOiCES-rm1-tele-sp2074-ch147193-sg0033-mc02-lav-clo-dg120.wav","answer":"but theseus wept shall i leave you o my mother but she answered weep not for me that which is fated must be and grief is easy to those who do nought but grieve","subset":"tele","task_type":"understanding","prediction":"but theseus wept shall i leave you o my mother but she answered weep not for me that which is fated must be and grief is easy to those who do not but grieve","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":605,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2074\/Lab41-SRI-VOiCES-rm1-tele-sp2074-ch149033-sg0017-mc01-stu-clo-dg040.wav","answer":"as soon as he is alone he rushes to ethel's door i say said mister salteena excitedly i have had some tea in bed sometimes visitors came to the house nothing much in that to us but how consummately this child must have studied them","subset":"tele","task_type":"understanding","prediction":"as soon as he is alone he rushes to ethel s door i say said mr salteena excitedly i have had some tea in bed sometimes visitors came to the house nothing much in that to us but how consummately this child must have studied em","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":606,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm1-tele-sp2110-ch161100-sg0030-mc02-lav-clo-dg110.wav","answer":"he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died","subset":"tele","task_type":"understanding","prediction":"he went into the wine business which fact led sheridan to make the witty suggestion that he inscribe over his shop michael kelly composer of wines and importer of music he was born in seventeen sixty four and died","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":607,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm1-tele-sp2156-ch025563-sg0014-mc01-stu-clo-dg180.wav","answer":"there is not nor play neither snapped phelan i've got to go out and chase up a drunk or throw a faint or git run over or somethin desperate to square mesilf with the captain i'm an hour overdue at the station","subset":"tele","task_type":"understanding","prediction":"there is not nor play neither snapped fayler i ve got to go out and chase up a drunk or throw a faint or get run over or something desperate to square meself with the captain i m an hour overdue at the station","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":608,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2294\/Lab41-SRI-VOiCES-rm1-tele-sp2294-ch161707-sg0011-mc02-lav-clo-dg100.wav","answer":"and the next instant there was a thud and a bump a bump again a half stifled cry and then a hurried vision of some black carpeting that flapped and shook as though all the winds of eblis were in its folds and then apparently disgorged from its inmost recesses a little man","subset":"tele","task_type":"understanding","prediction":"and the next instant there was a thud and a bump a bump again a half stifled cry and then a hurried vision of some black carpeting that flapped and shook as though all the winds of eddlys were in its folds and then apparently disgorged from its innermost recesses a little man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":609,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm1-tele-sp2412-ch153947-sg0010-mc01-stu-clo-dg150.wav","answer":"i see from my second preface that i took the book to messrs chapman and hall may first eighteen seventy one and on their rejection of it under the advice of one who has attained the highest rank among living writers i let it sleep till i took it to mister trubner early in eighteen seventy two","subset":"tele","task_type":"understanding","prediction":"i see from my second preface that i took the book to messrs chapman and hall may first eighteen seventy one and on their rejection of it under the advice of one who has attained the highest rank among living writers i let it sleep till i took it to mr trubner early in eighteen seventy two","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":610,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm1-tele-sp2412-ch153954-sg0015-mc01-stu-clo-dg040.wav","answer":"suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome","subset":"tele","task_type":"understanding","prediction":"suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":611,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2532\/Lab41-SRI-VOiCES-rm1-tele-sp2532-ch157475-sg0007-mc01-stu-clo-dg120.wav","answer":"and there is nothing but a hole they must have scooted right into the hole henny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down there penny dolls he called there was no answer","subset":"tele","task_type":"understanding","prediction":"and there is nothing but a hole they must have scooted right into the hole penny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down there penny dolls he called there was no answer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":612,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2532\/Lab41-SRI-VOiCES-rm1-tele-sp2532-ch157475-sg0007-mc02-lav-clo-dg120.wav","answer":"and there is nothing but a hole they must have scooted right into the hole henny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down there penny dolls he called there was no answer","subset":"tele","task_type":"understanding","prediction":"and there was nothing but a hole they must have scooted right into the hole penny the dutch doll said raggedy andy lay flat upon the shiny tin and looked down into the hole are you down in there penny dolls he called there was no answer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":613,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2673\/Lab41-SRI-VOiCES-rm1-tele-sp2673-ch156474-sg0006-mc02-lav-clo-dg030.wav","answer":"but before it could be executed circumstances intervened effectually to thwart that object while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress","subset":"tele","task_type":"understanding","prediction":"but before it could be executed circumstances intervened effectually to thwart that object where you going while the gradual occupation of the north carolina coast was going on two other expeditions of a similar nature were making steady progress","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":614,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2673\/Lab41-SRI-VOiCES-rm1-tele-sp2673-ch162130-sg0022-mc02-lav-clo-dg150.wav","answer":"and both temperate drinking and total abstinence correspondingly increasing it is unnecessary to appeal to statistics the familiar experience of every man whose memory runs back twenty or forty or sixty years","subset":"tele","task_type":"understanding","prediction":"in both temperate drinking and total abstinence correspondingly increasing it is unnecessary to appeal to statistics the familiar experience of every man whose memory runs back twenty or forty or sixty years","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":615,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2691\/Lab41-SRI-VOiCES-rm1-tele-sp2691-ch156745-sg0027-mc01-stu-clo-dg160.wav","answer":"merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances","subset":"tele","task_type":"understanding","prediction":"merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground francis","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":616,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm1-tele-sp2758-ch086588-sg0029-mc02-lav-clo-dg030.wav","answer":"fifteen sixty two has collected a great number of classic anecdotes to illustrate this saying recapitulation those who desire to become artists can greatly facilitate their work","subset":"tele","task_type":"understanding","prediction":"fifteen sixty two has collected a great number of classic anecdotes to illustrate this saying recapitulation those who desire to become artists can greatly facilitate their work","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":617,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm1-tele-sp2764-ch036619-sg0024-mc01-stu-clo-dg000.wav","answer":"and each man now wanted only to catch up on his eating and sleeping to make up for the time he had so stupidly sacrificed with typical human fickleness they jumped from one extreme to the other inevitably the most enthusiastic supporters of the undertaking became its most energetic opponents","subset":"tele","task_type":"understanding","prediction":"and each man now wanted only to catch up on his eating and sleeping to make up for the time he had so stupidly sacrificed with typical human fickleness they jumped from one extreme to the other inevitably the most enthusiastic supporters of the undertaking became its most energetic opponents","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":618,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm1-tele-sp2803-ch154320-sg0003-mc01-stu-clo-dg060.wav","answer":"their minds were so distracted at this change of route as to be quite unhinged","subset":"tele","task_type":"understanding","prediction":"their minds were so distracted at this change of route as to be quite unhinged","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":619,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm1-tele-sp2803-ch161169-sg0005-mc02-lav-clo-dg110.wav","answer":"walk down the sloping foot path now and be careful to keep out of the way of the little cars that are coming and going on each side of you loaded on one side and empty on the other and seeming to run up and down by themselves","subset":"tele","task_type":"understanding","prediction":"walk down the sloping footpath now and be careful to keep out of the way of the little cars that are coming and going on each side of you loaded on one side and empty on the other and seeming to run up and down by themselves","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":620,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm1-tele-sp2911-ch007601-sg0022-mc02-lav-clo-dg010.wav","answer":"in approaching him had stalked with his black shadow before him and enveloped the victim and it was the mournful influence of the unperceived shadow that caused him to feel although he neither saw nor heard to feel the presence of my head within the room","subset":"tele","task_type":"understanding","prediction":"in approaching him had stalked with his black shadow before him and enveloped the victim and it was the mournful influence of the unprescient shadow that caused him to feel although he neither saw nor heard to feel the presence of my hand within the room","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":621,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm1-tele-sp2911-ch007601-sg0045-mc01-stu-clo-dg110.wav","answer":"and became more distinct i talked more freely to get rid of the feeling but it continued and gained definiteness until at length i found that the noise was not within my ears no doubt i now grew very pale but i talked more fluently","subset":"tele","task_type":"understanding","prediction":"and became more distinct i talked more freely to get rid of the feeling but it continued and gained definiteness until at length i found that the noise was not within my ears no doubt i now grew very pale but i talked more fluently","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":622,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm1-tele-sp2911-ch012359-sg0019-mc01-stu-clo-dg100.wav","answer":"for either port or stout is put into counterfeit cheshire cheese to make up for the richness it lacks while some combinations of cheeses and wines may turn out palatable we prefer taking ours straight when something more fiery is needed","subset":"tele","task_type":"understanding","prediction":"for either port or stout is put into counterfeit cheshire cheese to make up for the richness it lacks while some combinations of cheeses and wines may turn out palatable we prefer taking ours straight when something more fiery is needed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":623,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm1-tele-sp3368-ch170950-sg0014-mc02-lav-clo-dg020.wav","answer":"why he said are they not capable of defending themselves no i said not if we were right in the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success","subset":"tele","task_type":"understanding","prediction":"why you said are they not capable of defending themselves no i said now if we were right that the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":624,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm1-tele-sp3368-ch170951-sg0018-mc01-stu-clo-dg110.wav","answer":"and no good thing is hurtful no indeed and that which is not hurtful hurts not certainly not and that which hurts not does no evil no and can that which does no evil be a cause of evil impossible and the good is advantageous yes","subset":"tele","task_type":"understanding","prediction":"and no good thing is hurtful no indeed and that which is not hurtful hurts not certainly not and that which hurts not does no evil no and can that which does no evil be a cause of evil impossible and the good is advantageous yes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":625,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp3521\/Lab41-SRI-VOiCES-rm1-tele-sp3521-ch007591-sg0013-mc02-lav-clo-dg010.wav","answer":"there was no light of any kind emanating from lamp or candle within the suite of chambers but in the corridors that followed the suite there stood opposite to each window a heavy tripod bearing a brazier of fire that projected its rays through the tinted glass and so glaringly illumined the room","subset":"tele","task_type":"understanding","prediction":"there was no light of any kind emanating from lamp or candle within the suite of chambers but in the corridors that followed the suite there stood opposite each window a heavy tripod bearing a brazier of fire that projected its rays through the tinted glass and so glaringly illumined the room","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":626,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_1212-3521\/sp3521\/Lab41-SRI-VOiCES-rm1-tele-sp3521-ch012715-sg0020-mc02-lav-clo-dg030.wav","answer":"boil a small handful of hops in a couple of quarts of water when the strength is obtained from them strain the liquor put it back on the fire take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour stir it into the liquor when it boils","subset":"tele","task_type":"understanding","prediction":"Boil a small handful of hops in a couple of quarts of water. When the strength is obtained from them. Strain the liquor. Put it back on the fire. Take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour. Stir it into the liquor, when it boils.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":627,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm1-tele-sp3549-ch008890-sg0023-mc02-lav-clo-dg080.wav","answer":"his daughter being a few steps in advance it is hardly the line of life for a girl like grace after what she's been accustomed to i didn't foresee that in sending her to boarding school and letting her travel and what not to make her a good bargain for giles","subset":"tele","task_type":"understanding","prediction":"his daughter being a few steps in advance it is hardly the line of life for a girl like grace after what she has been accustomed to i did foresee that in sending her to boarding school and letting her travel and what not to make her a good bargain for giles","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":628,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm1-tele-sp3549-ch171171-sg0001-mc01-stu-clo-dg040.wav","answer":"and so much of the wall as enclosed the city on the west side this wall was spared in order to afford a camp for such as were to lie in garrison as were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified","subset":"tele","task_type":"understanding","prediction":"And so much of the wall as enclosed, the city on the west side, this wall was spared in order to afford a camp for such as were to lie a garrison. As were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":629,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3645\/Lab41-SRI-VOiCES-rm1-tele-sp3645-ch077173-sg0036-mc01-stu-clo-dg160.wav","answer":"and beg to assure you of my devoted services i am madam yours obediently alfonso pinzato editor for a long time the excuse that she would have to make to galva before she could leave the island had been worrying anna","subset":"tele","task_type":"understanding","prediction":"and beg to assure you of my devoted services i am madam yours obediently alphonso pinzato editor for a long time the excuse that she would have to make to galva before she could leave the island had been worrying anna","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":630,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm1-tele-sp3923-ch153309-sg0039-mc01-stu-clo-dg060.wav","answer":"and manufactures his own concoctions in a house he has rented here on a lonely road some half mile out of town wellgood does the man named wellgood mister grey exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town","subset":"tele","task_type":"understanding","prediction":"and manufactures his own concoctions in a house he has rented here on a lonely road some half mile out of town wellgood does the man named wellgood mr gray exclaimed with all the astonishment the other secretly expected yes wellgood james wellgood there is no other in town","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":631,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3972\/Lab41-SRI-VOiCES-rm1-tele-sp3972-ch005791-sg0023-mc02-lav-clo-dg030.wav","answer":"which must draw much blood on both sides before his royal father's presence can regain what he has lost ah my lord replied wallace is it to be nothing but war have you now a stronghold of any force in all the highlands is not the greater part of the lowlands free","subset":"tele","task_type":"understanding","prediction":"which must draw much blood on both sides before his royal father s presence can regain what he has lost ah my lord replied wallace is it to be nothing but war have you now a stronghold of any force in all the highlands is not the greater part of the lowlands free","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":632,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3972\/Lab41-SRI-VOiCES-rm1-tele-sp3972-ch185074-sg0018-mc02-lav-clo-dg150.wav","answer":"on the spot where he was killed no one can judge of my feelings on seeing this mournful spectacle and what greatly added to my distress was the fact that he had fallen by the murderous hand of his brother i felt my situation unsupportable","subset":"tele","task_type":"understanding","prediction":"on the spot where he was killed no one can judge of my feelings on seeing this mournful spectacle and what greatly added to my distress was the fact that he had fallen by the murderous hand of his brother i felt my situation unsupportable","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":633,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3989\/Lab41-SRI-VOiCES-rm1-tele-sp3989-ch182389-sg0005-mc02-lav-clo-dg150.wav","answer":"gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mister rabbit the grandfather a thousand times removed of peter rabbit was always getting into trouble yes sir old mister rabbit was always getting into trouble","subset":"tele","task_type":"understanding","prediction":"gathered around him on the bank of the smiling pool chug a rum said grandfather frog old mr rabbit the grandfather a thousand times removed of peter rabbit was always getting into trouble yes sir old mr rabbit was always getting into trouble","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":634,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3989\/Lab41-SRI-VOiCES-rm1-tele-sp3989-ch182389-sg0019-mc02-lav-clo-dg040.wav","answer":"now in spite of the trouble mister rabbit was forever making for other people by his dreadful curiosity and meddling with other people's affairs all his neighbors had a warm place in their hearts for mister rabbit and they all promised that they would help him","subset":"tele","task_type":"understanding","prediction":"now in spite of the trouble mr rabbit was for ever making for other people by his dreadful curiosity and meddling with other people s affairs all his neighbours held a warm place in their hearts for mr rabbit and they all promised that they would help him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":635,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3989\/Lab41-SRI-VOiCES-rm1-tele-sp3989-ch182402-sg0012-mc01-stu-clo-dg010.wav","answer":"now peter knew that there must be a good story about spotty and his house and you know peter dearly loves a good story so at the very first opportunity the next day he hurried over to the smiling pool to ask grandfather frog about it","subset":"tele","task_type":"understanding","prediction":"now peter knew that there must be a good story about spotty and his house and you know peter dearly loves a good story so at the very first opportunity the next day he hurried over to the smiling pool to ask grandfather frog about it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":636,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp3994\/Lab41-SRI-VOiCES-rm1-tele-sp3994-ch011512-sg0017-mc01-stu-clo-dg130.wav","answer":"the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved","subset":"tele","task_type":"understanding","prediction":"the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":637,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4010\/Lab41-SRI-VOiCES-rm1-tele-sp4010-ch010801-sg0011-mc01-stu-clo-dg070.wav","answer":"and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operations of the spiritual as of the physical world are simply a turning again to the source","subset":"tele","task_type":"understanding","prediction":"and calling aloud it is thine it is mine i am thine and therefore i am mine the vast operation of the spiritual as of the physical world are simply a turning again to the source","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":638,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-tele-sp4014-ch186176-sg0015-mc02-lav-clo-dg120.wav","answer":"won't do it slim muttered oh yes you will counseled joe shake hands the two of you slim's good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we're square said slim","subset":"tele","task_type":"understanding","prediction":"won t do it slim muttered oh yes you will counseled joe shake hands the two of you slim s good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we re square said slim","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":639,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm1-tele-sp4014-ch186176-sg0043-mc01-stu-clo-dg170.wav","answer":"and made me run a mile in nothing flat added jerry and fought me to a knockout finish later mused joe and nearly smothered me to death spoke the lieutenant and was finally corralled by an irish engineer said slim gone concluded jerry","subset":"tele","task_type":"understanding","prediction":"it made me run a mile nothing flat added jerry and fought me to a knock out finish later used joe and nearly smothered me to death spoke lieutenant and was finally corralled by an irish engineer said slim gone concluded jerry","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":640,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4110\/Lab41-SRI-VOiCES-rm1-tele-sp4110-ch011535-sg0002-mc01-stu-clo-dg130.wav","answer":"as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming","subset":"tele","task_type":"understanding","prediction":"as though the very heart of the sun had burst and hurled part of its flaming mass outward into space on it came with unbelievable speed but there was no telling yet the form of the things which were coming","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":641,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4145\/Lab41-SRI-VOiCES-rm1-tele-sp4145-ch034497-sg0032-mc02-lav-clo-dg100.wav","answer":"inevitable he thought things could not go on as before but he said something different it can't go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life","subset":"tele","task_type":"understanding","prediction":"inevitable he thought things could not go on as before but he said something different it can t go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":642,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm1-tele-sp4535-ch279852-sg0000-mc01-stu-clo-dg180.wav","answer":"captured halt there the command came from behind they whipped about and found themselves facing a raised rifle the man was a civilian tall and lanky he waved the rifle from one to the other where're you going he demanded chattanooga","subset":"tele","task_type":"understanding","prediction":"captured halt there command came from behind they whipped about and found themselves facing a raised rifle the man was a civilian tall and lanky he waved the rifle from one to the other where you going he demanded chattanooga","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":643,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4586\/Lab41-SRI-VOiCES-rm1-tele-sp4586-ch061776-sg0022-mc01-stu-clo-dg050.wav","answer":"nor show any sign of an intention to do so but sate in the saddle stooped forward his eyes turned upon the ground in that vacant gaze which denotes reflection dog gone my cats he drawled out in slow soliloquy","subset":"tele","task_type":"understanding","prediction":"nor show any sign of an intention to do so but sat in the saddle stooped forward his eyes turned upon the ground in that vacant gaze which denotes reflection doggone my cats he drawled out in slow soliloquy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":644,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4586\/Lab41-SRI-VOiCES-rm1-tele-sp4586-ch061776-sg0028-mc01-stu-clo-dg030.wav","answer":"as if fully satisfied on this score he took up his bridle rein muttered some words to his mare and commenced moving off along the edge of the chapparal having advanced about a mile in the direction of the nueces river he abruptly changed his course","subset":"tele","task_type":"understanding","prediction":"as if fully satisfied on the score he took up his bridle rein muttered some words to his mare and commenced moving off along the edge of the chaparral having advanced about a mile in the direction of the neches river he abruptly changed his course","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":645,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4590\/Lab41-SRI-VOiCES-rm1-tele-sp4590-ch018005-sg0011-mc02-lav-clo-dg010.wav","answer":"as i was by this time worn out for want of sleep having spent so many nights on the look out i was just dozing off comfortably when suddenly i felt my arm seized and on looking up saw mahina pointing in the direction of the goats sher","subset":"tele","task_type":"understanding","prediction":"as i was by this time worn out for want of sleep having spent so many nights on the look out i was just dozing off comfortably when suddenly i felt my arm seized and on looking up saw mahina pointing in the direction of the gallops","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":646,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm1-tele-sp4839-ch015304-sg0025-mc01-stu-clo-dg040.wav","answer":"and raising his eyes he said to lord ludovico my lord i thank you for the courtesy you have done me please god to pay it back to you he was in a fine large court yard then he began to set spurs to his horse the which gave four or five jumps so gayly that it could not be better done","subset":"tele","task_type":"understanding","prediction":"and raising his eyes he said to lord ludovico my lord i thank you for the courtesy you have done me please god to pay it back to you he was in a fine large courtyard then he began to set spurs to his horse the which gave four or five jumps so gayly that it could not be better done","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":647,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm1-tele-sp4839-ch015307-sg0003-mc01-stu-clo-dg050.wav","answer":"and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at treviso when emperor maximilian's commissioner presented himself in order to take possession of it","subset":"tele","task_type":"understanding","prediction":"and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at trevisa when emperor maximilian s commissioner presented himself in order to take possession of it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":648,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp4967\/Lab41-SRI-VOiCES-rm1-tele-sp4967-ch028868-sg0016-mc02-lav-clo-dg080.wav","answer":"i only meant that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for awhile and then repeated his words i think i will go abroad not for long i hope sir","subset":"tele","task_type":"understanding","prediction":"i only bet that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for a while and then repeated his words i think i will go abroad not for long i hope sir","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":649,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5157\/Lab41-SRI-VOiCES-rm1-tele-sp5157-ch047238-sg0003-mc01-stu-clo-dg170.wav","answer":"which should join you as soon as the weather would permit at present indeed it is not very encouraging for row boats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry","subset":"tele","task_type":"understanding","prediction":"which should join you as soon as the weather would permit at present indeed it is not very encouraging for rowboats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":650,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5338\/Lab41-SRI-VOiCES-rm1-tele-sp5338-ch024615-sg0013-mc01-stu-clo-dg000.wav","answer":"the court was spacious well paved and perfectly clean there being probably another entrance behind the stables for removing the litter","subset":"tele","task_type":"understanding","prediction":"The court was spacious, well paved and perfectly clean there, being probably another entrance behind the stables for removing the litter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":651,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5386\/Lab41-SRI-VOiCES-rm1-tele-sp5386-ch004145-sg0009-mc01-stu-clo-dg010.wav","answer":"her next aim was to vindicate the bible from sustaining the monstrous institution of slavery she said god has created of one blood all the nations of men to dwell on all the face of the earth to claim hold and treat a human being as property is felony against god and man","subset":"tele","task_type":"understanding","prediction":"her next aim was to vindicate the bible from sustaining the monstrous institution of slavery she said god has created of one blood all the nations of men to dwell on all the face of the earth to claim hold and treat a human being as property is felony against god and man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":652,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5400\/Lab41-SRI-VOiCES-rm1-tele-sp5400-ch034478-sg0009-mc01-stu-clo-dg090.wav","answer":"i know all about that but really what you're saying either has no meaning or it has a very wrong meaning how can you think it a matter of no importance whether the peasant whom you love as you assert i never did assert it thought konstantin levin dies without help","subset":"tele","task_type":"understanding","prediction":"i know all about that but really what you are saying either has no meaning or it has a very wrong meaning how can you think it a matter of no importance whether the peasant whom you love as you assert i never did assert it thought konstantin rovain dies without help","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":653,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm1-tele-sp5401-ch039508-sg0004-mc02-lav-clo-dg090.wav","answer":"thus next to a dike bituminous coal may be baked to coke or anthracite and chalk and limestone to crystalline marble sandstone may be converted into quartzite and shale into argillite a compact massive clay rock","subset":"tele","task_type":"understanding","prediction":"thus next to a dike a tumulus coil may be baked to coke or anthracite and chalk and limestone to crystalline marble sandstone may be converted into quartzite and shale into argillite a compact massive clay rock","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":654,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm1-tele-sp5401-ch039508-sg0007-mc01-stu-clo-dg150.wav","answer":"and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly play a very important part which will be more strongly altered","subset":"tele","task_type":"understanding","prediction":"and regional intrusions and the zone of change about them may be several miles in width in these changes heated waters and vapors from the masses of igneous rocks undoubtedly played a very important part which will be more strongly altered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":655,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm1-tele-sp5401-ch039515-sg0008-mc02-lav-clo-dg010.wav","answer":"these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood","subset":"tele","task_type":"understanding","prediction":"these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":656,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm1-tele-sp5456-ch058161-sg0009-mc01-stu-clo-dg020.wav","answer":"his was the rental of half havana and all matanzas and santa anna rich as he was could hardly hold a candle to light the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers","subset":"tele","task_type":"understanding","prediction":"his was the rental of half a van and all matanzas and santa anna rich as he was could hardly hold a candle to like the mines of gold our cuban owned choke full of diggers and broad plantations that in round figures were stocked with at least five thousand niggers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":657,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm1-tele-sp5456-ch062014-sg0015-mc02-lav-clo-dg030.wav","answer":"o o goo coo o o goo coo ez he flewed off inter de darkness here aunt phrony spread her arms like wings and made a swoop half way across the room to the bedside of the startled children an she continued","subset":"tele","task_type":"understanding","prediction":"ubu coo ubu coo as he flew off into the darkness here aunt frony spread her arms like wings and made a swoop half way across the room to the bedside of the startled children and she continued","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":10}
+{"index":658,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5583\/Lab41-SRI-VOiCES-rm1-tele-sp5583-ch041259-sg0033-mc02-lav-clo-dg110.wav","answer":"laura letter the fifteenth laura in continuation when we arrived at the town where we were to breakfast i was determined to speak with philander and gustavus and to that purpose as soon as i left the carriage","subset":"tele","task_type":"understanding","prediction":"laura letter the fifteenth laura in continuation when we arrived at the town where we were to breakfast i was determined to speak with filander on gustavus and to that purpose as soon as i left the carriage","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":659,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm1-tele-sp5635-ch053458-sg0026-mc01-stu-clo-dg040.wav","answer":"said popopo sternly for he felt the birds were getting the best of the argument the poor milliner's business will be ruined if i do not return you to her shop it seems you are necessary to trim the hats properly it is the fashion for women to wear birds upon their headgear so the poor milliner's wares","subset":"tele","task_type":"understanding","prediction":"said popopo sternly for he felt the birds were getting the best of the argument the poor milliner s business will be ruined if i do not return you to her shop it seems you are necessary to trim the hats properly it is the fashion for women to wear birds upon their headgear so the poor milliner s wares","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":660,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm1-tele-sp5635-ch053458-sg0027-mc01-stu-clo-dg080.wav","answer":"although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a black bird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion","subset":"tele","task_type":"understanding","prediction":"although beautified by lace and ribbons are worthless unless you are perched upon them fashions said a blackbird solemnly are made by men what law is there among birds or knooks that requires us to be the slaves of fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":661,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm1-tele-sp5868-ch055088-sg0015-mc02-lav-clo-dg050.wav","answer":"and the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth is whirled through europe without gaining a single idea worth crossing the street for","subset":"tele","task_type":"understanding","prediction":"on the price and quality of the liquor on the other hand franklin could not cross the channel without making observations useful to mankind while many a vacant thoughtless youth is whirled through europe without gaining a single idea worth crossing the street for","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":662,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm1-tele-sp5935-ch055927-sg0020-mc01-stu-clo-dg140.wav","answer":"and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps","subset":"tele","task_type":"understanding","prediction":"and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":663,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp6099\/Lab41-SRI-VOiCES-rm1-tele-sp6099-ch067860-sg0005-mc02-lav-clo-dg130.wav","answer":"i believe you are right estralla is a clever little darky and if she started in search of sylvia perhaps she has been able to find her i had not thought of it and mister fulton's voice had a new note of hope","subset":"tele","task_type":"understanding","prediction":"i believe you are right estralla is a clever little darky and if she started in search of sylvia perhaps she has been able to find her i had not thought of it and mr fulton s voice had a new note of hope","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":664,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_3549-6147\/sp6099\/Lab41-SRI-VOiCES-rm1-tele-sp6099-ch069550-sg0012-mc02-lav-clo-dg160.wav","answer":"and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful","subset":"tele","task_type":"understanding","prediction":"and pour out passionate words of prayer that just one little soul might be permitted to live no matter how long the night nor how bitter the struggle morning always found her bright and cheerful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":665,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm1-tele-sp6241-ch061946-sg0023-mc01-stu-clo-dg040.wav","answer":"accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion","subset":"tele","task_type":"understanding","prediction":"accustomed as i had been to the steam ferry boats of the elbe i found the long oars of the boatmen but sorry means of locomotion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":666,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm1-tele-sp6385-ch034655-sg0022-mc01-stu-clo-dg170.wav","answer":"representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners","subset":"tele","task_type":"understanding","prediction":"representing warriors queens and tritons armed with the scaly terminations of a hydra cut crystals combining prismatic effects with those of reflection mirrors repeated the light of precious stones and sparkles glittered in the darkest corners","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":667,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm1-tele-sp6385-ch034669-sg0003-mc01-stu-clo-dg160.wav","answer":"the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to gwynplaine the wolf appeared to him","subset":"tele","task_type":"understanding","prediction":"the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to gwynplaine the wolf appeared to him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":668,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm1-tele-sp6385-ch034669-sg0003-mc02-lav-clo-dg160.wav","answer":"the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to gwynplaine the wolf appeared to him","subset":"tele","task_type":"understanding","prediction":"the very moment in which all expectation has ceased bringing back health and deliverance a place of safety discovered at the most critical instant in the midst of crumbling ruins homo was all this to quinplane the wolf appeared to him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":669,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm1-tele-sp6395-ch084349-sg0006-mc01-stu-clo-dg030.wav","answer":"and if possible made him a greater idol than before in the eyes of the court at four years of age he is described as of slight but well shaped figure with a broad open forehead finely arched eyebrows and large blue eyes","subset":"tele","task_type":"understanding","prediction":"and if possible made him a greater idol than before in the eyes of the court at four years of age he is described as of slight but well shaped figure with a broad open forehead finely arched eyebrows and large blue eyes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":670,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm1-tele-sp6395-ch084349-sg0009-mc02-lav-clo-dg070.wav","answer":"the people in their destitute condition could only think of bread and believing the king could command possession of it familiarly styled him the baker so that now seeing the royal family's return they shouted joyously no more poverty","subset":"tele","task_type":"understanding","prediction":"The people in their destitute condition could only think of bread and believing the king could command possession of it. Familiarly styled him, the baker. So that now seeing the royal family's return, they shouted joyously, no more poverty.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":671,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm1-tele-sp6454-ch120342-sg0005-mc02-lav-clo-dg050.wav","answer":"and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people in the very lowest bolgie being ill natured enough to grieve","subset":"tele","task_type":"understanding","prediction":"and so tuesday night the metropolitan people gave up their unequal contest all good men and angels rejoicing at their discomfiture and only a few of the people and the very lowest fogey being ill natured enough to grieve","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":672,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm1-tele-sp6519-ch231834-sg0034-mc01-stu-clo-dg000.wav","answer":"which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greeb's very lively imagination yet even though he reduced her communications to bare facts","subset":"tele","task_type":"understanding","prediction":"which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greeb s very lively imagination yet even though he reduced her communications to bare facts","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":673,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm1-tele-sp6544-ch071420-sg0000-mc02-lav-clo-dg130.wav","answer":"chapter twenty nine a glass of poison margaret could do nothing but stare at the man before her he was heavy set and powerful and wont to having his own way mister styles she began but he put his hand over her mouth you are sick","subset":"tele","task_type":"understanding","prediction":"chapter twenty nine a glass of poison margaret could do nothing but stare at the man before her he was heavy set and powerful in want to having his own way mr styles she began but he put his hand over her mouth you are sick","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":674,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6696\/Lab41-SRI-VOiCES-rm1-tele-sp6696-ch073296-sg0005-mc01-stu-clo-dg020.wav","answer":"it makes me envious and miserable i who have never seen it south end is prohibited if you please my dear isabella i have not heard you make one inquiry after mister perry yet and he never forgets you oh good mister perry how is he sir","subset":"tele","task_type":"understanding","prediction":"it makes me envious and miserable i who have never seen it south end is prohibited if you please my dear isabella i have not heard you make one inquiry after mr carey yet and he never forgets you oh good mr payne how is he sir","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":675,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6848\/Lab41-SRI-VOiCES-rm1-tele-sp6848-ch252323-sg0009-mc02-lav-clo-dg040.wav","answer":"broke in craggs i was brigaded with arentschild's hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you're right","subset":"tele","task_type":"understanding","prediction":"broken crags i was brigaded with arnoldscharz hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you are right","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":676,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-tele-sp6895-ch092806-sg0009-mc02-lav-clo-dg180.wav","answer":"there was something in her manner that warned mister mc caskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware pig's face is it said missus mc caskey and hurled a stewpan full of bacon and turnips at her lord","subset":"tele","task_type":"understanding","prediction":"there was something in her manner that warned mr maccaskey when the corners of her mouth went down suddenly like a barometer it usually foretold a fall of crockery and tinware big space is it said mrs maccaskey and hurled a stewpan full of bacon and turnips at her lord","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":677,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm1-tele-sp6895-ch096175-sg0004-mc02-lav-clo-dg160.wav","answer":"and the bones of your mother and you can feel the bones in your fingers your fingers will become mere bone after you are dead as die you must those bones which you see around you are of course the bones of the men of whom we often speak","subset":"tele","task_type":"understanding","prediction":"and the bones of your mother and you can feel the bones in your fingers your fingers will become mere bone after you are dead as die you must those bones which you see around you are of course the bones of the men of whom we often speak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":678,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm1-tele-sp6965-ch277898-sg0011-mc01-stu-clo-dg030.wav","answer":"was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs","subset":"tele","task_type":"understanding","prediction":"was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":679,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm1-tele-sp7000-ch083708-sg0021-mc01-stu-clo-dg120.wav","answer":"i've got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy","subset":"tele","task_type":"understanding","prediction":"i have got another ball which you can have he produced a second ball from the same pocket from which the first had come i could scarcely believe my eyes but i was discovering with horatio that there were more things in heaven and earth than had been contained in my philosophy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":680,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm1-tele-sp7095-ch088483-sg0019-mc01-stu-clo-dg000.wav","answer":"that during the middle ages the priests and monks kept up the torch of learning that being the only literate people they brought back the study of the classics historically speaking this is about the most impudent statement that one could imagine","subset":"tele","task_type":"understanding","prediction":"that during the middle ages the priests and monks kept up the torch of learning that being the only literate people they brought back the study of the classics historically speaking this is about the most impudent statement that one could imagine","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":681,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm1-tele-sp7095-ch088483-sg0020-mc01-stu-clo-dg100.wav","answer":"later learned to read and write from the arabs jews and greeks exiled from constantinople after fourteen fifty three it is because they wanted to keep the power in their hands the people they did not permit to learn either to read or write","subset":"tele","task_type":"understanding","prediction":"later learned to read and write from the arabs jews and greeks exiled from constantinople after fourteen fifty three it is because they wanted to keep the power in their hands the people they did not permit to learn either to read or write","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":682,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7247\/Lab41-SRI-VOiCES-rm1-tele-sp7247-ch094108-sg0021-mc02-lav-clo-dg000.wav","answer":"below which is a shelving stone beach of generous width two high iron towers supporting the cable of a current ferry add dignity to the twin settlements a stone monument six feet high just observable through the willows on the right shore marks the boundary","subset":"tele","task_type":"understanding","prediction":"below which is a shelving stone beach of generous width two high iron towers supporting the cable of a current ferry add dignity to the twin settlements a stone monument six feet high just observable through the willows on the right shore marks the boundary","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":683,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7264\/Lab41-SRI-VOiCES-rm1-tele-sp7264-ch092310-sg0007-mc01-stu-clo-dg100.wav","answer":"the proprietor was always at the choice of publishing matter which did not affect him and saving his fortune or refusing it and jeopardizing his fortune he chose the former course in the second place there was an even more serious development advertisement","subset":"tele","task_type":"understanding","prediction":"the proprietor was always at the choice of publishing matter which did not affect him and saving his fortune or refusing it and jeopardizing his fortune he chose the former course in the second place there was an even more serious development advertisement","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":684,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7264\/Lab41-SRI-VOiCES-rm1-tele-sp7264-ch092316-sg0034-mc02-lav-clo-dg140.wav","answer":"but not a cabinet minister that could not pass an examination in the life vices vulnerability fortune investments and favours of the owner the change was rapidly admitted it came quickly but thoroughly at last like most rapid developments it exceeded itself","subset":"tele","task_type":"understanding","prediction":"but not a cabinet minister that could not pass an examination in the life vices vulnerability fortune investments and favours of the owner the change was rapidly admitted it came quickly but thoroughly at last like most rapid developments it exceeded itself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":685,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm1-tele-sp7278-ch104730-sg0026-mc02-lav-clo-dg060.wav","answer":"as then made up the house of representatives wore hardly even upon the iron temper and inflexible disposition of mister adams the most insignificant error of conduct in me at this time he writes in april","subset":"tele","task_type":"understanding","prediction":"as then made up the house of representatives were hardly even upon the iron temper and inflexible disposition of mr adams the most insignificant error of conduct in me at this time he writes in april","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":686,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094522-sg0005-mc02-lav-clo-dg040.wav","answer":"naturally received an accession of power during the minority and as it was now becoming a scene of business the members chose for the first time a speaker who might preserve order in their debates and maintain those forms which are requisite in all numerous assembles","subset":"tele","task_type":"understanding","prediction":"naturally received an accession of power during the minority and as it was now becoming a scene of business the members chose for the first time a speaker who might preserve order in their debates and maintain those forms which are requisite in all numerous assemblies","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":687,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094522-sg0028-mc02-lav-clo-dg130.wav","answer":"freedom of commerce in market towns without toll or impost and a fixed rent on lands instead of the services due by villainage these requests which though extremely reasonable in themselves the nation was not sufficiently prepared to receive","subset":"tele","task_type":"understanding","prediction":"freedom of commerce and market towns without toll or impost and a fixed rent on lands instead of the services due by villeinage these requests which though extremely reasonable in themselves the nation was not sufficiently prepared to receive","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":688,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094522-sg0037-mc01-stu-clo-dg160.wav","answer":"the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country","subset":"tele","task_type":"understanding","prediction":"the scots to the number of thirty thousand men attended by the french entered the borders of england by the west and carrying their ravages through cumberland westmoreland and lancashire collected a rich booty and then returned in tranquillity to their own country","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":689,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm1-tele-sp7445-ch094526-sg0027-mc02-lav-clo-dg020.wav","answer":"england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vicar of christ","subset":"tele","task_type":"understanding","prediction":"england of course was thrown into the other party and declared for urban thus the appellation of clementines and urbanists distracted europe for several years and each party damned the other as schismatics and as rebels to the true vigour of christ","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":690,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm1-tele-sp7498-ch099156-sg0013-mc02-lav-clo-dg000.wav","answer":"we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time","subset":"tele","task_type":"understanding","prediction":"we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till clodstock came again to hamburg this he did a year after we had seen one another for the first time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":691,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7517\/Lab41-SRI-VOiCES-rm1-tele-sp7517-ch100442-sg0003-mc01-stu-clo-dg170.wav","answer":"and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer's shop and you will find me in my spare evenings","subset":"tele","task_type":"understanding","prediction":"and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer shop and you will find me in my spare evenings","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":692,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm1-tele-sp7540-ch101262-sg0013-mc02-lav-clo-dg010.wav","answer":"soon got tired of being by himself and began to look about for something to amuse him what can there be in that twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other","subset":"tele","task_type":"understanding","prediction":"soon got tired of being by himself and began to look about for something to amuse him what can there be in the twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":693,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm1-tele-sp7540-ch101799-sg0030-mc01-stu-clo-dg080.wav","answer":"but contrary to usual experience they fought with the utmost valour and determination so that for some time after the ships had become engaged at close quarters the struggle was simply one for bare life on the part of the english","subset":"tele","task_type":"understanding","prediction":"but contrary to usual experience they fought with yellowish valor and determination so that for some time after the ships had become engaged at close quarter the struggle was simply one for bare life on the part of the english","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":694,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7704\/Lab41-SRI-VOiCES-rm1-tele-sp7704-ch106965-sg0010-mc01-stu-clo-dg000.wav","answer":"and killed so many men you would have burst and lost all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with severity in her tone","subset":"tele","task_type":"understanding","prediction":"and killed so many men you would have burst and lost all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with severity in her tone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":695,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm1-tele-sp7850-ch111771-sg0000-mc02-lav-clo-dg090.wav","answer":"through the influence of hon thomas l hamer he was admitted at west point in eighteen thirty nine","subset":"tele","task_type":"understanding","prediction":"through the influence of hon thomas l hammer he was admitted at west point in eighteen thirty nine","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":696,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm1-tele-sp7850-ch111771-sg0002-mc01-stu-clo-dg080.wav","answer":"grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field","subset":"tele","task_type":"understanding","prediction":"grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":697,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm1-tele-sp7868-ch110705-sg0008-mc01-stu-clo-dg030.wav","answer":"and these wreaths descended into and mixed with a beard and whiskers of the same exquisite workmanship which surrounded and decorated a very fierce little face of the reddest gold imaginable right in the front of the mug","subset":"tele","task_type":"understanding","prediction":"and these wreathed studded into and mixed with a beard and whiskers of the same exquisite workmanship which surrounded and decorated a very fierce little face of the reddest gold imaginable right in the front of the mug","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":698,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm1-tele-sp7868-ch110706-sg0021-mc02-lav-clo-dg160.wav","answer":"and fell thundering across his path and though he had repeatedly faced these dangers on the most terrific glaciers and in the wildest weather it was with a new and oppressive feeling of panic terror that he leaped the last chasm and flung himself","subset":"tele","task_type":"understanding","prediction":"and fell thundering across the pass and though he had repeatedly faced these dangers on the most terrific glaciers and in the wildest weather it was with a new and oppressive feeling of panic terror that he leaped the last chasm and flung himself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":699,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm1-tele-sp7881-ch110131-sg0018-mc02-lav-clo-dg100.wav","answer":"as he picked him up roughly and set him on his neck jose seized the giant's long beard and drew it around his neck so tightly that the giant fell to the floor dead then jose seized one of the money bags and ran home with it to his mother","subset":"tele","task_type":"understanding","prediction":"as he picked him up roughly and set him on his neck jose seized the giant s long beard and drew it around his neck so tightly that the giant fell to the floor dead then jose seized one of the money bags and ran home with it to his mother","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":700,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7910\/Lab41-SRI-VOiCES-rm1-tele-sp7910-ch080534-sg0049-mc02-lav-clo-dg000.wav","answer":"i've broke myself off that but if you was to leave me i've had hard things to go through do you know the burial club broke up just before she died i couldn't get not a ha'penny a lot o the money was stolen you may think how i felt clara with her lyin there","subset":"tele","task_type":"understanding","prediction":"i broke myself off that but if you was to leave me i had hard things to go through do you know the burial club broke up just before she died i could get not a hay penny a lot of the money was stolen you may think how i felt clara with her lying there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":701,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7910\/Lab41-SRI-VOiCES-rm1-tele-sp7910-ch294690-sg0005-mc02-lav-clo-dg180.wav","answer":"the parlor was empty i went into the kitchen i went into the upper rooms solitude everywhere the bailiff had left the place and his mother and his daughter had gone with him no friend or neighbor lingered near with a message","subset":"tele","task_type":"understanding","prediction":"the parlor was empty i went into the kitchen i went into the upper rooms solitude everywhere the bailiff had left the place and his mother and his daughter had gone with him no friend or neighbor lingered near with a message","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":702,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm1-tele-sp7932-ch093470-sg0010-mc01-stu-clo-dg070.wav","answer":"i believe that there is a struggle going on in her mind on the subject and that if she is to have peace and as you say health she must unburden her mind however mister powlett my advice in the matter is leave her alone do not press her in any way","subset":"tele","task_type":"understanding","prediction":"i believe that there is a struggle going on in her mind on the subject and that if she is to have peace and as you say health she must unburden her mind however mr powlett my advice in the matter is leave her alone do not press her in any way","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":703,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-tele-sp7981-ch112057-sg0025-mc01-stu-clo-dg170.wav","answer":"madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money","subset":"tele","task_type":"understanding","prediction":"madame de gondi herself setting the example of what a perfect lady of charity should be neither dirt discourtesy nor risk of infection could discourage this earnest disciple of vincent in spite of weak health she gave freely of her time her energy and her money","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":704,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm1-tele-sp7981-ch112058-sg0024-mc01-stu-clo-dg070.wav","answer":"and these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries","subset":"tele","task_type":"understanding","prediction":"in these two institutions the first of the famous seminaries which were later to spread all over france were powerful for the reform of the clergy one hundred and fifty years later the mission priests of saint lazare alone were at the head of sixty such seminaries","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":705,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp8057\/Lab41-SRI-VOiCES-rm1-tele-sp8057-ch296395-sg0002-mc01-stu-clo-dg130.wav","answer":"and with more or less indistinct markings of the tabby character it is of about ordinary size the tail is in form somewhat like that of most of our cats and the ears are largish and pointed in a slightly lynx like fashion","subset":"tele","task_type":"understanding","prediction":"and with more or less indistinct markings of the tabby character it is of about ordinary size the tail is in form somewhat like that of most of our cats and the ears are large and pointed in a slightly lynx like fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":706,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm1-tele-sp8225-ch274376-sg0002-mc01-stu-clo-dg060.wav","answer":"than the english parliament in order to allure that nation into a close confederacy openly declared their wishes of ecclesiastical reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used","subset":"tele","task_type":"understanding","prediction":"then the english parliament in order to allure that nation into a close confederacy openly declared their wishes of embracing the articles of reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":707,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm1-tele-sp8225-ch274376-sg0017-mc01-stu-clo-dg180.wav","answer":"and passively yielded to the torrent the general assembly of the church met at the same time with the convention and exercising an authority almost absolute over the whole civil power made every political consideration yield to their theological zeal and prejudices","subset":"tele","task_type":"understanding","prediction":"and passively yielded to the torrent the general assembly of the church met at the same time with the convention and exercising an authority almost absolute over the whole civil power made every political consideration yield to their theological zeal and prejudices","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":708,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm1-tele-sp8425-ch291444-sg0008-mc02-lav-clo-dg060.wav","answer":"sweetened it with the graces of sentiment like tacitus and infused into the whole the dignity the grandeur and magnificence of livy i am aware that i shall incur the censure of numerous very learned and judicious critics for","subset":"tele","task_type":"understanding","prediction":"sweetened it with the graces of sentiment like dactylist and infused into the whole the dignity the grandeur and magnificence of lythie i am aware that i shall incur the censure of numerous very learned and judicious critics for","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":709,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp8575\/Lab41-SRI-VOiCES-rm1-tele-sp8575-ch290349-sg0022-mc02-lav-clo-dg010.wav","answer":"it is also evident that it must touch one part of the flesh first and another after and so in succession and yet i believe nobody who ever felt the pain of such a shot or heard the blow against the two distant walls could perceive any succession either in the pain or sound of so swift a stroke","subset":"tele","task_type":"understanding","prediction":"it is also evident that it must touch one part of the flesh first and another after and so in succession and yet i believe nobody who ever felt the pain of such a shot or heard the blow against the two distant walls could perceive any succession either in the pain or sound of so swift a stroke","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":710,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp8605\/Lab41-SRI-VOiCES-rm1-tele-sp8605-ch292138-sg0022-mc01-stu-clo-dg110.wav","answer":"and clarence looked very approvingly at the nice plum cake and the madeira cake which is a sort of sponge cake with slices of preserved citron on top of it a favourite cake for teas in a few minutes the water boiled in spite of everybody watching it attentively","subset":"tele","task_type":"understanding","prediction":"and clarence looked very approvingly at the nice plum cake and the madeira cake which is a sort of sponge cake with slices of preserved citron on top of it a favourite cake for teas in a few minutes the water boiled in spite of everybody watching it attentively","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":711,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm1\/tele\/sp_6241-8713\/sp8635\/Lab41-SRI-VOiCES-rm1-tele-sp8635-ch295759-sg0012-mc02-lav-clo-dg100.wav","answer":"and in the rear of it the men of rank marched two and two when the corpse was put in the ground the guard fired their guns three times and then all the troops marched back to camp the red men the del a wares and shaw nees came to aid gen er al brad dock","subset":"tele","task_type":"understanding","prediction":"and in the rear of it the men of rank marched two and two when the corpse was put in the ground the guard fired their guns three times and then all the troops marched back to camp the red men the delawares and the shawnees came to aid general braddock","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":712,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm2-babb-sp0112-ch121671-sg0025-mc02-lav-clo-dg040.wav","answer":"the children all painted their faces to look as indians do when they are on the warpath and they caught the roosters and the turkey cock and pulled feathers from their tails to stick in their hair and then the boys made wooden tomahawks for the girls and bows and arrows for their own use","subset":"babb","task_type":"understanding","prediction":"the children all painted their faces to look as indians do when they are on the warpath and they caught the roosters and the turkey cock and pulled feathers from their tails to stick in their hair and then the boys made wooden tomahawks for the girls and bows and arrows for their own use","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":713,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm2-babb-sp0112-ch123216-sg0003-mc02-lav-clo-dg030.wav","answer":"said anne never mind i begin faintly to discern clear water ahead where no examination breakers loom girls do you can you realize that our redmond life is almost over i can't said anne sorrowfully","subset":"babb","task_type":"understanding","prediction":"said anne never mind i begin faintly to discern clear water ahead where no examination breakers live girls do you can you realize that our redmond life is almost over i can t said anne sorrowfully","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":714,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0188\/Lab41-SRI-VOiCES-rm2-babb-sp0188-ch135249-sg0019-mc01-stu-clo-dg080.wav","answer":"came with her mother and missus jasper bell but in jane the milk of human kindness had not been curdled by years of matrimonial bickerings her lines had fallen in pleasant places in spite of the fact as missus rachel lynde would say","subset":"babb","task_type":"understanding","prediction":"came with her mother and mrs jasper bell but in jane the milk of human kindness had not been curdled by years of matrimonial bickerings her lines had fallen in pleasant places in spite of the fact as mrs rachel lynde would say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":715,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0188\/Lab41-SRI-VOiCES-rm2-babb-sp0188-ch135249-sg0030-mc01-stu-clo-dg170.wav","answer":"but when we get a phone in that won't matter so much the situation is beautiful it looks to the sunset and has the great blue harbor before it the sand dunes aren't very far away the sea winds blow over them and the sea spray drenches them","subset":"babb","task_type":"understanding","prediction":"but when we get a phone in that won t matter so much the situation is beautiful it looks to the sunset and has the great blue harbour before it the sand dunes aren t very far away the sea winds blow over them and the sea spray drenches them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":716,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm2-babb-sp0204-ch287139-sg0020-mc01-stu-clo-dg170.wav","answer":"squalling was the word for it pew's anger rose so high at these objections till at last his passion completely taking the upper hand he struck at them right and left in his blindness and his stick sounded heavily on more than one","subset":"babb","task_type":"understanding","prediction":"squalling was the word for it pughes anger rose so high at these objections till at last his passion completely taking the upper hand he struck at them right and left in his blindness and his stick sounded heavily on more than one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":717,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm2-babb-sp0205-ch157088-sg0027-mc02-lav-clo-dg050.wav","answer":"but we can not because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains","subset":"babb","task_type":"understanding","prediction":"but we cannot because everything up here is locked away from us i repeat that isn t conservation if they had applied a little of it to the salmon industry but they didn t and the salmon are going like the buffalo of the plains","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":718,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0208\/Lab41-SRI-VOiCES-rm2-babb-sp0208-ch126600-sg0011-mc02-lav-clo-dg090.wav","answer":"freddie fisher fairly fussed when he came to eat his crust often on the floor he'd throw it hoping mother wouldn't know it goops all hate to eat the crust if you're told to then you must","subset":"babb","task_type":"understanding","prediction":"Freddy fished fairly fast when he came to eat his crust. Often on the floor, he d throw it, hoping mother wouldn t know it. Goofs all hate to eat the crust. If you re told to, then you must.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":719,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0208\/Lab41-SRI-VOiCES-rm2-babb-sp0208-ch128036-sg0004-mc02-lav-clo-dg180.wav","answer":"the cowslip has been much admired altho its proper name we're told is really the marsh marigold the cow bird picture i suspect is absolutely incorrect we make such errors now and then a sort of cow slip of the pen a sparrer","subset":"babb","task_type":"understanding","prediction":"the cowslip has been much admired although its proper name retold is really the marsh marigold the cupboard picture i suspect is absolutely incorrect you make such errors now and then i started off cowslip off the pan asparagus","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":16}
+{"index":720,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0240\/Lab41-SRI-VOiCES-rm2-babb-sp0240-ch144999-sg0038-mc02-lav-clo-dg000.wav","answer":"and by no means is it really necessary to a successful outing twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals","subset":"babb","task_type":"understanding","prediction":"and by no means is it really necessary to a successful hunter twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":721,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm2-babb-sp0242-ch122626-sg0030-mc01-stu-clo-dg170.wav","answer":"did she say that to me did you hear her eliza and georgiana won't i tell mama but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing","subset":"babb","task_type":"understanding","prediction":"did she say that to me do you hear her eliza and georgiana won t i tell mamma but first he ran headlong at me i felt him grasp my hair and my shoulder he had closed with a desperate thing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":722,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0296\/Lab41-SRI-VOiCES-rm2-babb-sp0296-ch142727-sg0031-mc01-stu-clo-dg090.wav","answer":"these derangements are the basis of emotion its physical basis and to be moved is to perceive them take away from the consciousness this physical reflex and emotion ceases it is no longer anything but an idea","subset":"babb","task_type":"understanding","prediction":"These derangements are the basis of emotion. Its physical basis and to be moved is to perceive them. Take away from the consciousness, this physical reflex and emotion ceases. It is no longer anything but an idea.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":723,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm2-babb-sp0459-ch127522-sg0015-mc01-stu-clo-dg030.wav","answer":"here at that same moment came news of another far away out in the marsh there arose all of a sudden a sound like the cry of anger then another on the back of it and then one horrid long drawn scream","subset":"babb","task_type":"understanding","prediction":"here at that same moment came news of another far away out in the marsh there arose all of a sudden a sound like the cry of anger then another on the back of it and then one horrid long drawn scream","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":724,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm2-babb-sp0472-ch129983-sg0011-mc02-lav-clo-dg180.wav","answer":"which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth","subset":"babb","task_type":"understanding","prediction":"which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":725,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm2-babb-sp0479-ch126480-sg0005-mc02-lav-clo-dg040.wav","answer":"i really couldn't couldn't eat mouse pie and i shall have to eat it because it is a party and my pie was going to be veal and ham a pink and white pie dish and so is mine just like ribby's dishes they were both bought at tabitha twitchit's","subset":"babb","task_type":"understanding","prediction":"i really couldnt couldnt eat nose pie and i shall have to eat it because it is party and my pie was going to be veal and ham a pink and white pie dish and so is mine just like ruby s dishes they were both bought in town with the titchwitz","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":13}
+{"index":726,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm2-babb-sp0479-ch134717-sg0034-mc02-lav-clo-dg020.wav","answer":"and the singer so shy to the rest receiv'd me the gray brown bird i know receiv'd us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird","subset":"babb","task_type":"understanding","prediction":"and the singer so shy to the rest received me the gray brown bird i know received us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":727,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm2-babb-sp0479-ch134717-sg0056-mc01-stu-clo-dg050.wav","answer":"weapons and each with musing soul retire to celebrate our dear commander's death no more for him life's stormy conflicts nor victory nor defeat no more time's dark events charging like ceaseless clouds across the sky but sing poet in our name","subset":"babb","task_type":"understanding","prediction":"weapons in each with musing soul retired a celebrator of dear commander s death no more for him life s stormy conflicts nor victory nor defeat no more time s dark events charging like ceaseless clouds across the sky but sing poet in our name","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":728,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm2-babb-sp0480-ch123176-sg0004-mc01-stu-clo-dg080.wav","answer":"pour it in a bowl on a slice of toast cut up and grate a little nutmeg over panada put some crackers crusts of dry bread or dried rusk in a sauce pan with cold water and a few raisins","subset":"babb","task_type":"understanding","prediction":"Pour it in a bowl on a slice of toast, cut up and grate a little nutmeg over it. Panada put some crackers, crusts of dry bread, or dried rusk in a saucepan with cold water and a few raisins.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":729,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm2-babb-sp0480-ch126336-sg0000-mc02-lav-clo-dg110.wav","answer":"king grisly beard a great king of a land far away in the east had a daughter who was very beautiful but so proud and haughty and conceited","subset":"babb","task_type":"understanding","prediction":"king grizzly bear a great king of a land far away in the east had a daughter who was very beautiful but so proud and haughty conceited","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":730,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131882-sg0000-mc01-stu-clo-dg030.wav","answer":"burlington gardens the house in which sheridan died in eighteen fourteen he was one of the most noticeable members of the reform club though he seemed always to avoid attracting attention an enigmatical personage","subset":"babb","task_type":"understanding","prediction":"burlington gardens the house in which sheraton died in eighteen forty he was one of the most noticeable members of the reform club though he seemed always to avoid attracting attention an anegmatical person","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":731,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131887-sg0009-mc02-lav-clo-dg100.wav","answer":"nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger","subset":"babb","task_type":"understanding","prediction":"nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":732,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131887-sg0022-mc01-stu-clo-dg080.wav","answer":"it is thirteen hundred and ten miles from suez to aden at the other end of the red sea and she has to take in a fresh coal supply and does she go from suez directly to bombay","subset":"babb","task_type":"understanding","prediction":"it is thirteen hundred and ten miles from suez to aden at the other end of the red sea and she has to take in a fresh coal supply and does she go from suez directly to bombay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":733,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-babb-sp0492-ch131899-sg0008-mc01-stu-clo-dg010.wav","answer":"he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation","subset":"babb","task_type":"understanding","prediction":"he made no account of this inconvenience and whilst his body was writhing under their effects his spirit bounded with hopeful exultation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":734,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm2-babb-sp0510-ch130101-sg0009-mc01-stu-clo-dg010.wav","answer":"they occupied themselves again in dragging their own tragedies toward the rear suddenly as the two friends marched on the tall soldier seemed to be overcome by a tremor his face turned to a semblance of gray paste","subset":"babb","task_type":"understanding","prediction":"they occupied themselves again in dragging their own tragedies toward the rear suddenly as the two friends marched on the tall soldier seemed to be overcome by a tremor his face turned to a semblance of gray paste","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":735,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm2-babb-sp0510-ch130101-sg0021-mc01-stu-clo-dg180.wav","answer":"he protested in a dulled way keeping his eyes fastened on the mystic place of his intentions no no don't tech me leave me be leave me be the youth aghast and filled with wonder at the tall soldier","subset":"babb","task_type":"understanding","prediction":"he protested in a dulled way keeping his eyes fastened on the mystic place of his intentions no no dont touch me leave me be leave me be the youth aghast and filled with wonder at the tall soldier","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":736,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm2-babb-sp0636-ch123163-sg0012-mc02-lav-clo-dg140.wav","answer":"the jar or pan should be of stone ware or fire proof yellow ware to boil salt cod put your fish to soak over night change the water in the morning and let it stay till you put it on which should be two hours before dinner","subset":"babb","task_type":"understanding","prediction":"the jar or pan should be of stoneware or fireproof yellow ware to boil salt cod put your fish to soak over night change the water in the morning and let it stay till you put it on it should be two hours before dinner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":737,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127579-sg0004-mc01-stu-clo-dg040.wav","answer":"i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat","subset":"babb","task_type":"understanding","prediction":"i naturally thought that anything collected at such pains must possess peculiar merits but one mouthful was a complete dose and great was the consternation of the old warrior at the rapidity with which i ejected his epicurean treat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":738,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127579-sg0029-mc02-lav-clo-dg170.wav","answer":"from whence they are drawn as occasion may require in this condition the tutao sometimes remains for years and even is thought to improve by age before it is fit to be eaten however it has to undergo an additional process","subset":"babb","task_type":"understanding","prediction":"promonts they are drawn as occasion may require in this condition the tutao sometimes remains for years and even is thought to improve by age before it is fit to be eaten however it has to undergo an additional process","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":739,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127595-sg0028-mc01-stu-clo-dg060.wav","answer":"i am convinced that it is as natural for a human being to swim as it is for a duck and yet in civilized communities how many able bodied individuals die like so many drowning kittens from the occurrence of the most trivial accidents","subset":"babb","task_type":"understanding","prediction":"i am convinced that it is as natural for a human being to swim as it is for a duck and yet in civilized communities how many able bodied individuals die like so many drowning kittens from the occurrence of the most trivial accidents","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":740,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm2-babb-sp0637-ch127597-sg0017-mc02-lav-clo-dg120.wav","answer":"this passage for no conceivable reason that i could devise was always closed after the household had retired to rest by drawing a heavy slide across it composed of a dozen or more bits of wood ingeniously fastened together by seizings of sinnate","subset":"babb","task_type":"understanding","prediction":"this passage for no conceivable reason that i could devise was always closed after the household had retired to rest by drawing a heavy slide across it composed of a dozen or more bits of wood ingeniously fastened together by seizings of sinnet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":741,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0770\/Lab41-SRI-VOiCES-rm2-babb-sp0770-ch131704-sg0003-mc01-stu-clo-dg170.wav","answer":"a region as large as the entire union of thirteen states at the close of the war of independence moreover within its boundaries was embraced all the great american gold field just on the eve of discovery for marshall had detected the shining particles in the mill race","subset":"babb","task_type":"understanding","prediction":"a region as large as the entire union of thirteen states at the close of the war of independence moreover within its boundaries was embraced all the great american gold field just on the eve of discovery for marshall had detected the shining particles in the mill race","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":742,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0948\/Lab41-SRI-VOiCES-rm2-babb-sp0948-ch132705-sg0009-mc01-stu-clo-dg090.wav","answer":"a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said","subset":"babb","task_type":"understanding","prediction":"a street sweeper walking in upon the world council of scholars it is not to be believed it is against all the rules and all the laws but we knew how to stop them our brothers we said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":743,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0948\/Lab41-SRI-VOiCES-rm2-babb-sp0948-ch132707-sg0020-mc01-stu-clo-dg140.wav","answer":"we have made a bow and many arrows we can kill more birds than we need for our food we find water and fruit in the forest at night we choose a clearing and we build a ring of fires around it","subset":"babb","task_type":"understanding","prediction":"we have made a bow and many arrows we can kill more birds than we need for our food we find water and fruit in the forest at night we choose a clearing and we build a ring of fires around it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":744,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0948\/Lab41-SRI-VOiCES-rm2-babb-sp0948-ch132707-sg0027-mc01-stu-clo-dg160.wav","answer":"and they wait obediently without questions till it pleases us to turn and go on we go on and we bless the earth under our feet but questions come to us again as we walk in silence","subset":"babb","task_type":"understanding","prediction":"and they wait obediently without question till it pleases us to turn and go on we go on and we bless the earth under our feet but questions come to us again as we walk in silence","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":745,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm2-babb-sp0949-ch134660-sg0008-mc02-lav-clo-dg140.wav","answer":"as seemed necessary to account for its extraordinary preservation and seasonable discovery were gradually propagated without opposition the custody of the true cross which on easter sunday was solemnly exposed to the people was intrusted to the bishop of","subset":"babb","task_type":"understanding","prediction":"as seemed necessary to account for its extraordinary preservation and seasonable discovery were gradually propagated without opposition the custody of the true cross which on easter sunday was solemnly exposed to the people was entrusted to the bishop","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":746,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm2-babb-sp0949-ch138545-sg0036-mc01-stu-clo-dg120.wav","answer":"the slaves nearly equalled or actually exceeded the whites in number in south carolina they formed almost two thirds of the population even in the middle colonies of delaware and pennsylvania about one fifth of the inhabitants were from africa to the north the proportion of slaves steadily diminished","subset":"babb","task_type":"understanding","prediction":"the slaves nearly equaled or actually exceeded the whites in number in south carolina they formed almost two thirds of the population even in the middle colonies of delaware and pennsylvania about one fifth of the inhabitants were from africa to the north the proportion of slaves steadily diminished","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":747,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm2-babb-sp1050-ch134119-sg0034-mc01-stu-clo-dg140.wav","answer":"but the little boys had their india rubber boots at last they discovered the little old woman they knew her by her hat it was steeple crowned without any vane they saw her digging with her trowel round a sassafras bush","subset":"babb","task_type":"understanding","prediction":"but the little boys had their india rubber boots at last they discovered the little old woman they knew her by her hat it was steeple crowned without any vane they saw her digging with her trowel round a sassafras bush","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":748,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm2-babb-sp1112-ch128136-sg0019-mc02-lav-clo-dg090.wav","answer":"are excessively tedious but when mister rodd leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed","subset":"babb","task_type":"understanding","prediction":"are excessively tedious but when mr rod leaves the problem of the unconditioned to take care of itself and makes no attempt to solve the mysteries of the ego and the non ego he is very pleasant reading indeed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":749,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm2-babb-sp1116-ch132847-sg0029-mc01-stu-clo-dg050.wav","answer":"the swallow is less swift than the wind the wind is less swift than the lightning but you my horse if you love me must be swifter than them all for there is a part of my heart that suffers the best part of my heart that is in danger and the horse heard her","subset":"babb","task_type":"understanding","prediction":"The swallow is less swift than the wind. The wind is less swift than the lightning. But you, my horse, if you love me, must be swifter than them all. There is a part of my heart that suffers the best part of my heart that is in danger. And the horse heard her.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":750,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm2-babb-sp1116-ch137572-sg0032-mc01-stu-clo-dg170.wav","answer":"this is why the unique value of children is their service as an entering wedge in the close grown love of husband and wife a wedge that widens and holds forever wider the unity of love it has penetrated other responsibilities other interests may serve a similar purpose","subset":"babb","task_type":"understanding","prediction":"This is why the unique value of children is their service as an entering wedge in the close grown love of husband and wife, a wedge that widens and holds forever wider. The unity of love, it has penetrated other responsibilities, other interests may serve a similar purpose.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":751,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1121\/Lab41-SRI-VOiCES-rm2-babb-sp1121-ch135824-sg0037-mc01-stu-clo-dg150.wav","answer":"then when i do wake up i have plenty to eat i might add said old mother nature that when he goes to sleep for the winter he curls up in a little ball with his long tail wrapped around him and in his bed of soft grass he sleeps very sound indeed","subset":"babb","task_type":"understanding","prediction":"then when i do wake up i have plenty to eat i might add said old mother nature that when he goes to sleep for the winter he curls up in a little ball with his long tail wrapped around him and in his bed of soft grass he sleeps very sound indeed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":752,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm2-babb-sp1160-ch134674-sg0005-mc02-lav-clo-dg050.wav","answer":"from the evidence of reason as well as history that the two marriages of valentinian with severa and with justina were successively contracted and that he used the ancient permission of divorce which was still allowed by the laws though it was condemned by the church","subset":"babb","task_type":"understanding","prediction":"from the evidence of reason as well as history that the two marriages of valentinian with sevira and with justina were successively contracted and that he used the ancient permission of divorce which was still allowed by the laws though it was condemned by the church","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":753,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm2-babb-sp1160-ch139336-sg0020-mc01-stu-clo-dg090.wav","answer":"and the happiness of the governed here then is the origin and rise of government namely a mode rendered necessary by the inability of moral virtue to govern the world here too is the design and end of government viz","subset":"babb","task_type":"understanding","prediction":"and the happiness of the governed here then is the origin and rise of government namely a mode rendered necessary by the inability of moral virtue to govern the world here too is the design and end of government viz","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":754,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_0032-1182\/sp1182\/Lab41-SRI-VOiCES-rm2-babb-sp1182-ch133396-sg0034-mc02-lav-clo-dg030.wav","answer":"inky with the soot of years hans straightened himself and tilting his leathern cap to one side began scratching his bullet head at last he drew a long breath yes good he muttered to himself he who jumps into the river must e e n swim the best he can","subset":"babb","task_type":"understanding","prediction":"inky with the sweat of years hawes straightened himself out tilting his leather cap to one side began scratching his bullet head at last he drew a long breath yes good he muttered to himself he who jumps into the river must even swim the best he can","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":755,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1235\/Lab41-SRI-VOiCES-rm2-babb-sp1235-ch135884-sg0012-mc02-lav-clo-dg160.wav","answer":"and resisting an order which disappointed her malice she cried out what are you doing husband sacrifice that cow your farmer has not a finer nor one fitter for the festival out of deference to my wife i came again to the cow","subset":"babb","task_type":"understanding","prediction":"at resisting an order which disappointed her malice she cried out what are you doing husband sacrifice that cow your farmer has not a finer nor one fitter for the festival out of deference to my wife i came again to the cow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":756,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1259\/Lab41-SRI-VOiCES-rm2-babb-sp1259-ch137770-sg0038-mc01-stu-clo-dg170.wav","answer":"and the servants to humanize and several kettles of helen's to keep on the boil her conscience pricked her a little about the basts she was not sorry to have lost sight of them no doubt leonard was worth helping but being henry's wife she preferred to help someone else","subset":"babb","task_type":"understanding","prediction":"and the servants to humanize and several kettles of hallens to keep on the boil her conscience pricked her a little about the basques she was not sorry to have lost sight of them no doubt leonard was worth helping but being henry s wife she preferred to help some one else","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":757,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm2-babb-sp1272-ch128104-sg0009-mc01-stu-clo-dg180.wav","answer":"he laments most bitterly the divorce that has been made between decorative art and what we usually call pictures makes the customary appeal to the last judgment and reminds us that in the great days of art michael angelo was the furnishing upholsterer","subset":"babb","task_type":"understanding","prediction":"he laments most bitterly the divorce that has been made between decorative art and what we usually call pictures makes a customary appeal to the last judgment and reminds us that in the great days of art michael angelo was the furnishing upholsterer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":758,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm2-babb-sp1272-ch135031-sg0024-mc02-lav-clo-dg150.wav","answer":"having returned to the royal cavern kaliko first pounded the gong and then sat in the throne wearing ruggedo's discarded ruby crown and holding in his hand the sceptre which ruggedo had so often thrown at his head","subset":"babb","task_type":"understanding","prediction":"Having returned to the royal cavern, Calico first pounded the gong and then SAT in the throne, wearing Ruggedo discarded ruby crown and folding in his hand. The scepter, which Ruggedo had so often thrown at his head.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":759,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm2-babb-sp1335-ch160602-sg0009-mc02-lav-clo-dg160.wav","answer":"whose fluttering leaves seemed beckoning him to come it dwelt in a sunny little nook where cool winds rustled by and murmuring bees and butterflies came on the flower's breast to lie","subset":"babb","task_type":"understanding","prediction":"whose fluttering leaves seemed beckoning him to come it dwelt in a sunny little nook where cool winds rustled by and murmuring bees and butterflies came on the flower s breast to lie","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":760,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm2-babb-sp1335-ch163935-sg0005-mc01-stu-clo-dg110.wav","answer":"then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander","subset":"babb","task_type":"understanding","prediction":"then throw in the rice and give it an occasional stir until the water begins to boil again after that it need not be stirred cook until a grain feels soft when rubbed between the thumb and finger then turn into a colander","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":761,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm2-babb-sp1383-ch130489-sg0031-mc01-stu-clo-dg120.wav","answer":"his troubled spirit shifted its load his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm","subset":"babb","task_type":"understanding","prediction":"his troubled spirit shifted and slowed his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":762,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm2-babb-sp1383-ch130533-sg0008-mc01-stu-clo-dg030.wav","answer":"i think we need neither doubt nor fear i think we ought to recur a moment to i think we shall all recognize i think we should do well to call to mind","subset":"babb","task_type":"understanding","prediction":"i think we need neither doubt nor fear i think we ought to recur a moment to i think we shall all recognize i think we should do well to call to mind","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":763,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-babb-sp1392-ch128226-sg0016-mc02-lav-clo-dg090.wav","answer":"they now fancied themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport to their body and this earth gentle is zarathustra to the sickly verily","subset":"babb","task_type":"understanding","prediction":"they now fancy themselves transported these ungrateful ones but to what did they owe the convulsion and rapture of their transport their body and the earth gentle as aratus treated the subject barely","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":764,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1425\/Lab41-SRI-VOiCES-rm2-babb-sp1425-ch139297-sg0036-mc01-stu-clo-dg120.wav","answer":"for during this interval a great change had taken place in master hugh and his once kind and affectionate wife the influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both","subset":"babb","task_type":"understanding","prediction":"For during this interval, a great change had taken place in Master Hugh and his once kind and affectionate wife. The influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":765,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1425\/Lab41-SRI-VOiCES-rm2-babb-sp1425-ch139297-sg0036-mc02-lav-clo-dg120.wav","answer":"for during this interval a great change had taken place in master hugh and his once kind and affectionate wife the influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both","subset":"babb","task_type":"understanding","prediction":"For during this interval, a great change had taken place in Master Hugh and his once kind and affectionate wife. The influence of brandy upon him and of slavery upon her had effected a disastrous change in the characters of both.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":766,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm2-babb-sp1472-ch139797-sg0004-mc02-lav-clo-dg180.wav","answer":"it would not make one sphere as immense as this star or sun around which revolve about five hundred worlds or planets many of which are greater than our jupiter with abounding interest i visited all the inhabited worlds of this vast system how long it took i have no way of knowing","subset":"babb","task_type":"understanding","prediction":"it would not make one sphere as immense as this star sign around which revolve about five hundred worlds or planets many of which are greater than our jupiter with abounding interest i visited all the inhabited worlds of this vast system how long it took i have no way of knowing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":767,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm2-babb-sp1472-ch285314-sg0011-mc02-lav-clo-dg040.wav","answer":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i'll set lon taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i'll hunt him up","subset":"babb","task_type":"understanding","prediction":"but of course you are to fit up the place at your own expense thank you very much sir exclaimed uncle john i ll set lawn taft at work at once where can he be found playing billiards at the hotel usually i suppose he is there now very good i ll hunt him up","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":768,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1536\/Lab41-SRI-VOiCES-rm2-babb-sp1536-ch141791-sg0006-mc01-stu-clo-dg090.wav","answer":"as soon as londonderry had fallen and it was universally supposed that the fall of londonderry could not be long delayed he might cross the sea with part of his forces and land in scotland where his friends were supposed to be numerous when he was once on british ground and in the midst of british adherents","subset":"babb","task_type":"understanding","prediction":"as soon as londonderry had fallen and it was universally supposed that the fall of londonderry could not be long delayed he might cross the sea with part of his forces and land in scotland where his friends were supposed to be numerous when he was once on british ground and in the midst of british adherents","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":769,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1607\/Lab41-SRI-VOiCES-rm2-babb-sp1607-ch149245-sg0039-mc02-lav-clo-dg160.wav","answer":"which had served in holland and which bore the names of their colonels mackay himself balfour and ramsay there was also a gallant regiment of infantry from england then called hastings's but now known as the thirteenth of the line","subset":"babb","task_type":"understanding","prediction":"which had served in holland and which bore the name of their colonel mackay himself delfour ramsay there was also a gallant regiment of infantry from england then called hastings but now known as the thirteenth of the line","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":770,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1841\/Lab41-SRI-VOiCES-rm2-babb-sp1841-ch150351-sg0013-mc01-stu-clo-dg070.wav","answer":"and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the indian came out and plunged into the cold water of a near by stream","subset":"babb","task_type":"understanding","prediction":"and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the antaeon came out and plunged into the cold water of a near by stream","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":771,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1851\/Lab41-SRI-VOiCES-rm2-babb-sp1851-ch151817-sg0036-mc01-stu-clo-dg150.wav","answer":"or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course they must be totally ignorant of all such things as flying machines and the like","subset":"babb","task_type":"understanding","prediction":"or watching for the monster bird of prey rather suggested the elder gillespie of course they couldn't distinguish our faces and our bodies were fairly well hidden and even more of course they must be totally ignorant of all such things as flying machines and the like","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":772,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm2-babb-sp1867-ch148436-sg0020-mc02-lav-clo-dg020.wav","answer":"and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothin","subset":"babb","task_type":"understanding","prediction":"and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":773,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm2-babb-sp1867-ch154071-sg0017-mc01-stu-clo-dg050.wav","answer":"the same distinction between their clothes was in their faces the finely modeled prettiness of her features and the big careless chiseling of the features of bill gregg ronicky doone did not wonder that after her first fear her gesture was one of disdain and surprise","subset":"babb","task_type":"understanding","prediction":"the same distinction between their clothes was in their faces the finely modelled prettiness of her features and the big careless chiselling of the features of bill gregg ronicky doone did not wonder that after her first fear her gesture was one of disdain and surprise","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":774,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1926\/Lab41-SRI-VOiCES-rm2-babb-sp1926-ch147987-sg0019-mc01-stu-clo-dg010.wav","answer":"and had left again on the six o'clock train for denver that morning the agent said his face was striped with court plaster and he carried his left hand in a sling he looked so used up that the agent asked him what had happened to him since ten o'clock the night before","subset":"babb","task_type":"understanding","prediction":"and had left again on the six o clock train for denver that morning the agent said his face was striped with cork plaster and he carried his left hand in a sling he looked so used up that the agent asked him what had happened to him since ten o clock the night before","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":775,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm2-babb-sp1961-ch149739-sg0018-mc02-lav-clo-dg070.wav","answer":"he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor","subset":"babb","task_type":"understanding","prediction":"he could find no trace of a clue to confirm his belief yet so intimately was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":776,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1963\/Lab41-SRI-VOiCES-rm2-babb-sp1963-ch142776-sg0013-mc02-lav-clo-dg060.wav","answer":"a little nutmeg one teaspoonful of flour one pint of cream one pint of milk forcemeat balls mace salt and pepper to taste bread crumbs one egg two quarts of water mode","subset":"babb","task_type":"understanding","prediction":"a little nutmeg one teaspoonful of flour one pint of cream one pint of milk horse meat balls mace salt and pepper to taste bread crumbs one egg two quarts of water melt","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":777,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm2-babb-sp1970-ch010594-sg0033-mc02-lav-clo-dg020.wav","answer":"at another time she might have resented these words especially the last but i had roused her curiosity her panting eager curiosity and she let them pass altogether unchallenged did you see this woman","subset":"babb","task_type":"understanding","prediction":"at another time she might have resented these words especially the last but i had roused her curiosity her panting eager curiosity and she let them pass altogether unchallenged did you see this woman","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":778,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm2-babb-sp1970-ch026100-sg0015-mc01-stu-clo-dg030.wav","answer":"everything points to an aeroplane it was done a hundred yes a thousand times in the war while i was over there with my hospital unit we used to get a lot of cases of motorcycle despatch riders who had been picked off by german aviators","subset":"babb","task_type":"understanding","prediction":"everything points to an airplane it was done a hundred yes a thousand times in the war while i was over there with my hospital unit we used to get a lot of cases of motorcycle dispatch riders who had been picked off by german aviators","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":779,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm2-babb-sp1970-ch028415-sg0006-mc01-stu-clo-dg050.wav","answer":"some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another","subset":"babb","task_type":"understanding","prediction":"some cut branches from the trees and waved them before the messiah it was a royal welcome only the priests and the rulers and the pharisees were sorry to see jesus come what is there we can do they said to one another","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":780,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2093\/Lab41-SRI-VOiCES-rm2-babb-sp2093-ch143262-sg0015-mc01-stu-clo-dg080.wav","answer":"and apparently bent on getting us away i caught such words as fever prisoner my head years misery despair always","subset":"babb","task_type":"understanding","prediction":"and apparently bent on getting us away i caught such words as fever prisoner my head years misery despair always","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":781,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2093\/Lab41-SRI-VOiCES-rm2-babb-sp2093-ch143271-sg0020-mc01-stu-clo-dg040.wav","answer":"we'll go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply","subset":"babb","task_type":"understanding","prediction":"will go to another tribe of the blacks make friends with them and get them to fight on our side nonsense doctor i said bitterly you are only saying this to comfort me to get you to act like a man he said sharply","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":782,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm2-babb-sp2110-ch161101-sg0036-mc01-stu-clo-dg050.wav","answer":"you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it","subset":"babb","task_type":"understanding","prediction":"you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":783,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2149\/Lab41-SRI-VOiCES-rm2-babb-sp2149-ch007239-sg0021-mc01-stu-clo-dg120.wav","answer":"what things came upon me at antioch at iconium at lystra what persecutions i endured","subset":"babb","task_type":"understanding","prediction":"what things came upon me at antioch at iconium at lystra what persecutions i endured","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":784,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm2-babb-sp2156-ch025563-sg0005-mc01-stu-clo-dg020.wav","answer":"that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan's name missus phelan's son came a running he had been on his way","subset":"babb","task_type":"understanding","prediction":"that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan s name mrs phelan s son came a running he had been on his way","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":785,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm2-babb-sp2285-ch149890-sg0019-mc02-lav-clo-dg100.wav","answer":"moderately interested in its welfare hurstwood's word however had gone the rounds it was to be a full dress affair the four boxes had been taken doctor norman mc neill hale and his wife were to occupy one","subset":"babb","task_type":"understanding","prediction":"moderately interested in its welfare hurstwood s word however had gone the rounds it was to be a full dress affair the four boxes had been taken dr norman mc neil hale and his wife were to occupy one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":786,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm2-babb-sp2289-ch152254-sg0028-mc02-lav-clo-dg020.wav","answer":"in among the roman ships towing behind them large boats filled with material that would easily burn these boats were set on fire and floated against the roman vessels which also were soon on fire the flames quickly spread","subset":"babb","task_type":"understanding","prediction":"animal ships towing behind them large boats filled with material that would easily burn these boats were set on fire and floated against the roman vessels which also were soon on fire the flames quickly spread","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":787,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm2-babb-sp2289-ch152258-sg0035-mc01-stu-clo-dg170.wav","answer":"of the mosque and chanting in a loud voice such words as these come to prayer come to prayer there is no god but god he giveth life and he dieth not i praise his perfection god is great in mecca","subset":"babb","task_type":"understanding","prediction":"of the mosque and chanting in a loud voice such words as these come to prayer come to prayer there is no god but god he giveth life and he dieth not i praise his perfection god is great in mecca","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":788,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-babb-sp2412-ch153947-sg0014-mc01-stu-clo-dg000.wav","answer":"i made a few further very trifling alterations before moulds were taken but since the summer of eighteen seventy two as new editions were from time to time wanted they have been printed from stereos then made","subset":"babb","task_type":"understanding","prediction":"i made a few further very trifling alterations before moulds were taken but since the summer of eighteen seventy two as new editions were from time to time wanted they have been printed from stereos then made","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":789,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-babb-sp2412-ch153954-sg0009-mc01-stu-clo-dg140.wav","answer":"i have always delighted in and reverenced beauty but i felt simply abashed in the presence of such a splendid type a compound of all that is best in egyptian greek and italian","subset":"babb","task_type":"understanding","prediction":"i have always delighted in and reverenced beauty but i felt simply abashed in the presence of such a splendid type a compound of all that is best in egyptian greek and italian","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":790,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-babb-sp2412-ch153954-sg0015-mc01-stu-clo-dg040.wav","answer":"suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome","subset":"babb","task_type":"understanding","prediction":"suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well in the answer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":791,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2481\/Lab41-SRI-VOiCES-rm2-babb-sp2481-ch012731-sg0026-mc01-stu-clo-dg080.wav","answer":"cold soap heat twenty six pounds of strained grease when melted mix it with four pailsful of lye made of twenty pounds of white potash let the whole stand in the sun stirring it frequently in the course of a week","subset":"babb","task_type":"understanding","prediction":"cold soap heat twenty six pounds of strained grease when melted mix it with four pails full of ley made of twenty pounds of white potash let the whole stand in the sun stirring it frequently in the course of a week","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":792,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2481\/Lab41-SRI-VOiCES-rm2-babb-sp2481-ch163597-sg0025-mc01-stu-clo-dg140.wav","answer":"with the intention of taking them out into the upper world for they all loved him and would not be separated from him each of them turned her palace into an egg for they were all enchantresses and they taught him how to turn the eggs into palaces and back again","subset":"babb","task_type":"understanding","prediction":"with the intention of taking them out into the upper world for they all loved him and would not be separated from him each of them turned her palace into an egg for they were all enchantresses and they taught him how to turn the eggs into palaces and back again","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":793,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2573\/Lab41-SRI-VOiCES-rm2-babb-sp2573-ch178450-sg0027-mc02-lav-clo-dg150.wav","answer":"aren't you ever goin to bed sheridan halted all right mamma he said with a vast sigh let's go up and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising lopsidedly in her drowsiness","subset":"babb","task_type":"understanding","prediction":"arent you ever going to bed sheridan halted all right mamma he said with a vast sigh lets go out and he snapped off the electric light leaving only the rosy glow of the fire did you speak to roscoe she yawned rising up sadly in her drowsiness","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":794,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2573\/Lab41-SRI-VOiCES-rm2-babb-sp2573-ch186232-sg0008-mc02-lav-clo-dg110.wav","answer":"and you would be doing the right thing at last i won't said aunt jane angrily it would also be considerate and just to the memory of mister bradley continued the girl what's going to became of kenneth","subset":"babb","task_type":"understanding","prediction":"and you would be doing the right thing at last i won't said aunt jane angrily it would also be considerate and just to the memory of mr bradley continued the girl what is going to become of kenneth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":795,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2673\/Lab41-SRI-VOiCES-rm2-babb-sp2673-ch162130-sg0014-mc01-stu-clo-dg020.wav","answer":"it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution","subset":"babb","task_type":"understanding","prediction":"it seems certainly deserving of discussion and i could not refrain from putting it forward as a possible means of relief from an intolerable situation but i do not wish to wind up on that note the right solution","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":796,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2691\/Lab41-SRI-VOiCES-rm2-babb-sp2691-ch156745-sg0027-mc02-lav-clo-dg160.wav","answer":"merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground frances","subset":"babb","task_type":"understanding","prediction":"merrily up and down in the clear water she lathered them with a freshly gathered soap root and cleansed them according to the ways of the spanish mission teachers as she tied the wet garments in a bundle and turned to carry them to the drying ground francis","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":797,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm2-babb-sp2758-ch086588-sg0001-mc02-lav-clo-dg160.wav","answer":"he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth","subset":"babb","task_type":"understanding","prediction":"he had inventions rare wordsworth when i had after many years of study and research in england and on the continent developed the theory that all practical technical education of youth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":798,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm2-babb-sp2758-ch161217-sg0012-mc01-stu-clo-dg170.wav","answer":"the power which they wielded over the fate of man was significantly indicated under the figure of a thread which they spun out for the life of each human being from his birth to the grave this occupation they divided between them","subset":"babb","task_type":"understanding","prediction":"The power, which they wielded over the fate of man, was significantly indicated under the figure of a thread, which they spun out for the life of each human being from his birth to the grave. This occupation, they divided between them.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":799,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm2-babb-sp2758-ch161217-sg0012-mc02-lav-clo-dg170.wav","answer":"the power which they wielded over the fate of man was significantly indicated under the figure of a thread which they spun out for the life of each human being from his birth to the grave this occupation they divided between them","subset":"babb","task_type":"understanding","prediction":"the power which they wielded over the fate of man was significantly indicated under the figure of a thread which they spun out for the life of each human being from his birth to the grave this occupation they divided between them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":800,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm2-babb-sp2803-ch154328-sg0018-mc01-stu-clo-dg120.wav","answer":"their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sounds that only a thin layer of earth prevented immediate communication","subset":"babb","task_type":"understanding","prediction":"their fingers bled but still they worked on after half an hour they had gone three feet deep they perceived by the increased sharpness of the sound that only a thin layer of earth prevented immediate communication","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":801,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm2-babb-sp2911-ch007601-sg0036-mc02-lav-clo-dg060.wav","answer":"if still you think me mad you will think so no longer when i describe the wise precautions i took for the concealment of the body the night waned and i worked hastily but in silence first of all i dismembered the corpse i cut off the head","subset":"babb","task_type":"understanding","prediction":"if still you think me mad you will think so no longer when i describe the wise precautions i took for the concealment of the body the night waned and i worked hastily but in silence first of all i dismembered the corpse i cut off the head","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":802,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm2-babb-sp3368-ch170951-sg0016-mc01-stu-clo-dg090.wav","answer":"now the founders of a state ought to know the general forms in which poets should cast their tales and the limits which must be observed by them but to make the tales is not their business very true he said but what are these forms of theology which you mean something of this kind i replied","subset":"babb","task_type":"understanding","prediction":"now the founders of a state ought to know the general forms in which poets should cast their tales and the limits which must be observed by them but to make the tales is not their business very true he said but what are these forms of theology which you mean something of this kind i replied","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":803,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-babb-sp3446-ch144021-sg0018-mc01-stu-clo-dg090.wav","answer":"mate down with fever ngora ngora sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset","subset":"babb","task_type":"understanding","prediction":"mate down with fever negoro negoro sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":804,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-babb-sp3446-ch176270-sg0045-mc01-stu-clo-dg020.wav","answer":"which had been commenced long ago as to enable them to perform divine service in it requested his holiness to consecrate it to this the pontiff willingly agreed and the florentines to exhibit the wealth of the city and the splendor of the edifice and do greater honor to the pope","subset":"babb","task_type":"understanding","prediction":"which had been commenced long ago as to enable them to perform divine service in it requested his holiness to consecrate it to this the pontiff willingly agreed and the florentines to exhibit the wealth of the city and the splendor of the edifice and do greater honor to the pope","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":805,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm2-babb-sp3835-ch178029-sg0008-mc01-stu-clo-dg060.wav","answer":"which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire","subset":"babb","task_type":"understanding","prediction":"which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":806,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp3972\/Lab41-SRI-VOiCES-rm2-babb-sp3972-ch005791-sg0005-mc01-stu-clo-dg090.wav","answer":"which would make me revere its possessor were he the lowliest man in your legions allow me noblest of scots to plead one word in vindication of him to whom my allegiance is pledged had he come hither conducted by war alone what would edward have been worse than any other conqueror","subset":"babb","task_type":"understanding","prediction":"which would make me revere its possessor were he the lowliest man in your legions allow me noblest of scots to plead one word in vindication of him to whom my allegiance is pledged had he come hither conducted by war alone what would edward have been worse than any other conqueror","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":807,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp3994\/Lab41-SRI-VOiCES-rm2-babb-sp3994-ch011512-sg0017-mc02-lav-clo-dg130.wav","answer":"the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved","subset":"babb","task_type":"understanding","prediction":"the perfection of community utilities such as transportation streets lighting and communication from the absence of individual homes and the housing of people in huge dormitories that some different less individualistic type of social organization than ours was involved","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":808,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4010\/Lab41-SRI-VOiCES-rm2-babb-sp4010-ch010798-sg0024-mc01-stu-clo-dg180.wav","answer":"is indeed the centre of your being your very heart nor does the lesson apply to those only who worship mammon who give their lives their best energies to the accumulation of wealth","subset":"babb","task_type":"understanding","prediction":"is indeed the center of your being your very heart nor does the lesson apply to those only who worship mammon who give their lives their best energies to the accumulation of wealth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":809,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4057\/Lab41-SRI-VOiCES-rm2-babb-sp4057-ch011254-sg0013-mc01-stu-clo-dg070.wav","answer":"or the lectures of the london institution of a third a city snob of taste at picture auctions at private views of exhibitions or at the opera or the philharmonic but intimacy is impossible in most cases","subset":"babb","task_type":"understanding","prediction":"or the lectures of the london institution of the third a city snob of taste at picture auctions at private views of exhibitions or at the opera or the philharmonic but intimacy is impossible in most cases","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":810,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4110\/Lab41-SRI-VOiCES-rm2-babb-sp4110-ch011528-sg0022-mc01-stu-clo-dg060.wav","answer":"unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and","subset":"babb","task_type":"understanding","prediction":"unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":811,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4160\/Lab41-SRI-VOiCES-rm2-babb-sp4160-ch011549-sg0016-mc02-lav-clo-dg060.wav","answer":"my late lamented parents at the respective ages of fifty and fifty seven my sister anastasia my only brother my sister in law his wife and my dear priscilla at seventeen years theo turned from the others to look at this last with a deeper interest","subset":"babb","task_type":"understanding","prediction":"my late lamented parents at the respective ages of fifty and fifty seven my sister anastasia my only brother my sister in law his wife and my dear priscilla at seventeen years theo turned from the others to look at this last with a deeper interest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":812,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-babb-sp4427-ch020023-sg0014-mc01-stu-clo-dg020.wav","answer":"i believe i have never mistaken a cow for a human being as was done by old doctor e it was many years ago when boston common was still used as a pasture and cows were daily to be met in the crooked streets of the city that this gentleman","subset":"babb","task_type":"understanding","prediction":"i believe i have never mistaken a cow for a human being as was done by old doctor e it was many years ago when boston common was still used as pasture and cows were daily to be met in the crooked streets of the city that this gentleman","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":813,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm2-babb-sp4438-ch052195-sg0010-mc02-lav-clo-dg100.wav","answer":"anger and hurt were beneath him he had seen a great vision and was as a god and he could feel only profound and awful pity for this maggot of a man he did not look at him and though his eyes passed over him he did not see him","subset":"babb","task_type":"understanding","prediction":"anger and hurt were beneath him he had seen a great vision and was as a god and he could feel only profound and awful pity for this maggot of a man he did not look at him and though his eyes passed over him he did not see him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":814,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm2-babb-sp4441-ch076262-sg0020-mc01-stu-clo-dg160.wav","answer":"and was making violent efforts to regain it i saw a spider this morning said rehnhjelm that predicts happiness araignee matin chagrin said falander have you never heard that what does that mean asked agnes a spider on the morrow grief and sorrow","subset":"babb","task_type":"understanding","prediction":"and was making violent efforts to regain it i saw a spider this morning said ranald that predicts happiness araigne matin chagrin said philander have you never heard of that what does that mean asked agnes a spider on the morrow grief and sorrow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":815,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm2-babb-sp4441-ch076263-sg0017-mc02-lav-clo-dg090.wav","answer":"quite true i'm going to lecture there on sunday next on sweden a good subject plenty to say if i should fall asleep on your sofa don't waken me i'm dead beat all right old chap go to sleep a few moments later olle was fast asleep and snoring loudly","subset":"babb","task_type":"understanding","prediction":"quite true i am going to lecture there on sunday next on sweden a good subject plenty to say if i should fall asleep on your sofa dont waken me i am dead beat all right old chap go to sleep a few moments later polly was fast asleep and snoring loudly","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":816,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279849-sg0033-mc02-lav-clo-dg130.wav","answer":"fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller","subset":"babb","task_type":"understanding","prediction":"fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":817,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279849-sg0044-mc02-lav-clo-dg070.wav","answer":"while the fireman hammered the top over now run back slowly an inch at a time ordered fuller the engineer opened the throttle and the texas crept away taking up the slack in the couplings the left wheel followed back along the groove its flange had cut in the tie","subset":"babb","task_type":"understanding","prediction":"while the firemen hammer the top over now run back slowly an inch at a time ordered ford the engineer opened the throttle and the texas crept away taking up the slack in the couplings the left wheel followed back along the groove its flange had cut in the timbers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":818,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279852-sg0028-mc01-stu-clo-dg050.wav","answer":"joe handed them candles and they followed him upstairs here's one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here's the other said joe leading the way down the corridor","subset":"babb","task_type":"understanding","prediction":"joe handed them candles and they followed him upstairs here is one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here is the other said joe leading the way down the corridor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":819,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-babb-sp4535-ch279852-sg0028-mc02-lav-clo-dg050.wav","answer":"joe handed them candles and they followed him upstairs here's one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here's the other said joe leading the way down the corridor","subset":"babb","task_type":"understanding","prediction":"joe handed them candles and they followed him upstairs here is one room he said two of you can sleep there you and shadrack take it said tom to wilson good night they shook hands here is the other said joe leading the way down the corridor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":820,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm2-babb-sp4839-ch015304-sg0022-mc01-stu-clo-dg030.wav","answer":"i have a good mind that the king of france's army and mine should come together in order that by battle it may be known to whom of right belongs this heritage for i see no other way to it by my sacred oath my lord said the good knight i would that it might be to morrow provided that i were out of captivity","subset":"babb","task_type":"understanding","prediction":"i have a good mind that the king of france s army and mine should come together in order that by battle it may be known to whom of rights belongs this heritage for i see no other way to it by my sacred oath my lord said the good knight i would that it might be to morrow provided that i were out of captivity","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":821,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm2-babb-sp4848-ch028247-sg0043-mc01-stu-clo-dg150.wav","answer":"vil villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion","subset":"babb","task_type":"understanding","prediction":"ville villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":822,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4859\/Lab41-SRI-VOiCES-rm2-babb-sp4859-ch026870-sg0018-mc01-stu-clo-dg130.wav","answer":"but often felt ill will toward her which she could not overcome once she had a talk with her friend natasha about sonya and about her own injustice toward her you know said natasha you have read the gospels a great deal there is a passage in them that just fits sonya what asked countess mary surprised","subset":"babb","task_type":"understanding","prediction":"but often felt ill will toward her which she could not overcome once she had a talk with her friend natasha about sonya and about her own injustice toward her you know said natasha you have read the gospels a great deal there is a passage in them that just fits sonya what asked countess mary surprised","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":823,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4957\/Lab41-SRI-VOiCES-rm2-babb-sp4957-ch023295-sg0026-mc02-lav-clo-dg130.wav","answer":"it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you","subset":"babb","task_type":"understanding","prediction":"it is always proper answered sandford for you to think of him though he should never think on you she burst into tears and said that she did think of him but she felt an apprehension of mentioning his name and she wept bitterly while she spoke do not think i reproved you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":824,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp4967\/Lab41-SRI-VOiCES-rm2-babb-sp4967-ch028868-sg0004-mc01-stu-clo-dg000.wav","answer":"but yet as he thought of what he had seen he shuddered with vexation i was thinking of the governor he said he shall be told everything that you met tregear certainly and that i kissed him","subset":"babb","task_type":"understanding","prediction":"but yet as he thought of what he had seen he shuddered with vexation i was thinking of the governor he said he shall be told everything that you met tregear certainly and that i kissed him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":825,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5126\/Lab41-SRI-VOiCES-rm2-babb-sp5126-ch027504-sg0031-mc02-lav-clo-dg060.wav","answer":"there's no saying what mister knightley might do if his wife had been here thank god she's away at bathurst said starlight i hate seeing women put out besides everybody bows down to missus knightley she's as good as she's handsome i believe and","subset":"babb","task_type":"understanding","prediction":"there is no saying what mr knightley might do if his wife had been here thank god she is away at battersea said starlight i hate seeing women put out besides everybody bows down to mrs knightley she is as good as she is handsome i believe and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":826,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm2-babb-sp5154-ch026558-sg0009-mc02-lav-clo-dg130.wav","answer":"the image of wax answered never a word again the monkey said this time in a little louder voice o peddler boy peddler boy please give me a banana just one little ripe little","subset":"babb","task_type":"understanding","prediction":"the image of what he asked again this time in a little louder voice oh peppa boy peppa boy please give me a banana just one little ripe little","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":10}
+{"index":827,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm2-babb-sp5189-ch059288-sg0027-mc01-stu-clo-dg060.wav","answer":"expressing their pleasure at the expected treat by gentle bleatings the squire stooped to spread the salt the black ram either from most uncivil impatience or mistaking the movement of the proprietor's coat tail for a challenge pitched into him incontinently","subset":"babb","task_type":"understanding","prediction":"expressing their pleasure at the expected treat by gentle bleatings the squire stooped to spread the salt the black ram either from most uncivil impatience or mistaking the movement of the proprietor s coat tail for a challenge pitched into him incontinently","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":828,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5319\/Lab41-SRI-VOiCES-rm2-babb-sp5319-ch084357-sg0004-mc01-stu-clo-dg150.wav","answer":"published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers","subset":"babb","task_type":"understanding","prediction":"published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":829,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5338\/Lab41-SRI-VOiCES-rm2-babb-sp5338-ch024615-sg0002-mc01-stu-clo-dg160.wav","answer":"occasionally indeed when such a consummation seemed inevitable a watchful old grandam with her close cap distaff and spindle rushed like a sibyl in frenzy out of one of these miserable cells dashed into the middle of the path and snatching up her own charge from among the sunburnt loiterers saluted him with a sound cuff and transported him back to his dungeon the little white headed varlet screaming all the while from the very top of his lungs a shrilly treble to the growling remonstrances of the enraged matron","subset":"babb","task_type":"understanding","prediction":"occasionally indeed when such a consummation seemed inevitable a watchful old grandam with her close capped distaff and spindle rushed like a sibyl in frenzy out of one of these miserable cells dashed into the middle of the pack and snatching up her own charge from among the sunburnt loiterers saluted him with a sound cuff and transported him back to his dungeon the little white headed varlet screaming all the while from the very top of his lungs a shrilly treble to the growling remonstrances of the enraged matron","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":830,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5338\/Lab41-SRI-VOiCES-rm2-babb-sp5338-ch284437-sg0015-mc02-lav-clo-dg180.wav","answer":"perhaps you are trying to ridicule me she continued regarding the sailor's face closely","subset":"babb","task_type":"understanding","prediction":"perhaps you are trying to ridicule me she continued regarding the sailor s face closely","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":831,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5386\/Lab41-SRI-VOiCES-rm2-babb-sp5386-ch008684-sg0041-mc01-stu-clo-dg050.wav","answer":"and showing himself very different from what he had been before he went out to see the world but one day he said to his father that he should like to marry and have a house of his own when i served the king's chief herdsman added he i saw his daughter and i am resolved to try if i cannot win her for my wife","subset":"babb","task_type":"understanding","prediction":"and showing himself very different from what he had been before he went out to see the world but one day he said to his father that he should like to marry and have a house of his own when i served the king s chief herdsman added he i saw his daughter and i am resolved to try if i cannot win her for my wife","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":832,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5400\/Lab41-SRI-VOiCES-rm2-babb-sp5400-ch034479-sg0026-mc02-lav-clo-dg060.wav","answer":"the crescent shaped curve of the cut grass the grass and flower heads slowly and rhythmically falling before the blade of his scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came","subset":"babb","task_type":"understanding","prediction":"the crescent shaped curve of the cut grass the grass and flower head slowly and rhythmically falling before the blade of the scythe and ahead of him the end of the row where would come the rest suddenly in the midst of his toil without understanding what it was or whence it came","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":833,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm2-babb-sp5401-ch102526-sg0028-mc02-lav-clo-dg090.wav","answer":"at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter","subset":"babb","task_type":"understanding","prediction":"at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":834,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm2-babb-sp5456-ch062043-sg0023-mc01-stu-clo-dg170.wav","answer":"they wanted to learn the game at two o'clock the captain asked the mate how we were getting on oh pretty glibly sir replied the mate we can scarcely tell what headway we are making for we are obliged to keep the middle of the river and there is the shadow of a fog rising","subset":"babb","task_type":"understanding","prediction":"they wanted to learn the game at two o clock the captain asked the mate how we were getting on oh pretty glibly sir replied the mate we can scarcely tell what headway we are making for we are obliged to keep the middle of the river and there is the shadow of a fog rising","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":835,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm2-babb-sp5456-ch062043-sg0024-mc02-lav-clo-dg020.wav","answer":"this wood seems rather better than that we took in at yellow face's but we're nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask em what's the price of wood up here i've got you again","subset":"babb","task_type":"understanding","prediction":"this wood seems rather better than that we took in yellow faces but we are nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask them what is the price of wood up here i have got you again","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":836,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm2-babb-sp5635-ch044582-sg0004-mc01-stu-clo-dg040.wav","answer":"is really very rapid rotation from the first thought to the second and back again just as in the above cited experiment the attention must shift from one hand to the other until one or the other movement becomes partly or wholly automatic whatever is the psychological truth of this contention","subset":"babb","task_type":"understanding","prediction":"is really very rapid rotation from the first thought to the second and back again just as in the above cited experiment the attention must shift from one hand to the other until one or the other movement becomes partly or wholly automatic whatever is the psychological truth of this contention","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":837,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm2-babb-sp5635-ch044582-sg0010-mc02-lav-clo-dg020.wav","answer":"don't anticipate divide your attention and you divide your power this matter of the effect of the inner man upon the outer needs a further word here particularly as touching concentration what do you read my lord","subset":"babb","task_type":"understanding","prediction":"dont anticipate divide your attention and you divide your power the matter of the effect of the inner man upon the outer needs a further word here particularly as touching concentration what do you read my lord","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":838,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm2-babb-sp5635-ch058137-sg0014-mc01-stu-clo-dg060.wav","answer":"with a party of friends mister jimmy hurrying out with a slate in his hand begged me to stop a moment and thus addressed me well mister carlton this algebra is a most powerful thing ain't it indeed it is mister jimmy have you been looking into it","subset":"babb","task_type":"understanding","prediction":"with a party of friends mr jimmy hurrying out with a slate in his hand begged me to stop a moment and thus addressed me well mr carlton this algebra is a most powerful thing ain t it indeed it is mr jimmy have you been looking into it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":839,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm2-babb-sp5678-ch043303-sg0015-mc01-stu-clo-dg070.wav","answer":"mister phillips arrived the next morning as usual just as mabel had left the old lady's room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver's room","subset":"babb","task_type":"understanding","prediction":"mister phillips arrived the next morning as usual just as mabel had left the old lady's room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver's room","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":840,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm2-babb-sp5717-ch100145-sg0017-mc02-lav-clo-dg070.wav","answer":"of course obray count erskyll planetary proconsul of aditya didn't realize that he didn't even know what javasan meant just free them commodore vann shatrak couldn't see much of a problem either he would have answered","subset":"babb","task_type":"understanding","prediction":"of course obray count briscoe planetary proconsul of aditya didn t realize that he didn t even know what javasan meant just free them commodore van shechtach couldn t see much of a problem either he would have answered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":841,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5740\/Lab41-SRI-VOiCES-rm2-babb-sp5740-ch097610-sg0031-mc02-lav-clo-dg110.wav","answer":"for while rejoicings were still loud over the departure of the enemy there came a knock at missus tracy's door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier","subset":"babb","task_type":"understanding","prediction":"for while rejoicings were still loud over the departure of the enemy there came a knock at missus tracy s door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":842,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5789\/Lab41-SRI-VOiCES-rm2-babb-sp5789-ch057158-sg0004-mc01-stu-clo-dg100.wav","answer":"she wants you to go to her at cheltenham for a month oh mister morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me","subset":"babb","task_type":"understanding","prediction":"she wants you to go to her at cheltenham for a month oh mr morton would you like to go how should i not like to go lady ushant is my dearest dearest friend it is so very good of her to think of me","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":843,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5789\/Lab41-SRI-VOiCES-rm2-babb-sp5789-ch057158-sg0013-mc01-stu-clo-dg150.wav","answer":"i don't want any amusement at any rate you will answer lady ushant of course i shall answer her perhaps you can let me know she wishes me to take you to cheltenham i shall go for a couple of days but i shall not stay longer","subset":"babb","task_type":"understanding","prediction":"i don t want any amusement at any rate you will answer lady ushant of course i shall answer her perhaps you can let me know she wishes me to take you to cheltenham i shall go for a couple of days but i shall not stay long","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":844,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5802\/Lab41-SRI-VOiCES-rm2-babb-sp5802-ch066347-sg0026-mc02-lav-clo-dg050.wav","answer":"the conflicting tints began to get in their deadly work and within two hours he was completely doubled up the pain he suffered was awful agony was bliss alongside of the pangs that now afflicted him and all the palliatives and pain killers known to man were tried without avail","subset":"babb","task_type":"understanding","prediction":"the conflicting tints began to get in their deadly work and within two hours he was completely doubled up the pain he suffered was awful agony was bliss alongside of the pangs that now afflicted him and all the palliatives or pain killers known to man were tried without avail","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":845,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch055088-sg0028-mc02-lav-clo-dg100.wav","answer":"and that which is above men you began to find out that truly divine mystery that you had a mother on earth simply by lying soft and warm upon her bosom and so as our lord told the jews of old","subset":"babb","task_type":"understanding","prediction":"back which is above me you began to find out that truly divine mystery that you had a mother on earth simply by lying soft and so as our lord told the jews of old","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":846,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch055088-sg0034-mc01-stu-clo-dg170.wav","answer":"over the whole earth for my part i know not save that all shall be as god wills the tree has been cut down already again and again and yet has always thrown out fresh shoots and dropped fresh poison from its boughs","subset":"babb","task_type":"understanding","prediction":"of the whole earth for my part i know not save that all shall be as god wills the tree has been cut down already again and again and yet has always thrown out fresh shoots and dropped fresh poison from its boughs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":847,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch066166-sg0005-mc02-lav-clo-dg160.wav","answer":"and a fringe of gray hair circling his head like a crown as he took off his tarpaulin i observed that the top of his head was quite smooth and flat as if somebody had sat down on him when he was very young there was something noticeably hearty in this man's bronzed face","subset":"babb","task_type":"understanding","prediction":"and a fringe of grey hair circling his head like a crown as he took off his topper i observed that the top of his head was quite smooth and flat as if some weight had sat down on him when he was very young there was something noticeably haughty in this man s bronzed face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":848,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5868\/Lab41-SRI-VOiCES-rm2-babb-sp5868-ch066166-sg0031-mc02-lav-clo-dg140.wav","answer":"and i've no doubt that other parts of his body were illustrated in the same agreeable manner i imagine he was fond of drawings and took this means of gratifying his artistic taste it was certainly very ingenious and convenient a portfolio might be misplaced or dropped overboard","subset":"babb","task_type":"understanding","prediction":"and i have no doubt that other parts of his body were illustrated in the same agreeable manner i imagine he was fond of drawings and took this means of gratifying his artistic taste it was certainly very ingenious and convenient for torrio might be misplaced or dropped overboard","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":849,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-babb-sp5935-ch043322-sg0015-mc02-lav-clo-dg170.wav","answer":"will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure","subset":"babb","task_type":"understanding","prediction":"will stand the pedestal with the emblematic figure upon it and so far as i understand from the absence of directions each such figure will remain in place until the eve of the next quarterly feast what kind of figure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":850,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-babb-sp5935-ch055927-sg0020-mc01-stu-clo-dg140.wav","answer":"and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps","subset":"babb","task_type":"understanding","prediction":"and that is that the best way to secure the benefit of the expansive power of steam is to permit it to escape from a pipe having a long series of orifices and to impinge upon a correspondingly numerous series of vanes or perhaps","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":851,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-babb-sp5935-ch055927-sg0026-mc02-lav-clo-dg080.wav","answer":"each screw requires a separate set of engines and the main object of the duplication is to lessen the risk of the vessel being left helpless in case of accident to one or other the advisability of placing each engine and shafting in a separate water tight compartment","subset":"babb","task_type":"understanding","prediction":"each screw requires a separate set of engines and the main object of the duplication is to lessen the risk of the vessel being left helpless in case of accident to one or other the advisability of placing each engine and shafting in a separate water tight compartment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":852,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp5968\/Lab41-SRI-VOiCES-rm2-babb-sp5968-ch061356-sg0007-mc02-lav-clo-dg020.wav","answer":"the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father's house in london and alice peel was she thinking of him","subset":"babb","task_type":"understanding","prediction":"the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father s house in london and alice peel was she thinking of him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":853,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp6099\/Lab41-SRI-VOiCES-rm2-babb-sp6099-ch067860-sg0033-mc01-stu-clo-dg120.wav","answer":"speaking very slowly i think mister robert waite is just like the knights in that book the age of chivalry they always did exactly what was right","subset":"babb","task_type":"understanding","prediction":"Speaking very slowly. I think Mr. Robert Waite is just like the knights in that book. The age of chivalry. They always did. exactly what was right.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":854,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm2-babb-sp6147-ch034606-sg0021-mc02-lav-clo-dg140.wav","answer":"just like any one else he would gaily set fire to a cot of woodwork and thatch and just scorch those within but he would rebuild their houses in stone he insulted two ladies one was unmarried he gave her a portion the other was married he had her husband appointed chaplain","subset":"babb","task_type":"understanding","prediction":"just like anyone else even gaius set fire to a cottage of woodwork and thatch it just scorched those within but he rebuilt their houses in stone he insulted two ladies one was unmarried he gave her a portion the other was married he had her husband appointed chaplain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":10}
+{"index":855,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm2-babb-sp6241-ch061943-sg0005-mc01-stu-clo-dg060.wav","answer":"the fact is the castle is much later than the time of the heroic prince of denmark","subset":"babb","task_type":"understanding","prediction":"Fact is, the castle is much later than the time of the heroic prince of Denmark.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":856,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm2-babb-sp6395-ch086708-sg0030-mc01-stu-clo-dg120.wav","answer":"and danglars wrote the address as he spoke yes and that's all settled exclaimed caderousse who by a last effort of intellect had followed the reading of the letter and instinctively comprehended all the misery which such a denunciation must entail","subset":"babb","task_type":"understanding","prediction":"danglars wrote the address as he spoke yes and that is all settled exclaimed caterus who by a last effort of intellect had followed the reading of the letter and instinctively comprehended all the misery which such a denunciation must entail","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":857,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm2-babb-sp6395-ch087997-sg0003-mc01-stu-clo-dg180.wav","answer":"he wrote that account of his own life which together with his other papers he has left to your care my account therefore shall begin where his ends he set out for london towards the end of april and at morpeth","subset":"babb","task_type":"understanding","prediction":"he wrote that account of his own life which together with his other papers he has left to your care my account therefore shall begin where his ends he set out for london towards the end of april and at bordeaux","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":858,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm2-babb-sp6415-ch116629-sg0020-mc02-lav-clo-dg050.wav","answer":"this very reserve however was rather distasteful to judith as regarded herself but she liked it towards others she had planned it all out that dietrich should marry veronica soon after the confirmation that they should set up a pretty little establishment and be her beloved neighbors","subset":"babb","task_type":"understanding","prediction":"this very reserve however was rather distasteful to judith as regarded herself but she liked it towards others she had planned it all out that dietrich should marry veronica soon after confirmation that they should set up a pretty little establishment and be her beloved neighbours","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":859,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm2-babb-sp6454-ch107462-sg0026-mc02-lav-clo-dg100.wav","answer":"deasey concluded at once it was a foully murdered corpse but then again you could not well conceal a corpse in someone's waistcoat and gold coins would melt or be mislaid amongst the loose bricks of a sooty chimney","subset":"babb","task_type":"understanding","prediction":"these he concluded at once it was a foully murdered corpse but then again you could not well conceal a corpse in some one s waistcoat and gold coins would melt or be mislaid amongst the loose bricks of a sooty chimney","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":860,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm2-babb-sp6519-ch069411-sg0032-mc02-lav-clo-dg070.wav","answer":"and afterwards taken such advantage of by herself and others a pebble had done it all a pebble placed in the gateway by bela's hands as she described this and insisted upon the fact in face of the judge's almost frenzied disclaimer","subset":"babb","task_type":"understanding","prediction":"and afterward taken such advantage of by herself and others a pebble had done it all a pebble placed in the gateway by bella s hands as she described this and insisted on the fact in the face of the judges in almost frenzied disclaimer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":861,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-babb-sp6544-ch067863-sg0004-mc02-lav-clo-dg050.wav","answer":"and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had not come into the house he seemed much older to sylvia than he did on her visit to the plantation in october","subset":"babb","task_type":"understanding","prediction":"and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had now come into the house he seemed much older to sylvia than he did at her visit to the plantation in october","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":862,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-babb-sp6544-ch067863-sg0023-mc01-stu-clo-dg110.wav","answer":"and aunt connie rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with missus carleton a little while before supper and told her of what uncle peter had said that ships from the north were on the way to the aid of fort sumter","subset":"babb","task_type":"understanding","prediction":"and aunt connie rolled her eyes and lifted her hands as if she could already taste its richness all that afternoon sylvia could think of nothing but the proposed trip she sat with mrs carlton a little while before supper and told her of what uncle peter had said that ships from the north were on their way to the aid of fort sumter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":863,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-babb-sp6544-ch231862-sg0036-mc02-lav-clo-dg000.wav","answer":"he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost","subset":"babb","task_type":"understanding","prediction":"he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":864,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm2-babb-sp6574-ch070756-sg0035-mc01-stu-clo-dg170.wav","answer":"the labour of winding among the little paths of the mountain and fixing my feet firmly as i advanced perplexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the halfway resting place and seated myself beside the fountain","subset":"babb","task_type":"understanding","prediction":"the labor of winding among the little paths of the mountain and fixing my feet firmly as i advanced perplexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the half way resting place and seated myself beside the fountain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":865,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6696\/Lab41-SRI-VOiCES-rm2-babb-sp6696-ch068773-sg0013-mc01-stu-clo-dg060.wav","answer":"me mister forbes me yes tom i'll pay you twenty dollars a week to start with and more if you serve me faithfully and you'll board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself","subset":"babb","task_type":"understanding","prediction":"me mr forbes me yes tom i will pay you twenty dollars a week to start with and more if you serve me faithfully and you board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":866,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6788\/Lab41-SRI-VOiCES-rm2-babb-sp6788-ch092420-sg0019-mc02-lav-clo-dg180.wav","answer":"but happening to read on we became fixed and charmed and have retained from its perusal the sweetest picture of life lived in this land ever afforded us out of the pale of personal observation that such things are","subset":"babb","task_type":"understanding","prediction":"but happening to read on we became fixed and charmed and have retained from its perusal the sweetest picture of life lived in this land ever afforded us out of the pale of personal observation that such things are","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":867,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm2-babb-sp6965-ch277898-sg0002-mc02-lav-clo-dg180.wav","answer":"some fraction of a shilling or franc or whatever the prevailing coinage might be should be diverted from his pocket or service into that of a hard up companion a two franc cigar would be cheerfully offered to a wealthy patron","subset":"babb","task_type":"understanding","prediction":"some fraction of a shilling or franc or whatever the prevailing coinage might be should be diverted from his pocket or service into that of a hard up companion a two franc cigar would be cheerfully offered to a wealthy patron","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":868,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm2-babb-sp7000-ch083708-sg0025-mc01-stu-clo-dg170.wav","answer":"he remarked as he produced a fourth ball from the same pocket of his tightly fitting trousers which had contained the other three a swipe does warm me so your kind of bowling mister s just the thing it was kind of him to say so though to my thinking","subset":"babb","task_type":"understanding","prediction":"he remarked as he produced a fourth ball from the same pocket of his tightly fitting trousers which had contained the other three a swipe does warm me so your kind of bowling mister is just the thing it was kind of him to say so though to my thinking","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":869,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm2-babb-sp7095-ch088489-sg0035-mc02-lav-clo-dg000.wav","answer":"both leading authorities at princeton university fundamentalism in the united states furnished the spectacle of the trial in nineteen twenty five of a school teacher named scopes for teaching the theory of evolution","subset":"babb","task_type":"understanding","prediction":"both leading authorities at princeton university fundamentalism in the united states furnished the spectacle of the trial in nineteen twenty five of a schoolteacher named scopes for teaching the theory of evolution","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":870,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-babb-sp7148-ch007763-sg0008-mc02-lav-clo-dg140.wav","answer":"the whole foundation on which my life was constructed fell down all my happiness was to have been found in the continual pursuit of this end the end had ceased to charm and how could there ever again be any interest in the means","subset":"babb","task_type":"understanding","prediction":"the whole foundation on which my life was constructed fell down all my happiness was to have been found in the continual pursuit of this end the end had ceased to charm and how could there ever again be any interest in the means","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":871,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-babb-sp7148-ch007763-sg0027-mc02-lav-clo-dg160.wav","answer":"were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connexions between things not dependent on our will and feelings natural laws by virtue of which in many cases","subset":"babb","task_type":"understanding","prediction":"were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connections between things not dependent on our will and feelings natural laws by virtue of which in many cases","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":872,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7247\/Lab41-SRI-VOiCES-rm2-babb-sp7247-ch101864-sg0020-mc02-lav-clo-dg180.wav","answer":"and for four years she lived on the streets and in the sweat shops enduring almost unbelievable poverty and hardships by jove exclaimed ned under his breath it was only seven or eight months before the wedding that she was found went on frank","subset":"babb","task_type":"understanding","prediction":"and for four years she lived on the streets and in the sweatshops enduring almost unbelievable poverty and hardships by jove exclaimed ned under his breath it was only seven or eight months before the wedding that she was found went on frank","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":873,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7264\/Lab41-SRI-VOiCES-rm2-babb-sp7264-ch092314-sg0011-mc02-lav-clo-dg050.wav","answer":"never deals with matters vital to its prestige on the contrary it deliberately side tracks any vital discussion that sincere conviction may have forced upon the public and spoils the scent with false issues","subset":"babb","task_type":"understanding","prediction":"never deals with matters vital to its prestige handicapper it deliberately sidetracks any vital discussion that sincere conviction may have forced upon the public and spoils the scent with false issues","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":874,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7264\/Lab41-SRI-VOiCES-rm2-babb-sp7264-ch092316-sg0021-mc01-stu-clo-dg180.wav","answer":"the great dailies were thought grey not wicked only general and vague the free press in its beginnings did not attack as an enemy it only timidly claimed to be heard it regarded itself as a speciality it was humble and there went with it a mass of ex centric stuff","subset":"babb","task_type":"understanding","prediction":"the great dailies were thought great not wicked only general and vague the free press in its beginnings did not attack as an enemy it only timidly claimed to be heard it regarded itself as a speciality it was humble and there went with it a mass of eccentric stuff","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":875,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7276\/Lab41-SRI-VOiCES-rm2-babb-sp7276-ch092427-sg0032-mc01-stu-clo-dg000.wav","answer":"but we have not people over us whose careless hasty anger drives us to seek excuses for our failures if so perhaps perhaps who knows we the better educated rigidly immaculately true as we are at present might tell falsehoods","subset":"babb","task_type":"understanding","prediction":"but we have not people over us whose careless hasty anger drives us to seek excuses for our failures if so perhaps perhaps who knows we the better educated originally immaculately true as we are at present might tell falsehoods","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":876,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm2-babb-sp7278-ch104730-sg0039-mc02-lav-clo-dg090.wav","answer":"i said that in another part of the capitol it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence' here a loud cry of order order burst forth in which the speaker yelled the loudest","subset":"babb","task_type":"understanding","prediction":"i said that in another part of the capital it had been threatened that if a northern abolitionist should go to north carolina and utter a principle of the declaration of independence here a loud cry of order order burst forth in which the speaker yelled the loudest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":877,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm2-babb-sp7445-ch094526-sg0039-mc02-lav-clo-dg070.wav","answer":"the appearance of valor spirit abilities in any great man extended his interest very far and if the sovereign were deficient in these qualities he was no less if not more exposed to the usurpations of the aristocracy than even during the vigor of the feudal system","subset":"babb","task_type":"understanding","prediction":"the appearance of valor spirit abilities in any great man extended his interest very far and if the sovereign were deficient in these qualities he was no less if not more exposed to the usurpations of the aristocracy than even during the vigor of the feudal system","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":878,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7517\/Lab41-SRI-VOiCES-rm2-babb-sp7517-ch100442-sg0003-mc02-lav-clo-dg170.wav","answer":"and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer's shop and you will find me in my spare evenings","subset":"babb","task_type":"understanding","prediction":"and lordly people like you and me with a pint of cherry gin is not this to follow the king of trades some day i shall open a grocer shop and you will find me in my spare evenings","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":879,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm2-babb-sp7540-ch101258-sg0030-mc01-stu-clo-dg110.wav","answer":"and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the whale had thrown up came sailing along and anchored close by","subset":"babb","task_type":"understanding","prediction":"and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the well had thrown up came sailing along and anchored close by","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":880,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7704\/Lab41-SRI-VOiCES-rm2-babb-sp7704-ch106965-sg0010-mc02-lav-clo-dg000.wav","answer":"and killed so many men you would have burst and lost all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with severity in her tone","subset":"babb","task_type":"understanding","prediction":"and killed so many men you would have burst to most all your buttons and not had one left like father there was a round of applause at this but the small maiden remained undaunted is that a true story you told she demanded with spirit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":881,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7704\/Lab41-SRI-VOiCES-rm2-babb-sp7704-ch106969-sg0013-mc01-stu-clo-dg080.wav","answer":"will that be deserting to the enemy it will be sure and certain defeat but then of course my captain won't let me be beaten if i stick close to him and so they talked a strange couple but the younger of them had a faith which the elder might envy","subset":"babb","task_type":"understanding","prediction":"will that be deserting to the enemy it will be sure and certain defeat but then of course my captain well that may be beanie if i stick close to him so they talked a strange couple but the younger of them had a faith which the elder might envy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":882,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-babb-sp7850-ch111771-sg0004-mc01-stu-clo-dg010.wav","answer":"indeed if ever a general deserved honor grant had won it he had opened the mississippi to navigation and had captured nearly one hundred thousand prisoners and arms","subset":"babb","task_type":"understanding","prediction":"indeed if ever a general deserved honor grant had won it he had opened the mississippi to navigation and had captured nearly one hundred thousand prisoners and arms","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":883,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-babb-sp7850-ch281318-sg0017-mc02-lav-clo-dg160.wav","answer":"here wood pigeon said mother magpie you must place those sticks through and across criss cross criss cross so","subset":"babb","task_type":"understanding","prediction":"Here, woodpigeon said, mother magpie, you must place those sticks through and across crisscross, crisscross so.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":884,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-babb-sp7850-ch286674-sg0005-mc01-stu-clo-dg140.wav","answer":"they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies","subset":"babb","task_type":"understanding","prediction":"they did not breathe it into their mouths or through gills but took it in through some openings in the back part of their bodies","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":885,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7867\/Lab41-SRI-VOiCES-rm2-babb-sp7867-ch110528-sg0013-mc02-lav-clo-dg100.wav","answer":"which she had taken from the lock but dropped in her fright she hastily quitted the room shut and locked the door and ran to her own chamber to calm herself before returning to her guests but she was unable to rest for an instant so dreadful were her feelings","subset":"babb","task_type":"understanding","prediction":"which she had taken from the lock but dropped in her fright she hastily quitted the room shut and locked the door and ran to her own chamber to calm herself before returning to her guests but she was unable to rest for an instant so dreadful were her feelings","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":886,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7867\/Lab41-SRI-VOiCES-rm2-babb-sp7867-ch110742-sg0034-mc02-lav-clo-dg090.wav","answer":"he went a long voyage he is my kinsman if i could see him he could give me some account of missus rugg sir said missus croft i never heard of john foy where did he live just above here in orange tree lane there is no such place in this neighbourhood","subset":"babb","task_type":"understanding","prediction":"you went a long voyage he is my kinsman if i could see him he could give me some account of mrs rugg sir said mrs cragge i never heard of john foy where did he live just above here in orange tree lane there is no such place in this neighbourhood","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":887,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-babb-sp7868-ch246932-sg0019-mc02-lav-clo-dg030.wav","answer":"i heard what was plainly a lady's voice right sweet and womanly it was though full of pain even agony i thought but heroically suppressed she soothed she expostulated she condoled she coaxed","subset":"babb","task_type":"understanding","prediction":"i heard what was plainly a lady s voice bright sweet and womanly it was though full of pain even agony i thought but heroically suppressed she soothed she expostulated she condoled she coaxed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":888,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm2-babb-sp7932-ch110056-sg0022-mc01-stu-clo-dg180.wav","answer":"and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by","subset":"babb","task_type":"understanding","prediction":"and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":889,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm2-babb-sp7981-ch112056-sg0007-mc02-lav-clo-dg060.wav","answer":"and that as he was evidently destined to do great work for god it would be to his advantage to have powerful and influential friends although the prospect of such a post filled the humble parish priest with consternation","subset":"babb","task_type":"understanding","prediction":"and that as he was evidently destined to do great work for god it would be to his advantage that a call should be made upon his talents all the prospect of such a call filled the humble parish priest with consternation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":11}
+{"index":890,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm2-babb-sp7981-ch112058-sg0010-mc01-stu-clo-dg040.wav","answer":"and a poor priest who had lately joined them before setting out on their mission journeys they used to give the key of the house to a neighbor but as there was nothing in it to steal there was little cause for anxiety in the course of their travels other priests realizing the greatness of the work asked","subset":"babb","task_type":"understanding","prediction":"and a poor priest who had lately joined them before setting out on their mission journeys they used to give the key of the house to a neighbor but as there was nothing in it to steal there was little cause for anxiety in the course of their travels other priests realizing the greatness of the work asked","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":891,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8057\/Lab41-SRI-VOiCES-rm2-babb-sp8057-ch284428-sg0028-mc01-stu-clo-dg150.wav","answer":"no i didn't know that admitted the sailor it's a fact said the king nothing can kill us until we've lived to the last day of our appointed lives when the final minute is up we die but we're obliged to live all of the six hundred years whether we want to or not","subset":"babb","task_type":"understanding","prediction":"no i didn t know that admitted the sailor it s a fact said the king nothing can kill us until we have lived to the last day of our appointed lives when the final minute is up we die but we re obliged to live all of the six hundred years whether we want to or not","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":892,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm2-babb-sp8108-ch280354-sg0022-mc02-lav-clo-dg160.wav","answer":"oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus's lyre","subset":"babb","task_type":"understanding","prediction":"oak poplar lime beech laurel ash pine plane and maple and many another tree had gathered together here drawn from their distant forest homes by the sounds of orpheus lyre","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":893,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm2-babb-sp8108-ch280359-sg0022-mc02-lav-clo-dg120.wav","answer":"loki wriggled his slippery slimy length through thor's fingers but the thunderer grasped him tightly by the tail and holding him in this manner in this hand waded to the shore there father odin and the other gods met him and","subset":"babb","task_type":"understanding","prediction":"Loki wriggled his slippery, slimy length through Thor's fingers, but the thunderer grasped him tightly by the tail and holding him in this manner in his hand, waded to the shore there. Father Odin and the other gods met him, and.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":894,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8118\/Lab41-SRI-VOiCES-rm2-babb-sp8118-ch114476-sg0004-mc02-lav-clo-dg130.wav","answer":"and as we have come three miles it must be only five miles away correct said warner who was in an uncommonly fine humor your mathematical power grows every day frank let x equal the whole distance from the gap to the antietam which is eight miles","subset":"babb","task_type":"understanding","prediction":"and as we have come three miles it must be only five miles away correct said warner who was in an uncommonly fine humor your mathematical power grows every day frank let x equal the whole distance from the gap to the antietam which is eight miles","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":895,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8152\/Lab41-SRI-VOiCES-rm2-babb-sp8152-ch258974-sg0000-mc01-stu-clo-dg130.wav","answer":"as the field and its fertile qualities and those called artificial as improvements and machinery according as these resources are more or less developed as labor is employed in a fertile or a barren field with a sharp tool or a dull one","subset":"babb","task_type":"understanding","prediction":"as the field and its fertile qualities and those called artificial as improvements and machinery according as these resources are more or less developed as labor is employed in a fertile or barren field with a sharp tool or a dull one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":896,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm2-babb-sp8225-ch274375-sg0038-mc01-stu-clo-dg120.wav","answer":"and had expressed an intention of delivering hull into his hands but their conspiracy being detected they were arrested and sent prisoners to london where without any regard to their former services they fell both of them victims to the severity of the parliament","subset":"babb","task_type":"understanding","prediction":"and had expressed an intention of delivering hull into his hands but their conspiracy being detected they were arrested and sent prisoners to london where without any regard to their former services they fell both of them victims to the severity of the parliament","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":897,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-babb-sp8266-ch258263-sg0021-mc02-lav-clo-dg100.wav","answer":"and lullilooed with cries of joy so that all the palace rang again and the captains of the army awoke and said what is to do so they made for the palace and asked the eunuchs hath one of the king's women given birth to a child and they answered","subset":"babb","task_type":"understanding","prediction":"and lulli lude with cries of joy so that all the palace rang again and the captains of the army awoke and said what is to do so they made for the palace and asked the eunuchs hath one of the king s women given birth to a child and they answered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":898,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-babb-sp8266-ch258263-sg0022-mc02-lav-clo-dg000.wav","answer":"no but rejoice ye for king gharib hath returned to you so they rejoiced and gharib after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him","subset":"babb","task_type":"understanding","prediction":"no but rejoice ye for king harim hath returned to you so they rejoiced and harim after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":899,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm2-babb-sp8425-ch291444-sg0000-mc02-lav-clo-dg020.wav","answer":"of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative old age and day by day dropping piecemeal into the tomb in a little while thought i and those revered dutch burghers","subset":"babb","task_type":"understanding","prediction":"of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative all the age and day by day dropping piecemeal into the tomb in a little while how far high had those revered dutch burghers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":900,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm2-babb-sp8425-ch292520-sg0013-mc02-lav-clo-dg040.wav","answer":"light green in the deeps like your eyes in sunshine winds the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel","subset":"babb","task_type":"understanding","prediction":"light green in the deeps like your eyes in sunshine winds the canal lazy and brown as a water snake full of dazzle and sheen where the breeze sweeps the water with gossamer garments that shake the reeds standing sentinel","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":901,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8677\/Lab41-SRI-VOiCES-rm2-babb-sp8677-ch296078-sg0001-mc02-lav-clo-dg130.wav","answer":"and perhaps make a motion to lay the book down wait a moment girls and boys too i advise you to read on and see what came in this case of playing with dolls there were a good many thousands of boys in england at that time","subset":"babb","task_type":"understanding","prediction":"and perhaps make a motion to lay the book down wait a moment girls and boys too i invite you to read on and see what came in this case of playing with dolls there were a good many thousands of boys in england at that time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":902,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm2-babb-sp8713-ch296159-sg0005-mc02-lav-clo-dg010.wav","answer":"for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling","subset":"babb","task_type":"understanding","prediction":"for another he had now a luxurious leisure in which to polish up the proofs of his last novel and to arrange his ideas for its successor compared with this great work all former efforts would seem to the taste they had created as so much literary trifling","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":903,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/babb\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm2-babb-sp8713-ch296159-sg0045-mc01-stu-clo-dg110.wav","answer":"and know what reaction it was capable of in a word to experimentalise in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use","subset":"babb","task_type":"understanding","prediction":"and know what reaction it was capable of in a word to experimentalize in cold blood on the living nerve and brain tissue was his plan of work for the year eighteen ninety six making a mental note of several of the above phrases for future use","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":904,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0093\/Lab41-SRI-VOiCES-rm2-musi-sp0093-ch126208-sg0003-mc02-lav-clo-dg000.wav","answer":"an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a whity brown tilt obtained for a few pounds more and in this turn out it became jude's business thrice a week to carry loaves of bread to the villagers","subset":"musi","task_type":"understanding","prediction":"an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a witty brown tilt obtained for a few pounds more and in this turn out it became jude s business thrice a week to carry loaves of bread to the villagers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":905,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm2-musi-sp0112-ch121671-sg0027-mc02-lav-clo-dg010.wav","answer":"then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaves of bread altogether the baker man was terribly frightened","subset":"musi","task_type":"understanding","prediction":"then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaf of bread altogether the baker man was terribly frightened","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":906,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm2-musi-sp0112-ch123216-sg0022-mc02-lav-clo-dg000.wav","answer":"gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written him a nice little note of thanks but she had never worn the trinket tonight she fastened it about her white throat with a dreamy smile she and phil walked to redmond together","subset":"musi","task_type":"understanding","prediction":"gilbert had called her carrots and vainly tried to make his peace with a pink candy heart had written her a nice little note of thanks but she had never worn the trinket tonight she fastened it around her white throat with a dreamy smile she and phil walked to redmond together","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":907,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm2-musi-sp0122-ch129752-sg0000-mc01-stu-clo-dg100.wav","answer":"cakes crullers and eclairs almond cakes one pound sifted flour one half pound butter three fourths pound sugar two eggs one half teaspoon ground cinnamon","subset":"musi","task_type":"understanding","prediction":"cakes crullers and eclairs almond cakes one pound sifted flour one half pound butter three fourths pound sugar two eggs one half teaspoon ground cinnamon","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":908,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0159\/Lab41-SRI-VOiCES-rm2-musi-sp0159-ch121902-sg0000-mc01-stu-clo-dg010.wav","answer":"verily wondrous great are thy promises yet i do not doubt but thou canst make them good only keep me not in suspense after raising such hopes learn then first said she how that power ever waits upon the good","subset":"musi","task_type":"understanding","prediction":"verily wondrous great are thy promises yet i do not doubt but thou canst make them good only keep me not in suspense after raising such hopes learn then first said she how that power ever waits upon the good","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":909,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm2-musi-sp0204-ch148920-sg0005-mc01-stu-clo-dg180.wav","answer":"but as they were not learned men they could only walk about and stare enjoy the little knowledge of natural history they possessed and wish with all their hearts they had acquired more even the skeleton of the mouse puzzled jacob what wonder","subset":"musi","task_type":"understanding","prediction":"but as they were not learned men they could only walk about and stare enjoy the little knowledge of natural history they possessed and wish with all their hearts they had acquired more even the skeleton of the mouse puzzled jacob what wonder","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":910,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm2-musi-sp0205-ch157088-sg0027-mc02-lav-clo-dg050.wav","answer":"but we can not because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains","subset":"musi","task_type":"understanding","prediction":"but we cannot because everything up here is locked away from us i repeat that isn t conservation if they had applied a little of it to the salmon industry but they didn t and the salmon are going like the buffalo of the plains","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":911,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm2-musi-sp0209-ch157830-sg0033-mc02-lav-clo-dg130.wav","answer":"and on many lesser occasions had endeavoured to give elizabeth the advantage of her own better judgement and experience but always in vain elizabeth would go her own way and never had she pursued it in more decided opposition to lady russell than in this selection of missus clay","subset":"musi","task_type":"understanding","prediction":"and on many lesser occasions had endeavoured to give elizabeth the advantage of her own better judgment and experience but always in vain elizabeth would go her own way and never had she pursued it in more decided opposition to lady russell than in this selection of mrs clay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":912,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0224\/Lab41-SRI-VOiCES-rm2-musi-sp0224-ch128660-sg0018-mc01-stu-clo-dg020.wav","answer":"hair one hundred twenty four coarse hair indicates good nature fine hair quick temper northern ohio one hundred twenty five red hair indicates a spit fire massachusetts and chestertown maryland","subset":"musi","task_type":"understanding","prediction":"hair one hundred twenty four coarse hair indicates good nature fine hair quick temper northern ohio one hundred twenty five red hair indicates a spitfire massachusetts and chestertown maryland","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":913,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0224\/Lab41-SRI-VOiCES-rm2-musi-sp0224-ch128660-sg0019-mc02-lav-clo-dg060.wav","answer":"beware of that man be he friend or brother whose hair is one color and moustache another portland me one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of one's future husband","subset":"musi","task_type":"understanding","prediction":"beware of that man be he friend or brother whose hair is one color and mustache another portland may one hundred twenty seven the color of the hair growing on the neck indicates the color of the hair of ones future husband","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":914,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm2-musi-sp0242-ch122625-sg0004-mc02-lav-clo-dg090.wav","answer":"conventionality is not morality self righteousness is not religion to attack the first is not to assail the last to pluck the mask from the face of the pharisee is not to lift an impious hand to the crown of thorns","subset":"musi","task_type":"understanding","prediction":"Conventiuality is not morality. Self righteousness is not religion to attack. The first is not to assail the last, to pluck the mask from the face of the Pharisee is not to lift an impious hand to the crown of thorns.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":915,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0288\/Lab41-SRI-VOiCES-rm2-musi-sp0288-ch121741-sg0015-mc02-lav-clo-dg150.wav","answer":"and enough likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god's making one would say","subset":"musi","task_type":"understanding","prediction":"and in that likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god s making one would say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":916,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0288\/Lab41-SRI-VOiCES-rm2-musi-sp0288-ch131220-sg0017-mc01-stu-clo-dg150.wav","answer":"and diamond's chief pleasure seemed to be to lie amongst them and breathe the pure air but all the time he was dreaming of the country at the back of the north wind and trying to recall the songs the river used to sing for this was more like being at the back of the north wind","subset":"musi","task_type":"understanding","prediction":"and diamond s chief pleasure seemed to be to lie amongst them and breathe the pure air but all the time he was dreaming of the country at the back of the north wind and trying to recall the song the river used to sing for this was more like being at the back of the north wind","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":917,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0296\/Lab41-SRI-VOiCES-rm2-musi-sp0296-ch129659-sg0002-mc01-stu-clo-dg150.wav","answer":"to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding","subset":"musi","task_type":"understanding","prediction":"to the different sources or faculties of cognition by which alone their relation to each other can be rightly determined the first question which occurs in considering our representations is to what faculty of cognition do they belong to the understanding","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":918,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm2-musi-sp0479-ch134717-sg0050-mc02-lav-clo-dg040.wav","answer":"comrades mine and i in the midst and their memory ever to keep for the dead i loved so well for the sweetest wisest soul of all my days and lands and this for his dear sake lilac and star and bird twined with the chant of my soul","subset":"musi","task_type":"understanding","prediction":"comrades mine and i in the midst and their memory ever to keep for the dead i loved so well for the sweetest wisest soul of all my days and lands and this for his dear sake lilac and star and bird twine with the chant of my soul","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":919,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-musi-sp0492-ch131887-sg0025-mc02-lav-clo-dg030.wav","answer":"fix left alone was more impatient than ever having a presentiment that the robber was on board the mongolia if he had indeed left london intending to reach the new world","subset":"musi","task_type":"understanding","prediction":"fixed left alone was more impotent than ever having a presentiment that the robber was on board the mongolia if he had indeed left london intentionally to reach the new world","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":920,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-musi-sp0492-ch131899-sg0001-mc02-lav-clo-dg090.wav","answer":"blew a gale and retarded the steamer the rangoon rolled heavily and the passengers became impatient of the long monstrous waves which the wind raised before their path","subset":"musi","task_type":"understanding","prediction":"blew a gale and retarded the steamer the raccoon rolled heavily and the passengers became impatient of the long monstrous waves which the wind raised before their path","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":921,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-musi-sp0492-ch131899-sg0023-mc02-lav-clo-dg070.wav","answer":"who heard what passed would willingly have embraced the pilot while fix would have been glad to twist his neck what is the steamer's name asked mister fogg the carnatic","subset":"musi","task_type":"understanding","prediction":"who heard what pat would willingly have embraced the pilot while fix would have been glad to twist his neck what is this steamer s name asked mr fogg the kantik","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":922,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm2-musi-sp0510-ch130103-sg0015-mc02-lav-clo-dg180.wav","answer":"the clanking arms of the column near him made him soar on the red wings of war for a few moments he was sublime he thought that he was about to start for the front indeed he saw a picture of himself","subset":"musi","task_type":"understanding","prediction":"the clanking arms of the column near him made him soar on the red wings of war for a few moments he was sublime he thought that he was about to start for the front indeed he saw a picture of himself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":923,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm2-musi-sp0510-ch130560-sg0000-mc02-lav-clo-dg060.wav","answer":"karmu was a farmer and dharmu was a trader once when dharmu was away from home karmu gave a religious feast and did not invite dharmu's household when dharmu returned and learnt this","subset":"musi","task_type":"understanding","prediction":"karmu was a farmer and dharmu was a trader once when dharmu was away from home karmu gave a religious feast and did not invite dharmu s household when dharmu returned and learnt this","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":924,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm2-musi-sp0636-ch128331-sg0015-mc01-stu-clo-dg090.wav","answer":"with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building","subset":"musi","task_type":"understanding","prediction":"with marvellous quickness at a distance the more readily because certain men who had by some wonderful exercise of agility climbed up the external architecture to look in from the windows knew madame defarge well and acted as a telegraph between her and the crowd outside the building","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":925,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm2-musi-sp0637-ch127579-sg0010-mc02-lav-clo-dg070.wav","answer":"induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object","subset":"musi","task_type":"understanding","prediction":"induces me to give at some length a general description of the tree and the various modes in which the fruit is prepared the bread fruit tree in its glorious prime is a grand and towering object","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":926,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0652\/Lab41-SRI-VOiCES-rm2-musi-sp0652-ch130737-sg0002-mc02-lav-clo-dg080.wav","answer":"with entrees serve clarets or other red wines such as swiss bordeaux hungarian or italian wines","subset":"musi","task_type":"understanding","prediction":"With entrees, serve clarets or other red wines such as Swiss. Bordeaux, Hungarian or Italian wines.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":927,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0652\/Lab41-SRI-VOiCES-rm2-musi-sp0652-ch130737-sg0010-mc01-stu-clo-dg060.wav","answer":"sauterne is a white bordeaux a strong luscious wine the best known varieties being","subset":"musi","task_type":"understanding","prediction":"sauterne is a white bordeaux a strong luscious wine the best known varieties being","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":928,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0770\/Lab41-SRI-VOiCES-rm2-musi-sp0770-ch134592-sg0010-mc02-lav-clo-dg000.wav","answer":"now he was just a blind breathing carcase nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there were something in these wise old dogs that did not perish utterly with death","subset":"musi","task_type":"understanding","prediction":"now it was just a blind breathing carcass nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there was something in these wise old dogs that did not perish utterly with death","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":929,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0868\/Lab41-SRI-VOiCES-rm2-musi-sp0868-ch131295-sg0032-mc02-lav-clo-dg020.wav","answer":"why not as welcome death as life they are but counterparts one of the other the night and day of brahma through the disintegration of the old re creation becomes possible we have worshipped death","subset":"musi","task_type":"understanding","prediction":"why not as welcome death as life they are but counterparts one of the other the night and day of brahma through the disintegration of the old re creation becomes possible we have worshipped death","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":930,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0882\/Lab41-SRI-VOiCES-rm2-musi-sp0882-ch123268-sg0033-mc02-lav-clo-dg090.wav","answer":"this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour","subset":"musi","task_type":"understanding","prediction":"this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":931,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm2-musi-sp0949-ch134657-sg0023-mc02-lav-clo-dg040.wav","answer":"but his knowledge of his own temper prompted him to encourage and even to solicit the reproof of his friends and ministers and whenever they ventured to oppose the irregular sallies of his passions the spectators could observe the shame as well as the gratitude of their monarch","subset":"musi","task_type":"understanding","prediction":"but his knowledge of his own temper prompted him to encourage and even to solicit the reproof of his friends and ministers and whenever they ventured to oppose the irregular sallies of his passions the spectators could observe the shame as well as the gratitude of the monarch","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":932,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm2-musi-sp0949-ch138545-sg0032-mc02-lav-clo-dg120.wav","answer":"this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown","subset":"musi","task_type":"understanding","prediction":"this effort was futile for the royal governor promptly vetoed it from time to time similar bills were passed only to meet with royal disapproval south carolina in seventeen sixty absolutely prohibited importation but the measure was killed by the british crown","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":933,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp0949\/Lab41-SRI-VOiCES-rm2-musi-sp0949-ch162667-sg0034-mc01-stu-clo-dg020.wav","answer":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","subset":"musi","task_type":"understanding","prediction":"and after the deaths of many emperors the empire of constantinople devolved upon zeno and that of rome upon orestes and augustulus his son who obtained the sovereignty by fraud while they were designing to hold by force what they had obtained by treachery","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":934,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp1052\/Lab41-SRI-VOiCES-rm2-musi-sp1052-ch139307-sg0027-mc01-stu-clo-dg160.wav","answer":"he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what council could it be that gathered there","subset":"musi","task_type":"understanding","prediction":"he perceived there were now eight though how the newcomer had arrived he had not observed they made no gestures of greeting they stood regarding him as in the nineteenth century a group of men might have stood in the street regarding a distant balloon that had suddenly floated into view what council could it be that gathered there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":935,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm2-musi-sp1066-ch103481-sg0026-mc02-lav-clo-dg080.wav","answer":"each huddled dumbly to each but eyes could not lift from the sea only hands touched in the dawn he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream","subset":"musi","task_type":"understanding","prediction":"each huddled dumbly to each but eyes could not lift from the sea only hands touched in the darkness he would have gone my man he was like that in the night when i awoke with a start and brought his voice up from my dream","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":936,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm2-musi-sp1112-ch001043-sg0006-mc01-stu-clo-dg070.wav","answer":"but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cozy","subset":"musi","task_type":"understanding","prediction":"but the iron gates once closed and tended by the lodge keeper now stood permanently open the day of the motor car had come no one had time for closed gates and lodge keepers the lodge at sunnyside was merely a sort of supplementary servants quarters it was as convenient in its appointments as the big house and infinitely more cozy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":937,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm2-musi-sp1160-ch139717-sg0004-mc01-stu-clo-dg160.wav","answer":"however it gave him so high an opinion of my abilities in the confuting way that he seriously proposed my being his colleague in a project he had of setting up a new sect he was to preach the doctrines and i was to confound all opponents","subset":"musi","task_type":"understanding","prediction":"however it gave him so high an opinion of my abilities in the confuting way that he seriously proposed my being his colleague in the project he had of setting up a new sect he was to preach the doctrines and i was to confound all opponents","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":938,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm2-musi-sp1160-ch139730-sg0019-mc01-stu-clo-dg050.wav","answer":"undertook to repeat what he called the philadelphia experiments and after they were performed before the king and court all the curious of paris flocked to see them i will not swell this narrative with an account of that capital experiment","subset":"musi","task_type":"understanding","prediction":"Undertook to repeat what he called the Philadelphia experiments. And after they were performed before the king and court, all the curious of Paris flocked to see them. I will not swell this narrative with an account of that capital experiment.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":939,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_0032-1182\/sp1182\/Lab41-SRI-VOiCES-rm2-musi-sp1182-ch133396-sg0014-mc01-stu-clo-dg150.wav","answer":"he waited for a while and then knocked again rap tap tap presently with a click a little square wicket that pierced the door was opened and a woman's face peered out through the iron bars the one eyed hans whipped off his leathern cap","subset":"musi","task_type":"understanding","prediction":"he waited for a while and then knocked again presently with a click a little square wicket that pierced the door was opened and the woman's face peered out through the iron bars the one eyed hans whipped off his leather cap","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":940,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch124548-sg0029-mc01-stu-clo-dg140.wav","answer":"pointing with pride harry haydock as chairman introduced honest jim blausser and i am proud to say my fellow citizens that in his brief stay here mister blausser has become my warm personal friend as well as my fellow booster","subset":"musi","task_type":"understanding","prediction":"pointing with pride harry haydock as chairman introduced honest jim blausser and i am proud to say my fellow citizens that in his brief stay here mr blausser has become my warm personal friend as well as my fellow booster","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":941,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch135815-sg0009-mc01-stu-clo-dg150.wav","answer":"johnny here is not fond of the green forest but loves the old orchard and the green meadows in some parts of the country there are members of his family who prefer to live just on the edge of the green forest you will notice that johnny has stout claws","subset":"musi","task_type":"understanding","prediction":"johnny here is not fond of the green forest but loves the old orchard and the green meadows in some parts of the country there are members of this family who prefer to live just on the edge of the green forest you will notice that johnny has stout claws","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":942,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch135815-sg0010-mc01-stu-clo-dg140.wav","answer":"i can climb if i have to retorted johnny chuck indignantly i've climbed up bushes and low trees lots of times and if i can get a good run first i can climb up the straight trunk of a tree with rough bark to the first branches if they are not too far above ground","subset":"musi","task_type":"understanding","prediction":"i can climb if i have to retorted johnny chuck indignantly i have climbed up bushes and low trees lots of times and if i can get a good run first i can climb up the straight trunk of a tree with rough bark to the first branches if they are not too far above ground","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":943,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm2-musi-sp1246-ch135815-sg0012-mc02-lav-clo-dg000.wav","answer":"peter was delighted to air his knowledge the last one i was in said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it","subset":"musi","task_type":"understanding","prediction":"peter was delighted to air his knowledge the last one i was in he said he was a long tunnel slanting down for quite a distance and then straightening out the entrance was quite large with a big heap of sand out in front of it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":944,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm2-musi-sp1335-ch027593-sg0036-mc01-stu-clo-dg180.wav","answer":"and simmer for twenty minutes in one quart of milk being careful that it does not boil season with salt pepper mace and cayenne add one cup of cream stir until very smooth","subset":"musi","task_type":"understanding","prediction":"and simmer for twenty minutes in one quart of milk being careful that it does not boil season with salt pepper mace and cayenne add one cup of cream stir until very smooth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":945,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm2-musi-sp1335-ch163935-sg0023-mc01-stu-clo-dg060.wav","answer":"boil with this a little bag of mixed spices and two onions unless the meat has a good deal of fat use crisco or oil two cups of rice will be the right amount to use with two pounds of meat","subset":"musi","task_type":"understanding","prediction":"Boil with this. A little bag of mixed spices and two onions. Unless the meat has a good deal of fat, use Crisco or oil,2 cups of rice will be the right amount to use with £2 of meat.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":946,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm2-musi-sp1383-ch130489-sg0031-mc02-lav-clo-dg120.wav","answer":"his troubled spirit shifted its load his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm","subset":"musi","task_type":"understanding","prediction":"his troubled spirit shifted and slowed his vagrant thoughts were in full career his voice insensibly grew inquisitorial his voice was thick with resentment and futile protest his whole face was lighted with a fierce enthusiasm","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":947,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-musi-sp1392-ch128240-sg0014-mc02-lav-clo-dg020.wav","answer":"fain likewise would it play with the fire of the fagot and stake and be on thy guard also against the assaults of thy love too readily doth the recluse reach his hand to any one who meeteth him","subset":"musi","task_type":"understanding","prediction":"fain likewise would it play with the fire of the faggot and stake and be on thy guard also against the assaults of thy love too readily doff the recluse reach his hand to any one who needed it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":948,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-musi-sp1392-ch135659-sg0021-mc01-stu-clo-dg010.wav","answer":"is derived merely from custom it may be asked how it happens that men so much surpass animals in reasoning and one man so much surpasses another has not the same custom the same influence on all","subset":"musi","task_type":"understanding","prediction":"is derived merely from custom it may be asked how it happens that man so much surpasses animals in reasoning and one man so much surpasses another has not the same custom the same influence on all","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":949,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1417\/Lab41-SRI-VOiCES-rm2-musi-sp1417-ch001539-sg0019-mc02-lav-clo-dg160.wav","answer":"here fanned by cool breezes and surrounded by fair women and brave men one may do a bit of tissue restoring moreover there is little danger up here of being slugged by our moth eaten acquaintance of this morning a man with trousers like his would not be allowed in","subset":"musi","task_type":"understanding","prediction":"here fanned by cool breezes and surrounded by fair women and brave men what may do a bit of tissue restoring moreover there is little danger up here of being snubbed by our moth eaten acquaintance of this morning a man with trousers like his would not be allowed in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":950,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1425\/Lab41-SRI-VOiCES-rm2-musi-sp1425-ch139291-sg0008-mc02-lav-clo-dg040.wav","answer":"here too the slaves of all the other farms received their monthly allowance of food and their yearly clothing the men and women slaves received as their monthly allowance of food eight pounds of pork or its equivalent in fish and one bushel of corn meal","subset":"musi","task_type":"understanding","prediction":"Here, too, the slaves of all the other farms received their monthly allowance of food and their yearly clothing. The men and women slaves received as their monthly allowance of food,£8 of pork or its equivalent in fish, and one bushel of corn meal.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":951,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1607\/Lab41-SRI-VOiCES-rm2-musi-sp1607-ch134636-sg0016-mc01-stu-clo-dg070.wav","answer":"and africa were accustomed to revere constans the third of his sons as the representative of the great constantine he fixed dalmatius on the gothic frontier to which he annexed the government of thrace macedonia and greece","subset":"musi","task_type":"understanding","prediction":"and africa were accustomed to revere constans the third of his sons as the representative of the great constantine he fixed dalmatius on the gothic frontier to which he annexed the government of thrace macedonia and greece","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":952,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1607\/Lab41-SRI-VOiCES-rm2-musi-sp1607-ch150715-sg0043-mc01-stu-clo-dg010.wav","answer":"and the heiress of the norman line might struggle to check her despotic husband and to save the patrimony of her new born son of an emperor so famous in the next age under the name of frederic the second ten years after this revolution","subset":"musi","task_type":"understanding","prediction":"and the heiress of the norman line might struggle to check her despotic husband and to save the patrimony of her new born son of an emperor so famous in the next age under the name of frederic the second ten years after this revolution","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":953,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1841\/Lab41-SRI-VOiCES-rm2-musi-sp1841-ch179183-sg0017-mc01-stu-clo-dg110.wav","answer":"now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful","subset":"musi","task_type":"understanding","prediction":"now broken off or lengthened or swelling they rise and sink beneath my fingers they are full of sudden starts and pauses and their variety is inexhaustible and wonderful so you see i am not shut out from the region of the beautiful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":954,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm2-musi-sp1874-ch165701-sg0007-mc01-stu-clo-dg090.wav","answer":"but also recited doggerel satire of his own concoction punning and emitting sparks of wit lincoln was hailed as the capper of any good things on the rounds even then his friends saw the germs of the statesman in the lank homely crack voiced hobbledehoy","subset":"musi","task_type":"understanding","prediction":"but also recited doggerel satire of his own concoction punning and emitting sparks of wit lincoln was hailed as the capper of any good things on the rounds even then his friends saw the germs of the statesman in the lank homely cracked voiced hobbledehoy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":955,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm2-musi-sp1961-ch145733-sg0011-mc02-lav-clo-dg030.wav","answer":"here he had to stay but the whole day he sat working and when evening was come he had made a pretty little pot all round it were little bells and when the pot boiled they jingled most beautifully and played the old tune where is augustus dear","subset":"musi","task_type":"understanding","prediction":"here he had to stay but the whole day he sat working and when evening was come he had made a pretty little pot all around it were little bells and when the pot boiled they jingled most beautifully and played the old tune where is augustus dear","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":956,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm2-musi-sp1961-ch149739-sg0018-mc02-lav-clo-dg070.wav","answer":"he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor","subset":"musi","task_type":"understanding","prediction":"he could find no trace of a clue to confirm his belief yet so intimate was he with the spirit of the place that he knew how he knew he could not have told yet he did know that someone had entered his room sat on his benches and walked over his floor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":957,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2269\/Lab41-SRI-VOiCES-rm2-musi-sp2269-ch088761-sg0002-mc02-lav-clo-dg010.wav","answer":"but i developed with great rapidity and i believe men of science will tell you that this is always the case with low organisms that for instance while it takes years to develop the man from the baby and months to develop the dog from the puppy","subset":"musi","task_type":"understanding","prediction":"but i developed with great rapidity and i believe men of science will tell you that this is always the case with low organisms that for instance while it takes years to develop the man from the baby and months to develop the dog from the puppy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":958,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2269\/Lab41-SRI-VOiCES-rm2-musi-sp2269-ch088761-sg0032-mc01-stu-clo-dg160.wav","answer":"for it seems such a dreadful fate for poor gertrude the curate looked startled why i don't profess to like mister zaluski he said but i don't know anything exactly against him but i do","subset":"musi","task_type":"understanding","prediction":"poor it seems such a dreadful fate for poor gertrude the curate looks startled why i don't profess to like mr zaluski he said but i don't know anything exactly against him but i do","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":959,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm2-musi-sp2285-ch149890-sg0019-mc02-lav-clo-dg100.wav","answer":"moderately interested in its welfare hurstwood's word however had gone the rounds it was to be a full dress affair the four boxes had been taken doctor norman mc neill hale and his wife were to occupy one","subset":"musi","task_type":"understanding","prediction":"moderately interested in its welfare hurstwood s word however had gone the rounds it was to be a full dress affair the four boxes had been taken dr norman mc neil hale and his wife were to occupy one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":960,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm2-musi-sp2285-ch149890-sg0024-mc02-lav-clo-dg070.wav","answer":"where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mister hurstwood came from the first individual recognised glad to see you said the latter grasping his hand lightly","subset":"musi","task_type":"understanding","prediction":"where the lights were turned up and a company of gentlemen were laughing and talking in the open space back of the seats why how do you do mr hurstwood came from the first individual recognized glad to see you said the latter grasping his hand lightly","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":961,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm2-musi-sp2285-ch163381-sg0018-mc02-lav-clo-dg010.wav","answer":"en give half un it to you en de yuther half to de yuther woman dat's de way sollermun was gwyne to do wid de chile now i want to ast you","subset":"musi","task_type":"understanding","prediction":"and give half on it to you and de yuther half to de yuther woman dat s de way solomon was gwine to do wid de chile now i want to ask you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":962,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2289\/Lab41-SRI-VOiCES-rm2-musi-sp2289-ch152258-sg0008-mc01-stu-clo-dg030.wav","answer":"this woman was a widow who was carrying on the business left her by her husband as soon as the camel driver saw mohammed he stopped him and said my mistress wishes to see you before noon i think she intends to engage you to take charge of her caravans","subset":"musi","task_type":"understanding","prediction":"this woman was a widow who was carrying on the business left her by her husband as soon as the camel driver saw mohammed he stopped him and said my mistress wishes to see you before noon i think she intends to engage you to take charge of her caravans","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":963,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2294\/Lab41-SRI-VOiCES-rm2-musi-sp2294-ch161707-sg0041-mc02-lav-clo-dg180.wav","answer":"and finally shoot out point foremost into space through the open window and go up and up and up with a sound of rending atmospheres that seemed to tear like riven silk in one prolonged shriek under my head and to close up in thunder astern until my reeling senses could stand it no longer","subset":"musi","task_type":"understanding","prediction":"and finally shoot up point foremost into space through the open window and go up and up and up with sound of rending atmospheres that seemed to tear like ribboned silk in one prolonged shriek under my head and to close up and thunder astern until my reeling senses could stand it no longer","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":964,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2294\/Lab41-SRI-VOiCES-rm2-musi-sp2294-ch161714-sg0009-mc02-lav-clo-dg060.wav","answer":"and there in the twilight was the litter of the feast still about gold cups and silver broken bread and meat the convolvulus flowers all turning their pallid faces to the rosy daylight making pools of brightness between the shadows","subset":"musi","task_type":"understanding","prediction":"and there in the twilight was the litter of the feast still about gold cups and silver broken bread and meat the convolvulus flowers all turning their pallid faces to the rosy daylight making pools of brightness between the shadows","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":965,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2294\/Lab41-SRI-VOiCES-rm2-musi-sp2294-ch161714-sg0019-mc01-stu-clo-dg090.wav","answer":"this latter was careening over as a dusky group of men lifted aboard to a heap of tumbled silks and stuffs in the stern such a sweet piece of insensible merchandise as no man i at least of all could mistake it was heru herself and the rogues were ladling her on board like so much sandal wood or cotton sheeting","subset":"musi","task_type":"understanding","prediction":"this latter was careering over as a dusky group of men lifted aboard to a heap of tumbled silks and stuffs in the stern such a sweet piece of insensible merchandise as no man ay least of all could mistake it was heru herself and the robes were lailing her on board like so much sandal wood or cotton sheet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":966,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-musi-sp2412-ch153948-sg0006-mc02-lav-clo-dg100.wav","answer":"i was to see the sheep not necessarily close at hand nor to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet","subset":"musi","task_type":"understanding","prediction":"i was to see the sheep not necessarily close at hand or to get them in a single mob but to see enough of them here and there to feel easy that nothing had gone wrong this was no difficult matter for there were not above eight hundred of them and being all breeding ewes they were pretty quiet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":967,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-musi-sp2412-ch153954-sg0015-mc02-lav-clo-dg040.wav","answer":"suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome","subset":"musi","task_type":"understanding","prediction":"suffice it that i found myself taken before the chief magistrate and by his orders was placed in an apartment with two other people who were the first i had seen looking anything but well and handsome","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":968,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2532\/Lab41-SRI-VOiCES-rm2-musi-sp2532-ch157475-sg0017-mc02-lav-clo-dg070.wav","answer":"marcella came up to the nursery and played all day watching the rain patter upon the new tin gutter she wondered where raggedy andy was although she did not get worried about him until she had asked mama where he might be he must be just where you left him mama said","subset":"musi","task_type":"understanding","prediction":"marcella came up to the nursery and played all day watching the rain patter upon the new tin gutter she wondered where raggily andy was although she did not get worried about him until she had asked mamma where he might be he must be just where you left him mamma said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":969,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2573\/Lab41-SRI-VOiCES-rm2-musi-sp2573-ch178449-sg0048-mc01-stu-clo-dg140.wav","answer":"he could only stare bewildered every evening i want you they sha'n't hurt you again and she held out her hand to him it was strong and warm in his tremulous clasp if i could i'd go and feed the strips of zinc to the machine with you she said","subset":"musi","task_type":"understanding","prediction":"he could only stare bewildered every evening i want you they shan hurt you again and she held out her hand to him it was strong and warm in his tremulous clasp if i could i go and feed the strips of zinc to the machine with you she said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":970,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp2691\/Lab41-SRI-VOiCES-rm2-musi-sp2691-ch156750-sg0023-mc02-lav-clo-dg100.wav","answer":"for it had a beautiful picture near the back showing a little girl with a sprinkling pot watering her garden of stocks sweet williams and hollyhocks her hair was in four long curls and she had trimming on her dress apron and long pantalets","subset":"musi","task_type":"understanding","prediction":"for it had a beautiful picture near the back showing a little girl with a sprinkling pot watering her garden of stocks sweet williams and hollyhocks her hair was in four long curls and she had trimming on her dress apron and long pantaloons","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":971,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3235\/Lab41-SRI-VOiCES-rm2-musi-sp3235-ch028433-sg0003-mc01-stu-clo-dg060.wav","answer":"where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more","subset":"musi","task_type":"understanding","prediction":"where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":972,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3235\/Lab41-SRI-VOiCES-rm2-musi-sp3235-ch028433-sg0003-mc02-lav-clo-dg060.wav","answer":"where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more","subset":"musi","task_type":"understanding","prediction":"where he could do beach mining i was not above doing any honest work and felt confident that i could make my way if i could gain an entrance into that country the english people were all workers and i had known them for ten years or more","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":973,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3235\/Lab41-SRI-VOiCES-rm2-musi-sp3235-ch028452-sg0013-mc02-lav-clo-dg110.wav","answer":"for which she has a whole heartful of love and the sight of which is better to her than medicine during the month of july we eagerly watched the incoming steamers and welcomed all new comers who landed in chinik","subset":"musi","task_type":"understanding","prediction":"for which she has a whole heart full of love and the sight of which is better to her than medicine during the month of july we eagerly watched the incoming steamers and welcomed all newcomers who landed in chinik","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":974,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm2-musi-sp3368-ch170951-sg0019-mc01-stu-clo-dg130.wav","answer":"and therefore the cause of well being yes it follows therefore that the good is not the cause of all things but of the good only assuredly then god if he be good is not the author of all things as the many assert but he is the cause of","subset":"musi","task_type":"understanding","prediction":"and therefore the cause of well being yes it follows therefore that the good is not the cause of all things but of the good only assuredly then god if he be good is not the author of all things as the many assert but he is the cause","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":975,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-musi-sp3446-ch144021-sg0018-mc02-lav-clo-dg090.wav","answer":"mate down with fever ngora ngora sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset","subset":"musi","task_type":"understanding","prediction":"mate down with fever negoro negoro sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":976,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-musi-sp3446-ch176270-sg0003-mc02-lav-clo-dg030.wav","answer":"the inhabitants of which although faithful to their rulers being influenced more by immediate danger than by attachment to their distant friends surrendered in the same manner they obtained massa and serezana toward the end of may they proceeded in the direction of lucca","subset":"musi","task_type":"understanding","prediction":"the inhabitants of which although faithful to their rulers being influenced more by immediate danger than by attachment to their distant friends surrendered in the same manner they obtained massa and serenzana towards the end of may they proceeded in the direction of lucca","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":977,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm2-musi-sp3483-ch119637-sg0013-mc01-stu-clo-dg110.wav","answer":"that did not seem real to me and my mind still resisted i remember gazing with staring eyes at that picture the sweat pouring down my face searching eagerly for some visible evidence of fraud and being unable to find it it was the identical likeness of wilma","subset":"musi","task_type":"understanding","prediction":"they did not seem real to me and my mind still resisted i remember gazing with staring eyes at that picture the sweat pouring down my face searching eagerly for some visible evidence of fraud and being unable to find it it was the identical likeness of wilmot","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":978,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm2-musi-sp3483-ch119637-sg0028-mc02-lav-clo-dg040.wav","answer":"this creature his most prized possession san lan with the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil arts had i not seen the naked horror of her soul","subset":"musi","task_type":"understanding","prediction":"this creature his most prized possession san lawn of the utmost moral callousness ordered to seduce me urging her to apply without stint and to its fullest extent her knowledge of evil arts had i not seen the naked horror of her soul","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":979,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm2-musi-sp3549-ch171171-sg0023-mc02-lav-clo-dg070.wav","answer":"and as great a quantity of provisions as would suffice them for a long time and let himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old","subset":"musi","task_type":"understanding","prediction":"and as great a quantity of provisions as would suffice them for a long time and led himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":980,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm2-musi-sp3549-ch173591-sg0001-mc01-stu-clo-dg090.wav","answer":"but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots","subset":"musi","task_type":"understanding","prediction":"but a dull exile in a petty fort by a hot and sickly river with hard labor bad fare prospective famine and nothing to break the weary sameness but some passing canoe or floating alligator gathered in knots","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":981,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm2-musi-sp3835-ch178029-sg0001-mc02-lav-clo-dg100.wav","answer":"caused russians to grieve he had such a sad face when shown into the emperor's study that the latter at once asked have you brought me sad news colonel very sad sire replied michaud lowering his eyes with a sigh the abandonment of moscow","subset":"musi","task_type":"understanding","prediction":"caused russians to grieve he had such a sad face when shown into the emperor s study that the latter at once asked have you brought me sad news colonel very sad sir replied mashuk covering his eyes with a sigh the abandonment of moscow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":982,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm2-musi-sp3835-ch178030-sg0027-mc01-stu-clo-dg010.wav","answer":"everything went well and easily the landowner to whom nicholas went was a bachelor an old cavalryman a horse fancier a sportsman the possessor of some century old brandy and some old hungarian wine who had a snuggery where he smoked","subset":"musi","task_type":"understanding","prediction":"everything went well and easily the landowner to whom nicholas went was a bachelor an old cavalryman a horse fancier a sportsman the possessor of some century old brandy and some old hungarian wine who had a snuggery where he smoked","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":983,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm2-musi-sp3923-ch153309-sg0024-mc02-lav-clo-dg100.wav","answer":"he took it for the instinctive recognition it undoubtedly was he therefore watched him narrowly and succeeded in getting one glance from his eye it was enough the man was commonplace commonplace in feature dress and manner but his eye gave him away","subset":"musi","task_type":"understanding","prediction":"took it for the instinctive recognition it undoubtedly was he therefore watched him narrowly and succeeded in getting one glance from his eyes it was enough the man was commonplace commonplace in feature and dress and manner but his eye gave him away","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":984,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm2-musi-sp3923-ch174992-sg0031-mc02-lav-clo-dg050.wav","answer":"to whom can i apply to appoint others don't you know what vested interests mean lord chiltern then nobody can manage his own property as he pleases nobody can unless he does the work himself if i were to go and live in trumpeton wood i could do it but you see i have to live here","subset":"musi","task_type":"understanding","prediction":"to whom can i apply to appoint others don t you know what vested interests mean orchard that nobody can manage his own property as he pleases nobody can unless he does the work himself if i were to go and live in trumpeton what i could do but you see i have to live here","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":985,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp3972\/Lab41-SRI-VOiCES-rm2-musi-sp3972-ch185074-sg0012-mc02-lav-clo-dg020.wav","answer":"no one can conceive of the constant trouble that i daily endured on their account on the account of my two oldest sons whom i loved equally and with all the feelings and affection of a tender mother stimulated by an anxious concern for their fate","subset":"musi","task_type":"understanding","prediction":"no one can conceive of the constant trouble that i daily endured on their account on the account of my two oldest sons whom i loved equally and with all the feelings and affection of a tender mother stimulated by an anxious concern for their fate","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":986,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm2-musi-sp4014-ch186176-sg0015-mc01-stu-clo-dg120.wav","answer":"won't do it slim muttered oh yes you will counseled joe shake hands the two of you slim's good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we're square said slim","subset":"musi","task_type":"understanding","prediction":"won t do it slim muttered oh yes you will counseled joe shake hands the two of you slim s good nature overcame his feigned reluctance but as jerry grasped his hand he gave jerry a jerk that nearly took him off his feet now we re square said slim","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":987,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4057\/Lab41-SRI-VOiCES-rm2-musi-sp4057-ch011254-sg0000-mc01-stu-clo-dg000.wav","answer":"great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse","subset":"musi","task_type":"understanding","prediction":"great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":988,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4057\/Lab41-SRI-VOiCES-rm2-musi-sp4057-ch011254-sg0000-mc02-lav-clo-dg000.wav","answer":"great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse","subset":"musi","task_type":"understanding","prediction":"great city snobs there is no disguising the fact that this series of papers is making a prodigious sensation among all classes in this empire notes of admiration of interrogation of remonstrance approval or abuse","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":989,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm2-musi-sp4064-ch012118-sg0036-mc02-lav-clo-dg020.wav","answer":"his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her","subset":"musi","task_type":"understanding","prediction":"his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":990,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm2-musi-sp4064-ch077779-sg0014-mc02-lav-clo-dg010.wav","answer":"and provokes a great deal of innocent mirth you don't yourself believe that last yarn about the prohibition candidate do you i haven't heard any yarn about him said the bibliomaniac that he is the owner of a brewery up in rochester","subset":"musi","task_type":"understanding","prediction":"and provokes a great deal of innocent mirth you dont yourself believe that last yarn about the prohibition candidate do you i havent heard any yarn about him said the bibliomaniac that he is the owner of the brewery of the brochester","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":991,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4110\/Lab41-SRI-VOiCES-rm2-musi-sp4110-ch011528-sg0022-mc02-lav-clo-dg060.wav","answer":"unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and","subset":"musi","task_type":"understanding","prediction":"unblinking eyes glaring tentacles writhing warily little spurts of used water trickling from their helmets keep together warned stanley so that if any one of us loses his light he can get it from the hose of one of the other two and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":992,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4110\/Lab41-SRI-VOiCES-rm2-musi-sp4110-ch011533-sg0015-mc01-stu-clo-dg130.wav","answer":"jaska merely smiled her inscrutable smile and did not answer by intuition she already knew let sarka arrive at her conclusion by scientific methods if he desired and she would simply smile anew","subset":"musi","task_type":"understanding","prediction":"jaska merely smiled her inscrutable smile and did not answer by intuition she already knew let sarka arrive at her conclusion by scientific methods if he desired and she would simply smile anew","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":993,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4145\/Lab41-SRI-VOiCES-rm2-musi-sp4145-ch034497-sg0032-mc02-lav-clo-dg100.wav","answer":"inevitable he thought things could not go on as before but he said something different it can't go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life","subset":"musi","task_type":"understanding","prediction":"inevitable he thought things could not go on as before but he said something different it can go on i hope that now you will leave him i hope he was confused and reddened that you will let me arrange and plan our life","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":994,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4160\/Lab41-SRI-VOiCES-rm2-musi-sp4160-ch011549-sg0020-mc01-stu-clo-dg120.wav","answer":"she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin's wishes in the matter of military balls and blue satin slippers","subset":"musi","task_type":"understanding","prediction":"she insisted upon wearing blue satin slippers and a low necked dress oh dear said theodora secretly conscious of a guilty sympathy for the giddy young person who ran counter to brother benjamin s wishes in the matter of military balls and blue satin slippers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":995,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4331\/Lab41-SRI-VOiCES-rm2-musi-sp4331-ch057179-sg0029-mc01-stu-clo-dg170.wav","answer":"with a great effort she restrained all emotion and simply shook her head she did it very well and betrayed nothing i ask said the duchess because i have been very glad to hear that you are engaged to marry him lord drummond tells me that he is a most respectable young man","subset":"musi","task_type":"understanding","prediction":"with a great effort she restrained all emotion and simply shook her head she did it very well and betrayed nothing i ask said the duchess because i have been very glad to hear that you are engaged to marry him lord drummond tells me that he is a most respectable young man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":996,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch012471-sg0006-mc02-lav-clo-dg090.wav","answer":"and had promised to render the water such as they desired it to be in case they would be subservient to him in what he should enjoin them to do and this not after a remiss or negligent manner and when they asked what they were to do in order to have the water changed for the better","subset":"musi","task_type":"understanding","prediction":"and had promised to render the water such as they desired it to be in case they would be subservient to him in what he should enjoin them to do and this not after a remiss or negligent manner and when they asked what they were to do in order to have the water changed for the better","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":997,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch012471-sg0008-mc01-stu-clo-dg160.wav","answer":"and meeting with no relief they were in a very desponding condition and by fixing their attention upon nothing but their present misfortunes they were hindered from remembering what deliverances they had received from god and those by the virtue and wisdom of moses also","subset":"musi","task_type":"understanding","prediction":"and meeting with no relief they were in a very desponding condition and by fixing their attention upon nothing but their present misfortunes they were hindered from remembering what deliverances they had received from god and those by the virtue and wisdom of moses also","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":998,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch020028-sg0020-mc01-stu-clo-dg140.wav","answer":"she never forgot it and always packed it very carefully too i asked her two or three times to let me put it in my trunk where i had slyly arranged a nice little place full of hard surfaces and sharp corners but she always had plenty of room","subset":"musi","task_type":"understanding","prediction":"she never forgot it and always packed it very carefully too i asked her two or three times to let me put it in my trunk where i had slyly arranged a nice little place full of hard surfaces and sharp corners but she always had plenty of room","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":999,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-musi-sp4427-ch041933-sg0009-mc01-stu-clo-dg040.wav","answer":"but as he felt much stronger and better he made up his mind that this strange adventure must really have happened and he sprang on his horse and rode off with a light heart to look for his companions in a few weeks they began to set out on their return home","subset":"musi","task_type":"understanding","prediction":"but as he felt much stronger and better he made up his mind that this strange adventure must really have happened and he sprang on his horse and rode off with a light heart to look for his companions in a few weeks they began to set out on their return home","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1000,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm2-musi-sp4438-ch048513-sg0013-mc01-stu-clo-dg170.wav","answer":"when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her","subset":"musi","task_type":"understanding","prediction":"when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1001,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm2-musi-sp4441-ch076263-sg0010-mc02-lav-clo-dg160.wav","answer":"partly because he had no servant and partly because he had nothing with which to make a fire no servant had brushed his clothes or brought his coffee and yet he was standing before his easel whistling merrily engaged in painting a brilliant sunset when there came four knocks at the door","subset":"musi","task_type":"understanding","prediction":"partly because he had no servant and partly because he had nothing with which to make a fire no servant had brushed his clothes or brought his coffee and yet he was standing before his easel whistling merrily and engaged in painting a brilliant sunset when there came four knocks at the door","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1002,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm2-musi-sp4441-ch076263-sg0031-mc02-lav-clo-dg050.wav","answer":"the figure the amount i could do with say sixty crowns good lord how modest you are remarked borg and turned to levin yes it is very little said the latter take as much as you can get falk while the purse is open","subset":"musi","task_type":"understanding","prediction":"the figure the amount i could do with say sixty crowns good lord how modest you are remarked bour and turned to levin yes it is very little said the latter take as much as you can get fob while the purse is open","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1003,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-musi-sp4535-ch279849-sg0033-mc01-stu-clo-dg130.wav","answer":"fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller","subset":"musi","task_type":"understanding","prediction":"fuller waved his arms up and down slowly to the engineer as a signal to come to a gradual stop they coasted down upon the box car picked it up and carried it on with them fuller and murphy climbed to the top of it murphy staying at the rear end to repeat the signals of fuller","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1004,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-musi-sp4535-ch279852-sg0008-mc02-lav-clo-dg120.wav","answer":"i'll let a bullet go smack into the first man that makes a move he shouldn't here was a man they couldn't talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later","subset":"musi","task_type":"understanding","prediction":"i ll let a bullet go smack into the first man that makes a move he shouldn t here was a man they couldn t talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1005,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4586\/Lab41-SRI-VOiCES-rm2-musi-sp4586-ch061758-sg0016-mc01-stu-clo-dg160.wav","answer":"were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of head gear it was possible he might have seen fit to change the fashion","subset":"musi","task_type":"understanding","prediction":"were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of headgear it was possible he might have seen fit to change the fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1006,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4586\/Lab41-SRI-VOiCES-rm2-musi-sp4586-ch061758-sg0016-mc02-lav-clo-dg160.wav","answer":"were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of head gear it was possible he might have seen fit to change the fashion","subset":"musi","task_type":"understanding","prediction":"were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of headgear it was possible he might have seen fit to change the fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1007,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4744\/Lab41-SRI-VOiCES-rm2-musi-sp4744-ch031668-sg0002-mc02-lav-clo-dg000.wav","answer":"it was curious this instinctive aversion she felt to being shut in by trees especially a kind of claustrophobia almost probably due as has been said to the days in india when the trees took her husband off and surrounded him with dangers","subset":"musi","task_type":"understanding","prediction":"it was curious this instinctive aversion she felt to being shut in by trees especially a kind of claustrophobia almost probably due as had been said to the days in india when the trees took her husband off and surrounded him with dangers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1008,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4744\/Lab41-SRI-VOiCES-rm2-musi-sp4744-ch031668-sg0017-mc01-stu-clo-dg120.wav","answer":"this she could understand in a fashion at least and make allowances for she had yielded gently even sweetly to his choice of their english home for in the little island there is nothing that suggests the woods of wilder countries so nearly as the new forest","subset":"musi","task_type":"understanding","prediction":"this she could understand in a fashion at least and make allowances for she had yielded gently even sweetly to his choice of their english home for in the little island there is nothing that suggests the woods of wilder countries so nearly as the new forest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1009,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm2-musi-sp4839-ch015307-sg0003-mc01-stu-clo-dg050.wav","answer":"and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor of agnadello and his allies of cambrai but at treviso when emperor maximilian's commissioner presented himself in order to take possession of it","subset":"musi","task_type":"understanding","prediction":"and ordered its commandants to evacuate such places as they still held nearly all such submitted without a struggle to the victor von jedlau and his allies of combrein but at treviso when emperor maximilian s commissioner presented himself in order to take possession of it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1010,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm2-musi-sp4848-ch101836-sg0009-mc01-stu-clo-dg180.wav","answer":"let me out of this trap and i will not hurt you save me from the rain that i may save you from the sun if you should need help so mvoo laana believed him and let him out of the trap and simba kongway before going his way said","subset":"musi","task_type":"understanding","prediction":"let me out of this trap and i will not hurt you save me from the rain that i may save you from the sun if you should need help so mavoullon had believed him and let him out of the trap and simbaconway before going his way said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1011,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4859\/Lab41-SRI-VOiCES-rm2-musi-sp4859-ch022176-sg0008-mc02-lav-clo-dg110.wav","answer":"and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman","subset":"musi","task_type":"understanding","prediction":"and yet so similar in that they had both lived and both died and in the love he felt for both of them pierre drove up to the house of the old prince in a most serious mood the house had escaped the fire it showed signs of damage but its general aspect was unchanged the old footman","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1012,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4957\/Lab41-SRI-VOiCES-rm2-musi-sp4957-ch023295-sg0011-mc02-lav-clo-dg120.wav","answer":"without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sandford interrupted the menace prepared for utterance saying and you still mean i suppose to make mister rushbrook your heir","subset":"musi","task_type":"understanding","prediction":"without farther argument if she obeys me in this i will provide for her as my daughter during my life and leave her a fortune at my death but if she dares sanford interrupted the menace prepared for utterance saying and you still mean i suppose to make mr rushworth your heir","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1013,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4967\/Lab41-SRI-VOiCES-rm2-musi-sp4967-ch026520-sg0005-mc02-lav-clo-dg170.wav","answer":"because it could not be avoided but their bodies and colors must be changed with their diet especially while they would be clearly discovered by the finer appearance of the other children who would fare better and thus they should bring him into danger and occasion him to be punished","subset":"musi","task_type":"understanding","prediction":"because it could not be avoided but their bodies and colours must be changed with their dying especially while it would be clearly discovered by the finer appearance of the other children who would fare better and thus they should bring him into danger and occasion him to be punished","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1014,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp4967\/Lab41-SRI-VOiCES-rm2-musi-sp4967-ch028868-sg0016-mc01-stu-clo-dg080.wav","answer":"i only meant that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for awhile and then repeated his words i think i will go abroad not for long i hope sir","subset":"musi","task_type":"understanding","prediction":"i only meant that of course they will stumble across each other in london i think i will go abroad said the duke he was silent for a while and then repeated his words i think i will go abroad not for long i hope sir","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1015,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5126\/Lab41-SRI-VOiCES-rm2-musi-sp5126-ch034483-sg0024-mc01-stu-clo-dg000.wav","answer":"but this time she found a big one quite of herself and there was a general scream of delight lily has found a mushroom then they reached the river put the horses under the birch trees and went to the bathing place","subset":"musi","task_type":"understanding","prediction":"but this time she found a big one quite of herself and there was a general scream of delight lily has found a mushroom then they reached the river put the horses under the birch trees and went to the bathing place","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1016,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm2-musi-sp5154-ch026558-sg0010-mc01-stu-clo-dg140.wav","answer":"sweet little banana the image of wax answered never a word then the monkey called out in his loudest voice o peddler boy peddler boy if you don't give me a banana i'll give you such a push that it will upset","subset":"musi","task_type":"understanding","prediction":"sweet little banana the image of wax as if never a word then the monkey called out in his loudest voice oh peddler boy peddler boy if you don t give me a banana i ll give you such a push that it will upset","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1017,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5154\/Lab41-SRI-VOiCES-rm2-musi-sp5154-ch026558-sg0022-mc01-stu-clo-dg150.wav","answer":"the monkey was at last able to pull out one of his hands the sun poured down more of his hottest rays and soon the monkey was able to pull out his two hands then he could pull out one foot then another and in a little while his body too","subset":"musi","task_type":"understanding","prediction":"The monkey was at last able to pull out one of his hands. The sun poured down more of his hottest rays, and soon the monkey was able to pull out his two hands. Then he could pull out 1 ft. Then another. And in a little while, his body, too.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1018,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5157\/Lab41-SRI-VOiCES-rm2-musi-sp5157-ch047238-sg0003-mc02-lav-clo-dg170.wav","answer":"which should join you as soon as the weather would permit at present indeed it is not very encouraging for row boats we wait a courier from vienna to decide the march of eight thousand eight hundred infantry","subset":"musi","task_type":"understanding","prediction":"which should join you as soon as the weather would permit at present indeed it is not very encouraging for rupees we wait a courier from vienna to decide the march of eight thousand eight hundred infantry","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1019,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm2-musi-sp5189-ch056574-sg0007-mc02-lav-clo-dg120.wav","answer":"sich a magnificent chance to make it manifest try yoor self particularly on custer tho after all continyood he in a musin abstracted sort a way wich he's fallen into lately the fellow is sich a triflin bein","subset":"musi","task_type":"understanding","prediction":"such a magnificent chance to make it manifest try yourself particularly on custer though after all continued he in a musing abstracted sort of way which he has fallen into lately the fellow is such a trifling being","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":12}
+{"index":1020,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm2-musi-sp5189-ch059288-sg0037-mc01-stu-clo-dg060.wav","answer":"combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting","subset":"musi","task_type":"understanding","prediction":"combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1021,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5319\/Lab41-SRI-VOiCES-rm2-musi-sp5319-ch084357-sg0004-mc01-stu-clo-dg150.wav","answer":"published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers","subset":"musi","task_type":"understanding","prediction":"published in eighteen forty seven and purporting to be by john sobieski and charles edward stuart some suggestive hints it is true had been thrown out as early as eighteen twenty two in a volume of poems by one of these brothers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1022,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm2-musi-sp5401-ch039515-sg0002-mc01-stu-clo-dg020.wav","answer":"the mesozoic comprises three systems the triassic named from its threefold division in germany the jurassic which is well displayed in the jura mountains and the cretaceous which contains the extensive chalk latin creta deposits of europe in eastern north america","subset":"musi","task_type":"understanding","prediction":"the mesozoic comprises three systems the triassic named from its threefold division in germany the jurassic which is well displayed in the jura mountains and the cretaceous which contains the extensive chalk latin creta deposits of europe in eastern north america","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1023,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm2-musi-sp5401-ch039515-sg0008-mc01-stu-clo-dg010.wav","answer":"these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood","subset":"musi","task_type":"understanding","prediction":"these triassic rocks which are chiefly sandstones hold no marine fossils and hence were not laid in open arms of the sea but their layers are often ripple marked and contain many tracks of reptiles imprints of raindrops and some fossil wood","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1024,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch024741-sg0014-mc01-stu-clo-dg050.wav","answer":"which association arises in the mind according to the order and association of the modifications affectiones of the human body i say first it is an association of those ideas only","subset":"musi","task_type":"understanding","prediction":"which associations arises in the mind according to the order and association of the modifications affections of the human body i say first it is an association of those ideas only","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1025,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch024741-sg0019-mc01-stu-clo-dg070.wav","answer":"and hence we can further clearly understand why the mind from the thought of one thing should straightway arrive at the thought of another thing which has no similarity with the first for instance from the thought of the word pomum an apple","subset":"musi","task_type":"understanding","prediction":"and hence we can further clearly understand why the mind from the thought of one thing should straightway arrive at the thought of another thing which has no similarity with the first for instance from the thought of the word pomum an apple","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1026,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch062014-sg0015-mc01-stu-clo-dg030.wav","answer":"o o goo coo o o goo coo ez he flewed off inter de darkness here aunt phrony spread her arms like wings and made a swoop half way across the room to the bedside of the startled children an she continued","subset":"musi","task_type":"understanding","prediction":"ooh goo coo ooh goo coo as he flewed off into de darkness here aunt phrony spread her arms like wings and made a swoop halfway across the room to the bedside of the startled troy and she continued","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":1027,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm2-musi-sp5456-ch062043-sg0024-mc02-lav-clo-dg020.wav","answer":"this wood seems rather better than that we took in at yellow face's but we're nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask em what's the price of wood up here i've got you again","subset":"musi","task_type":"understanding","prediction":"this wood seems rather better than that we took in at yellow faces but we are nearly out again and must be looking out for more i saw a light just ahead on the right shall we hail yes yes replied the captain ring the bell and ask them what is the price of wood up here i have got you again","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1028,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm2-musi-sp5635-ch044582-sg0022-mc01-stu-clo-dg080.wav","answer":"such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration","subset":"musi","task_type":"understanding","prediction":"such as looking fixedly at a blank spot in the ceiling or twisting a watch charm four what effect do such habits have on the audience five what relation does pause bear to concentration","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1029,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm2-musi-sp5678-ch043302-sg0023-mc01-stu-clo-dg030.wav","answer":"she loved to see him like this his confident flushed face the enthusiasm in his blue eyes and the knowledge of his pain pricked her feeling with passion she bent forward and kissed him suddenly my dear i am so proud of you oh oliver he said nothing","subset":"musi","task_type":"understanding","prediction":"she loved to see him like this his confident flushed face the enthusiasm in his blue eyes and the knowledge of his pain pricked her feeling with passion she bent forward and kissed him suddenly my dear i am so proud of you oh oliver he said nothing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1030,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm2-musi-sp5717-ch094876-sg0029-mc01-stu-clo-dg140.wav","answer":"but what's happened to you where did you get that donkey head really i wouldn't have known you at all shaggy man if i hadn't looked at your feet the shaggy man introduced johnny dooit to dorothy and toto and button bright and the rainbow's daughter","subset":"musi","task_type":"understanding","prediction":"but what has happened to you where did you get that donkey head really i wouldn't have known you at all shaggy man if i hadn't looked at your feet the shaggy man introduced johnny dooit to dorothy and toto and button bright and the rainbow star","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1031,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5740\/Lab41-SRI-VOiCES-rm2-musi-sp5740-ch039910-sg0011-mc01-stu-clo-dg030.wav","answer":"sat before the fire and listened to the wind howling about the house i'm glad i'm not driving over the prairie tonight said mister joseph it's quite a storm i hope it will be fine tomorrow for the children's sake they've set their hearts on having a sleigh ride","subset":"musi","task_type":"understanding","prediction":"sat before the fire and listened to the wind howling about the house i am glad i am not driving over the prairie to night said mr joseph it is quite a storm i hope it will be fine to morrow for the childrens sake they have set their hearts on having a sleigh ride","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1032,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5740\/Lab41-SRI-VOiCES-rm2-musi-sp5740-ch097593-sg0001-mc02-lav-clo-dg080.wav","answer":"he was a young scarecrow and this was his first one he was strongly made and although his wooden joints creaked a little when the wind blew he did not grow in the least rickety every morning when the wintry sun peered like a hard yellow eye across the dry corn stubble","subset":"musi","task_type":"understanding","prediction":"he was a young scarecrow and this was his first one he was strongly made and although his wooden joints creaked a little when the wind blew he did not grow the least rickety every morning when the wintry sun peered like a hard yellow eye across the dry corn stubble","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1033,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-musi-sp5935-ch043305-sg0006-mc02-lav-clo-dg120.wav","answer":"that they were already in the tunnel the stoppage might arise from many causes and he was not greatly excited nor did it seem that others in the carriage took it very seriously he could hear after a moment's silence the talking recommence beyond the partition","subset":"musi","task_type":"understanding","prediction":"that they were already in the tunnel the stoppage might arise from many causes and he was not greatly excited nor did it seem that others in the carriage took it very seriously he could hear after a moment s silence the talking recommence beyond the partition","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1034,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-musi-sp5935-ch043322-sg0019-mc01-stu-clo-dg020.wav","answer":"after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not","subset":"musi","task_type":"understanding","prediction":"after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1035,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-musi-sp5935-ch055927-sg0036-mc02-lav-clo-dg100.wav","answer":"had the effect of enabling shippers to realise upon the goods carried more speedily than would have been possible under the old system of sail power alone it is already found that in the matter of economy of working including interest on cost of vessel and cargo","subset":"musi","task_type":"understanding","prediction":"had the effect of enabling shippers to realize upon the goods carried more speedily than would have been possible under the old system of sail power alone it is already found that in the matter of economy of working including interest on cost of vessel and cargo","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1036,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp5968\/Lab41-SRI-VOiCES-rm2-musi-sp5968-ch061356-sg0007-mc02-lav-clo-dg020.wav","answer":"the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father's house in london and alice peel was she thinking of him","subset":"musi","task_type":"understanding","prediction":"the music was weird and discordant yet john found it all very stimulating dance after dance was gone through while he stayed and watched till there came to his mind pictures of the old home his father s house in london and alice peel was she thinking of him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1037,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm2-musi-sp6147-ch034607-sg0017-mc02-lav-clo-dg170.wav","answer":"predicted that being the elder sister of fire she would be queen and so she was thanks to astrology and the revolution of sixteen eighty eight she had the humiliation of having only gilbert archbishop of canterbury for godfather to be godchild of the pope was no longer possible in england","subset":"musi","task_type":"understanding","prediction":"predicted that being the elder sister of fire she would be queen and so she was thanks to astrology and the revolution of sixteen eighty eight she had the humiliation of having only gilbert archbishop of canterbury for godfather to be godchild of the pope was no longer possible in england","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1038,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm2-musi-sp6147-ch034607-sg0031-mc02-lav-clo-dg080.wav","answer":"in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher wren is a very passable mansard somers is as good as lamoignon anne has a racine in dryden","subset":"musi","task_type":"understanding","prediction":"in it there is enough to deceive the eye add god save the queen which might have been taken from lulli and the ensemble becomes an illusion not a personage is missing christopher red is a very passable mousart somers is as good as le moignon anne has a racine in dryden","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1039,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061943-sg0013-mc02-lav-clo-dg080.wav","answer":"then without further remark he put his finger to his lips frowned darkly and descended into the small boat which awaited us","subset":"musi","task_type":"understanding","prediction":"Then, without further remark, he put his finger to his lips. Frowned darkly and descended into the small boat, which awaited us.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1040,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061946-sg0006-mc01-stu-clo-dg130.wav","answer":"i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur","subset":"musi","task_type":"understanding","prediction":"i could not help smiling to see him look so big on his little horse his long legs now and then touching the ground made him look like a six footed centaur","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1041,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061946-sg0011-mc01-stu-clo-dg130.wav","answer":"here and there could be seen an isolated farm some solitary bur or icelandic house built of wood earth fragments of lava looking like beggars on the highway of life","subset":"musi","task_type":"understanding","prediction":"here and there could be seen an isolated farm some solitary ver or icelandic house built of wood earth fragments of lava looking like beggars on the highway of life","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1042,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch061946-sg0020-mc01-stu-clo-dg060.wav","answer":"at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor's legs and left him standing with both feet on a separate stone like the colossus of rhodes","subset":"musi","task_type":"understanding","prediction":"at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor s legs and left him standing with both feet on a separate stone like the colossus of rhodes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1043,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm2-musi-sp6241-ch066616-sg0008-mc01-stu-clo-dg140.wav","answer":"curiously enough the blood of wabi ran almost pure to his indian forefathers while minnetaki as she became older developed less of the wild beauty of her mother and more of the softer loveliness of the white race her wealth of soft jet black hair and her great dark eyes contrasting with the lighter skin of her father's blood","subset":"musi","task_type":"understanding","prediction":"Curiously enough, the blood of Wabi ran almost pure to his Indian forefathers, while Minnetaki, as she became older, developed less of the wild beauty of her mother and more of the softer loveliness of the white race. Her wealth of soft jet black hair and her great dark eyes, contrasting with the lighter skin of her father's blood.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1044,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm2-musi-sp6385-ch220959-sg0035-mc01-stu-clo-dg000.wav","answer":"which can be compared to father and mother and it is absolute perfection but the darkness has neither substance nor form neither father nor mother and it is absolute imperfection the substance of adam's physical life was earth","subset":"musi","task_type":"understanding","prediction":"which can be compared to father and mother and it is absolute perfection but the darkness has neither substance nor form neither father nor mother and it is absolute imperfection the substance of adam s physical life was earth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1045,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm2-musi-sp6395-ch084349-sg0027-mc02-lav-clo-dg070.wav","answer":"for months this system of solitary confinement was endured by the child who reduced to a state of helpless stupidity no longer attempted to change his linen or cleanse himself and was allowed to drift into a condition of utter imbecility","subset":"musi","task_type":"understanding","prediction":"For months, this system of solitary confinement was endured by the child who reduced to the state of helpless stupidity, no longer attempted to change his linen or cleanse himself and was allowed to drift into a condition of utter imbecility.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1046,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm2-musi-sp6519-ch231834-sg0034-mc02-lav-clo-dg000.wav","answer":"which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greeb's very lively imagination yet even though he reduced her communications to bare facts","subset":"musi","task_type":"understanding","prediction":"which she was quite unable to define save in terms more or less vague lucian dismissed such hints of criminality from his mind as the outcome of miss greene s very lively imagination yet even though he reduced her communications to bare facts","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1047,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-musi-sp6544-ch071420-sg0016-mc02-lav-clo-dg150.wav","answer":"if you go back do you know what they will do they will surely hang you oh merciful heaven do not say that i wouldn't if it wasn't so but i've been talking to the coroner and the chief of police and they have all of the evidence as straight as a string","subset":"musi","task_type":"understanding","prediction":"if you go back do you know what they will do they will surely hang you oh merciful heaven do not say that i wouldnt if it wasnt so but i have been talking to the coroner and the chief of police and they have all the evidence as straight as a string","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1048,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-musi-sp6544-ch231862-sg0036-mc02-lav-clo-dg000.wav","answer":"he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost","subset":"musi","task_type":"understanding","prediction":"he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1049,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm2-musi-sp6574-ch070753-sg0034-mc01-stu-clo-dg000.wav","answer":"the arrival of the arabian now infused new life into his soul when the news reached leghorn that felix was deprived of his wealth and rank the merchant commanded his daughter to think no more of her lover but to prepare to return to her native country","subset":"musi","task_type":"understanding","prediction":"The arrival of the Arabian now infused new life into his soul. When the news reached Leghorn that Felix was deprived of his wealth and rank, the merchant commanded his daughter to think no more of her lover. But to prepare to return to her native country.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1050,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm2-musi-sp6574-ch070756-sg0028-mc01-stu-clo-dg070.wav","answer":"and become linked to the chain of existence and events from which i am now excluded i paused some time to reflect on all he had related and the various arguments which he had employed i thought of the promise of virtues which he had displayed on the opening of his existence","subset":"musi","task_type":"understanding","prediction":"and become linked to the chain of existence and events from which i am now excluded i paused some time to reflect on all he had related and the various arguments which he had employed i thought of the promise of virtues which he had displayed on the opening of his existence","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1051,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6696\/Lab41-SRI-VOiCES-rm2-musi-sp6696-ch073296-sg0037-mc02-lav-clo-dg080.wav","answer":"emma's attempts to stop her father had been vain and when he had reached such a point as this she could not wonder at her brother in law's breaking out mister perry said he in a voice of very strong displeasure would do as well to keep his opinion till it is asked for","subset":"musi","task_type":"understanding","prediction":"emmas attempts to stop her father had been vain and when he had reached such a point as this she could not wonder at her brother in laws breaking out mr perry said he in a voice of very strong displeasure would do as well to keep his opinion till it is asked for","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1052,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6788\/Lab41-SRI-VOiCES-rm2-musi-sp6788-ch111574-sg0028-mc02-lav-clo-dg010.wav","answer":"the oyster fixed in its bed unable to hunt for food thus makes its dinner come to it what a strange use for a beard it not only serves as lungs but also helps the animal to catch its daily bread","subset":"musi","task_type":"understanding","prediction":"the oyster fixed in its bed unable to hunt for food thus makes its dinner come to it what a strange use for a beard it not only serves as lungs but also helps the animal to catch its daily bread","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1053,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6848\/Lab41-SRI-VOiCES-rm2-musi-sp6848-ch076049-sg0018-mc01-stu-clo-dg060.wav","answer":"she had had no husband of the lord and master type so to speak but only a prince consort well in hand why shouldn't the grammont heiress dominate her male belonging if it came to that in the same fashion","subset":"musi","task_type":"understanding","prediction":"she had had no husband of the lord and master type so to speak but only a prince consort well in hand why shouldn t the grammont heiress dominate her male belonging if it came to that in the same fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1054,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6848\/Lab41-SRI-VOiCES-rm2-musi-sp6848-ch252323-sg0009-mc01-stu-clo-dg040.wav","answer":"broke in craggs i was brigaded with arentschild's hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you're right","subset":"musi","task_type":"understanding","prediction":"broken crags i was brigaded with arnolds and hanoverians in spain and they used to sit outside the tents every evening and sing by jove how they did sing all together like the swell of a church organ yes you are right","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1055,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm2-musi-sp6965-ch277898-sg0011-mc02-lav-clo-dg030.wav","answer":"was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs","subset":"musi","task_type":"understanding","prediction":"was his breathless greeting i spoke evasively of the situation in portugal where more trouble seemed brewing but laploshka listened with the abstraction of the deaf adder and quickly returned to the subject of the two francs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1056,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm2-musi-sp6965-ch277898-sg0012-mc01-stu-clo-dg100.wav","answer":"but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart's action was the doctor's verdict","subset":"musi","task_type":"understanding","prediction":"but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart s action was the doctor s verdict","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1057,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm2-musi-sp6965-ch291718-sg0013-mc02-lav-clo-dg100.wav","answer":"and have only the old pieces which nobody wants two things troubled me very much while i was confined to the cradle one was that everybody who came in to see your mother laughed as if they never could stop","subset":"musi","task_type":"understanding","prediction":"and have only the old pieces which nobody wants two things troubled me very much when i was confined to the cradle one was that everybody who came in to see your mother laughed as if they never could stop","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1058,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm2-musi-sp7000-ch083696-sg0027-mc02-lav-clo-dg000.wav","answer":"well he said it's a pity it should be wasted i'll eat it myself which he did and me standing in the rain there looking on that did put my back up mister evans i said short and sharp i wish you a good day i am going","subset":"musi","task_type":"understanding","prediction":"well he said it is a pity it should be wasted i will eat it myself which he did and me standing in the rain there looking on that did put my back up mr evans i said short and sharp i wish you a good day i am going","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1059,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm2-musi-sp7000-ch083706-sg0015-mc01-stu-clo-dg000.wav","answer":"if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mister hedges any objections which i might urge would appear quite trivial","subset":"musi","task_type":"understanding","prediction":"if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mr hedges any objections which i might urge would appear quite trivial","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1060,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-musi-sp7148-ch059157-sg0015-mc02-lav-clo-dg050.wav","answer":"she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny brawne","subset":"musi","task_type":"understanding","prediction":"she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny bron.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1061,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-musi-sp7148-ch082991-sg0020-mc02-lav-clo-dg020.wav","answer":"and i will add to it a wish that the pope may forge her marriage chains to her royal husband faster than ever a foolish wish cried bryan why mark you are clean crazed","subset":"musi","task_type":"understanding","prediction":"and i will add to it a wish that the pope may forge her marriage chains to her royal husband faster than ever a foolish wish cried bryan why mark you are clean crazed","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1062,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7276\/Lab41-SRI-VOiCES-rm2-musi-sp7276-ch090847-sg0006-mc02-lav-clo-dg060.wav","answer":"alas what are we to do i can not take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing","subset":"musi","task_type":"understanding","prediction":"alas what are we to do i cannot take you with me dear child for it is forbidden on pain of death to bring mortals to the assembly nor can i leave you here in this lonely wood to this marianna replied do not fear dear father give me but yon crystal flask of the water of healing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1063,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm2-musi-sp7278-ch246956-sg0017-mc02-lav-clo-dg030.wav","answer":"she was a free woman and as leopold had chosen other counsellors had thus declared her unworthy of confidence and after all that she had suffered and done for love of him","subset":"musi","task_type":"understanding","prediction":"she was a free woman and as leopold had chosen other counsellors had thus declared her unworthy of confidence and after all that she had suffered and done for love of him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1064,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7445\/Lab41-SRI-VOiCES-rm2-musi-sp7445-ch094523-sg0014-mc02-lav-clo-dg040.wav","answer":"and though the term of the commission was limited it was easy to foresee that the intentions of the party were to render it perpetual and that power would with great difficulty be wrested from those grasping hands to which it was once committed richard however was obliged to submit","subset":"musi","task_type":"understanding","prediction":"and though the term of the commission was limited it was easy to foresee that the intentions of the party were to render it perpetual and that power would with great difficulty be wrested from those grasping hands to which it was once committed richard however was obliged to submit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1065,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm2-musi-sp7498-ch099124-sg0010-mc01-stu-clo-dg040.wav","answer":"humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former","subset":"musi","task_type":"understanding","prediction":"humanity will draw a veil over this part of her character which it cannot approve and may perhaps prompt some to impute her actions to her situation more than to her dispositions and to lament the unhappiness of the former","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1066,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7517\/Lab41-SRI-VOiCES-rm2-musi-sp7517-ch100442-sg0004-mc02-lav-clo-dg090.wav","answer":"aproned behind the counter look out for the currants in the window as you come in i have an idea for something artistic in the way of patterns there but as you love me do not offer to buy any","subset":"musi","task_type":"understanding","prediction":"aproned behind the counter look out for the currants in the window as you come in i have an idea for something artistic in the way of patterns there but as you love me do not offer to buy any","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1067,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm2-musi-sp7540-ch101258-sg0030-mc01-stu-clo-dg110.wav","answer":"and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the whale had thrown up came sailing along and anchored close by","subset":"musi","task_type":"understanding","prediction":"and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the well had thrown up came sailing along and anchored close by","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1068,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm2-musi-sp7540-ch101262-sg0013-mc01-stu-clo-dg010.wav","answer":"soon got tired of being by himself and began to look about for something to amuse him what can there be in that twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other","subset":"musi","task_type":"understanding","prediction":"soon got tired of being by himself and began to look about for something to amuse him what can there be in the twelfth cellar he thought to himself which i must not see and he went downstairs and unlocked the doors one after the other","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1069,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7688\/Lab41-SRI-VOiCES-rm2-musi-sp7688-ch109656-sg0016-mc02-lav-clo-dg080.wav","answer":"it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing a meal or two and sleeping comfortably on your saddle blankets on a soft mattress of mesquite grass","subset":"musi","task_type":"understanding","prediction":"it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing a meal or two and sleeping comfortably on your saddle blankets in a soft mattress of mesquite grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1070,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-musi-sp7850-ch111771-sg0001-mc01-stu-clo-dg140.wav","answer":"at this time grant was not taken with war and probably evinced little interest in army tactics","subset":"musi","task_type":"understanding","prediction":"at this time grant was not taken with bore had probably evinced little interest in army tactics","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1071,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-musi-sp7868-ch110705-sg0027-mc01-stu-clo-dg090.wav","answer":"for five minutes without stopping apparently with the view of ascertaining if he were quite correctly put together while gluck stood contemplating him in speechless amazement he was dressed in a stashed doublet of spun gold so fine in its texture","subset":"musi","task_type":"understanding","prediction":"for five minutes without stopping apparently with the view of ascertaining if he were quite correctly put together while gluck stood contemplating him speechless amazed he was dressed in a stach doublet of spun gold so fine in its texture","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1072,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-musi-sp7868-ch110706-sg0013-mc01-stu-clo-dg030.wav","answer":"which sprang from one of the lower and snowless elevations was now nearly in shadow all but the uppermost jets of spray which rose like slow smoke above the undulating line of the cataract and floated away in feeble wreaths upon the morning wind","subset":"musi","task_type":"understanding","prediction":"which sprang from when the lower and snowless elevations was now merely in shadow all but the uttermost jets of spray which rose like slow smoke above the undulating line of the cataract and floated away in feeble wreaths upon the morning wind","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1073,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-musi-sp7868-ch110706-sg0035-mc01-stu-clo-dg040.wav","answer":"and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball","subset":"musi","task_type":"understanding","prediction":"and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1074,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7910\/Lab41-SRI-VOiCES-rm2-musi-sp7910-ch105673-sg0041-mc01-stu-clo-dg130.wav","answer":"there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries","subset":"musi","task_type":"understanding","prediction":"there was only one particular in which henry was quite decisive because he was there impelled by his avarice or more properly speaking his rapacity the consequence of his profusion this measure was the entire destruction of the monasteries","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1075,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch093470-sg0011-mc02-lav-clo-dg120.wav","answer":"i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruth's own wish that it should be told to others","subset":"musi","task_type":"understanding","prediction":"i think that what you said to me before is likely to be verified and that if she unburdens herself it will be to mary and you may be sure whatever is the nature of the secret my daughter will keep it inviolate unless it is ruths own wish that it should be told to others","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1076,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch110056-sg0022-mc01-stu-clo-dg180.wav","answer":"and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by","subset":"musi","task_type":"understanding","prediction":"and say in a kind tone madam or sir where is such a street if you please you should be careful to give this title to persons whom you address even if they should be porters or hucksters it is particularly to these that you should have recourse for in addressing persons passing by","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1077,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch278228-sg0011-mc01-stu-clo-dg070.wav","answer":"in spite of those heartless words which she had spoken in the bitter hour of their parting clement could not thoroughly believe in the baseness of the woman he had trusted again and again he went over the same ground trying to find some lurking circumstance no matter how unlikely in its nature","subset":"musi","task_type":"understanding","prediction":"in spite of those heartless words which she had spoken in the bitter hour of their parting clement could not thoroughly believe in the baseness of the woman he had trusted again and again he went over the same ground trying to find some lurking circumstance no matter how unlikely in its nature","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1078,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm2-musi-sp7932-ch278228-sg0025-mc02-lav-clo-dg180.wav","answer":"said the detective i was away in glasgow hunting up the particulars of the great scotch plaid robberies all last summer and i can't say i remember much of what was done in the wilmot business mister dunbar himself offered a reward for the apprehension of the guilty party didn't he","subset":"musi","task_type":"understanding","prediction":"said the detective i was away in glasgow hunting up the particulars of the great scotch plaid robberies all last summer and i can t say i remember much of what was done in the will not business mr dunbar himself offered a reward for the apprehension of the guilty party didn t he","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1079,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm2-musi-sp7976-ch105575-sg0013-mc02-lav-clo-dg010.wav","answer":"when morning came the firing opened and for all that day the battle raged fiercely at the left and center left we getting the worst of it too","subset":"musi","task_type":"understanding","prediction":"when morning came the firing opened and for all that day the battle raged fiercely at the left center left we getting the worst of it too","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1080,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm2-musi-sp7976-ch110523-sg0017-mc02-lav-clo-dg020.wav","answer":"creep in said the witch and see if it is hot enough and then we will put in the bread but she intended when grethel got in to shut up the oven and let her bake so that she might eat her as well as hansel","subset":"musi","task_type":"understanding","prediction":"preheat said the witch and see if it is hot enough and then we will put in the bread but she intended when gretel got in to shut up the oven and let her bake so that she might eat her as well as hansel","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1081,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm2-musi-sp7995-ch276908-sg0012-mc02-lav-clo-dg070.wav","answer":"of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature","subset":"musi","task_type":"understanding","prediction":"of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1082,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8051\/Lab41-SRI-VOiCES-rm2-musi-sp8051-ch119902-sg0019-mc01-stu-clo-dg000.wav","answer":"and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits","subset":"musi","task_type":"understanding","prediction":"and you need no bread at all at some meals an extra potato or a serving of rice can be eaten instead of the usual two slices of bread and the body will be supplied with the same amount of energy do not be the slave of old food habits","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1083,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8118\/Lab41-SRI-VOiCES-rm2-musi-sp8118-ch114476-sg0027-mc01-stu-clo-dg090.wav","answer":"here was a full half day for the army of the potomac enough in which to destroy a divided portion of the army of northern virginia but colonel winchester raged again and again in vain there was no attack brigade after brigade in blue came up and sat down before the antietam","subset":"musi","task_type":"understanding","prediction":"here was a full half day for the army of the potomac enough in which to destroy a divided portion of the army of northern virginia but colonel winchester raged again and again in vain there was no attack brigade after brigade in blue came up and sat down before the intrenchment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1084,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm2-musi-sp8225-ch274375-sg0001-mc02-lav-clo-dg110.wav","answer":"those parliamentary leaders it must be owned who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity","subset":"musi","task_type":"understanding","prediction":"those parliamentary leaders say it must be the holland who had introduced such mighty innovations into the english constitution and who had projected so much greater had not engaged in an enterprise which exceeded their courage and capacity","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1085,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-musi-sp8266-ch258262-sg0001-mc01-stu-clo-dg020.wav","answer":"they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered","subset":"musi","task_type":"understanding","prediction":"they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1086,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-musi-sp8266-ch258263-sg0037-mc01-stu-clo-dg030.wav","answer":"then she abode in the castle and her son grew up and was reared with the children of the king they used to ride forth together a hunting and birding and he became skilled in the chase of wild beasts and ravening lions and ate of their flesh till his heart became harder than the rock","subset":"musi","task_type":"understanding","prediction":"then she abode in the castle and her son grew up and was reared with the children of the king they used to ride forth together a hunting and birding and he became skilled in the chase of wild beasts and ravening lions and ate of their flesh till his heart became harder than the rock","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1087,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-musi-sp8266-ch279363-sg0000-mc01-stu-clo-dg140.wav","answer":"colonel woodville had begun to swear it was not the torrent of loud imprecation that dick had heard in jackson but subdued and all the more fierce because it was so like the ferocious whine of a powerful and hurt wild animal swearing was common enough among the older men of the south","subset":"musi","task_type":"understanding","prediction":"colonel woodville had begun to swear it was not the torrent of loud imprecation that dick had heard in jackson but subdued and all the more fierce because it was so like the ferocious whine of a powerful and hurt wild animal swearing was common enough among the older men of the south","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1088,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm2-musi-sp8425-ch291444-sg0000-mc02-lav-clo-dg020.wav","answer":"of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative old age and day by day dropping piecemeal into the tomb in a little while thought i and those revered dutch burghers","subset":"musi","task_type":"understanding","prediction":"of this venerable and ancient city gradually slipping from our grasp trembling on the lips of narrative old age and day by day dropping piecemeal into the tomb then a little while afar high had those revered dutch burghers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1089,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm2-musi-sp8425-ch292520-sg0014-mc02-lav-clo-dg120.wav","answer":"and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wave and solemnly sway to the wash and swell of our passing","subset":"musi","task_type":"understanding","prediction":"and the marginal line of birches and willows our little steamer pulls its way with jingle of bells and panting throb of old engines in stiff array the water reeds wraith and solemnly sway to the wash and swell of our passage","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1090,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8575\/Lab41-SRI-VOiCES-rm2-musi-sp8575-ch290350-sg0034-mc01-stu-clo-dg080.wav","answer":"should be co existent to the motion we measure by or any other periodical revolution but it suffices to this purpose that we have the idea of the length of any regular periodical appearances which we can in our minds apply to duration with which the motion or appearance never co existed","subset":"musi","task_type":"understanding","prediction":"should be coexistent to the motion we measure by or any other periodical revolution but it suffices to this purpose that we have the idea of the length of any regular periodical appearances which we can in our minds apply to duration with which the motion or appearance never coexisted","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1091,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8635\/Lab41-SRI-VOiCES-rm2-musi-sp8635-ch295759-sg0011-mc01-stu-clo-dg140.wav","answer":"the guard formed two lines that stood face to face let their guns rest on the ground and leaned their heads on the butts the corpse was borne twixt these two rows of men with the sword and sash on the top of the box in which he lay","subset":"musi","task_type":"understanding","prediction":"the guard formed two lines that stood face to face let their guns rest on the ground and lean their heads on the butts the corpse was borne twixt these two rows of men with the sword and sash on the top of the box in which he lay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1092,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8677\/Lab41-SRI-VOiCES-rm2-musi-sp8677-ch296078-sg0025-mc02-lav-clo-dg130.wav","answer":"there were many sheep on the downs and there was one special flock that florence knew very well it belonged to old roger a shepherd who had often worked for her father roger and his good dog cap were both friends of florence's","subset":"musi","task_type":"understanding","prediction":"There were many sheep on the downs. And there was one special flock that Florence knew very well. It belonged to old Roger, a shepherd who had often worked for her father, Roger and his good dog cap were both friends of Florence's.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1093,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/musi\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm2-musi-sp8713-ch302111-sg0010-mc02-lav-clo-dg080.wav","answer":"answered in the words which follow song of birds is idle chatter and the throstle's merely chirping as a child a daughter's treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seat thee","subset":"musi","task_type":"understanding","prediction":"answered in the words which follow song of birds is idle chatter and the thrushes merely chirping as a child the daughter is treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seek thee","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1094,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0093\/Lab41-SRI-VOiCES-rm2-none-sp0093-ch126208-sg0003-mc02-lav-clo-dg000.wav","answer":"an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a whity brown tilt obtained for a few pounds more and in this turn out it became jude's business thrice a week to carry loaves of bread to the villagers","subset":"none","task_type":"understanding","prediction":"an aged horse with a hanging head had been purchased for eight pounds at a sale a creaking cart with a witty brown tilt obtained for a few pounds more and in this turn out it became jude s business thrice a week to carry loaves of bread to the villagers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1095,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0093\/Lab41-SRI-VOiCES-rm2-none-sp0093-ch126209-sg0001-mc02-lav-clo-dg120.wav","answer":"having promised to call at a flour mill near cresscombe to execute a commission for his aunt he was in an enthusiastic mood he seemed to see his way to living comfortably in christminster in the course of a year or two and knocking at the doors of one of those strongholds of learning","subset":"none","task_type":"understanding","prediction":"having promised to call at a flour mill near crescomb to execute a commission for his aunt he was in an enthusiastic mood he seemed to see his way to living comfortably in christminster in the course of a year or two and knocking at the doors of one of the strongholds of learning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1096,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0093\/Lab41-SRI-VOiCES-rm2-none-sp0093-ch126209-sg0027-mc01-stu-clo-dg030.wav","answer":"springing to her feet she said bring back what is lying there jude was now aware that no message on any matter connected with her father's business had prompted her signal to him he set down his basket of tools","subset":"none","task_type":"understanding","prediction":"springing to her feet she said bring back what is lying there jude was now aware that no message on any matter connected with her father s business had prompted her signal to him he set down his basket of tools","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1097,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm2-none-sp0112-ch121671-sg0004-mc01-stu-clo-dg050.wav","answer":"with white gravel paths and many beds of bright colored flowers the old woman was very happy and contented there until one day she received a letter saying that her daughter hannah was dead and had sent her family of five children to their grandmother to be taken care of","subset":"none","task_type":"understanding","prediction":"with white gravel paths and many beds of bright colored flowers the old woman was very happy and contented there until one day she received a letter saying that her daughter hannah was dead and had sent her family of five children to their grandmother to be taken care of","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1098,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0112\/Lab41-SRI-VOiCES-rm2-none-sp0112-ch121671-sg0027-mc01-stu-clo-dg010.wav","answer":"then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaves of bread altogether the baker man was terribly frightened","subset":"none","task_type":"understanding","prediction":"then a flight of arrows came from the bushes and although they were blunt and could do him no harm they rattled all over his body and one hit his nose and another his chin while several stuck fast in the loaves of bread altogether the baker man was terribly frightened","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1099,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0174\/Lab41-SRI-VOiCES-rm2-none-sp0174-ch168635-sg0003-mc01-stu-clo-dg070.wav","answer":"he suffered all the pangs of a mother and he knew not what it meant for that great and singular movement of a heart which begins to love is a very obscure and a very sweet thing","subset":"none","task_type":"understanding","prediction":"he suffered all the pangs of a mother and he knew not what it meant for that great and singular movement of a heart which begins to love is a very obscure and a very sweet thing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1100,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm2-none-sp0204-ch148920-sg0015-mc02-lav-clo-dg020.wav","answer":"knew no better than to be venturesome why let him tumble horror what mean that heavy crashing sound ben could not stir he could only gasp jacob jacob cried another startled voice","subset":"none","task_type":"understanding","prediction":"do know better than to be venturesome why let him tumble horror what mean that heavy crashing sound ben could not stir he could only gasp jacob jacob cried another startled voice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1101,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm2-none-sp0205-ch123882-sg0036-mc02-lav-clo-dg020.wav","answer":"bill and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely as the great swamp just this side of the bridge over the ossawippi","subset":"none","task_type":"understanding","prediction":"bell and sam as if they were all one family what is it now nine thirty ah then we must be nearing the town this big bush that we are passing through you remember it surely is the great swamp just this side of the bridge over the osawimpee","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1102,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm2-none-sp0205-ch157088-sg0027-mc01-stu-clo-dg050.wav","answer":"but we can not because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains","subset":"none","task_type":"understanding","prediction":"but we cannot because everything up here is locked away from us i repeat that isn't conservation if they had applied a little of it to the salmon industry but they didn't and the salmon are going like the buffalo of the plains","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1103,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0208\/Lab41-SRI-VOiCES-rm2-none-sp0208-ch126600-sg0025-mc01-stu-clo-dg150.wav","answer":"when john d pell wants something done d'you think he asks of anyone oh no he orders someone to with get my hat or tie my shoe the goops all say rude things like these but you of course say","subset":"none","task_type":"understanding","prediction":"When John D. Pell wants something done, do you think he asks of anyone. Oh, no. He orders somebody with get my hat or tie my shoe. The goops all say, with things like these. But you, of course, say.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1104,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm2-none-sp0209-ch004731-sg0033-mc01-stu-clo-dg050.wav","answer":"that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware","subset":"none","task_type":"understanding","prediction":"that the evening flew away at a very unusual rate and the supper table which always closed such parties and for which she had been used to sit and watch the due time was all set out and ready and moved forwards to the fire before she was aware","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1105,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0240\/Lab41-SRI-VOiCES-rm2-none-sp0240-ch160592-sg0001-mc01-stu-clo-dg080.wav","answer":"as he defeated dying on whose forbidden ear the distant strains of triumph break agonized and clear two our share of night to bear","subset":"none","task_type":"understanding","prediction":"as he defeated dying on whose forbidden ear the distant strains of triumph break agonized and clear two our share of night to bear","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1106,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm2-none-sp0242-ch122625-sg0002-mc01-stu-clo-dg170.wav","answer":"i turn to another class a small one so far as i know but not therefore to be overlooked i mean the timorous or carping few who doubt the tendency of such books as jane eyre in whose eyes whatever is unusual is wrong","subset":"none","task_type":"understanding","prediction":"i turn to another class a small one so far as i know but not therefore to be overlooked i mean the timorous or carping few who doubt the tendency of such books as jane eyre in whose eyes whatever is unusual is wrong","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1107,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm2-none-sp0242-ch126842-sg0035-mc02-lav-clo-dg010.wav","answer":"peter no i don't want to hear about it said uncle alec sternly i don't care what you were fighting about but you must settle your quarrels in a different fashion remember my commands felix peter","subset":"none","task_type":"understanding","prediction":"peter no i don t want to hear about it said uncle alec sternly i don t care what you were fighting about but you must settle your quarrel in a different fashion remember my commands felix peter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1108,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0288\/Lab41-SRI-VOiCES-rm2-none-sp0288-ch130994-sg0002-mc02-lav-clo-dg000.wav","answer":"i shall now proceed in the enumeration of the most important of those defects which have hitherto disappointed our hopes from the system established among ourselves to form a safe and satisfactory judgment of the proper remedy it is absolutely necessary","subset":"none","task_type":"understanding","prediction":"i shall now proceed to the enumeration of the most important of those defects which have hitherto disappointed our hopes from the system established among ourselves to form a safe and satisfactory judgment of the proper remedy it is absolutely necessary","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1109,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0296\/Lab41-SRI-VOiCES-rm2-none-sp0296-ch142727-sg0031-mc01-stu-clo-dg090.wav","answer":"these derangements are the basis of emotion its physical basis and to be moved is to perceive them take away from the consciousness this physical reflex and emotion ceases it is no longer anything but an idea","subset":"none","task_type":"understanding","prediction":"these derangements are the basis of emotion its physical basis and to be moved is to perceive them take away from the consciousness this physical reflex and emotion ceases it is no longer anything but an idea","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1110,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm2-none-sp0459-ch127522-sg0016-mc01-stu-clo-dg020.wav","answer":"the rocks of the spy glass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain","subset":"none","task_type":"understanding","prediction":"the rocks of the spyglass re echoed it a score of times the whole troop of marsh birds rose again darkening heaven with a simultaneous whirr and long after that death yell was still ringing in my brain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1111,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm2-none-sp0472-ch129979-sg0025-mc01-stu-clo-dg100.wav","answer":"i am so glad we are got acquainted at last continued charlotte and now i hope we shall always be great friends you can't think how much i longed to see you it is so delightful that you should live at the cottage nothing can be like it to be sure","subset":"none","task_type":"understanding","prediction":"i am so glad we are got acquainted at last continued charlotte and now i hope we shall always be great friends you can not think how much i longed to see you it is so delightful that you should live at the cottage nothing can be like it to be sure","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1112,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm2-none-sp0472-ch129983-sg0011-mc01-stu-clo-dg180.wav","answer":"which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth","subset":"none","task_type":"understanding","prediction":"which is a melancholy and shocking extremity is her son determined to submit to this and to all the tediousness of the many years of suspense in which it may involve you rather than run the risk of her displeasure for a while by owning the truth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1113,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm2-none-sp0479-ch134717-sg0034-mc01-stu-clo-dg020.wav","answer":"and the singer so shy to the rest receiv'd me the gray brown bird i know receiv'd us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird","subset":"none","task_type":"understanding","prediction":"and the singer so shy to the rest received me the gray brown bird i know received us comrades three and he sang the carol of death and a verse for him i love from deep secluded recesses from the fragrant cedars and the ghostly pines so still came the carol of the bird","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1114,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm2-none-sp0480-ch126292-sg0015-mc02-lav-clo-dg020.wav","answer":"to mister korbes the fox today soon after came up a millstone an egg a duck and a pin and chanticleer gave them all leave to get into the carriage and go with them when they arrived at mister korbes's house","subset":"none","task_type":"understanding","prediction":"to mr korbes the fox today soon after came up a millstone an egg a duck and a pin and chanticleer gave them all leave to get into the carriage and go with them when they arrived at mr korbes house","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1115,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm2-none-sp0480-ch127525-sg0029-mc02-lav-clo-dg150.wav","answer":"not having reached him where the ball passed not one of us precisely knew but i fancy it must have been over our heads and that the wind of it may have contributed to our disaster","subset":"none","task_type":"understanding","prediction":"not having reached it where the ball passed not one of us precisely knew but i fancy it must have been over our heads and that the wind of it may have contributed to our disaster","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1116,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-none-sp0492-ch131887-sg0009-mc01-stu-clo-dg100.wav","answer":"nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger","subset":"none","task_type":"understanding","prediction":"nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1117,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-none-sp0492-ch131887-sg0009-mc02-lav-clo-dg100.wav","answer":"nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger","subset":"none","task_type":"understanding","prediction":"nervously pacing up and down and unable to stand still for a moment this was fix one of the detectives who had been dispatched from england in search of the bank robber it was his task to narrowly watch every passenger","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1118,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-none-sp0492-ch131890-sg0031-mc01-stu-clo-dg140.wav","answer":"on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the roadstead and was soon once more on the indian ocean","subset":"none","task_type":"understanding","prediction":"on returning to the steamer i see that it is by no means useless to travel if a man wants to see something new at six p m the mongolia slowly moved out of the roghstead and was soon once more on the indian ocean","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1119,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0510\/Lab41-SRI-VOiCES-rm2-none-sp0510-ch130103-sg0047-mc01-stu-clo-dg180.wav","answer":"then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled","subset":"none","task_type":"understanding","prediction":"then as if the heads were moved by one muscle all the faces were turned toward him with wide derisive grins he seemed to hear some one make a humorous remark in a low tone at it the others all crowed and cackled","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1120,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0597\/Lab41-SRI-VOiCES-rm2-none-sp0597-ch133239-sg0006-mc02-lav-clo-dg060.wav","answer":"the interjection shows surprise as oh how pretty ah how wise the whole are called nine parts of speech which reading writing speaking teach to tell the age of horses","subset":"none","task_type":"understanding","prediction":"the interjection shows surprise as oh how pretty ah how wise the whole are called nine parts of speech which reading writing speaking teach to tell the age of horses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1121,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm2-none-sp0637-ch127579-sg0002-mc02-lav-clo-dg030.wav","answer":"for the purpose of collecting various species of rare sea weed some of which among these people are considered a great luxury after a whole day spent in this employment he would return about nightfall with several cocoanut shells filled with different descriptions of kelp","subset":"none","task_type":"understanding","prediction":"for the purpose of collecting various species of rare seaweed some of which among these people are considered a great luxury after a whole day spent in this employment he would return about nightfall with several cocoanut shells filled with different descriptions of kelp","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1122,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0770\/Lab41-SRI-VOiCES-rm2-none-sp0770-ch134592-sg0013-mc02-lav-clo-dg120.wav","answer":"there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcotes and aclands and many other newer names that she had forgotten","subset":"none","task_type":"understanding","prediction":"there had been a palmerston that had been a name down tiverton way tiverton was not a far journey as the crow flies but to martha it was almost a foreign country later there had been northcotes and aclands and many other newer names that she had forgotten","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1123,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0868\/Lab41-SRI-VOiCES-rm2-none-sp0868-ch131296-sg0005-mc02-lav-clo-dg170.wav","answer":"the seven kilns of enshiu are well known to all students of japanese pottery many of our textile fabrics bear the names of tea masters who conceived their color or design it is impossible indeed to find any department of art","subset":"none","task_type":"understanding","prediction":"the seven kilns of inshu are well known to all students of japanese pottery many of our textile fabrics bear the names of tea masters who conceived their color or design it is impossible indeed to find any department of art","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1124,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0882\/Lab41-SRI-VOiCES-rm2-none-sp0882-ch123266-sg0040-mc01-stu-clo-dg000.wav","answer":"we were kindly received and without taxing too much the goodness of these folks i would willingly have tarried here to recruit after my fatigues but my uncle who wanted no recruiting would not hear of it and the next morning we had to bestride our beasts again the soil told of the neighbourhood of the mountain","subset":"none","task_type":"understanding","prediction":"we were kindly received and without taxing too much the goodness of these folks i would willingly have tarried here to recruit after my fatigue but my uncle who wanted no recruiting would not hear of it and the next morning we had to bestride our beasts again the soil told of the neighbourhood of the mountain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1125,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp0882\/Lab41-SRI-VOiCES-rm2-none-sp0882-ch123268-sg0033-mc02-lav-clo-dg090.wav","answer":"this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour","subset":"none","task_type":"understanding","prediction":"this dense veil hung across the sun threw a deep shadow over the mountain if that huge revolving pillar sloped down it would involve us in its whirling eddies this phenomenon which is not unfrequent when the wind blows from the glaciers is called in icelandic mistour","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1126,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm2-none-sp1050-ch134121-sg0013-mc01-stu-clo-dg120.wav","answer":"but something was the matter she could not pull it up there was the dinner but she could not reach it all the family in turn went and tried all pulled together in vain the dinner could not be stirred","subset":"none","task_type":"understanding","prediction":"but something was the matter she could not pull it up there was the dinner but she could not reach it all the family in turn went and tried all pulled together in vain the dinner could not be stirred","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1127,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm2-none-sp1066-ch005330-sg0005-mc01-stu-clo-dg130.wav","answer":"should mamma see you it will kill her outright i can't live on as i am living he answered gloomily i have been working in london ever since in london interrupted barbara in london and have never stirred out of it","subset":"none","task_type":"understanding","prediction":"should mamma see you it will kill her outright i can live on as i am living he answered gloomily i have been working in london ever since in london interrupted barbara in london and have never stirred out of it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1128,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm2-none-sp1066-ch005330-sg0006-mc02-lav-clo-dg110.wav","answer":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty's ministers or that i was a gentleman at large living on my fortune","subset":"none","task_type":"understanding","prediction":"a stable yard she uttered in a deeply shocked tone richard did you expect it would be as a merchant or a banker or perhaps as secretary to one of her majesty s ministers or that i was a gentleman at large living on my fortune","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1129,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm2-none-sp1112-ch001043-sg0032-mc02-lav-clo-dg150.wav","answer":"she wore nothing but a stocking on her right foot and in spite of the unlocked door she escaped by the window and again i thought of gertrude's sprained ankle","subset":"none","task_type":"understanding","prediction":"she wore nothing but a stocking on her right foot and in spite of the unlocked door she escaped by the window and again i thought of gertrude sprained ankle","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1130,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1121\/Lab41-SRI-VOiCES-rm2-none-sp1121-ch135824-sg0002-mc02-lav-clo-dg160.wav","answer":"began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny's cousins more closely related to him than to any other members of the mouse family","subset":"none","task_type":"understanding","prediction":"began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny s cousins more closely related to him than to any other members of the mouse family","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1131,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1121\/Lab41-SRI-VOiCES-rm2-none-sp1121-ch135824-sg0019-mc02-lav-clo-dg080.wav","answer":"her eyes twinkled nimbleheels saw this and knew that she was only pretending to be severe before he could reply johnny chuck began to chuckle the chuckle became a laugh and presently johnny was laughing so hard he had to hold his sides","subset":"none","task_type":"understanding","prediction":"her eyes twinkled nimbleheels saw this and knew that she was only pretending to be severe before he could reply johnny chuck began to chuckle the chuckle became a laugh and presently johnny was laughing so hard he had to hold his sides","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1132,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm2-none-sp1160-ch134674-sg0015-mc01-stu-clo-dg000.wav","answer":"as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps","subset":"none","task_type":"understanding","prediction":"as a brother not as a rival and advised the empress with her son valentinian to fix their residence at milan in the fair and peaceful province of italy while he assumed the more arduous command of the countries beyond the alps","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1133,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_0032-1182\/sp1182\/Lab41-SRI-VOiCES-rm2-none-sp1182-ch134981-sg0026-mc02-lav-clo-dg100.wav","answer":"as she and curdken were driving their flock through the gate she said as she passed under oh falada tis you hang there and the head replied tis you pass under princess fair if your mother only knew her heart would surely break in two","subset":"none","task_type":"understanding","prediction":"as she and kirkkin were driving their flock through the gate she said as she passed under o falada tis you hang there and the hen replied tis you pass under princess fair if your mother only knew her heart would surely break in two","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1134,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1212\/Lab41-SRI-VOiCES-rm2-none-sp1212-ch014653-sg0003-mc02-lav-clo-dg160.wav","answer":"for for the sake of my reputation i suggested softly yes he looked doubtfully at me mistrusting the amiable deference of my manner that would be awfully good of you","subset":"none","task_type":"understanding","prediction":"for for the sake of my reputation i suggested softly yes he looked doubtfully at me mistrusting the amiable deference of my manner that would be awfully good of you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1135,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1212\/Lab41-SRI-VOiCES-rm2-none-sp1212-ch185485-sg0019-mc01-stu-clo-dg030.wav","answer":"a funny incident occurred to me in connection with this great pill in the year eighteen thirty six while i was travelling through the states of alabama mississippi and louisiana i became convinced by reading doctor brandreth's advertisements that i needed his pills","subset":"none","task_type":"understanding","prediction":"a funny incident occurred to me in connection with this great pill in the year eighteen thirty six while i was traveling through the states of alabama mississippi and louisiana i became convinced by reading dr brandreth s advertisements that i needed his pills","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1136,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1235\/Lab41-SRI-VOiCES-rm2-none-sp1235-ch135884-sg0002-mc01-stu-clo-dg000.wav","answer":"my desire of having children only induced me to purchase a slave by whom i had a son who was extremely promising my wife being jealous cherished a hatred for both mother and child","subset":"none","task_type":"understanding","prediction":"my desire of having children only induced me to purchase a slave by whom i had a son who was extremely promising my wife being jealous cherished a hatred for both mother and child","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1137,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm2-none-sp1246-ch124550-sg0011-mc02-lav-clo-dg090.wav","answer":"were the members of the tincomb methodist church a vast red brick tabernacle vida sherwin had given her a letter to an earnest woman with eye glasses plaid silk waist and a belief in bible classes who introduced her to the pastor and the","subset":"none","task_type":"understanding","prediction":"were the members of the tincomb methodist church a vast red brick tabernacle vinice sherman had given her a letter to an earnest woman with eyeglasses plaid silk waist and a belief in bible classes who introduced her to the pastor and the","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1138,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm2-none-sp1272-ch128104-sg0011-mc01-stu-clo-dg170.wav","answer":"in fact he is quite severe on mister ruskin for not recognising that a picture should denote the frailty of man and remarks with pleasing courtesy and felicitous grace that many phases of feeling","subset":"none","task_type":"understanding","prediction":"in fact he is quite severe on mr ruskin for not recognising that a picture should denote the frailty of man and remarks with pleasing courtesy and felicitous grace that many phases of feeling","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1139,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm2-none-sp1335-ch027593-sg0000-mc02-lav-clo-dg170.wav","answer":"sweetbreads with mushrooms lay half a dozen sweetbreads in cold water for twelve hours changing the water several times then boil them five minutes drop into cold water","subset":"none","task_type":"understanding","prediction":"sweetbreads with mushrooms lay half a dozen sweetbreads in cold water for twelve hours changing the water several times then boil them five minutes drop into cold water","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1140,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1335\/Lab41-SRI-VOiCES-rm2-none-sp1335-ch027593-sg0034-mc01-stu-clo-dg050.wav","answer":"mixed with a little good sauce espagnole fill the dish and on the top layer put truffles place in the oven a few minutes and serve with grated parmesan cheese on a separate dish","subset":"none","task_type":"understanding","prediction":"mixed with a little good sauce espagnole fill the dish and on the top layer put truffles place in the oven a few minutes and serve with grated parmesan cheese on a separate dish","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1141,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm2-none-sp1383-ch130532-sg0018-mc02-lav-clo-dg020.wav","answer":"i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions","subset":"none","task_type":"understanding","prediction":"i shall take a broader view of the subject i shall take it for granted here i shall therefore endeavor i shall touch upon one or two questions","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1142,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1383\/Lab41-SRI-VOiCES-rm2-none-sp1383-ch130532-sg0033-mc02-lav-clo-dg090.wav","answer":"i take it for granted i take leave to say i take one picture as an illustration i take pleasure in saying i take the liberty of observing","subset":"none","task_type":"understanding","prediction":"i take it for granted i take leave to say i take one picture as an illustration i take pleasure in saying i take the liberty of observing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1143,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-none-sp1392-ch135654-sg0002-mc02-lav-clo-dg050.wav","answer":"of the event more steady and secure this process of the thought or reasoning may seem trivial and obvious but to those who consider it more narrowly it may perhaps afford matter for curious speculation","subset":"none","task_type":"understanding","prediction":"of the event more steady and secure this process of the thought or reasoning may seem trivial and obvious but to those who consider it more narrowly it may perhaps afford matter for curious speculation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1144,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1425\/Lab41-SRI-VOiCES-rm2-none-sp1425-ch139290-sg0005-mc01-stu-clo-dg130.wav","answer":"my mother and i were separated when i was but an infant before i knew her as my mother it is a common custom in the part of maryland from which i ran away to part children from their mothers at a very early age frequently before the child has reached its twelfth month","subset":"none","task_type":"understanding","prediction":"my mother and i were separated when i was but an infant before i knew her as my mother it is a common custom in the part of maryland from which i ran away to part children from their mothers at a very early age frequently before the child has reached its twelfth month","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1145,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm2-none-sp1472-ch142848-sg0012-mc01-stu-clo-dg110.wav","answer":"there are about a dozen different kinds but the principal are bohea congou and souchong and signify respectively inferior middling and superior teas are often perfumed and flavoured with the leaves of different kinds of plants grown on purpose","subset":"none","task_type":"understanding","prediction":"there are about a dozen different kinds but the principal are bohea conju and suchong and signify respectively inferior middling and superior teas are often perfumed and flavoured with the leaves of different kinds of plants grown on purpose","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1146,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1536\/Lab41-SRI-VOiCES-rm2-none-sp1536-ch138488-sg0025-mc02-lav-clo-dg090.wav","answer":"two generations of public men have since laboured with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment","subset":"none","task_type":"understanding","prediction":"two generations of public men have since labored with imperfect success to repair the error which was then committed nor is it improbable that some of the penalties of that error may continue to afflict a remote posterity the bill by which the oath was settled passed the upper house without amendment","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1147,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1737\/Lab41-SRI-VOiCES-rm2-none-sp1737-ch142396-sg0021-mc02-lav-clo-dg020.wav","answer":"there was no handsome expression of regret on the discovery of the real culprit what harold had felt was not so much the imprisonment indeed he had very soon escaped by the window with assistance from his allies and had only gone back in time for his release as the olympian habit","subset":"none","task_type":"understanding","prediction":"there was no handsome expression of regret on the discovery of the real culprit what harold had felt was not so much the imprisonment indeed he had very soon escaped by the window with assistance from his allies and had only gone back in time for his release as the olympian habit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1148,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1841\/Lab41-SRI-VOiCES-rm2-none-sp1841-ch159771-sg0031-mc01-stu-clo-dg010.wav","answer":"well peter mink had surprised many a one swimming in the brook if it hadn't been for the meadow mice perhaps he wouldn't have visited the brook so often even in winter master meadow mouse just had to have his cold dip now and then","subset":"none","task_type":"understanding","prediction":"well peter meek had surprised many a one swimming in the brook if it hadn't been for the meadow mice perhaps he wouldn't have visited the brook so often even in winter master meadow mouse just had to have his cold dip now and then","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1149,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1841\/Lab41-SRI-VOiCES-rm2-none-sp1841-ch159771-sg0042-mc02-lav-clo-dg000.wav","answer":"and the day came at last when it was well worth his while to take the little extra trouble of peeping out before he had his swim for master meadow mouse caught a glimpse of a snakelike head that darted out from under the bank of the brook and darted back again out of sight","subset":"none","task_type":"understanding","prediction":"and the day came at last when it was well worth his while to take the little extra trouble of peeping out before he had his swim for master mettamouse caught a glimpse of a snake like head that darted out from under the bank of the brook and darted back again out of sight","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1150,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm2-none-sp1867-ch154075-sg0018-mc02-lav-clo-dg130.wav","answer":"as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance","subset":"none","task_type":"understanding","prediction":"as if she were preparing herself for the explosion you don't have to put up your hands said ronicky doone wondering at the familiarity of the face of the man of the sneer he had brooded on it so often in the past few days that it was like the face of an old acquaintance","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1151,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm2-none-sp1874-ch165702-sg0020-mc01-stu-clo-dg150.wav","answer":"april fourteenth assassinated in ford's theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett","subset":"none","task_type":"understanding","prediction":"april fourteenth assassinated at ford s theater washington by a mad actor wilkes booth april nineteenth body lay in state at washington april twenty sixth booth slain in resisting arrest by sergeant boston corbett","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1152,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1926\/Lab41-SRI-VOiCES-rm2-none-sp1926-ch143879-sg0015-mc01-stu-clo-dg010.wav","answer":"missus ludlow sacrificed as i say to paris yet had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations","subset":"none","task_type":"understanding","prediction":"mrs ludlow sacrificed as i say to paris it had doubts and wonderments not allayed at that altar and after her husband had joined her found further chagrin in his failure to throw himself into these speculations","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1153,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm2-none-sp1961-ch145733-sg0016-mc01-stu-clo-dg130.wav","answer":"what does he say asked the princess i really hardly like to tell you answered the lady in waiting oh then you can whisper it to me he is disobliging said the princess and went away","subset":"none","task_type":"understanding","prediction":"what does he say asked the princess i really hardly like to tell you answered the lady in waiting oh then you can whisper it to me ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta ta","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":229}
+{"index":1154,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm2-none-sp1970-ch010594-sg0003-mc01-stu-clo-dg120.wav","answer":"under her great determination to keep gwendolen in her own care but with jupp to watch the dock and a man in plain clothes at the door of the small hotel she was at present bound for i thought i might remain in yonkers contentedly the whole day","subset":"none","task_type":"understanding","prediction":"under her great determination to keep gwendolen in her own care but with jupp to watch the dock and a man in plain clothes at the door of the small hotel she was at present bound for i thought i might remain in yonkers contentedly the whole day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1155,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp1970\/Lab41-SRI-VOiCES-rm2-none-sp1970-ch010594-sg0039-mc01-stu-clo-dg140.wav","answer":"till yesterday yesterday her great eyes haggard with suffering rose to mine then they fell on the bead which i had taken from my pocket the cry she gave was not loud but it effectually settled all my doubts","subset":"none","task_type":"understanding","prediction":"till yesterday yesterday her great eyes haggard with suffering rose to mine then they fell on the bead which i had taken from my pocket the cry she gave was not loud but it effectually settled all my doubts","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1156,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm2-none-sp2012-ch139355-sg0023-mc02-lav-clo-dg030.wav","answer":"another phenomenon on which the savants are not agreed perhaps said fragoso they might ask the opinions of the caymans dolphins and manatees for they certainly prefer the black waters to the others to enjoy themselves in","subset":"none","task_type":"understanding","prediction":"another phenomenon on which the savants are not agreed perhaps said fragoso they might ask the opinions of the caymans dolphins and manatees for they certainly prefer the black waters to the others to enjoy themselves in","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1157,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm2-none-sp2012-ch139358-sg0006-mc02-lav-clo-dg030.wav","answer":"nothing can be truer but while you have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency","subset":"none","task_type":"understanding","prediction":"nothing can be truer but while you have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1158,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm2-none-sp2012-ch139358-sg0032-mc01-stu-clo-dg100.wav","answer":"either by swimming through the waters propelled by their tails or running along the bank with a speed no man can equal it is on these huge beaches that the caymans are born live and die not without affording extraordinary examples of longevity","subset":"none","task_type":"understanding","prediction":"either by swimming through the waters propelled by their tails or running along the bank with a speed no man can equal it is on these huge beaches that the caymans are born live and die not without affording extraordinary examples of longevity","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1159,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2060\/Lab41-SRI-VOiCES-rm2-none-sp2060-ch150855-sg0011-mc01-stu-clo-dg130.wav","answer":"there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was varden who to rickie's bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy","subset":"none","task_type":"understanding","prediction":"there was lloyd he would not learn the school anthem saying that it hurt his throat and above all there was vardit who to rickie s bewilderment was now a member of dunwood house he had to go somewhere said agnes lucky for his mother that we had a vacancy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1160,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2093\/Lab41-SRI-VOiCES-rm2-none-sp2093-ch143262-sg0010-mc01-stu-clo-dg110.wav","answer":"but he is saving us i said taking us to our friends jimmy no know jimmy tink doctor somewhere right long big hill gib black white fellow topper topper make um tink more","subset":"none","task_type":"understanding","prediction":"but he is saving us i said taking us to our friends jimmy not know jimmy take doctor somewhere right long big hill give black white fellow topper topper make him think more","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1161,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm2-none-sp2110-ch161100-sg0026-mc02-lav-clo-dg180.wav","answer":"it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing","subset":"none","task_type":"understanding","prediction":"it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1162,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm2-none-sp2110-ch161101-sg0036-mc02-lav-clo-dg050.wav","answer":"you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it","subset":"none","task_type":"understanding","prediction":"you can imagine that it was all the more unendurable because i did not dare to say to him much too quick moreover it is much easier to play rapidly than slowly you can drop a few notes in passages without any one noticing it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1163,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2149\/Lab41-SRI-VOiCES-rm2-none-sp2149-ch007239-sg0001-mc02-lav-clo-dg180.wav","answer":"paul an apostle of jesus christ by the will of god according to the promise of life which is in christ jesus","subset":"none","task_type":"understanding","prediction":"Paul, an apostle of Jesus Christ by the will of God. According to the promise of life, which is in Christ Jesus.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1164,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2149\/Lab41-SRI-VOiCES-rm2-none-sp2149-ch008912-sg0009-mc01-stu-clo-dg120.wav","answer":"they had heard of his arrival but had not seen him enter and imagining him still in the court discussed freely the possible reason of his calling they marvelled at his temerity for though most of the tongues which had been let loose attributed the chief blame worthiness to fitzpiers","subset":"none","task_type":"understanding","prediction":"they had heard of his arrival but had not seen him enter and imagining him still in the court discussed freely the possible reason of his calling they marvelled at his temerity for though most of the tongues which had been let loose attributed the chief blameworthiness to fitzpiers","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1165,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm2-none-sp2156-ch025563-sg0005-mc01-stu-clo-dg020.wav","answer":"that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan's name missus phelan's son came a running he had been on his way","subset":"none","task_type":"understanding","prediction":"that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan s name mrs phelan s son came a running he had been on his way","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1166,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm2-none-sp2156-ch025563-sg0005-mc02-lav-clo-dg020.wav","answer":"that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan's name missus phelan's son came a running he had been on his way","subset":"none","task_type":"understanding","prediction":"that she had been the dupe of an unscrupulous criminal instead of which he ground his teeth went to the little panel door and shouted phelan s name mrs phelan s son came a running he had been on his way","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1167,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2156\/Lab41-SRI-VOiCES-rm2-none-sp2156-ch025563-sg0014-mc01-stu-clo-dg180.wav","answer":"there is not nor play neither snapped phelan i've got to go out and chase up a drunk or throw a faint or git run over or somethin desperate to square mesilf with the captain i'm an hour overdue at the station","subset":"none","task_type":"understanding","prediction":"there is not nor a play neither snapped phelan i ve got to go out and chase up a drunk or throw a faint or get run over or something desperate to square myself with the captain i m an hour overdue at the station","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1168,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2269\/Lab41-SRI-VOiCES-rm2-none-sp2269-ch165387-sg0033-mc02-lav-clo-dg040.wav","answer":"he will pleasure you with one of his best dances before you go accordingly after thanking the bramin for the account he had given us we all promised to leave mister bruin to his own meditation upon which","subset":"none","task_type":"understanding","prediction":"he will pleasure you with one of his best dances before you go accordingly after thanking the brahmin for the account he had given us we all promised to leave mr bruin to his own meditation upon which","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1169,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-none-sp2412-ch153947-sg0006-mc02-lav-clo-dg140.wav","answer":"but this had an effect of which i have little reason to complain for i was allowed almost to call them life long self deceivers to their faces and they said it was quite true but that it did not matter","subset":"none","task_type":"understanding","prediction":"but this had an effect of which i have little reason to complain for i was allowed almost to call them lifelong self deceivers to their faces and they said it was quite true but that it did not matter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1170,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2573\/Lab41-SRI-VOiCES-rm2-none-sp2573-ch178450-sg0031-mc02-lav-clo-dg110.wav","answer":"better do it roscoe assented sullenly when'd you begin this thing i always did drink a little ever since i grew up that is leave that talk out you know what i mean well i don't know as i ever had too much in office hours until the other day","subset":"none","task_type":"understanding","prediction":"better do it rascal was saying sullenly when do you begin this thing i always did drink a little ever since i grew up that is leave that talk out you know what i mean well i don't know as i ever had too much in office hours until the other day","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1171,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2673\/Lab41-SRI-VOiCES-rm2-none-sp2673-ch156474-sg0019-mc02-lav-clo-dg150.wav","answer":"where the union ships congress and cumberland lay at anchor these saw the uncouth monster coming and prepared for action the minnesota the saint lawrence and the roanoke lying at fortress monroe also saw her","subset":"none","task_type":"understanding","prediction":"where the union ships congress and cumberland lay at anchor these saw the uncouth monster coming and prepared for action the minnesota the st lawrence and the roanoke lying at port royce monroe also saw her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1172,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm2-none-sp2758-ch086588-sg0024-mc01-stu-clo-dg060.wav","answer":"and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all","subset":"none","task_type":"understanding","prediction":"and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1173,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm2-none-sp2758-ch086588-sg0024-mc02-lav-clo-dg060.wav","answer":"and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all","subset":"none","task_type":"understanding","prediction":"and who take no real interest in anything except spending money and gossiping are to be really pitied is true some of them once had minds and these are the most pitiful or pitiable of all","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1174,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036616-sg0001-mc01-stu-clo-dg100.wav","answer":"this mystery puzzled me finding it impossible to form any views i drifted from one extreme to the other something was out there that much was certain and any doubting thomas was invited to place his finger on the scotia's wound when i arrived in new york","subset":"none","task_type":"understanding","prediction":"this mystery puzzled me finding it impossible to form any views i drifted from one extreme to the other something was out there that much was certain and any doubting thomas was invited to place his finger on the scotia's wound when i arrived in new york","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1175,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036616-sg0038-mc01-stu-clo-dg110.wav","answer":"not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day's delay would have been unforgivable","subset":"none","task_type":"understanding","prediction":"not even a twenty four hour breather was granted to commander farragut his provisions were loaded on board his coal bunkers were overflowing not a crewman was missing from his post to cast off he needed only to fire and stoke his furnaces half a day s delay would have been unforgivable","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1176,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036617-sg0016-mc01-stu-clo-dg130.wav","answer":"don't bother counting just squeeze it all in and hurry what about master's collections conseil ventured to observe we'll deal with them later what the archaeotherium hyracotherium oreodonts cheiropotamus and master's other fossil skeletons","subset":"none","task_type":"understanding","prediction":"dont bother counting just squeeze it all in and hurry what about masters collections called say venture to observe we ll deal with them later what the archaeotherium hyracotherium oreodonts carpopotamus and masters other fossil skeletons","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":11}
+{"index":1177,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2764\/Lab41-SRI-VOiCES-rm2-none-sp2764-ch036617-sg0038-mc01-stu-clo-dg110.wav","answer":"it hugged this sand covered strip of land where thousands of spectators acclaimed us one more time the escort of boats and tenders still followed the frigate and only left us when we came abreast of the lightship whose two signal lights mark the entrance of the narrows to upper new york bay","subset":"none","task_type":"understanding","prediction":"it hugged this sand covered strip of land where thousands of spectators acclaimed us one more time the escort of boats and tenders still followed the frigate and only left us when we came abreast of the lightship whose two signal lights mark the entrance of the narrows to upper new york bay","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1178,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm2-none-sp2803-ch154320-sg0014-mc01-stu-clo-dg060.wav","answer":"but as to getting alongside the duncan god forbid","subset":"none","task_type":"understanding","prediction":"but as to getting alongside the duncan god forbid","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1179,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm2-none-sp3368-ch170951-sg0047-mc02-lav-clo-dg010.wav","answer":"he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a chorus neither shall we allow teachers to make use of them in the instruction of the young meaning","subset":"none","task_type":"understanding","prediction":"he it is who has slain my son these are the kind of sentiments about the gods which will arouse our anger and he who utters them shall be refused a course neither shall we allow teachers to make use of them in the instruction of the young meaning","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1180,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-none-sp3446-ch144019-sg0042-mc01-stu-clo-dg140.wav","answer":"so these two fella they go eat m when they finish eat m my word they fright like hell and they go hide along scrub and god he come walk about along garden and he sing out adam adam he no speak","subset":"none","task_type":"understanding","prediction":"so these two fella they go eat em when they finish eat em my word they fright like hell and they go hide along scrub and god he come walk about along garden and he sing out adam adam he no speak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1181,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-none-sp3446-ch144021-sg0006-mc01-stu-clo-dg020.wav","answer":"but neither of us was seriously maimed the voyage was our idea of a good time i built the snark and paid for it and for all expenses i contracted to write thirty five thousand words descriptive of the trip for a magazine which was to pay me the same rate i received for stories written at home","subset":"none","task_type":"understanding","prediction":"but neither of us was seriously maimed the voyage was our idea of a good time i built the snark and paid for it and for all expenses i contracted to write thirty five thousand words descriptive of the trip for a magazine which was to pay me the same rate i received for stories written at home","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1182,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-none-sp3446-ch144021-sg0018-mc01-stu-clo-dg090.wav","answer":"mate down with fever ngora ngora sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset","subset":"none","task_type":"understanding","prediction":"mate down with fever negoro negoro sunday march fifteenth nineteen o eight at daybreak found that the boy bagua had died during the night on dysentery he was about fourteen days sick at sunset","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1183,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp3521\/Lab41-SRI-VOiCES-rm2-none-sp3521-ch012715-sg0017-mc01-stu-clo-dg090.wav","answer":"rice bread boil a pint of rice till soft then mix it with a couple of quarts of rice or wheat flour when cool add half a tea cup of yeast a little salt and milk to render it of the consistency of rye bread when light bake it in small buttered pans","subset":"none","task_type":"understanding","prediction":"rice bread boil a pint of rice till soft then mix it with a couple of quarts of rice or wheat flour when cool add half a tea cup of yeast a little salt and milk to render it of the consistency of rye bread when light bake it in small buttered pans","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1184,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_1212-3521\/sp3521\/Lab41-SRI-VOiCES-rm2-none-sp3521-ch012715-sg0020-mc02-lav-clo-dg030.wav","answer":"boil a small handful of hops in a couple of quarts of water when the strength is obtained from them strain the liquor put it back on the fire take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour stir it into the liquor when it boils","subset":"none","task_type":"understanding","prediction":"Boil a small handful of hops in a couple of quarts of water. When the strength is obtained from them, strain the liquor, put it back on the fire. Take a little of the liquor and mix smoothly with three heaping table spoonsful of wheat flour. Stir it into the liquor, when it boils.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1185,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm2-none-sp3549-ch171171-sg0023-mc01-stu-clo-dg070.wav","answer":"and as great a quantity of provisions as would suffice them for a long time and let himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old","subset":"none","task_type":"understanding","prediction":"and as great a quantity of provisions as would suffice them for a long time and let himself and all them down into a certain subterraneous cavern that was not visible above ground now so far as had been digged of old","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1186,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm2-none-sp3835-ch178029-sg0001-mc01-stu-clo-dg100.wav","answer":"caused russians to grieve he had such a sad face when shown into the emperor's study that the latter at once asked have you brought me sad news colonel very sad sire replied michaud lowering his eyes with a sigh the abandonment of moscow","subset":"none","task_type":"understanding","prediction":"caused russians to grieve he had such a sad face when shown into the emperor s study that the latter at once asked have you brought me sad news colonel very sad sire replied mashuk covering his eyes with a sigh the abandonment of moscow","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1187,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm2-none-sp3835-ch178029-sg0008-mc02-lav-clo-dg060.wav","answer":"which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire","subset":"none","task_type":"understanding","prediction":"which required a direct answer sire will you allow me to speak frankly as befits a loyal soldier he asked to gain time colonel i always require it replied the emperor conceal nothing from me i wish to know absolutely how things are sire","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1188,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3835\/Lab41-SRI-VOiCES-rm2-none-sp3835-ch178029-sg0017-mc02-lav-clo-dg080.wav","answer":"the emperor suddenly turned away as if to hide from michaud the tears that rose to his eyes and went to the further end of his study having stood there a few moments he strode back to michaud and pressed his arm below the elbow with a vigorous movement the emperor's mild and handsome face","subset":"none","task_type":"understanding","prediction":"the emperor suddenly turned away as if to hide from mishu the tears that rose to his eyes and went to the further end of his study having stood there a few moments he strode back to mishu and pressed his arm below the elbow with a vigorous movement the emperor s mild and handsome face","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1189,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm2-none-sp3923-ch181420-sg0015-mc02-lav-clo-dg030.wav","answer":"thither came charles kingsley canon of chester who married a grenfell and who coupled his verse with scientific study and made geological excursions to the river's mouth with the then master of mostyn house school in these excursions the youthful wilfred was a participant","subset":"none","task_type":"understanding","prediction":"thither came charles kingsley canon of chester who married a grenfell and who coupled his verse with scientific study and made geological excursions to the river s mouth with the then master of mostyn house school in these excursions the youthful wilfred was a participant","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1190,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3972\/Lab41-SRI-VOiCES-rm2-none-sp3972-ch185074-sg0031-mc01-stu-clo-dg060.wav","answer":"thomas was anxious to go with me but as i have before observed the chiefs would not suffer him to leave them on the account of his courage and skill in war expecting that they should need his assistance he was a great counsellor and a chief when quite young","subset":"none","task_type":"understanding","prediction":"thomas was anxious to go with me but as i have before observed the chiefs would not suffer him to leave them on the account of his courage and skill in war expecting that they should need his assistance he was a great counsellor and a chief when quite young","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1191,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3989\/Lab41-SRI-VOiCES-rm2-none-sp3989-ch182389-sg0002-mc02-lav-clo-dg010.wav","answer":"shouted happy jack i i don't want to stammered peter you mean you can't jeered happy jack peter pretended not to hear and a few minutes later he hopped away towards the dear old briar patch lipperty lipperty lip","subset":"none","task_type":"understanding","prediction":"shouted happy jack i i don t want to stammered peter you mean you can t jeered happy jack peter pretended not to hear and a few minutes later he hopped away towards the dear old briar patch lipperty lipperty lip","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1192,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3989\/Lab41-SRI-VOiCES-rm2-none-sp3989-ch182394-sg0024-mc01-stu-clo-dg150.wav","answer":"and they began to look down on those who still lived in the water and to put on airs and hold their heads very high now of course old mother nature didn't like this and to punish them she said that they should no longer be able to live in the water even if they wanted to","subset":"none","task_type":"understanding","prediction":"and they began to look down on those who still lived in the water and to put on airs and hold their heads very high now of course old mother nature didn t like this and to punish them she said that they should no longer be able to live in the water even if they wanted to","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1193,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp3994\/Lab41-SRI-VOiCES-rm2-none-sp3994-ch156757-sg0000-mc01-stu-clo-dg010.wav","answer":"chapter twenty nine great smallpox epidemic saint mary's hall thanksgiving day in california another brother in law missus brunner has become too childish to have the responsibility of young girls","subset":"none","task_type":"understanding","prediction":"chapter twenty nine great smallpox epidemic st marys hall thanksgiving day in california another brother in law mrs brunner has become too childish to have the responsibility of young girls","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1194,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4010\/Lab41-SRI-VOiCES-rm2-none-sp4010-ch010801-sg0016-mc01-stu-clo-dg000.wav","answer":"is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne","subset":"none","task_type":"understanding","prediction":"is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1195,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4014\/Lab41-SRI-VOiCES-rm2-none-sp4014-ch186179-sg0001-mc01-stu-clo-dg090.wav","answer":"it was that same day that the three boys from brighton were for the first time assigned to a regular unit of the signal corps also with a real thrill they learned that they were almost immediately to see war service for american troops were already in the trenches","subset":"none","task_type":"understanding","prediction":"it was that same day that the three boys from brighton were for the first time assigned to a regular unit of the signal corps also with a real thrill they learned that they were almost immediately to see war service for american troops were already in the trenches","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1196,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4116\/Lab41-SRI-VOiCES-rm2-none-sp4116-ch013256-sg0047-mc01-stu-clo-dg050.wav","answer":"it is your home with me as long as you choose to remain but in this matter i must act as i fully believe jesus would in my place i am willing to bear all that society may say or do society is not my god by the side of this poor soul","subset":"none","task_type":"understanding","prediction":"it is your home with me as long as you choose to remain but in this matter i must act as i fully believe jesus would in my place i am willing to bear all that society may say or do society is not my god by the side of this poor soul","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1197,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4160\/Lab41-SRI-VOiCES-rm2-none-sp4160-ch014187-sg0021-mc02-lav-clo-dg120.wav","answer":"quite replied thorndyke i have entertained it from the first and the new facts that you have gathered increase its probability you remember i said that four hypotheses were possible that the robbery was committed either by reuben by walter by john hornby or by some other person","subset":"none","task_type":"understanding","prediction":"quite replied thorndyke i have entertained it from the first and the new facts that you have gathered increase its probability you remember i said that four hypotheses were possible that the robbery was committed either by reuben by walter by john hornby or by some other person","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1198,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-none-sp4427-ch012471-sg0015-mc02-lav-clo-dg070.wav","answer":"though it come not immediately if it be present with them before they suffer any great misfortune that they ought to reason thus that god delays to assist them not because he has no regard to them but because he will first try their fortitude and the pleasure they take in their freedom","subset":"none","task_type":"understanding","prediction":"though it come not immediately if it be present with them before they suffer any great misfortune that they ought to reason thus that god delays to assist them not because he has no regard to them but because he will first try their fortitude and the pleasure they take in their freedom","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1199,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-none-sp4427-ch020028-sg0002-mc02-lav-clo-dg180.wav","answer":"no indeed we ran shivering through the long windy entries all wrapped in shawls and hugging ourselves to retain the friendly warmth of the fire as long as possible far from devising ways of letting in the air we tried hard to keep it out","subset":"none","task_type":"understanding","prediction":"no indeed we ran shivering through the long windy entries all wrapped in shawls and hugging ourselves to retain the friendly warmth of the fire as long as possible far from devising ways of letting in the air we tried hard to keep it out","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1200,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-none-sp4427-ch041933-sg0011-mc01-stu-clo-dg060.wav","answer":"in a moment kostiei's words rushed into the king's mind and he began to weep bitterly to the surprise of everybody who had expected him nearly to die of joy at the sight of his son but try as he would and work as hard as he might","subset":"none","task_type":"understanding","prediction":"in a moment codzi's words rushed into the king s mind and he began to weep bitterly to the surprise of everybody who had expected him nearly to die of joy at the sight of his son but try as he would and work as hard as he might","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1201,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm2-none-sp4438-ch048513-sg0013-mc02-lav-clo-dg170.wav","answer":"when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her","subset":"none","task_type":"understanding","prediction":"when he told her he was going to stay the night was so grateful so really thankful that her eyes red from the waves of grief that had engulfed her at intervals during the afternoon ever since that is the sight of her dead father lying so remote from her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1202,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm2-none-sp4438-ch052195-sg0025-mc02-lav-clo-dg140.wav","answer":"because of the years i put in on the sea if i'd put in the same years cow punching with my body young and pliable i wouldn't be rolling now but i'd be bow legged and so with that girl you noticed that her eyes were what i might call hard she has never been sheltered","subset":"none","task_type":"understanding","prediction":"because of the years i put in on the sea if i put in the same years cow punching with my body young and pliable i wouldnt be rolling now but id be bowlegged and so with that girl you noticed that her eyes were what i might call hard she has never been sheltered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":1203,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm2-none-sp4441-ch076250-sg0035-mc02-lav-clo-dg110.wav","answer":"yes and another thing try to meet my brother find out all you can about his circumstances and friends make up to him worm yourself into his confidence the latter's an easy job become his friend tell him that i've cheated him","subset":"none","task_type":"understanding","prediction":"yes and another thing try to meet my brother find out all you can about his circumstances and friends make up to him worm yourself into his confidence the latter is an easy job become his friend tell him that i have cheated him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1204,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-none-sp4535-ch279852-sg0008-mc01-stu-clo-dg120.wav","answer":"i'll let a bullet go smack into the first man that makes a move he shouldn't here was a man they couldn't talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later","subset":"none","task_type":"understanding","prediction":"i ll let a bullet go smack into the first man that makes a move he shouldn t here was a man they couldn t talk down he was probably a good shot and ready to keep his threat if only they could get him at a disadvantage and pull their revolvers before he could fire but such hopes were shattered a few minutes later","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1205,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4586\/Lab41-SRI-VOiCES-rm2-none-sp4586-ch061758-sg0003-mc02-lav-clo-dg100.wav","answer":"as rapidly as if the injured limb no longer impeded him the hunter suspected his intent standing over six feet he saw the bloody knife blade lying along the cloak it was for that the mustanger was making","subset":"none","task_type":"understanding","prediction":"as rapidly as if the injured limb no longer impeded him the hunter suspected his intent standing over six feet he saw the bloody knife blade lying along the cloak it was for that the mustanger was making","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1206,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4590\/Lab41-SRI-VOiCES-rm2-none-sp4590-ch018005-sg0048-mc02-lav-clo-dg110.wav","answer":"who nightly broke into our tents and took our fellow workers from our side in presenting you with this bowl we all add our prayers for your long life happiness and prosperity we shall ever remain sir your grateful servants","subset":"none","task_type":"understanding","prediction":"who nightly broke into our tents and took our fellow workers from our side in presenting you with this bowl we all add our prayers for your long life happiness and prosperity we shall ever remain sir your grateful servants","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1207,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm2-none-sp4839-ch015307-sg0030-mc01-stu-clo-dg010.wav","answer":"it needs not so much thought my lord send word to the emperor that we are all ready i am even now a weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of ymbercourt","subset":"none","task_type":"understanding","prediction":"it needs not so much thought my lord send word to the emperor that we are all ready i am even now weary of the fields for the nights are cold and then the good wines are beginning to fail us whereat every one burst out a laughing all agreed to what was said by the lord of umbacor","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1208,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm2-none-sp4848-ch028247-sg0043-mc01-stu-clo-dg150.wav","answer":"vil villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion","subset":"none","task_type":"understanding","prediction":"ville villa he cried out in his excitement dropping the marble which was broken into atoms by the fall what else could this fragment be but the sole surviving remnant of some sumptuous mansion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1209,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm2-none-sp4848-ch029108-sg0009-mc02-lav-clo-dg030.wav","answer":"bigger child why what's two hundred thousand dollars pocket money mere pocket money look at the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along behind it","subset":"none","task_type":"understanding","prediction":"bigger child why wants two hundred thousand dollars pocket money where pocket money look the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along behind it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1210,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4957\/Lab41-SRI-VOiCES-rm2-none-sp4957-ch030119-sg0028-mc02-lav-clo-dg130.wav","answer":"so it would be no wonder if he lost all sense of direction even had not the remarks of the girl at his side completely absorbed him beth drove slowly down the main street up a lane back by the lake road and along the street again and this programme was repeated several times","subset":"none","task_type":"understanding","prediction":"so it would be no wonder if he lost all sense of direction even had not the remarks of the girl at his side completely absorbed him bat drove slowly down the main street up a lane back by the lake road and along the street again and this programme was repeated several times","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1211,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp4967\/Lab41-SRI-VOiCES-rm2-none-sp4967-ch026553-sg0010-mc01-stu-clo-dg060.wav","answer":"o little white hen may i go with you asked the river the little white hen told the river that he might go with her and asked him to ride in the little brown basket so the river climbed into the little brown basket","subset":"none","task_type":"understanding","prediction":"oh little white hen may i go with you asked the river the little white hen told the river that he might go with her and asked him to ride in the little brown basket so the river climbed into the little brown basket","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1212,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5126\/Lab41-SRI-VOiCES-rm2-none-sp5126-ch027504-sg0008-mc01-stu-clo-dg140.wav","answer":"and falls backards and breaks his neck if he ain't watched whose business was it to have learned me better that i can't rightly say but it seemed it was the business of the government people to gaol me and iron me and flog me was that justice","subset":"none","task_type":"understanding","prediction":"and falls backward and breaks his neck if he aint watched whose business was it to have learned me better that i can t rightly say but it seemed it was the business of the government people to gallow me and iron me and flog me was that justice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1213,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5126\/Lab41-SRI-VOiCES-rm2-none-sp5126-ch027504-sg0031-mc02-lav-clo-dg060.wav","answer":"there's no saying what mister knightley might do if his wife had been here thank god she's away at bathurst said starlight i hate seeing women put out besides everybody bows down to missus knightley she's as good as she's handsome i believe and","subset":"none","task_type":"understanding","prediction":"there is no saying what mr knightley might do if his wife had been here thank god she is away at battersea said starlight i hate seeing women put out besides everybody bows down to mrs knightley she is as good as she is handsome i believe and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1214,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5157\/Lab41-SRI-VOiCES-rm2-none-sp5157-ch047237-sg0019-mc01-stu-clo-dg000.wav","answer":"persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from day break","subset":"none","task_type":"understanding","prediction":"persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from daybreak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1215,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5157\/Lab41-SRI-VOiCES-rm2-none-sp5157-ch047237-sg0019-mc02-lav-clo-dg000.wav","answer":"persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from day break","subset":"none","task_type":"understanding","prediction":"persano monday night january sixteenth seventeen ninety two for your long and interesting letter i can only write a line to tell you i am well we have been out till an hour in the night from daybreak","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1216,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm2-none-sp5189-ch037999-sg0002-mc01-stu-clo-dg130.wav","answer":"this is of course mainly a parent's problem and is best solved by resorting to the following formula let a and b represent two young girls finishing schools in the east missus raleigh jones x from the west sends her daughter to a","subset":"none","task_type":"understanding","prediction":"this is of course mainly a parent s problem and is best solved by resorting to the following formula let a and b represent two young girls finishing schools in the east mrs raleigh jones x from the west sends her daughter to a","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1217,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5319\/Lab41-SRI-VOiCES-rm2-none-sp5319-ch042637-sg0003-mc02-lav-clo-dg120.wav","answer":"it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position","subset":"none","task_type":"understanding","prediction":"it will be seen that there has never been the slightest ground for such an apprehension no colored man in that state ever occupied a judicial position above that of justice of the peace and very few aspired to that position","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1218,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5319\/Lab41-SRI-VOiCES-rm2-none-sp5319-ch084357-sg0034-mc02-lav-clo-dg020.wav","answer":"the circumstantial evidence against the allegation that prince charles had left a legitimate child is so strong that no amount of romance of history could upset it in his latter days when separated from his wife the princess louisa","subset":"none","task_type":"understanding","prediction":"the circumstantial evidence against the allegation that prince charles had left a legitimate child is so strong that no amount of romance of history could upset it in his latter days when separated from his wife the princess louisa","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1219,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5338\/Lab41-SRI-VOiCES-rm2-none-sp5338-ch024640-sg0005-mc02-lav-clo-dg170.wav","answer":"he certainly possesses talents beyond the rude sphere in which he moves and being neither destitute of ambition nor encumbered with scruples he will probably attempt by every means to distinguish himself during the period of these unhappy commotions","subset":"none","task_type":"understanding","prediction":"He certainly possesses talents beyond the rude sphere in which he moves and being neither destitute of ambition nor encumbered with scruples. He will probably attempt, by every means. To distinguish himself during the period of these unhappy commotions.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1220,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5400\/Lab41-SRI-VOiCES-rm2-none-sp5400-ch034479-sg0015-mc01-stu-clo-dg000.wav","answer":"tit made room and levin started behind him the grass was short close to the road and levin who had not done any mowing for a long while and was disconcerted by the eyes fastened upon him cut badly for the first moments though he swung his scythe vigorously behind him he heard voices","subset":"none","task_type":"understanding","prediction":"tit made room and levine started behind him the grass was short close to the road and levine who had not done any mowing for a long while and was disconcerted by the eyes fastened upon him cut badly for the first moments though he swung his scythe vigorously behind he heard voices","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1221,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5401\/Lab41-SRI-VOiCES-rm2-none-sp5401-ch102526-sg0028-mc01-stu-clo-dg090.wav","answer":"at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter","subset":"none","task_type":"understanding","prediction":"at last a man of ability worked himself up to the surface this was alexius comnenus nephew of the emperor isaac comnenus whose short reign we related in the opening paragraph of this chapter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1222,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5456\/Lab41-SRI-VOiCES-rm2-none-sp5456-ch062014-sg0008-mc02-lav-clo-dg050.wav","answer":"so de nex night de gal went off an comed back late wid de young man her mammy ax him in an gin him a seat by de fire an dar he sot all wrop up in his blinkit wid his haid turnt way f'um de light","subset":"none","task_type":"understanding","prediction":"so the next night the gal went off and come back late with the young man her mammy ax him in and give him a seat by the fire and down he sat all wrapped up in his blanket with his head turned away from the light","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":21}
+{"index":1223,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5583\/Lab41-SRI-VOiCES-rm2-none-sp5583-ch041259-sg0043-mc01-stu-clo-dg180.wav","answer":"and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain","subset":"none","task_type":"understanding","prediction":"and philander acted all the rest to say the truth this tragedy was not only the best but the only play that we ever performed and after having acted it all over england and wales we came to scotland to exhibit it over the remainder of great britain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1224,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5635\/Lab41-SRI-VOiCES-rm2-none-sp5635-ch058137-sg0014-mc02-lav-clo-dg060.wav","answer":"with a party of friends mister jimmy hurrying out with a slate in his hand begged me to stop a moment and thus addressed me well mister carlton this algebra is a most powerful thing ain't it indeed it is mister jimmy have you been looking into it","subset":"none","task_type":"understanding","prediction":"with a party of friends mr jimmy hurrying up with a slate in his hand begged me to stop a moment and thus addressed me well mr carlton this algebra is a most powerful thing ain t it indeed it is mr jimmy have you been looking into it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1225,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043301-sg0015-mc01-stu-clo-dg000.wav","answer":"had been composed with both skill and ardour they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ's words themselves were quoted","subset":"none","task_type":"understanding","prediction":"had been composed with both skill and ardor they had a religious ring the unintelligent christian could sing them without a qualm yet their sense was plain enough the old human creed that man was all even christ s words themselves were quoted","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1226,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043301-sg0026-mc01-stu-clo-dg160.wav","answer":"and a storm of laughter rippled round the throng of heads she heard an indrawn hiss behind her chair and the next instant an exclamation from mabel what was that there was a sharp crack and the tiny gesticulating figure staggered back a step","subset":"none","task_type":"understanding","prediction":"and a storm of laughter rippled around the throng of heads she heard an indrawn hiss behind her chair and the next instant an exclamation from mabel what was that there was a sharp crack and the tiny gesticulating figure staggered back a step","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1227,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043302-sg0005-mc02-lav-clo-dg150.wav","answer":"she said then she broke off and sat back why did he shoot just then she asked oliver turned his eyes for an instant towards his mother but she was knitting tranquilly then he answered with a curious deliberateness","subset":"none","task_type":"understanding","prediction":"she said then she broke off and sat back why did he shoot just then she asked oliver turned his eyes for an instant towards his mother but she was knitting tranquilly then he answered with a curious deliberateness","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1228,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5678\/Lab41-SRI-VOiCES-rm2-none-sp5678-ch043303-sg0015-mc01-stu-clo-dg070.wav","answer":"mister phillips arrived the next morning as usual just as mabel had left the old lady's room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver's room","subset":"none","task_type":"understanding","prediction":"mr phillips arrived the next morning as usual just as mabel had left the old lady s room and asked news of her she is a little better i think said mabel she must be very quiet all day the secretary bowed and turned aside into oliver s room","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1229,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm2-none-sp5717-ch100145-sg0017-mc01-stu-clo-dg070.wav","answer":"of course obray count erskyll planetary proconsul of aditya didn't realize that he didn't even know what javasan meant just free them commodore vann shatrak couldn't see much of a problem either he would have answered","subset":"none","task_type":"understanding","prediction":"of course obray count erskyll planetary proconsul of aditya didn't realize that he didn't even know what javasan meant just free them commodore van shatrak couldn't see much of a problem either he would have answered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1230,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5740\/Lab41-SRI-VOiCES-rm2-none-sp5740-ch039910-sg0028-mc02-lav-clo-dg130.wav","answer":"missus ralston went over to the christmas table and looked at the little gifts half tenderly and half pityingly they're not much like the contents of our basket are they she said as she touched the calendar jimmie had made for mollie out of cardboard and autumn leaves and grasses","subset":"none","task_type":"understanding","prediction":"mrs ralston went over to the christmas table and looked at the little gifts half tenderly and half pityingly they are not much like the contents of our basket are they she said as she touched the calendar jimmy had made for molly out of cardboard and autumn leaves and grasses","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1231,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5740\/Lab41-SRI-VOiCES-rm2-none-sp5740-ch097610-sg0031-mc01-stu-clo-dg110.wav","answer":"for while rejoicings were still loud over the departure of the enemy there came a knock at missus tracy's door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier","subset":"none","task_type":"understanding","prediction":"for while rejoicings were still loud over the departure of the enemy there came a knock at eces tracey s door and while she was wondering whether she dared open it it was pushed ajar and a tall soldier entered what a scream of delight greeted that soldier","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1232,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5789\/Lab41-SRI-VOiCES-rm2-none-sp5789-ch070653-sg0003-mc02-lav-clo-dg110.wav","answer":"and those who were to be called on to give evidence occupied chairs to one side of the table behind which the coroner sat while the jury in double row with plastered hair and a spurious ease of manner flanked him on the other side","subset":"none","task_type":"understanding","prediction":"and those who were to be called on to give evidence occupied chairs to one side of the table behind which the coroner sat while the jury in double row with plastered hair and a spurious ease of manner flanked it on the other side","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1233,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-none-sp5935-ch043305-sg0009-mc02-lav-clo-dg150.wav","answer":"again came the crying of voices again the signals and once more a car whirled past followed almost immediately by another there was a jerk a smooth movement percy staggered and fell into a seat","subset":"none","task_type":"understanding","prediction":"again came the crying of voices again the signals and once more a car whirled past followed almost immediately by another there was a jerk a smooth movement percy staggered and fell into a seat","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1234,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-none-sp5935-ch055927-sg0018-mc02-lav-clo-dg050.wav","answer":"thus while the screw outside of the hull is applying the force continuously the steam in the inside is driving the shafting with equal evenness and regularity the steam turbine does not appear to have by any means reached finality in its form","subset":"none","task_type":"understanding","prediction":"thus while the screw outside of the hull is applying the force continuously the steam in the inside is driving the shafting with equal evenness and regularity the steam turbine does not appear to have by any means reached finality in its form","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1235,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm2-none-sp6147-ch034605-sg0030-mc01-stu-clo-dg160.wav","answer":"it was a necessity doubtless but what a pity josiana appreciated lord david and showed him off there was between them a tacit agreement neither to conclude nor to break off the engagement they eluded each other this method of making love one step in advance and two back","subset":"none","task_type":"understanding","prediction":"it was a necessity doubtless but what a pity josiana appreciated lord david and showed him off there was between them a tacit agreement neither to conclude nor to break off the engagement they eluded each other this method of making love one step in advance and two back","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1236,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6319\/Lab41-SRI-VOiCES-rm2-none-sp6319-ch064726-sg0018-mc02-lav-clo-dg070.wav","answer":"then the prince took the princess by the hand she was dressed in great splendour but he did not hint that she looked as he had seen pictures of his great grandmother look he thought her all the more charming for that","subset":"none","task_type":"understanding","prediction":"then the prince took the princess by the hand she was dressed in great splendour but he did not hint that she looked as he had seen pictures of his great grandmother look he thought her all the more charming for that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1237,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6395\/Lab41-SRI-VOiCES-rm2-none-sp6395-ch086708-sg0006-mc01-stu-clo-dg100.wav","answer":"and yet dantes need not die death alone can separate them remarked fernand you talk like a noodle my friend said caderousse and here is danglars who is a wide awake clever deep fellow who will prove to you that you are wrong","subset":"none","task_type":"understanding","prediction":"and yet dantes need not die death alone can separate them remarked fernand you talk like a noodle my friend said caderousse and here is danglars who is a wide awake clever deep fellow who will prove to you that you are wrong","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1238,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm2-none-sp6415-ch111615-sg0024-mc02-lav-clo-dg120.wav","answer":"who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible","subset":"none","task_type":"understanding","prediction":"who was standing on chestnut street studying a pocket notebook his umbrella leaned against a shop window on the sill of which he had laid a carefully rolled up newspaper by his feet was a neat leather brief case plumply filled with contents not discernible","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1239,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm2-none-sp6454-ch093938-sg0016-mc02-lav-clo-dg080.wav","answer":"i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business","subset":"none","task_type":"understanding","prediction":"i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1240,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm2-none-sp6519-ch069411-sg0014-mc01-stu-clo-dg040.wav","answer":"when that something else huddled in oozing blood on the floor beneath drew them unto itself with the irresistibleness of grim reality and he forgot all else in the horror of a sight for which his fears however great","subset":"none","task_type":"understanding","prediction":"when that something else huddled in oozing blood on the floor beneath drew them unto itself with the irresistibleness of grim reality and he forgot all else in the horror of the sight for which his fears however great","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1241,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6519\/Lab41-SRI-VOiCES-rm2-none-sp6519-ch231834-sg0020-mc02-lav-clo-dg170.wav","answer":"but what grounds have you to believe him any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence","subset":"none","task_type":"understanding","prediction":"but what grounds have you to believe in any one of the three this question also puzzled the landlady as she had no reasonable grounds for her wild statements nevertheless she made a determined attempt to substantiate them by hearsay evidence","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1242,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-none-sp6544-ch067863-sg0034-mc01-stu-clo-dg150.wav","answer":"i am so glad i thought about it but it was really estralla she said if i was black we could come sylvia had replied then the boat swung clear and headed toward charleston i am not going to land at the big wharves said sylvia i am going to that wharf near miss patten's garden","subset":"none","task_type":"understanding","prediction":"i am so glad i thought about it but it was really estralla she said if i was black we could come sylvia had replied then the boat swung clear and headed toward charleston i am not going to land at the big wharves said sylvia i am going to that wharf near miss patten s garden","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1243,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm2-none-sp6574-ch120583-sg0041-mc02-lav-clo-dg020.wav","answer":"there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best","subset":"none","task_type":"understanding","prediction":"there is not a thing behind us to regret then a blow of pain struck us our first and our only we thought of the golden one we thought of the golden one whom we shall never see again then the pain passed it is best","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1244,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6696\/Lab41-SRI-VOiCES-rm2-none-sp6696-ch068773-sg0013-mc01-stu-clo-dg060.wav","answer":"me mister forbes me yes tom i'll pay you twenty dollars a week to start with and more if you serve me faithfully and you'll board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself","subset":"none","task_type":"understanding","prediction":"me mr forbes me yes tom i will pay you twenty dollars a week to start with and more if you serve me faithfully and you will board here of course then tom gates broke down and began to cry like a child although he tried hard to control himself","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1245,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6788\/Lab41-SRI-VOiCES-rm2-none-sp6788-ch096241-sg0028-mc01-stu-clo-dg120.wav","answer":"but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also","subset":"none","task_type":"understanding","prediction":"but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1246,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6788\/Lab41-SRI-VOiCES-rm2-none-sp6788-ch096241-sg0028-mc02-lav-clo-dg120.wav","answer":"but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also","subset":"none","task_type":"understanding","prediction":"but endlessly pursues phenomena moving without end or aim like a squirrel in its wheel till tired out at last he stops at some point or other arbitrarily chosen and now desires to extort respect for it from others also","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1247,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6848\/Lab41-SRI-VOiCES-rm2-none-sp6848-ch076049-sg0018-mc02-lav-clo-dg060.wav","answer":"she had had no husband of the lord and master type so to speak but only a prince consort well in hand why shouldn't the grammont heiress dominate her male belonging if it came to that in the same fashion","subset":"none","task_type":"understanding","prediction":"she had had no husband of a lord and master type so to speak but only a prince consort well in hand why shouldn t the grammont heiress dominate her male belonging if it came to that in the same fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1248,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6848\/Lab41-SRI-VOiCES-rm2-none-sp6848-ch252322-sg0006-mc01-stu-clo-dg090.wav","answer":"turning as he went to look back towards the bed and evidently going with reluctance is it fever asked the sick man in a faint but unfaltering accent it's a kind of cerebral congestion a matter of them membranes that's over the brain","subset":"none","task_type":"understanding","prediction":"turning as he went to look back towards the bed and evidently going with reluctance is it fever asked the sick man in a faint but unfaltering accent it is a kind of cerebral congestion a matter of them membranes that is over the brain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1249,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm2-none-sp6895-ch092805-sg0031-mc02-lav-clo-dg010.wav","answer":"oh i don't know says he and he begins to tell them about a cab driver at sixth avenue and broadway those ideas don't suit me i'm not tied down to anything that isn't eight thousand miles in diameter just put me down as e rushmore coglan citizen of the terrestrial sphere","subset":"none","task_type":"understanding","prediction":"oh i don t know says he and he begins to tell them about a cab drive at sixth avenue and broadway those ideas don t suit me i m not tied down to anything that isn t eight thousand miles in diameter just put me down as eve rushmore coglan citizen of the terrestrial sphere","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":1250,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm2-none-sp7000-ch083706-sg0015-mc02-lav-clo-dg000.wav","answer":"if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mister hedges any objections which i might urge would appear quite trivial","subset":"none","task_type":"understanding","prediction":"if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mr hedges any objections which i might urge would appear quite trivial","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1251,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm2-none-sp7095-ch088483-sg0007-mc02-lav-clo-dg130.wav","answer":"just because he has said it for so long and so often the force of repetition is great it is in fact taken by a vast majority of men as the equivalent of proof most men have to accept their religions ready made","subset":"none","task_type":"understanding","prediction":"just because he has said it for so long and so often the force of repetition is great it is in fact taken by a vast majority of men as the equivalent of proof most men have to accept their religions ready made","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1252,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm2-none-sp7095-ch088489-sg0000-mc01-stu-clo-dg020.wav","answer":"when copernicus showed that the earth was not the center of the universe when darwin proved that man's origin was not the result of direct creation when freud explained that man was not the master of his own thoughts or actions","subset":"none","task_type":"understanding","prediction":"when copernicus showed that the earth was not the center of the universe when darwin proved that man s origin was not the result of direct creation when freud explained that man was not the master of his own thoughts or actions","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1253,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-none-sp7148-ch007763-sg0027-mc01-stu-clo-dg160.wav","answer":"were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connexions between things not dependent on our will and feelings natural laws by virtue of which in many cases","subset":"none","task_type":"understanding","prediction":"were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connections between things not dependent on our will and feelings natural laws by virtue of which in many cases","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1254,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-none-sp7148-ch007763-sg0027-mc02-lav-clo-dg160.wav","answer":"were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connexions between things not dependent on our will and feelings natural laws by virtue of which in many cases","subset":"none","task_type":"understanding","prediction":"were it not that we owe to analysis our clearest knowledge of the permanent sequences in nature the real connections between things not dependent on our will and feelings natural laws by virtue of which in many cases","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1255,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7247\/Lab41-SRI-VOiCES-rm2-none-sp7247-ch077778-sg0016-mc01-stu-clo-dg120.wav","answer":"that was one instance two weeks later i went again this time to hear goetterdaemmerung the results were the same only the effect was instantaneous the curtain had hardly risen before i retired to the little ante room of the box our party occupied","subset":"none","task_type":"understanding","prediction":"that was one instance two weeks later i went again this time to hear gotterdammerung the results were the same only the effect was instantaneous the curtain had hardly risen before i retired to the little anteroom of the box our party occupied","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1256,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7247\/Lab41-SRI-VOiCES-rm2-none-sp7247-ch077778-sg0034-mc02-lav-clo-dg090.wav","answer":"to be well shaken before taken will be an effective remedy for a torpid liver and the man or woman who suffers from lassitude will doubtless find in the lively airs of our two step composers an efficient tonic to bring their vitality up to a high standard of activity","subset":"none","task_type":"understanding","prediction":"to be well shaken before taken will be an effective remedy for a torpid liver and the man or woman who suffers from lassitude will doubtless find in the lively airs of our two step composers an efficient tonic to bring their vitality up to a high standard of activity","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1257,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7247\/Lab41-SRI-VOiCES-rm2-none-sp7247-ch101864-sg0004-mc02-lav-clo-dg090.wav","answer":"the farther away they could get from the oil that made the machinery of life run easily and noiselessly the better pleased they were the dining room looked particularly pleasant this july evening a gentle breeze stirred the curtains at the open windows","subset":"none","task_type":"understanding","prediction":"the farther away they could get from the oil that made the machinery of life run easily and noiselessly the better pleased they were the dining room looked particularly pleasant this july evening a gentle breeze stirred the curtains at the open windows","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1258,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7276\/Lab41-SRI-VOiCES-rm2-none-sp7276-ch090847-sg0045-mc02-lav-clo-dg030.wav","answer":"and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen","subset":"none","task_type":"understanding","prediction":"and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1259,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7276\/Lab41-SRI-VOiCES-rm2-none-sp7276-ch284424-sg0042-mc01-stu-clo-dg130.wav","answer":"what can the answer be trot looked the boy over carefully she didn't see any wings on him the only queer thing about him was his big umbrella oh she said suddenly clapping her hands together i know now","subset":"none","task_type":"understanding","prediction":"what can the answer be trot looked the boy over carefully she didn t see any wings on him the only queer thing about him was his big umbrella oh she said suddenly clapping her hands together i know now","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1260,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm2-none-sp7498-ch099156-sg0013-mc01-stu-clo-dg000.wav","answer":"we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time","subset":"none","task_type":"understanding","prediction":"we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1261,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7688\/Lab41-SRI-VOiCES-rm2-none-sp7688-ch105390-sg0042-mc02-lav-clo-dg110.wav","answer":"rumour has it in france that your highness could an you would give the truest account of that enigmatical wayside flower he looked quickly and keenly at marguerite as he spoke but she betrayed no emotion and her eyes met his quite fearlessly","subset":"none","task_type":"understanding","prediction":"Rumor has it in France that your highness could, and you would give the truest account of that enigmatical wayside flower. He looked quickly and keenly at Marguerite as he spoke, but she betrayed no emotion. And her eyes met his, quite fearlessly.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1262,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7688\/Lab41-SRI-VOiCES-rm2-none-sp7688-ch109656-sg0020-mc02-lav-clo-dg180.wav","answer":"there was a big lump in his throat as he thought of the cross words he had spoken to his wife surely it was hard enough for her to live in that horrible country without having to bear the burden of his abuse he cursed himself grimly and felt a sudden flush of shame that","subset":"none","task_type":"understanding","prediction":"there was a big lump in his throat as he thought of the cross words he had spoken to his wife surely it was hard enough for her to live in that horrible country without having to bear the burden of his abuse he cursed himself grimly and felt a sudden flush of shame that","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1263,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-none-sp7850-ch281318-sg0009-mc02-lav-clo-dg120.wav","answer":"so in a great company they came fluttering hopping twittering up to the elm tree where mother magpie nestled comfortably in her new house","subset":"none","task_type":"understanding","prediction":"so in a great company they came fluttering hopping twittering up to the elm tree where mother magpie nestled comfortably in her new house","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1264,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-none-sp7850-ch281318-sg0010-mc02-lav-clo-dg110.wav","answer":"o wise mother magpie dear mother magpie they cried teach us how to build our nests like yours for it is growing night and we are tired and sleepy","subset":"none","task_type":"understanding","prediction":"oh wise mother magpie dear mother magpie they cried teach us how to build our nests like yours for it is growing night and we are tired and sleepy","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1265,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-none-sp7850-ch286674-sg0000-mc01-stu-clo-dg070.wav","answer":"a person would think that after a family had lived so long in a place all the neighbors would be fond of them yet it is not so","subset":"none","task_type":"understanding","prediction":"a person would think that after a family had lived so long in a place all the neighbors would be fond of them yet it is not so","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1266,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-none-sp7868-ch110706-sg0031-mc01-stu-clo-dg120.wav","answer":"and long snake like shadows crept up along the mountain sides hans struggled on the sun was sinking but its descent seemed to bring no coolness the leaden weight of the dead air pressed upon his brow and heart but","subset":"none","task_type":"understanding","prediction":"and long snake like shadows crept up along the mountain sides kahn struggled on the sun was sinking but its descent seemed to bring no coolness the leaden weight of the dead air pressed upon his brow and heart but","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1267,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-none-sp7868-ch110706-sg0035-mc01-stu-clo-dg040.wav","answer":"and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball","subset":"none","task_type":"understanding","prediction":"and a flash of blue lightning rose out of the east shaped like a sword it shook thrice over the whole heaven and left it dark with one heavy impenetrable shade the sun was setting it plunged toward the horizon like a red hot ball","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1268,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm2-none-sp7881-ch105574-sg0015-mc01-stu-clo-dg040.wav","answer":"yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us","subset":"none","task_type":"understanding","prediction":"yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1269,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm2-none-sp7881-ch105574-sg0034-mc01-stu-clo-dg060.wav","answer":"i was always careful that this should not keep me away from the command when enduring hard marches or when engagements were coming on when in camp i kept my rifle in one of the ammunition wagons of several of which i had charge but if the alarm sounded my rifle was on my shoulder","subset":"none","task_type":"understanding","prediction":"i was always careful that this should not keep me away from the command when enduring hard marches or when engagements were coming on when in camp i kept my rifle in one of the ammunition wagons of several of which i had charge but if the alarm sounded my rifle was on my shoulder","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1270,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm2-none-sp7881-ch109662-sg0027-mc01-stu-clo-dg180.wav","answer":"and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet","subset":"none","task_type":"understanding","prediction":"and among its soft convolutions he did not feel the prick of the thorn that was to pierce him later how glad how shy how tremulous she was how she fluttered like a snared bird when he laid his mightiness at her feet","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1271,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7910\/Lab41-SRI-VOiCES-rm2-none-sp7910-ch080534-sg0007-mc02-lav-clo-dg180.wav","answer":"eagles was absorbed in the study of a certain branch of political statistics the enthusiasm of his life was financial reform every budget presented to parliament he criticised with extraordinary thoroughness and in fact with an acumen","subset":"none","task_type":"understanding","prediction":"eagles was absorbed in the study of a certain branch of political statistics the enthusiasm of his life was financial reform every budget presented to parliament he criticised with extraordinary thoroughness and in fact with an acumen","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1272,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm2-none-sp7976-ch110523-sg0000-mc02-lav-clo-dg090.wav","answer":"he had little enough to break or bite and once when there was a great famine in the land he could hardly procure even his daily bread and as he lay thinking in his bed one night he sighed and said to his wife what will become of us","subset":"none","task_type":"understanding","prediction":"he had little enough to break or bite and once when there was a great famine in the land he could hardly procure even his daily bread and as he lay thinking in his bed one night he sighed and said to his wife what will become of us","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1273,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm2-none-sp7981-ch112061-sg0025-mc01-stu-clo-dg020.wav","answer":"justly indignant begged to be allowed to give the great lady a piece of his mind come on said vincent our business lies in another direction is it not strange he said smiling a few moments later as he tried to staunch the blood with his handkerchief","subset":"none","task_type":"understanding","prediction":"justly indignant begged to be allowed to give the great lady a piece of his mind come on said vincent our business lies in another direction is it not strange he said smiling a few moments later as he tried to staunch the blood with his handkerchief","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1274,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm2-none-sp7995-ch276908-sg0012-mc01-stu-clo-dg070.wav","answer":"of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature","subset":"none","task_type":"understanding","prediction":"of which she was a perfect mistress she said i do not wonder at your amazement captain booth nor indeed at the concern which you so plainly discover for me for i well know the goodness of your nature","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1275,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm2-none-sp7995-ch276908-sg0017-mc02-lav-clo-dg090.wav","answer":"not of that monster man mister booth i am undone am revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech","subset":"none","task_type":"understanding","prediction":"not of that monster man mr booth i am undone am revenged and have now no more business for life let them take it from me when they will our poor gentleman turned pale with horror at this speech","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1276,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm2-none-sp7995-ch280250-sg0028-mc01-stu-clo-dg040.wav","answer":"hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it","subset":"none","task_type":"understanding","prediction":"hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1277,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm2-none-sp7995-ch280250-sg0028-mc02-lav-clo-dg040.wav","answer":"hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it","subset":"none","task_type":"understanding","prediction":"hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1278,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm2-none-sp8108-ch280354-sg0017-mc02-lav-clo-dg040.wav","answer":"he turned to gaze on his beloved dimly he saw her but for the last time for a power she could not resist drew her back orpheus stretched out his arms and tried to seize her but he only clasped the empty air","subset":"none","task_type":"understanding","prediction":"he turned to gaze on his beloved dimly he saw her but for the last time for a power she could not resist drew her back orpheus stretched out his arms and tried to seize her but he only clasped the empty air","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1279,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm2-none-sp8108-ch280359-sg0006-mc01-stu-clo-dg100.wav","answer":"sometimes he hid himself as one among a troop of timid reindeer sometimes he lay in the nest of a wood pigeon sometimes he swam a bright spotted fish in the sea but wherever he was among living creatures","subset":"none","task_type":"understanding","prediction":"Sometimes he hid himself as one among a troop of timid reindeer. Sometimes he lay in the nest of a wood pigeon. Sometimes he swam a bright spotted fish in the sea. But wherever he was among living creatures.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1280,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm2-none-sp8225-ch274374-sg0019-mc02-lav-clo-dg140.wav","answer":"son of lord say he himself as well as his father a great parliamentary leader was governor and commanded a garrison of two thousand five hundred foot and two regiments one of horse another of dragoons the fortifications not being complete or regular","subset":"none","task_type":"understanding","prediction":"son of lord say he himself as well as his father a great parliamentary leader was governor and commanded a garrison of two thousand five hundred foot and two regiments one horse another of dragoons the fortifications not being complete or regular","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1281,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8225\/Lab41-SRI-VOiCES-rm2-none-sp8225-ch274376-sg0002-mc01-stu-clo-dg060.wav","answer":"than the english parliament in order to allure that nation into a close confederacy openly declared their wishes of ecclesiastical reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used","subset":"none","task_type":"understanding","prediction":"then the english parliament in order to allure that nation into a close confederacy openly declared their wishes of ecclesiastical reformation and of imitating the example of their northern brethren when war was actually commenced the same artifices were used","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1282,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-none-sp8266-ch258262-sg0001-mc02-lav-clo-dg020.wav","answer":"they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered","subset":"none","task_type":"understanding","prediction":"they said we will not slay him save in our own land then they sailed on till they came to the city of karaj the builder whereof was an amalekite fierce and furious and he had set up at each gate of the city a magical figure of copper which whenever a stranger entered","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1283,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-none-sp8266-ch258262-sg0012-mc02-lav-clo-dg050.wav","answer":"and the land of the enchanted calf so called because its king al muzalzil had a pied calf which he had clad in housings brocaded with red gold and worshipped as a god one day the king and his people went in to the calf and found him trembling so the king said","subset":"none","task_type":"understanding","prediction":"and the land of the enchanted calf so called because its king al murzazul had a piebald calf which he had clad in housings brocaded with red gold and worshipped as a god one day the king and his people went in to the calf and found him trembling so the king said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1284,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-none-sp8266-ch258263-sg0022-mc02-lav-clo-dg000.wav","answer":"no but rejoice ye for king gharib hath returned to you so they rejoiced and gharib after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him","subset":"none","task_type":"understanding","prediction":"no but rejoice ye for king gharib hath returned to you so they rejoiced and gharib after salams to the women came forth amongst his comrades who threw themselves upon him and kissed his hands and feet returning thanks to almighty allah and praising him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1285,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8425\/Lab41-SRI-VOiCES-rm2-none-sp8425-ch291444-sg0001-mc01-stu-clo-dg140.wav","answer":"who serve as the tottering monuments of good old times will be gathered to their fathers their children engrossed by the empty pleasures or insignificant transactions of the present age will neglect to treasure up the recollections of the past","subset":"none","task_type":"understanding","prediction":"who serve as the tottering monuments of good old times will be gathered to their fathers their children engrossed by the empty pleasures or insignificant transactions of the present age will neglect to treasure up the recollections of the past","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1286,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8575\/Lab41-SRI-VOiCES-rm2-none-sp8575-ch290351-sg0028-mc01-stu-clo-dg140.wav","answer":"on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small","subset":"none","task_type":"understanding","prediction":"on the other side the ordinary smallest measure we have of either is looked on as an unit in number when the mind by division would reduce them into less fractions though on both sides both in addition and division either of space or duration when the idea under consideration becomes very big or very small","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1287,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8605\/Lab41-SRI-VOiCES-rm2-none-sp8605-ch276939-sg0024-mc01-stu-clo-dg170.wav","answer":"and exulting with the thoughts of presently seeing her beloved friend she was answered at the door that the lady was not at home nor could she upon telling her name obtain any admission this considering the account she had received of the lady's cold greatly surprized her","subset":"none","task_type":"understanding","prediction":"and exulting with the thoughts of presently seeing her beloved friend she was answered at the door that the lady was not at home nor could she upon telling her name obtain any admission this considering the account she had received of the lady s cold greatly surprised her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1288,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8605\/Lab41-SRI-VOiCES-rm2-none-sp8605-ch291172-sg0006-mc02-lav-clo-dg070.wav","answer":"and she intimated to me that it was only the baby girl with whom she intended to feed the little baby boy as he had not got fair play and so the majesty of justice was maintained cats are greatly sensible of the honour of maternity","subset":"none","task_type":"understanding","prediction":"and she intimated to me that it was only the baby girl with whom she intended to feed the little baby boy as he had not got fair play and so the majesty of justice was maintained cats are greatly sensible of the honour of maternity","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1289,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8605\/Lab41-SRI-VOiCES-rm2-none-sp8605-ch292138-sg0005-mc01-stu-clo-dg170.wav","answer":"she greeted her two little playmates from the vicarage all three were bubbling over with glee at the prospect of an outing this bright june afternoon upon the river thames they were to go up stream to a pretty little nook in a quiet backwater","subset":"none","task_type":"understanding","prediction":"she greeted her two little playmates from the vicarage all three were bubbling over with glee at the prospect of an outing this bright june afternoon upon the river thames they were to go up stream to a pretty little nook in a quiet backwater","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1290,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/none\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm2-none-sp8713-ch302111-sg0010-mc02-lav-clo-dg080.wav","answer":"answered in the words which follow song of birds is idle chatter and the throstle's merely chirping as a child a daughter's treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seat thee","subset":"none","task_type":"understanding","prediction":"answered in the words which follow song of birds is idle chatter and the thrushes merely chirping as a child a daughter is treated but a maid must needs be married come into my sledge o maiden in the sledge beside me seek thee","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1291,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0122\/Lab41-SRI-VOiCES-rm2-tele-sp0122-ch129752-sg0041-mc02-lav-clo-dg040.wav","answer":"sweetened and flavored with a few drops of vanilla put on the top cake and dust with powdered sugar date cake sift two cups of flour with four level teaspoons of baking powder one half level teaspoon of salt","subset":"tele","task_type":"understanding","prediction":"Sweetened and flavored with a few drops of vanilla. Put on the top cake and dust with powdered sugar date cake. Sift 2 cups of flour with 4 level teaspoons of baking powder, one half level teaspoon of salt.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1292,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0159\/Lab41-SRI-VOiCES-rm2-tele-sp0159-ch121902-sg0007-mc01-stu-clo-dg070.wav","answer":"it was concluded that the whole aim of man's will though the means of pursuit vary is set intently upon happiness i do remember that this too was proved dost thou also call to mind how happiness is absolute good","subset":"tele","task_type":"understanding","prediction":"it was concluded that the whole aim of man s will though the means of pursuit vary is set intently upon happiness i do remember that this too was proved dost thou also call to mind how happiness is absolutely good","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1293,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0159\/Lab41-SRI-VOiCES-rm2-tele-sp0159-ch135897-sg0010-mc02-lav-clo-dg030.wav","answer":"in a manner answerable to our condition but i added i rather believe you wish to marry again i shall feel much surprised if such be the case after the experience you have had of the little satisfaction there is in wedlock","subset":"tele","task_type":"understanding","prediction":"in a manner answerable to our condition but i added i rather believe you wish to marry again i shall feel much surprised if such be the case after the experience you have had of the little satisfaction there is in redlack","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1294,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0188\/Lab41-SRI-VOiCES-rm2-tele-sp0188-ch141613-sg0021-mc01-stu-clo-dg040.wav","answer":"for who better than himself could understand the need of a child's presence for that matter pollyanna talked to everybody about jamie she assumed that everybody would be as interested as she herself was","subset":"tele","task_type":"understanding","prediction":"for who better than himself could understand the need of a child's presence for that matter pollyanna talked to everybody about jamie she assumed that everybody would be as interested as she herself was","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1295,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0204\/Lab41-SRI-VOiCES-rm2-tele-sp0204-ch148920-sg0003-mc01-stu-clo-dg050.wav","answer":"relics of the days when the countrymen of julius caesar had settled there where have they not settled i for one would hardly be astonished if relics of the ancient romans should someday be found deep under the grass growing around the bunker hill monument","subset":"tele","task_type":"understanding","prediction":"relics of the days when the countrymen of julius caesar had settled there where have they not settled i for one would hardly be astonished if relics of the ancient romans should some day be found deep under the grass growing around the bunker hill monument","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1296,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0205\/Lab41-SRI-VOiCES-rm2-tele-sp0205-ch123882-sg0030-mc01-stu-clo-dg080.wav","answer":"and the new limited and the maritime express that holds the record of six hundred whirling miles from paris to marseilles but what are they to this this mad career this breakneck speed this thundering roar of the mariposa local driving hard to its home","subset":"tele","task_type":"understanding","prediction":"and the new limited and the maritime express that holds the record of six hundred whirling miles from paris to marseilles but what are they to this this mad career this breakneck speed this thundering roar of the mariposa local driving hard to its home","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1297,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0208\/Lab41-SRI-VOiCES-rm2-tele-sp0208-ch126600-sg0011-mc02-lav-clo-dg090.wav","answer":"freddie fisher fairly fussed when he came to eat his crust often on the floor he'd throw it hoping mother wouldn't know it goops all hate to eat the crust if you're told to then you must","subset":"tele","task_type":"understanding","prediction":"Freddy Fisher fairly fussed when he came to eat his crust. Often on the floor, he d throw it, hoping mother wouldn t know it. Goofs all hate to eat the crust. If you re told to, then you must.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1298,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0208\/Lab41-SRI-VOiCES-rm2-tele-sp0208-ch126600-sg0030-mc01-stu-clo-dg170.wav","answer":"just look at percival b sloop a most unpleasant sort of goop he pokes his fingers in his nose and wipes his hands upon his clothes he does a lot of things that you","subset":"tele","task_type":"understanding","prediction":"just look at percival b slugh a most unpleasant sort of goop he pokes his fingers in his nose and wipes his hands upon his gloves he does a lot of things that you","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1299,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm2-tele-sp0209-ch004731-sg0002-mc02-lav-clo-dg030.wav","answer":"comprehended many such not unfrequently through emma's persuasion he had some of the chosen and the best to dine with him but evening parties were what he preferred and unless he fancied himself at any time unequal to company","subset":"tele","task_type":"understanding","prediction":"Comprehended many such, not unfrequently through Emma's persuasion. He had some of the chosen and the best to dine with him. But evening parties were what he preferred. And unless he fancied himself at any time, unequal to company.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1300,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0209\/Lab41-SRI-VOiCES-rm2-tele-sp0209-ch157830-sg0016-mc02-lav-clo-dg050.wav","answer":"it did not appear to him that sir walter could materially alter his style of living in a house which had such a character of hospitality and ancient dignity to support in any other place sir walter might judge for himself and would be looked up to as regulating the modes of life","subset":"tele","task_type":"understanding","prediction":"it did not appear to him that sir walter could materially alter his style of living in a house which had such a character of hospitality and ancient dignity to support in any other place sir walter might judge for himself and would be looked up to as regulating the modes of life","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1301,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0240\/Lab41-SRI-VOiCES-rm2-tele-sp0240-ch144999-sg0038-mc02-lav-clo-dg000.wav","answer":"and by no means is it really necessary to a successful outing twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals","subset":"tele","task_type":"understanding","prediction":"and by no means is it really necessary to a successful hunter twelve the best hunter is the man who finds the most game kills the least and leaves behind him no wounded animals","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1302,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0242\/Lab41-SRI-VOiCES-rm2-tele-sp0242-ch126842-sg0035-mc01-stu-clo-dg010.wav","answer":"peter no i don't want to hear about it said uncle alec sternly i don't care what you were fighting about but you must settle your quarrels in a different fashion remember my commands felix peter","subset":"tele","task_type":"understanding","prediction":"Peter, no, I don't want to hear about it, said Uncle Alec sternly. I don't care what you were fighting about, but you must settle your quarrel in a different fashion. Remember my commands, Felix, Peter.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1303,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0288\/Lab41-SRI-VOiCES-rm2-tele-sp0288-ch121741-sg0015-mc01-stu-clo-dg150.wav","answer":"and enough likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god's making one would say","subset":"tele","task_type":"understanding","prediction":"and enough likewise to serve as a background to my description of kirsty kirsty was a highland woman who had the charge of the house in which the farm servants lived she was a cheerful gracious kind woman a woman of god s making one would say","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1304,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm2-tele-sp0459-ch127521-sg0029-mc01-stu-clo-dg000.wav","answer":"but silver from the other boat looked sharply over and called out to know if that were me and from that moment i began to regret what i had done the crews raced for the beach but the boat i was in having some start and being at once the lighter and the better manned","subset":"tele","task_type":"understanding","prediction":"but silver from the other boat looked sharply over and called out to know if that were me and from that moment i began to regret what i had done the crews raced for the beach but the boat i was in having some start and being at once the lighter and the better manned","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1305,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0459\/Lab41-SRI-VOiCES-rm2-tele-sp0459-ch127522-sg0003-mc01-stu-clo-dg120.wav","answer":"another followed and soon over the whole surface of the marsh a great cloud of birds hung screaming and circling in the air i judged at once that some of my shipmates must be drawing near along the borders of the fen nor was i deceived","subset":"tele","task_type":"understanding","prediction":"another followed and soon over the whole surface of the marsh a great cloud of birds hung screaming and circling in the air i judged at once that some of my shipmates must be drawing near along the borders of the fen nor was i deceived","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1306,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0472\/Lab41-SRI-VOiCES-rm2-tele-sp0472-ch129983-sg0032-mc01-stu-clo-dg160.wav","answer":"to which both of them submitted without any reluctance for nothing had been said on either side to make them dislike each other less than they had done before and elinor sat down to the card table with the melancholy persuasion that edward was not only without affection for the person who was to be his wife","subset":"tele","task_type":"understanding","prediction":"to which both of them submitted without any reluctance for nothing had been said on either side to make them dislike each other less than they had done before and elinor sat down to the card table with the melancholy persuasion that edward was not only without affection for the person who was to be his wife","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1307,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0479\/Lab41-SRI-VOiCES-rm2-tele-sp0479-ch107479-sg0005-mc02-lav-clo-dg150.wav","answer":"and in order to quiet all suspicion of my real status in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and","subset":"tele","task_type":"understanding","prediction":"and it required also special precautions in the van raffles household i was compelled to act the part in a fashion which revolted me otherwise the position was pleasant and","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":10}
+{"index":1308,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm2-tele-sp0480-ch123176-sg0011-mc02-lav-clo-dg130.wav","answer":"and season it with wine or lemon juice tapioca jelly wash the tapioca well and let it soak for several hours in cold water put it in a sauce pan with the same water and let it boil slowly till it is clear and thick","subset":"tele","task_type":"understanding","prediction":"and season it with wine or lemon juice tapioca jelly wash the tapioca well and let it soak for several hours in cold water put it in a saucepan with the same water and let it boil slowly till it is clear and thick","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1309,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm2-tele-sp0480-ch126292-sg0029-mc02-lav-clo-dg070.wav","answer":"partlet and having dug a grave for her he laid her in it and made a little hillock over her then he sat down by the grave and wept and mourned till at last he died too","subset":"tele","task_type":"understanding","prediction":"having dug a grave for her he laid her in it down the hall and made a little hillock over her then he sat down by the grave and wept and mourned till at last he died too","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1310,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0480\/Lab41-SRI-VOiCES-rm2-tele-sp0480-ch126336-sg0008-mc01-stu-clo-dg030.wav","answer":"ah unlucky wretch that i am sighed she would that i had married king grisly beard next they came to some fine meadows whose are these beautiful green meadows said she","subset":"tele","task_type":"understanding","prediction":"unlucky wretch that i am said she would that i had married king grizzly beard next they came to some fine meadows whose are these beautiful green meadows said she","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1311,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0492\/Lab41-SRI-VOiCES-rm2-tele-sp0492-ch131882-sg0007-mc01-stu-clo-dg120.wav","answer":"insects phileas fogg was a member of the reform and that was all the way in which he got admission to this exclusive club was simple enough he was recommended by the barings with whom he had an open credit","subset":"tele","task_type":"understanding","prediction":"insects the late fog was a member of the reform and that was all the way in which he got admission to his exclusive club was simple enough he was recommended by the barings with whom he had an open credit","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1312,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch123163-sg0044-mc01-stu-clo-dg100.wav","answer":"grated bread soaked in cream put in the omelet some think an improvement the dripping of a nice ham some persons use for omelet instead of butter to boil eggs have the water boiling and look at your watch as you put them in","subset":"tele","task_type":"understanding","prediction":"Grated bread soaked in cream, put in the omelet. Some think an improvement. The dripping of a nice ham. Some persons use for omelet instead of butter to boil eggs. Have the water boiling and look at your watch as you put them in.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1313,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch128310-sg0034-mc01-stu-clo-dg080.wav","answer":"looking silently on at the morning traffic in fleet street with their two heads as near to one another as the two eyes of each were bore a considerable resemblance to a pair of monkeys the resemblance was not lessened by the accidental circumstance that the mature jerry bit and spat out straw","subset":"tele","task_type":"understanding","prediction":"looking silently on at the morning traffic in fleet street with their two heads as near to one another as the two eyes of each were bore a considerable resemblance to a pair of monkeys the resemblance was not lessened by the accidental circumstance that the mature jerry bit and spat out straw","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1314,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch128331-sg0002-mc02-lav-clo-dg180.wav","answer":"had this work always ready for it now that it could strike the fingers of the knitting women were vicious with the experience that they could tear there was a change in the appearance of saint antoine the image had been hammering into this for hundreds of years","subset":"tele","task_type":"understanding","prediction":"had this work always ready for it now that it could strike the fingers of the knitting women were vicious with the experience that they could tear there was a change in the appearance of saint antoine the image had been hammering into this for hundreds of years","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1315,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0636\/Lab41-SRI-VOiCES-rm2-tele-sp0636-ch128331-sg0021-mc01-stu-clo-dg150.wav","answer":"and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth","subset":"tele","task_type":"understanding","prediction":"and silently and composedly looked at him while they made ready and while he besought her the women passionately screeching at him all the time and the men sternly calling out to have him killed with grass in his mouth","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1316,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0637\/Lab41-SRI-VOiCES-rm2-tele-sp0637-ch127597-sg0003-mc01-stu-clo-dg010.wav","answer":"his native valley and that he intended to return to it the same day at once it struck me that could i but reach that valley under his protection i might easily from thence reach nukuheva by water and animated by the prospect which this plan held out","subset":"tele","task_type":"understanding","prediction":"his native valley and that he intended to return to it the same day at once it struck me that could i but reach that valley under his protection i might easily from thence reach nukuheva by water and animated by the prospect which this plan held out","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1317,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0770\/Lab41-SRI-VOiCES-rm2-tele-sp0770-ch134592-sg0010-mc02-lav-clo-dg000.wav","answer":"now he was just a blind breathing carcase nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there were something in these wise old dogs that did not perish utterly with death","subset":"tele","task_type":"understanding","prediction":"now he was just a blind breathing carcass nothing more and she still worked with frail energy still swept and baked and washed fetched and carried if there were something in these wise old dogs that did not perish utterly with death","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1318,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp0948\/Lab41-SRI-VOiCES-rm2-tele-sp0948-ch132707-sg0018-mc01-stu-clo-dg010.wav","answer":"their hand in ours and that night we knew that to hold the body of women in our arms is neither ugly nor shameful but the one ecstasy granted to the race of men","subset":"tele","task_type":"understanding","prediction":"their hand in ours and that night we knew that to hold the body of a woman in our arms is neither ugly nor shameful but the one ecstasy granted to the race of men","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1319,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm2-tele-sp1050-ch134121-sg0013-mc01-stu-clo-dg120.wav","answer":"but something was the matter she could not pull it up there was the dinner but she could not reach it all the family in turn went and tried all pulled together in vain the dinner could not be stirred","subset":"tele","task_type":"understanding","prediction":"But something was the matter. She could not pull it up. There was the dinner, but she could not reach it all. The family, in turn, went and tried. All pulled together in vain. The dinner could not be stirred.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1320,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm2-tele-sp1050-ch134121-sg0023-mc01-stu-clo-dg070.wav","answer":"yes said agamemnon they found there pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mister peterkin reached the carpenter's shop","subset":"tele","task_type":"understanding","prediction":"yes said agamemnon they found their pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mr peterkin reached the carpenter shop","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1321,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1050\/Lab41-SRI-VOiCES-rm2-tele-sp1050-ch134121-sg0023-mc02-lav-clo-dg070.wav","answer":"yes said agamemnon they found there pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mister peterkin reached the carpenter's shop","subset":"tele","task_type":"understanding","prediction":"yes said agamemnon they found their pots and kettles now i should like to know how they did it and i mean to borrow a book and read i think it was done with a pickaxe so the party set out but when mr peterkin reached the carpenter shop","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1322,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1052\/Lab41-SRI-VOiCES-rm2-tele-sp1052-ch132776-sg0021-mc01-stu-clo-dg020.wav","answer":"would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped","subset":"tele","task_type":"understanding","prediction":"would have excluded from parliament and office all who refused to declare on oath that they thought resistance in every case unlawful but his vigorous understanding now thoroughly awakened by anxiety for the public interests and for his own was no longer to be duped","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1323,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1052\/Lab41-SRI-VOiCES-rm2-tele-sp1052-ch139308-sg0001-mc01-stu-clo-dg130.wav","answer":"and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there","subset":"tele","task_type":"understanding","prediction":"and he began to recall that along all the vast chambers and passages he had traversed with howard he had observed no windows at all had there been windows there were windows on the street indeed but were they for light or was the whole city lit day and night for evermore so that there was no night there","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1324,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1066\/Lab41-SRI-VOiCES-rm2-tele-sp1066-ch103481-sg0002-mc02-lav-clo-dg080.wav","answer":"and hope looked out again from tired eyes down where the white point gardens drank the sun and rippled to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a taunt","subset":"tele","task_type":"understanding","prediction":"and hope looked out again from tired eyes down where the white point gardens strike the sun and ripple to the lift of springing grass the women came and after them the aged and the lame that war had hurled back at them like a tod","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1325,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1112\/Lab41-SRI-VOiCES-rm2-tele-sp1112-ch128136-sg0010-mc02-lav-clo-dg030.wav","answer":"as if the bulk of twenty million whales were worth one pleading soul or all the laws that rule the lifeless suns could soothe the sense of outrage in a loving human heart sublime majestic","subset":"tele","task_type":"understanding","prediction":"as if the bulk of twenty million whales were worth one pleading soul or all the laws that rule the lifeless suns could soothe the sense of outrage in a loving human heart sublime majestic","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1326,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1116\/Lab41-SRI-VOiCES-rm2-tele-sp1116-ch137572-sg0003-mc02-lav-clo-dg060.wav","answer":"when one has received the promise of something greatly desired but must wait awhile before its delivery the happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight","subset":"tele","task_type":"understanding","prediction":"when one has received the promise of something greatly desired but must wait a while before its delivery happiness of the waiting period is characterized by the absence of a critical spirit and therefore is apt to be thought of as an experience of pure delight","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1327,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1121\/Lab41-SRI-VOiCES-rm2-tele-sp1121-ch135824-sg0002-mc01-stu-clo-dg160.wav","answer":"began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny's cousins more closely related to him than to any other members of the mouse family","subset":"tele","task_type":"understanding","prediction":"began old mother nature just as chatterer the red squirrel who was late came hurrying up quite out of breath way up in the far north are two of danny s cousins more closely related to him than to any other members of the mouse family","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1328,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm2-tele-sp1160-ch139727-sg0010-mc01-stu-clo-dg040.wav","answer":"unless their vast estates were in the same act expressly excused and they had even taken bonds of these deputies to observe such instructions the assemblies for three years held out against this injustice","subset":"tele","task_type":"understanding","prediction":"unless their vast estates were in the same act expressly excused and they had even taken bonds of these deputies to observe such instructions the assemblies for three years bellowed out against this injustice","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1329,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1160\/Lab41-SRI-VOiCES-rm2-tele-sp1160-ch139730-sg0007-mc01-stu-clo-dg000.wav","answer":"should assist in comprehending the following he procur'd an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely form'd by instrument makers his lectures","subset":"tele","task_type":"understanding","prediction":"should assist in comprehending the following he procured an elegant apparatus for the purpose in which all the little machines that i had roughly made for myself were nicely formed by instrument makers his lectures","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1330,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_0032-1182\/sp1182\/Lab41-SRI-VOiCES-rm2-tele-sp1182-ch133396-sg0013-mc02-lav-clo-dg070.wav","answer":"two days later a very stout little one eyed man clad in a leathern jerkin and wearing a round leathern cap upon his head came toiling up the path to the postern door of trutz drachen his back bowed under the burthen of a great peddler's pack it was our old friend the one eyed hans","subset":"tele","task_type":"understanding","prediction":"two days later a very stout little one eyed man clad in a leathern jerkin and wearing a round leathern cap upon his head came toiling up the path to the postern door of trutz thal his back bowed under the burden of a great pedlar s pack it was our old friend the one eyed hans","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1331,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1235\/Lab41-SRI-VOiCES-rm2-tele-sp1235-ch135883-sg0034-mc02-lav-clo-dg030.wav","answer":"he then related what had passed betwixt him and the genie and informed her that he had given him his oath to return at the end of the year to receive death from his hands when they heard this afflicting intelligence they all began to lament in the most distressing manner","subset":"tele","task_type":"understanding","prediction":"he then related what had passed betwixt him and the genie and informed her that he had given him his oath to return at the end of the year to receive death from his hands when they heard this afflicting intelligence they all began to lament in the most distressing manner","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1332,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm2-tele-sp1246-ch124548-sg0014-mc01-stu-clo-dg170.wav","answer":"most of her red cross work ray still needed nursing she explained when carol saw him with his uniform off in a pepper and salt suit and a new gray felt hat she was disappointed he was not major wutherspoon he was raymie","subset":"tele","task_type":"understanding","prediction":"most of her red cross work ray still needed nursing she explained when carol saw him with his uniform off in a pepper and salt suit and a new gray felt hat she was disappointed he was not major weatherspoon he was raymie","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1333,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1246\/Lab41-SRI-VOiCES-rm2-tele-sp1246-ch135815-sg0017-mc01-stu-clo-dg160.wav","answer":"sometimes however if we cannot find a place that just suits us we go quite a distance are your babies born down in that little bedroom in the ground asked jumper the hare of course replied johnny chuck","subset":"tele","task_type":"understanding","prediction":"sometimes however if we cannot find a place that just suits us we go quite a distance are your babies born down in that little bedroom in the ground asked jumper the hare of course replied johnny chuck","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1334,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1259\/Lab41-SRI-VOiCES-rm2-tele-sp1259-ch027120-sg0000-mc02-lav-clo-dg040.wav","answer":"chapter eight at five o'clock the two ladies retired to dress and at half past six elizabeth was summoned to dinner to the civil inquiries which then poured in and amongst which she had the pleasure of distinguishing the much superior solicitude of mister bingley's","subset":"tele","task_type":"understanding","prediction":"chapter eight at five o clock the two ladies retired to dress and at half past six elizabeth was summoned to dinner to the civil inquiries which then poured in and amongst which she had the pleasure of distinguishing the much superior solicitude of mr bingley","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1335,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1271\/Lab41-SRI-VOiCES-rm2-tele-sp1271-ch133279-sg0037-mc02-lav-clo-dg140.wav","answer":"it constitutes a singular power so strangely composed of mingled good and evil that it is at the same time indispensable to the existence of freedom and nearly incompatible with the maintenance of public order","subset":"tele","task_type":"understanding","prediction":"it constitutes a singular power that so strangely composed of mingled good and evil that it is at the same time indispensable to the existence of freedom and merely incompatible with the maintenance of public order","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1336,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm2-tele-sp1272-ch135031-sg0002-mc02-lav-clo-dg090.wav","answer":"i have remained a prisoner only because i wished to be one and with this he stepped forward and burst the stout chains as easily as if they had been threads","subset":"tele","task_type":"understanding","prediction":"i have remained a prisoner only because i wished to be one and with this he stepped forward and burst the stout chains as easily as if they had been threads","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1337,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1272\/Lab41-SRI-VOiCES-rm2-tele-sp1272-ch141231-sg0023-mc02-lav-clo-dg160.wav","answer":"the strength that enables someone in a trance to hold his body stiff and unsupported except at two points the head and heels","subset":"tele","task_type":"understanding","prediction":"The strength that enables someone in a trance to hold his body stiff and unsupported. Except at two points, the head and heels.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1338,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch128226-sg0003-mc01-stu-clo-dg140.wav","answer":"thus did the world once seem to me thus once on a time did i also cast my fancy beyond man like all backworldsmen beyond man forsooth ah ye brethren","subset":"tele","task_type":"understanding","prediction":"thus did the world once seem to me thus once on a time did i also cast my fancy beyond man like all backworldsmen beyond man forsooth ah ye brethren","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1339,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch128240-sg0014-mc01-stu-clo-dg020.wav","answer":"fain likewise would it play with the fire of the fagot and stake and be on thy guard also against the assaults of thy love too readily doth the recluse reach his hand to any one who meeteth him","subset":"tele","task_type":"understanding","prediction":"fain likewise would it play with the fire of the faggot and stake and be on thy guard also against the assaults of thy love too readily doth the recluse reach his hand to any one who meeteth him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1340,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0001-mc02-lav-clo-dg120.wav","answer":"is regarded as certain and conclusive nor does any man ever entertain a doubt where he sees a piece of iron that it will have weight and cohesion of parts as in all other instances which have ever fallen under his observation","subset":"tele","task_type":"understanding","prediction":"is regarded as certain and conclusive nor does any man ever entertain a doubt where he sees a piece of iron that it will have weight and cohesion of parts as in all other instances which have ever fallen under his observation","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1341,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0018-mc01-stu-clo-dg180.wav","answer":"be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to men it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one","subset":"tele","task_type":"understanding","prediction":"be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to men it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1342,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0018-mc02-lav-clo-dg180.wav","answer":"be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to men it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one","subset":"tele","task_type":"understanding","prediction":"be trusted to the uncertain process of reasoning and argumentation were this doubtful with regard to man it seems to admit of no question with regard to the brute creation and the conclusion being once firmly established in the one","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1343,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1392\/Lab41-SRI-VOiCES-rm2-tele-sp1392-ch135659-sg0021-mc02-lav-clo-dg010.wav","answer":"is derived merely from custom it may be asked how it happens that men so much surpass animals in reasoning and one man so much surpasses another has not the same custom the same influence on all","subset":"tele","task_type":"understanding","prediction":"is derived merely from custom it may be asked how it happens that men so much surpass animals in reason and one man so much surpasses another has not the same custom the same influence on all","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1344,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1472\/Lab41-SRI-VOiCES-rm2-tele-sp1472-ch139797-sg0000-mc02-lav-clo-dg100.wav","answer":"chapter thirteen a world of high medical knowledge i spent a long and profitable season in the vicinity of the great dipper witnessing the almost infinite variations of human life as found from world to world and looking upon the wild wastes of the many planets that are not inhabited","subset":"tele","task_type":"understanding","prediction":"chapter thirteen a world of high medical knowledge i spent a long and profitable season in the vicinity of the great dipper witnessing the almost infinite variations of human life as found from world to world and looking upon the wild wastes of the many planets that are not inhabited","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1345,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1536\/Lab41-SRI-VOiCES-rm2-tele-sp1536-ch137608-sg0016-mc01-stu-clo-dg100.wav","answer":"and therewithal she turned her from the window and sir beaumains rode awayward from the castle making great dole and so he rode here and there and wist not where he rode till it was dark night and then it happened him to come to a poor man's house and there he was harboured all that night","subset":"tele","task_type":"understanding","prediction":"and therewithal she turned her from the window and sir beaumains rode awayward from the castle making great dole and so he rode here and there and wist not where he rode till it was dark night and then it happened him to come to a poor man s house and there he was harboured all that night","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1346,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1841\/Lab41-SRI-VOiCES-rm2-tele-sp1841-ch150351-sg0013-mc01-stu-clo-dg070.wav","answer":"and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the indian came out and plunged into the cold water of a near by stream","subset":"tele","task_type":"understanding","prediction":"and after he had entered and all openings were closed he poured water upon the stones until the room was filled with steam after enduring this process as long as he desired the antaeon came out and plunged into the cold water of a nearby stream","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1347,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1867\/Lab41-SRI-VOiCES-rm2-tele-sp1867-ch148436-sg0020-mc02-lav-clo-dg020.wav","answer":"and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothin","subset":"tele","task_type":"understanding","prediction":"and set about frying ham and making coffee this with crackers formed the meal he watched nash eat for a moment of solemn silence and then the foreman looked up to catch a meditative chuckle from the youngster let me in on the joke son nothing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1348,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm2-tele-sp1874-ch143361-sg0012-mc02-lav-clo-dg050.wav","answer":"and his firm moderation was soon rewarded by a solid and honorable peace he maintained with a powerful hand the balance of the west till it was at length overthrown by the ambition of clovis and although unable to assist his rash and unfortunate kinsman","subset":"tele","task_type":"understanding","prediction":"and his firm moderation was soon rewarded by a solid and honorable peace he maintained with a powerful hand the balance of the west till it was at length overthrown by the ambition of clovis and although unable to assist his rash and unfortunate kinsman","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1349,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1874\/Lab41-SRI-VOiCES-rm2-tele-sp1874-ch165702-sg0018-mc01-stu-clo-dg100.wav","answer":"emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four","subset":"tele","task_type":"understanding","prediction":"emancipation announced eighteen sixty three january first emancipation proclaimed november nineteenth gettysburg cemetery address december ninth pardon to rebels proclaimed eighteen sixty four","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1350,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1926\/Lab41-SRI-VOiCES-rm2-tele-sp1926-ch147979-sg0036-mc02-lav-clo-dg160.wav","answer":"several teachers experimented with him they found he had absolute pitch and a remarkable memory as a very young child he could repeat after a fashion any composition that was played for him no matter how many wrong notes he struck he never lost the intention of a passage","subset":"tele","task_type":"understanding","prediction":"several teachers experimented with him they found he had absolute pitch and a remarkable memory as a very young child he could repeat after a fashion any composition that was played for him no matter how many wrong notes he struck he never lost the attention of the passage","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1351,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm2-tele-sp1961-ch145733-sg0016-mc02-lav-clo-dg130.wav","answer":"what does he say asked the princess i really hardly like to tell you answered the lady in waiting oh then you can whisper it to me he is disobliging said the princess and went away","subset":"tele","task_type":"understanding","prediction":"what does he say asked the princess i really hardly like to tell you answered the lady in white and ear oh then you can whisper it to me and to supply to you said the princess and went away","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":8}
+{"index":1352,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1961\/Lab41-SRI-VOiCES-rm2-tele-sp1961-ch149739-sg0028-mc02-lav-clo-dg090.wav","answer":"why of course exclaimed the angel haven't you come to my party didn't you get my invitation i sent you one by mail asked freckles yes said the angel i had to help with the preparations and i couldn't find time to drive out but i wrote you a letter","subset":"tele","task_type":"understanding","prediction":"why of course exclaimed the angel havent you come to my party didn t you get my invitation i sent you one by mail asked freckles yes said the angel i had to help with the preparations and i could n t find time to drive up but i wrote you a letter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":7}
+{"index":1353,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp1963\/Lab41-SRI-VOiCES-rm2-tele-sp1963-ch147036-sg0034-mc02-lav-clo-dg050.wav","answer":"milburgh had gone too far tarling saw his face lengthen and the look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath the confession of odette rider","subset":"tele","task_type":"understanding","prediction":"milburgh had gone too far tarling saw his face lengthen and the look of apprehension in his cold blue eyes then without further hesitation he opened the paper and read the first line took away his breath a confession of odette rider","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1354,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm2-tele-sp2012-ch139358-sg0006-mc01-stu-clo-dg030.wav","answer":"nothing can be truer but while you have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency","subset":"tele","task_type":"understanding","prediction":"nothing can be truer but why we have been noticing that have you not seen that this annoying man never keeps his eyes off my father no matter if he is near to him or far from him and that he seems to have some spiteful secret intention in watching him with such unaccountable persistency","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1355,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2012\/Lab41-SRI-VOiCES-rm2-tele-sp2012-ch139358-sg0007-mc02-lav-clo-dg080.wav","answer":"what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words","subset":"tele","task_type":"understanding","prediction":"what i know not but to force my father to get rid of torres would perhaps be imprudent i repeat it i am afraid though no positive fact enables me to explain my fear to myself and benito seemed to shudder with anger as he said these words","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1356,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2074\/Lab41-SRI-VOiCES-rm2-tele-sp2074-ch147193-sg0010-mc02-lav-clo-dg000.wav","answer":"then she took him by the hand and went into the temple and prayed and came down again with theseus to her home and when a full year was past she led theseus up again to the temple and bade him lift the stone","subset":"tele","task_type":"understanding","prediction":"then she took him by the hand and went into the temple and prayed and came down again with theseus to her home and when a full year was passed she led theseus up again to the temple and bade him lift the stone","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1357,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2074\/Lab41-SRI-VOiCES-rm2-tele-sp2074-ch147193-sg0015-mc02-lav-clo-dg050.wav","answer":"till upon all the mountains there was no hunter so swift as theseus and he killed phaia the wild sow of crommyon which wasted all the land till all the people said surely the gods are with the lad","subset":"tele","task_type":"understanding","prediction":"till upon all the mountains there was no hunter so swift as theseus and he killed phaia the wild sow of chromium which wasted all the land till all the people said surely the gods are with the lad","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1358,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2093\/Lab41-SRI-VOiCES-rm2-tele-sp2093-ch143271-sg0025-mc01-stu-clo-dg120.wav","answer":"at last he crept from me to speak to mister francis it is of no use to stay longer i'm afraid my lad he whispered unless we wait and see whether the hut is left empty when the expedition party comes back","subset":"tele","task_type":"understanding","prediction":"At last, he crept from me to speak to Mr. Francis, it is of no use to stay longer, I am afraid, my lad, he whispered, unless we wait and see whether the hut is left empty. When the expedition party comes back.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1359,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2110\/Lab41-SRI-VOiCES-rm2-tele-sp2110-ch161100-sg0026-mc01-stu-clo-dg180.wav","answer":"it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing","subset":"tele","task_type":"understanding","prediction":"it would be an unwise measure to enter into a dry study you may take my word for it nature has made you a melodist and you would only disturb and perplex yourself reflect a little knowledge is a dangerous thing","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1360,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2149\/Lab41-SRI-VOiCES-rm2-tele-sp2149-ch007239-sg0011-mc01-stu-clo-dg110.wav","answer":"god's firm foundation stands having this seal the lord knew those who are his and","subset":"tele","task_type":"understanding","prediction":"Gods firm foundation stands. Having this seal, the Lord knew those who are his and.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1361,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm2-tele-sp2285-ch124595-sg0015-mc02-lav-clo-dg020.wav","answer":"without seeking to probe further into matters in which he had no personal concern it was hardly to be supposed however that the local population would show equal forbearance curiosity was widespread","subset":"tele","task_type":"understanding","prediction":"without seeking to probe further into matters in which he had no personal concern it was hardly to be supposed however that the local population would show equal forbearance curiosity was widespread","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1362,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2285\/Lab41-SRI-VOiCES-rm2-tele-sp2285-ch163381-sg0000-mc01-stu-clo-dg040.wav","answer":"by and by when we got up we turned over the truck the gang had stole off of the wreck and found boots and blankets and clothes and all sorts of other things and a lot of books and a spyglass","subset":"tele","task_type":"understanding","prediction":"By and by, we got up. We turned over the truck. The gang had stole off of the wreck, found boots and blankets and clothes and all sorts of other things and a lot of books and a spyglass.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1363,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2294\/Lab41-SRI-VOiCES-rm2-tele-sp2294-ch169656-sg0028-mc02-lav-clo-dg000.wav","answer":"the moors then boarded the san antonio and took her in tow when close to the land the captain was rowed ashore and the pirates spent part of the night in unloading the cargo next morning the san antonio was seen drifting out to sea and the captain who was afraid of being put to death","subset":"tele","task_type":"understanding","prediction":"the moors then boarded the san antonio and took her in tow when close to the land the captain was rowed ashore and the pirates spent part of the night in unloading the cargo next morning the san antonio was seen drifting out to sea and the captain who was afraid of being put to death","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1364,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-tele-sp2412-ch153948-sg0001-mc02-lav-clo-dg130.wav","answer":"it will be seen that i did not succeed in my design and that however much i may have met with that was new and strange i have been unable to reap any pecuniary advantage","subset":"tele","task_type":"understanding","prediction":"it will be seen that i did not succeed in my design and that however much i may have met with that was new and strange i have been unable to reap any pecuniary advantage","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1365,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2412\/Lab41-SRI-VOiCES-rm2-tele-sp2412-ch153954-sg0014-mc02-lav-clo-dg050.wav","answer":"in about four hours of walking from the time we started and after passing two or three more villages we came upon a considerable town and my guides made many attempts to make me understand something but i gathered no inkling of their meaning except that i need be under no apprehension of danger","subset":"tele","task_type":"understanding","prediction":"in about four hours of walking from the time we started and after passing two or three more villages we came upon a considerable town and my guides made many attempts to make me understand something but i gathered no inkling of their meaning except that i need be under no apprehension of danger","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1366,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2481\/Lab41-SRI-VOiCES-rm2-tele-sp2481-ch012731-sg0012-mc02-lav-clo-dg060.wav","answer":"stir them while boiling to keep them from spotting this dye will make a salmon or orange color according to the strength of it and the time the goods remain in drain them out of the dye and dry them quick in the shade when dry wash them in soft soap suds","subset":"tele","task_type":"understanding","prediction":"stir them while boiling to keep them from spotting this dye will make a salmon or orange color according to the strength of it and the time the goods remain in drain them out of the dye and dry them quick in the shade when dry wash them in soft soap suds","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1367,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2691\/Lab41-SRI-VOiCES-rm2-tele-sp2691-ch156755-sg0035-mc01-stu-clo-dg120.wav","answer":"grandpa had the grave enclosed with a white paling and we children planted castilian rose bushes at the head and foot of the mound and carried water to them from the house and in time their branches met and the grave was a bed of fragrant blossoms","subset":"tele","task_type":"understanding","prediction":"grandpa had the grave enclosed with white paling and we children planted castilian rose bushes at the head and foot of the mound and carried water to them from the house and in time their branches met and the grave was a bed of fragrant blossoms","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1368,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2758\/Lab41-SRI-VOiCES-rm2-tele-sp2758-ch161217-sg0020-mc01-stu-clo-dg100.wav","answer":"but though nemesis in her original character was the distributor of rewards as well as punishments the world was so full of sin that she found but little occupation in her first capacity and hence became finally regarded as the avenging goddess only","subset":"tele","task_type":"understanding","prediction":"but though nemesis in her original character was the distributor of rewards as well as punishments the world was so full of sin that she found but little occupation in her first capacity and hence became finally regarded as the avenging goddess only","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1369,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2803\/Lab41-SRI-VOiCES-rm2-tele-sp2803-ch154320-sg0000-mc01-stu-clo-dg080.wav","answer":"fortunately will halley was not a man in a hurry and did not use a press of canvas or his masts would inevitably have come down","subset":"tele","task_type":"understanding","prediction":"fortunately will halley was not a man in a hurry and did not use oppressive canvas or his mass would inevitably have come down","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1370,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm2-tele-sp2911-ch012359-sg0000-mc01-stu-clo-dg060.wav","answer":"fit for drink a country without a fit drink for cheese has no cheese fit for drink greece was the first country to prove its epicurean fitness according to the old saying above for it had wine to tipple","subset":"tele","task_type":"understanding","prediction":"fit for drink a country without a fit drink for cheese has no cheese fit for drink greece was the first country to approve its epicurean fitness according to the old saying above for it had wine to tipple","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1371,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp2911\/Lab41-SRI-VOiCES-rm2-tele-sp2911-ch012359-sg0022-mc02-lav-clo-dg180.wav","answer":"with any caraway seeded cheese or cream cheese with a handy saucer of caraway seeds in the section of france devoted to gin the juniper berries that flavor the drink also go into a local cheese fromage fort","subset":"tele","task_type":"understanding","prediction":"With any caraway seeded cheese or cream cheese with a handy saucer of caraway seeds in the section of France devoted to gin, the juniper berries that flavor the drink also go into a local cheese, Formage Port.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1372,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp3368\/Lab41-SRI-VOiCES-rm2-tele-sp3368-ch170950-sg0014-mc02-lav-clo-dg020.wav","answer":"why he said are they not capable of defending themselves no i said not if we were right in the principle which was acknowledged by all of us when we were framing the state the principle as you will remember was that one man cannot practise many arts with success","subset":"tele","task_type":"understanding","prediction":"why he said are they not capable of defending themselves no i said it is not if we were right that the principle which was acknowledged by all of us when we were framing this state the principle as you will remember was that one man cannot practise many arts with success","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1373,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-tele-sp3446-ch144019-sg0006-mc01-stu-clo-dg080.wav","answer":"preceded beche de mer english beche de mer was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose beche de mer english is a splendid argument for the esperanto enthusiasts","subset":"tele","task_type":"understanding","prediction":"preceded bechdeler english bechdeler was purely fortuitous but it was fortuitous in the deterministic way also from the fact that out of the need the lingo arose bechdeler english is a splendid argument for the esperanto enthusiasts","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":1374,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp3446\/Lab41-SRI-VOiCES-rm2-tele-sp3446-ch176270-sg0019-mc01-stu-clo-dg140.wav","answer":"or submit to any terms that could violate their liberty they then made arrangements for the defense of the city in the meantime the florentine forces were not idle and after innumerable mischiefs done to the country","subset":"tele","task_type":"understanding","prediction":"or submit to any terms that could violate their liberty they then made arrangements for the defence of the city in the meantime the florentine forces were not idle and after innumerable mischiefs done to the country","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1375,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_1212-3521\/sp3483\/Lab41-SRI-VOiCES-rm2-tele-sp3483-ch174132-sg0022-mc02-lav-clo-dg020.wav","answer":"then for the last time i saw the earth an enduring globule of radiant blue swimming in an eternity of ether and there i a fragile flake of soul dust flickered silently across the void from the distant blue into the expanse of the unknown","subset":"tele","task_type":"understanding","prediction":"then for the last time i saw the earth and a girding globule of radiant blue swimming in an eternity of ether and there i fragile flake of soul dust flickered silently across the void from the disc of blue into the expanse of the unknown","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1376,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp3549\/Lab41-SRI-VOiCES-rm2-tele-sp3549-ch171171-sg0001-mc02-lav-clo-dg040.wav","answer":"and so much of the wall as enclosed the city on the west side this wall was spared in order to afford a camp for such as were to lie in garrison as were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified","subset":"tele","task_type":"understanding","prediction":"And so much of the wall as enclosed, the city on the west side, this wall was spared in order to afford a camp for such as were to lie in garrison. As were the towers also spared in order to demonstrate to posterity what kind of city it was and how well fortified.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1377,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp3923\/Lab41-SRI-VOiCES-rm2-tele-sp3923-ch174992-sg0016-mc01-stu-clo-dg050.wav","answer":"hoping that in spite of the sacrilege committed he might be able to face a world that would be ignorant of his crime as the vulpicide on the afternoon of the day of the deed went along the corridor to his room one maid servant whispered to another and the poor victim of an imperfect sight","subset":"tele","task_type":"understanding","prediction":"hoping that in spite of the sacrilege committed he might be able to face a world that would be ignorant of his crime as the vulpo side on the afternoon of the day of the deed went along the corridor to his room one maid servant whispered to another and the poor victim of an imperfect sight","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1378,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp3972\/Lab41-SRI-VOiCES-rm2-tele-sp3972-ch170212-sg0014-mc01-stu-clo-dg020.wav","answer":"not unfrequently the shepherd was startled by the blare of trumpets and peering out beheld a cohort sometimes a legion in march and when the glittering crests were gone and the excitement incident to the intrusion over he bent himself to evolve the meaning of the eagles and gilded globes of the soldiery and the charm of a life so the opposite of his own yet these men rude and simple as they were had a knowledge and a wisdom of their own","subset":"tele","task_type":"understanding","prediction":"not unfrequently the shepherd was startled by the blare of trumpets and peering out beheld a cohort sometimes a legion in march and when the glittering crests were gone and the excitement incident to the intrusion over he bent himself to evolve the meaning of the eagles and gilded globes of the soldiery and the charm of a life so the opposite of his own yet these men rude and simple as they were had a knowledge and a wisdom of their own","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1379,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp3994\/Lab41-SRI-VOiCES-rm2-tele-sp3994-ch011512-sg0019-mc02-lav-clo-dg000.wav","answer":"recently power commissioner of new york city and the most capable power engineer in north america who following benda by two or three months resigned his position and accepted what his letter termed the place of director of power in the science community","subset":"tele","task_type":"understanding","prediction":"recently power commissioner of new york city and the most capable power engineer in north america who following benda by two or three months resigned his position and accepted what his letter termed the place of director of power in the science community","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1380,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4010\/Lab41-SRI-VOiCES-rm2-tele-sp4010-ch010801-sg0016-mc02-lav-clo-dg000.wav","answer":"is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne","subset":"tele","task_type":"understanding","prediction":"is the helping of our fellows i do not seek to point out this commending of our spirits to the father as a duty that is to turn the highest privilege we possess into a burden grievous to be borne","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1381,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm2-tele-sp4064-ch012118-sg0036-mc02-lav-clo-dg020.wav","answer":"his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her","subset":"tele","task_type":"understanding","prediction":"his time has not come yet senorita but when it does this must be the hand she lifted her own right hand with a significant movement as she said this and glided out into the darkness and was gone ere kate could recall her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1382,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm2-tele-sp4064-ch019132-sg0034-mc01-stu-clo-dg060.wav","answer":"nothing said the other she is simply ruining herself said oliver i've been trying to get reggie mann to have her introduced to missus devon but he says he wouldn't dare to take the risk no i presume not said montague","subset":"tele","task_type":"understanding","prediction":"nothing said the other she is simply ruining herself said oliver i have been trying to get reggie mann to have her introduced to mrs devon but he says he wouldn't dare to take the risk no i presume not said montague","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1383,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4064\/Lab41-SRI-VOiCES-rm2-tele-sp4064-ch077779-sg0032-mc02-lav-clo-dg090.wav","answer":"don't ask me laughed the idiot i don't know yet i admire all the candidates personally very much but what are your politics republican or democratic asked the lawyer oh that's different said the idiot","subset":"tele","task_type":"understanding","prediction":"don t ask me laughed the idiot i don t know yet i admire all the candidates personally very much but what are your politics republican or democratic asked the lawyer oh that s different said the idiot","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1384,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4145\/Lab41-SRI-VOiCES-rm2-tele-sp4145-ch014013-sg0023-mc01-stu-clo-dg050.wav","answer":"and the new byre you will think a prodigious improvement our dear little grand niece is in great health and much improved we reckon her extremely like our family particularly becky though she has a great look of bella at the same time then she laughs","subset":"tele","task_type":"understanding","prediction":"and the new buyer you will think a prodigious improvement our dear little grand niece is in great health and much improved we reckon her extremely like our family particularly becky though she has a great look of bella at the same time then she laughs","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1385,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4331\/Lab41-SRI-VOiCES-rm2-tele-sp4331-ch057179-sg0039-mc02-lav-clo-dg150.wav","answer":"were at once obliterated from the duchess's bosom arabella with many expressions of thanks and a good humoured countenance left the room cursing the untowardness of her fate which would let nothing run smooth lord rufford was to come that at any rate was now almost certain","subset":"tele","task_type":"understanding","prediction":"were at once obliterated from the duchess bosom arabella with many expressions of thanks and a good humoured countenance left the room cursing the untowardness of her fate which would let nothing run smooth lord rufford was to come that at any rate was now almost certain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1386,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4427\/Lab41-SRI-VOiCES-rm2-tele-sp4427-ch020028-sg0015-mc02-lav-clo-dg030.wav","answer":"and indisputably praiseworthy she was so good natured however and so happy in her delusion that i could not find it in my heart to remonstrate very vehemently except when she would make me listen to her interminable lectures upon the importance","subset":"tele","task_type":"understanding","prediction":"and indisputably praiseworthy she was so good natured however and so happy in her delusion that i could not find it in my heart to remonstrate very vehemently except when she would make me listen to her interminable lectures upon the importance","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1387,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4438\/Lab41-SRI-VOiCES-rm2-tele-sp4438-ch048525-sg0015-mc01-stu-clo-dg120.wav","answer":"then when he began to talk about the willows she found that such an idea as alterations hadn't entered his head she was to sleep in the very room that had been his and vera's in the very bed and positively","subset":"tele","task_type":"understanding","prediction":"then when he began to talk about the willows she found that such an idea as alterations hadn t entered his head she was to sleep in the very room that had been his and vera s in the very bed and positively","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1388,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4441\/Lab41-SRI-VOiCES-rm2-tele-sp4441-ch076262-sg0035-mc02-lav-clo-dg050.wav","answer":"they went to the vaults and engaged a private room where breakfast was served to them has my hair turned grey asked rehnhjelm passing his hand over his hair which was damp and clung closely to his skull no old man that doesn't often happen even i'm not grey","subset":"tele","task_type":"understanding","prediction":"they went to the vault and engaged a private room where breakfast was served to them has my hair turned grey asked wrenholme passing his hand over his hair which was damp and clung closely to his skull no old man that does not often happen even i am not grey","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1389,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4535\/Lab41-SRI-VOiCES-rm2-tele-sp4535-ch279856-sg0025-mc01-stu-clo-dg050.wav","answer":"star floated over the fence he had cleared it by a foot marjorie wheeled about dismounted and readjusted the stirrups there she said now now go i can never thank you he began don't please don't even try she interrupted","subset":"tele","task_type":"understanding","prediction":"star floated over the fence he had cleared it by a foot marjorie wheeled about dismounted and readjusted the stirrups there she said now now go i can never thank you he began dont please dont even try she interrupted","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1390,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4586\/Lab41-SRI-VOiCES-rm2-tele-sp4586-ch061758-sg0016-mc02-lav-clo-dg160.wav","answer":"were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of head gear it was possible he might have seen fit to change the fashion","subset":"tele","task_type":"understanding","prediction":"were not uncommon scores of southerners wore them in texas as elsewhere but he knew that the young irishman was accustomed to carry a mexican sombrero a very different kind of headgear it was possible he might have seen fit to change the fashion","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1391,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4839\/Lab41-SRI-VOiCES-rm2-tele-sp4839-ch015307-sg0029-mc02-lav-clo-dg130.wav","answer":"everybody was sent out of the room save the captains to whom the lord of la palisse made known the emperor's letter which was read twice for the better understanding of it they all looked at one another laughing for to see who would speak first then said the lord of ymbercourt to the lord of la palisse","subset":"tele","task_type":"understanding","prediction":"everybody was sent out of the room save the captains to whom the lord of la police made known the emperor s letter which was read twice for the better understanding of it they all looked at one another laughing for to see who would speak first then said the lord of imbuko to the lord of la police","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1392,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm2-tele-sp4848-ch029108-sg0009-mc02-lav-clo-dg030.wav","answer":"bigger child why what's two hundred thousand dollars pocket money mere pocket money look at the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along behind it","subset":"tele","task_type":"understanding","prediction":"bigger child why what's two hundred thousand dollars pocket money where pocket money look the railroad did you forget the railroad it ain't many months till spring it will be coming right along and the railroad swimming right along they come to","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1393,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp4848\/Lab41-SRI-VOiCES-rm2-tele-sp4848-ch029108-sg0034-mc01-stu-clo-dg040.wav","answer":"a spectacle of inconceivable sublimity so don't you see we've got the rail road to fall back on and in the meantime what are we worrying about that two hundred thousand dollars appropriation for that's all right","subset":"tele","task_type":"understanding","prediction":"a spectacle of inconceivable solemnity so don t say we ve got the railroad to fall back on and in the meantime what are we worrying about that two hundred thousand dollar appropriation for that s all right","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":9}
+{"index":1394,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5189\/Lab41-SRI-VOiCES-rm2-tele-sp5189-ch059288-sg0037-mc01-stu-clo-dg060.wav","answer":"combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting","subset":"tele","task_type":"understanding","prediction":"combativeness enormously developed alimentiveness large while conscientiousness is entirely wanting on the other hand look at this cranium here combativeness is a nullity absolutely wanting","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1395,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5338\/Lab41-SRI-VOiCES-rm2-tele-sp5338-ch024640-sg0001-mc02-lav-clo-dg020.wav","answer":"mister morton replied that far from making any claim upon his good opinion his only wish and the sole purpose of his visit was to find out the means of deserving it","subset":"tele","task_type":"understanding","prediction":"Mr. Morton replied that far from making any claim upon his good opinion, his only wish and the sole purpose of his visit was to find out the means of deserving it.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1396,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5338\/Lab41-SRI-VOiCES-rm2-tele-sp5338-ch024640-sg0003-mc02-lav-clo-dg000.wav","answer":"mister morton seemed particularly struck with the account of waverley's visit to donald bean lean","subset":"tele","task_type":"understanding","prediction":"Mr. Morton seemed particularly struck with the account of Waverley S visit to Donald B. Wee.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1397,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5400\/Lab41-SRI-VOiCES-rm2-tele-sp5400-ch003587-sg0006-mc01-stu-clo-dg120.wav","answer":"p'raps he's been eating too much eating said polly oh mamsie he hasn't had anything and she pointed with shame and remorse to the seed cup with only a few dried husks in the very bottom oh polly began missus pepper but seeing the look on her face she changed her tone for one more cheerful","subset":"tele","task_type":"understanding","prediction":"perhaps he has been eating too much eating said polly oh mamsie he hasn t had anything and she pointed with shame and remorse to the seed cup with only a few dried husks in the very bottom oh polly began mrs pepper but seeing the look on her face she changed her tone for one more cheerful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1398,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5400\/Lab41-SRI-VOiCES-rm2-tele-sp5400-ch034478-sg0001-mc02-lav-clo-dg120.wav","answer":"it's not right for you not to go to the meetings and altogether to keep out of the district business if decent people won't go into it of course it's bound to go all wrong we pay the money and it all goes in salaries and there are no schools nor district nurses nor midwives nor drugstores","subset":"tele","task_type":"understanding","prediction":"it is not right for you not to go to the meetings and altogether to keep out of the district business if decent people don t go into it of course it s bound to go all wrong we pay the money and it all goes in salaries and there are no schools nor district nurses nor midwives nor drug stores","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":5}
+{"index":1399,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5400\/Lab41-SRI-VOiCES-rm2-tele-sp5400-ch034479-sg0006-mc01-stu-clo-dg040.wav","answer":"it's splendid as exercise only you'll hardly be able to stand it said sergey ivanovitch without a shade of irony i've tried it it's hard work at first but you get into it i dare say i shall manage to keep it up really what an idea but tell me","subset":"tele","task_type":"understanding","prediction":"it splendid as exercise only youll hardly be able to stand it said sergey ivanovitch without a shade of irony i have tried it it is hard work at first but you get into it i dare say i shall manage to keep it up really what an idea but tell me","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1400,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5583\/Lab41-SRI-VOiCES-rm2-tele-sp5583-ch038026-sg0025-mc01-stu-clo-dg100.wav","answer":"and as soon as ever he put on the wig of moss he became so ugly and pale and miserable to look at no one would have known him again then he went up to the king's palace and begged first for leave to be in the kitchen and bring in wood and water for the cook","subset":"tele","task_type":"understanding","prediction":"and as soon as ever he put on the wig of moss he became so ugly and pale and miserable to look at no one would have known him again then he went up to the king s palace and begged first for leave to be in the kitchen and bring in wood and water for the cook","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1401,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5583\/Lab41-SRI-VOiCES-rm2-tele-sp5583-ch041919-sg0006-mc01-stu-clo-dg110.wav","answer":"laid it in the place where he usually slept and then hid himself in the night the draken came and each one hit the log a blow with his hatchet till it flew in pieces then they believed their object was gained and they lay down again","subset":"tele","task_type":"understanding","prediction":"laid it in the place where he usually slept and then hid himself in the night the draken came and each one hit the log a blow with his hatchet till it flew in pieces then they believed their object was gained and they lay down again","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1402,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm2-tele-sp5717-ch094876-sg0004-mc02-lav-clo-dg120.wav","answer":"so the hungry adventurers suddenly found themselves provided with plenty to eat and to drink they lost no time in picking the biggest strawberries and ripest oranges and soon had feasted to their hearts content","subset":"tele","task_type":"understanding","prediction":"so the hungry adventurers suddenly found themselves provided with plenty to eat and to drink they lost no time in picking the biggest strawberries and ripest oranges and soon had feasted to their hearts content","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1403,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5717\/Lab41-SRI-VOiCES-rm2-tele-sp5717-ch100145-sg0020-mc02-lav-clo-dg160.wav","answer":"a few looked apprehensively at the ceiling as though expecting the hellburners and planet busters and nega matter bombs at any moment then one of the members among the benches rose we don't know how we are going to do it prince trevannion he said","subset":"tele","task_type":"understanding","prediction":"a few looked apprehensively at the ceiling as though expecting to hell burners and planet busters and nega matter bombs at any moment then one of the members upon the benches rose we don t know how we are going to do it prince trevannion he said","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1404,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5789\/Lab41-SRI-VOiCES-rm2-tele-sp5789-ch057195-sg0025-mc01-stu-clo-dg040.wav","answer":"john morton might die and then who could tell whether lady ushant would ever return to cheltenham in this way the short lived peace soon came to an end especially as missus masters endeavoured to utilize for general family purposes","subset":"tele","task_type":"understanding","prediction":"john morton might die and then he could tell whether lady ushant would ever return to cheltenham in this way their short lived peace soon came to an end especially as mrs masters endeavoured to utilise for general family purposes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1405,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5802\/Lab41-SRI-VOiCES-rm2-tele-sp5802-ch066347-sg0015-mc02-lav-clo-dg110.wav","answer":"i rubbed my eyes and looked about me it was true the great auditorium was empty and was gradually darkening i put on my hat and walked out refreshed having slept from five twenty until twelve or six hours and forty minutes straight that was one instance","subset":"tele","task_type":"understanding","prediction":"i rubbed my eyes and looked about me it was true the great auditorium was empty and was gradually darkening i put on my hat and walked out in a daze having slept from five twenty until twelve or six hours and forty minutes straight that was one instance","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1406,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5802\/Lab41-SRI-VOiCES-rm2-tele-sp5802-ch066347-sg0037-mc02-lav-clo-dg130.wav","answer":"squills paregoric and other nasty tasting things they have now this alone will serve to popularize sickness and instead of being driven out of business their trade will pick up and the doctor and the doctor's gig and all the appurtenances of his profession","subset":"tele","task_type":"understanding","prediction":"squeals berrigarrick and other nasty tasting things they have now this alone will serve to popularize sickness and instead of being driven out of business their trade will pick up and the doctor and the doctors gig and all the appurtenances of his profession","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1407,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5802\/Lab41-SRI-VOiCES-rm2-tele-sp5802-ch076043-sg0024-mc02-lav-clo-dg150.wav","answer":"he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burthen without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great gnomon of silbury","subset":"tele","task_type":"understanding","prediction":"he wrestled with his ignorance as if he thought that by talking he might presently worry out some picture of this forgotten world without metals without beasts of burden without letters without any sculpture that has left a trace and yet with a sense of astronomical fact clear enough to raise the great gnomon of silbury","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1408,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5935\/Lab41-SRI-VOiCES-rm2-tele-sp5935-ch043322-sg0019-mc01-stu-clo-dg020.wav","answer":"after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not","subset":"tele","task_type":"understanding","prediction":"after the discourse he said it is this that will need special marshalling i suppose no rehearsal will be possible scarcely said oliver smiling the master of ceremonies sighed i feared not","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1409,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp5968\/Lab41-SRI-VOiCES-rm2-tele-sp5968-ch071320-sg0031-mc01-stu-clo-dg180.wav","answer":"and paused for a continuance of the communication thus auspiciously commenced you are doctor parkes i take it for granted said marston in the same tone your most obedient humble servant sir replied he with the polite formality of the day and another grave bow doctor demanded marston","subset":"tele","task_type":"understanding","prediction":"and paused for a continuance of the communication thus auspiciously commenced you are doctor parkes i take it for granted said marston in the same tone your most obedient humble servant sir replied he with the polite formality of the day and another grave bow doctor demanded marston","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1410,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp6099\/Lab41-SRI-VOiCES-rm2-tele-sp6099-ch069550-sg0044-mc02-lav-clo-dg120.wav","answer":"like an aureole above the head of yuki chan's mother as she knelt with clasped hands before the buddha on the shelf her moving lips had only one refrain the child the child","subset":"tele","task_type":"understanding","prediction":"like an aureole above the head of yuki chan s mother as she knelt with clasped hands before the buddha on the shelf her moving lips had only one refrain the child the child","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1411,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_3549-6147\/sp6147\/Lab41-SRI-VOiCES-rm2-tele-sp6147-ch034606-sg0018-mc01-stu-clo-dg090.wav","answer":"the gentleman behind him chastised him for this by a prick of his sword which made him spring round another prick in the back warned the fellow that one of noble blood was behind him and so on each one wounding him in his turn when the man closed round by the circle of swords and covered with blood","subset":"tele","task_type":"understanding","prediction":"the gentleman behind him chastised him for this by a prick of his sword which made him spring round another prick at the back warned the fellow that one of noble blood was behind him and so on each one wounding him in his turn when the man closed round by the circle of swords and covered with blood","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1412,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6241\/Lab41-SRI-VOiCES-rm2-tele-sp6241-ch061946-sg0020-mc01-stu-clo-dg060.wav","answer":"at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor's legs and left him standing with both feet on a separate stone like the colossus of rhodes","subset":"tele","task_type":"understanding","prediction":"at length the sturdy little pony spreading out his legs in a stiff and ludicrous attitude got from under the professor s legs and left him standing with both feet on a separate stone like the colossus of rhodes","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1413,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6319\/Lab41-SRI-VOiCES-rm2-tele-sp6319-ch057405-sg0001-mc02-lav-clo-dg100.wav","answer":"after jupiter had bound prometheus on mount caucasus and had sent diseases and cares into the world men became very very wicked","subset":"tele","task_type":"understanding","prediction":"after jupiter had bound prometheus on mount caucasus and had sent diseases and cares into the world men became very very wicked","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1414,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6319\/Lab41-SRI-VOiCES-rm2-tele-sp6319-ch275224-sg0006-mc02-lav-clo-dg020.wav","answer":"then the wind took another frolic round the garden and made up to the large white lily into whose refined ear he whispered a doubt as to the necessity or advantage of her thick powerful stem being propped up against a stupid ugly stick","subset":"tele","task_type":"understanding","prediction":"then the wind took another frolic round the garden and made up to the large white lily into whose refined ear he whispered a doubt as to the necessity or advantage of her thick powerful stem being propped up against a stupid ugly stick","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1415,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm2-tele-sp6385-ch034669-sg0006-mc02-lav-clo-dg140.wav","answer":"as the simple instinct of a faithful animal an animal is a lucid somnambulist there are cases in which the dog feels that he should follow his master others in which he should precede him then the animal takes the direction of sense","subset":"tele","task_type":"understanding","prediction":"as the simple instinct of a faithful animal an animal is a lucid synapheus there are cases in which the dog feels that he should follow his master others in which he should precede him then the animal takes the direction of sense","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1416,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6385\/Lab41-SRI-VOiCES-rm2-tele-sp6385-ch220959-sg0005-mc02-lav-clo-dg150.wav","answer":"on the contrary they are intellectual realities so love is a mental reality and not sensible for this reality the ear does not hear the eye does not see the smell does not perceive","subset":"tele","task_type":"understanding","prediction":"on the contrary they are intellectual realities so love is a mental reality and not sensible for this reality the ear does not hear the eye does not see the smell does not perceive","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1417,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm2-tele-sp6415-ch111615-sg0011-mc01-stu-clo-dg170.wav","answer":"came very near ending as a complete cynic though in what f p a would call his lastline he managed to wriggle into a more hopeful mood the first valuable discovery that the colyumist is likely to make is that all minds are very much the same","subset":"tele","task_type":"understanding","prediction":"came very near ending as a complete cynic though in what fpa would call his last line he managed to wriggle into a more hopeful mood the first valuable discovery that the columnists is likely to make is that all minds are very much the same","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":6}
+{"index":1418,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6415\/Lab41-SRI-VOiCES-rm2-tele-sp6415-ch116629-sg0007-mc01-stu-clo-dg060.wav","answer":"come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to","subset":"tele","task_type":"understanding","prediction":"come a little nearer to the well no one knows who may be behind those trees now listen can you tell me what is going wrong with dietrich he never whistles now he never laughs and his mother looks so sad and she rarely speaks even to answer when spoken to","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1419,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm2-tele-sp6454-ch093938-sg0016-mc01-stu-clo-dg080.wav","answer":"i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business","subset":"tele","task_type":"understanding","prediction":"i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1420,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm2-tele-sp6454-ch093938-sg0016-mc02-lav-clo-dg080.wav","answer":"i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business","subset":"tele","task_type":"understanding","prediction":"i gave two of the ponies slaps which started them off at a lope across the railroad tracks i swung myself into the saddle of the third and flicked him with the loose ends of the bridle in a way which made him understand that i meant business","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1421,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6454\/Lab41-SRI-VOiCES-rm2-tele-sp6454-ch093938-sg0018-mc02-lav-clo-dg000.wav","answer":"two hundred feet therefore brought me to the edge of the town and i wheeled my pony and rode down behind the rear of the buildings in turning i looked back and saw half a dozen mounted men already in pursuit","subset":"tele","task_type":"understanding","prediction":"200 feet, therefore, brought me to the edge of the town. And I wheeled my pony and rode down behind the rear of the buildings. In turning, I looked back and saw half a dozen mounted men already in pursuit.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1422,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-tele-sp6544-ch067863-sg0004-mc02-lav-clo-dg050.wav","answer":"and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had not come into the house he seemed much older to sylvia than he did on her visit to the plantation in october","subset":"tele","task_type":"understanding","prediction":"and wished that they could again visit the plantation philip had brought sylvia a letter from flora thanking her for the locket and hoping that they would see each other again philip had not come into the house he seemed much older to sylvia than he did on her visit to the plantation in october","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1423,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6544\/Lab41-SRI-VOiCES-rm2-tele-sp6544-ch231862-sg0036-mc01-stu-clo-dg000.wav","answer":"he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motion of despair lost lost he muttered all lost","subset":"tele","task_type":"understanding","prediction":"he cried out savagely and fought with the strength of two men however he could do little against his four adversaries and worn out with the struggle collapsed suddenly on to the dusty floor with a motionless stare lost lost he muttered all lost","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1424,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6574\/Lab41-SRI-VOiCES-rm2-tele-sp6574-ch070756-sg0035-mc02-lav-clo-dg170.wav","answer":"the labour of winding among the little paths of the mountain and fixing my feet firmly as i advanced perplexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the halfway resting place and seated myself beside the fountain","subset":"tele","task_type":"understanding","prediction":"the labour of winding among the little paths of the mountain and fixing my feet firmly as i advanced vexed me occupied as i was by the emotions which the occurrences of the day had produced night was far advanced when i came to the half way resting place and seated myself beside the fountain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1425,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6848\/Lab41-SRI-VOiCES-rm2-tele-sp6848-ch076049-sg0024-mc02-lav-clo-dg050.wav","answer":"and it shall be happy for you all i ask all i ask protect guard cherish for to mister gunter lake it seemed there could be no lovelier thing in life than a wife","subset":"tele","task_type":"understanding","prediction":"and it shall be happy for you all i ask all i ask protect guard cherish for to mr clinton lake it seemed there could be no lovelier thing in life than a wife","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1426,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6895\/Lab41-SRI-VOiCES-rm2-tele-sp6895-ch092805-sg0017-mc01-stu-clo-dg110.wav","answer":"and waved frantically his soft brimmed hat then he strayed through the smoke dropped into the vacant chair at our table and pulled out cigarettes the evening was at the period when reserve is thawed one of us mentioned three wuerzburgers to the waiter","subset":"tele","task_type":"understanding","prediction":"and waved frantically his soft brimmed hat then he strayed through the smoke dropped into the vacant chair at our table and pulled out cigarettes the evening was at the period when reserve is thawed one of us mentioned three wurzburgers to the waiter","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1427,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm2-tele-sp6965-ch277898-sg0012-mc02-lav-clo-dg100.wav","answer":"but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart's action was the doctor's verdict","subset":"tele","task_type":"understanding","prediction":"but his eyes bulged a little and his cheeks took on the mottled hues of an ethnographical map of the balkan peninsula that same day at sundown he died failure of the heart s action was the doctor s verdict","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1428,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp6965\/Lab41-SRI-VOiCES-rm2-tele-sp6965-ch291718-sg0029-mc01-stu-clo-dg090.wav","answer":"do you suppose it would do any good to shave the cat all over at this i could not resist the impulse to scream and your mother said i do believe the creature knows whenever we speak about her","subset":"tele","task_type":"understanding","prediction":"do you suppose it would do any good to shave the cat all over at this i could not resist the impulse to scream and your mother said i do believe the creature knows whenever we speak about her","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1429,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7000\/Lab41-SRI-VOiCES-rm2-tele-sp7000-ch083706-sg0015-mc02-lav-clo-dg000.wav","answer":"if not considerable in height was great in girth he would certainly have turned the scale at sixteen stone i felt that to cricketers who intended to play mister hedges any objections which i might urge would appear quite trivial","subset":"tele","task_type":"understanding","prediction":"if not considerable in height was great in girth it would certainly have turned the scale at sixteen a stone i felt that to cricketers who intended to play mr hedges any objections which i might urge would appear quite trivial","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1430,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7095\/Lab41-SRI-VOiCES-rm2-tele-sp7095-ch088489-sg0002-mc02-lav-clo-dg120.wav","answer":"instead of a steady progression of knowledge in this field there was a distinct retrogression according to the prevailing belief the earth was soon to be destroyed and the collecting of knowledge was futile and any study of its nature was vain","subset":"tele","task_type":"understanding","prediction":"instead of a steady progression of knowledge in this field there was a distinct retrogression according to the prevailing belief the earth was soon to be destroyed and the collecting of knowledge was futile and any study of its nature was vain","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1431,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-tele-sp7148-ch059157-sg0015-mc02-lav-clo-dg050.wav","answer":"she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny brawne","subset":"tele","task_type":"understanding","prediction":"she was unquestionably his good fairy as a poet this is the only matter upon which one is seriously disposed to quarrel with sir sidney colvin as a biographer he does not emphasize as he ought the debt we are under to fanny brawne","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1432,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-tele-sp7148-ch059157-sg0037-mc01-stu-clo-dg150.wav","answer":"his morbidness his mawkishness his fascination as by serpents on the other but in the resultant portrait it is a too respectable and virile keats that emerges keats was more virile as a man","subset":"tele","task_type":"understanding","prediction":"his morbidness his mawkishness his fascination as by serpents on the other but in the resultant portrait it is a too respectable and virile keats that emerges keats was more virile as a man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1433,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7148\/Lab41-SRI-VOiCES-rm2-tele-sp7148-ch082991-sg0013-mc02-lav-clo-dg170.wav","answer":"are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addle pate with a vengeance the knave has been speaking treason of the king's highness said the tall man","subset":"tele","task_type":"understanding","prediction":"are you gone mad or do you mistake me for a sheep or a bullock that you attack me in this fashion my strong ale must have got into your addled pate with a vengeance the knave has been speaking treason of the king s highness said the tall man","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1434,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7276\/Lab41-SRI-VOiCES-rm2-tele-sp7276-ch090847-sg0045-mc01-stu-clo-dg030.wav","answer":"and it is thanks to him that i have returned in time with the storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen","subset":"tele","task_type":"understanding","prediction":"and it is thanks to him that i have returned in time with a storm at my heels you marianna are the rightful queen of this country dear queen said the honest and gallant desire let me be the first of your subjects to salute you and he knelt before her and humbly kissed her hand nay prince said the young queen","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1435,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7278\/Lab41-SRI-VOiCES-rm2-tele-sp7278-ch104730-sg0015-mc02-lav-clo-dg180.wav","answer":"but in a moment mister glascock of georgia moved that the petition be not received debate sprang up on a point of order and two days later before the question of reception was determined a resolution was offered by mister jarvis of maine","subset":"tele","task_type":"understanding","prediction":"But in that moment, Mr. Glascock of Georgia moved that the petition be not received. Debate sprang up on a point of order. And two days later, before the question of reception was determined. A resolution was offered by Mr. Jarvis of Maine.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1436,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7498\/Lab41-SRI-VOiCES-rm2-tele-sp7498-ch099156-sg0013-mc02-lav-clo-dg000.wav","answer":"we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klopstock came again to hamburg this he did a year after we had seen one another for the first time","subset":"tele","task_type":"understanding","prediction":"we had not seen one another enough to love as if love must have more time than friendship this was sincerely my meaning and i had this meaning till klumpstock came again to hamburg this he did a year after we had seen one another for the first time","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1437,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7517\/Lab41-SRI-VOiCES-rm2-tele-sp7517-ch100437-sg0000-mc01-stu-clo-dg070.wav","answer":"a household book once on a time i discovered samuel butler not the other two but the one who wrote the way of all flesh the second best novel in the english language","subset":"tele","task_type":"understanding","prediction":"a household book once on a time i discovered samuel butler not the other two but the one who wrote the way of all flesh the second best novel in the english language","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1438,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm2-tele-sp7540-ch101258-sg0019-mc01-stu-clo-dg040.wav","answer":"the poor whale has been lying three years across the strait and men and horses have nearly trampled his back into his ribs is he to lie there much longer i will remember said vassili and he went on he walked and walked","subset":"tele","task_type":"understanding","prediction":"the poor well has been lying three years across a street and men and horses have nearly trampled his back into his ribs is he to lie there much longer i will remember said vassili and he went on he walked and walked","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1439,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm2-tele-sp7540-ch101258-sg0030-mc02-lav-clo-dg110.wav","answer":"and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than even mark the rich had and now the twelve ships which the whale had thrown up came sailing along and anchored close by","subset":"tele","task_type":"understanding","prediction":"and soon came to the old oak tree pushed it with his foot and it fell over there at the roots was more gold and silver than you can mark the rich amount and now the twelve ships which the well had thrown up came sailing along and anchored close by","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":4}
+{"index":1440,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7540\/Lab41-SRI-VOiCES-rm2-tele-sp7540-ch101799-sg0011-mc01-stu-clo-dg180.wav","answer":"had been tempted to put his hard earned money into certain projects that offering in their inception a too alluring promise of continuous prosperity and generous dividends had failed to withstand the test of time and the altered conditions of trade","subset":"tele","task_type":"understanding","prediction":"had been tempted to put his hard earned money into certain projects that offering in their inception a too alluring promise of continuous prosperity and generous dividends had failed to withstand the test of time and the altered conditions of trade","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1441,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7688\/Lab41-SRI-VOiCES-rm2-tele-sp7688-ch105390-sg0030-mc02-lav-clo-dg130.wav","answer":"is mostly unbecoming to your charming sex madame madame la comtesse de tournay de basserive said lord grenville introducing the lady this is a pleasure madame my royal father as you know is ever glad to welcome those of your compatriots","subset":"tele","task_type":"understanding","prediction":"is mostly unbecoming to your charming sex madame madame la comtesse de tournay de gasarit said lord grandbois introducing the lady this is a pleasure madame my royal father as you know is ever glad to welcome those of your compatriots","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1442,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7688\/Lab41-SRI-VOiCES-rm2-tele-sp7688-ch109656-sg0016-mc01-stu-clo-dg080.wav","answer":"it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing a meal or two and sleeping comfortably on your saddle blankets on a soft mattress of mesquite grass","subset":"tele","task_type":"understanding","prediction":"it was a mere nothing for a cattleman or a sheepman to be lost for a day or a night the thing often happened it was merely a matter of missing them a meal or two and sleeping comfortably on your saddle blankets in a soft mattress of mesquite grass","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1443,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-tele-sp7850-ch073752-sg0003-mc02-lav-clo-dg140.wav","answer":"this violent and triumphant revolution in his prospects and his fortunes was hardly yet completely comprehended by our friend ferdinand armine and when he had left a note for the generous mirabel whose slumbers he would not disturb at this early hour even with good news he strolled along up charles street and to the park in one of those wild and joyous reveries in which we brood over coming bliss and create a thousand glorious consequences","subset":"tele","task_type":"understanding","prediction":"this violent and triumphant revolution in his prospects and his fortunes was hardly yet completely comprehended by our friend ferdinand armine and when he had left a note for the generous mirabel whose slumbers he would not disturb at this early hour even with good news he strolled along up charles street and to the park in one of those wild and joyous reveries in which we brood over coming bliss and create a thousand glorious consequences","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1444,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-tele-sp7850-ch073752-sg0008-mc01-stu-clo-dg060.wav","answer":"four and twenty hours ago and he deemed himself the most miserable and forlorn of human beings and now all the blessings of the world seemed showered at his feet","subset":"tele","task_type":"understanding","prediction":"4 and 20 hours ago. And he deemed himself the most miserable and forlorn of human beings. And now, all the blessings of the world seemed showered at his feet.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1445,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7850\/Lab41-SRI-VOiCES-rm2-tele-sp7850-ch111771-sg0002-mc01-stu-clo-dg080.wav","answer":"grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field","subset":"tele","task_type":"understanding","prediction":"grant acted as mustering officer until being commissioned colonel of the twenty first illinois volunteers he took the field","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1446,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7867\/Lab41-SRI-VOiCES-rm2-tele-sp7867-ch275218-sg0023-mc01-stu-clo-dg000.wav","answer":"still it went on snowing and thawing and freezing till the ice was a mile deep over wisconsin and the whole united states was one great skating rink so it kept on for about a million years until once","subset":"tele","task_type":"understanding","prediction":"still it went on snowing and thawing and freezing till the ice was a mile deep over wisconsin and the whole united states was one great skating rink so it kept on for about a million years until once","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1447,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-tele-sp7868-ch110706-sg0013-mc02-lav-clo-dg030.wav","answer":"which sprang from one of the lower and snowless elevations was now nearly in shadow all but the uppermost jets of spray which rose like slow smoke above the undulating line of the cataract and floated away in feeble wreaths upon the morning wind","subset":"tele","task_type":"understanding","prediction":"which sprang from one of the lower and snowless elevations was now nearly in shadow all but the uppermost jet of spray which rose like slow smoke above the undulating line of cataract and floated away in feeble breaths upon the morning wind","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":3}
+{"index":1448,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-tele-sp7868-ch246932-sg0004-mc01-stu-clo-dg090.wav","answer":"but more air through the bars of its lungs i rose dressed and went out it was a still warm night no moon but plenty of star light the wind blowing as now gentle and sweet and cool","subset":"tele","task_type":"understanding","prediction":"but more air through the bars of its lungs i rose dressed and went out it was a still warm night no moon but plenty of starlight the wind blowing as now gentle and sweet and cool","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1449,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7868\/Lab41-SRI-VOiCES-rm2-tele-sp7868-ch246932-sg0006-mc01-stu-clo-dg080.wav","answer":"so long as the stars remained unclouded i could find my way back when i pleased i had been out perhaps an hour when through the soft air came a cry apparently from far off there was something in the tone that seemed to me unusually frightful","subset":"tele","task_type":"understanding","prediction":"so long as the stars remained unclouded i could find my way back when i pleased i had been out perhaps an hour when through the soft air came a cry apparently from far off there was something in the tone that seemed to me unusually frightful","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1450,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm2-tele-sp7881-ch105574-sg0015-mc02-lav-clo-dg040.wav","answer":"yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us","subset":"tele","task_type":"understanding","prediction":"yet few men were injured by them we were in more danger when a fool officer one day took our brigade of infantry down through a cornfield to assault a gunboat that lay in a creek close by the rebel commander had expected us","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1451,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7881\/Lab41-SRI-VOiCES-rm2-tele-sp7881-ch105574-sg0017-mc01-stu-clo-dg080.wav","answer":"in place of chasing murderers and guerrillas in missouri we entered new madrid one morning before daylight the enemy had left in awful haste i recall finding a dead rebel officer lying on a table in his tent in full uniform","subset":"tele","task_type":"understanding","prediction":"in place of chasing murderers and guerrillas in missouri we entered new madrid one morning before daylight the enemy had left in awful haste i recall finding a dead rebel officer lying on a table in his tent in full uniform","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1452,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7932\/Lab41-SRI-VOiCES-rm2-tele-sp7932-ch093470-sg0013-mc01-stu-clo-dg010.wav","answer":"i think that crying last night meant something one way or the other well we shall see we shall see i will be off back again to my work now i feel all the better for having had this talk with you hesba's a good woman and she is fond of the child","subset":"tele","task_type":"understanding","prediction":"i think that crying last night meant something one way or the other well we shall see we shall see i will be off back again to my work now i feel all the better for having had this talk with you hesba is a good woman she is fond of the child","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1453,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm2-tele-sp7976-ch105575-sg0029-mc02-lav-clo-dg050.wav","answer":"a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war","subset":"tele","task_type":"understanding","prediction":"a week after the battle my brother rode by there on a cavalry expedition and made the horrible discovery that hogs were eating up the bodies of our dead heroes that too was war","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1454,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7976\/Lab41-SRI-VOiCES-rm2-tele-sp7976-ch110124-sg0001-mc02-lav-clo-dg010.wav","answer":"every year at a certain day of a certain month he went away to a distant city to collect money on an account","subset":"tele","task_type":"understanding","prediction":"every year at a certain day of a certain month he went away to a distant city to collect money on an account","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1455,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7981\/Lab41-SRI-VOiCES-rm2-tele-sp7981-ch112061-sg0002-mc02-lav-clo-dg180.wav","answer":"bishoprics and abbeys had been too often given to most unworthy persons in france the crown was almost supreme in such matters the queen therefore determined to appoint a council of conscience consisting of five members","subset":"tele","task_type":"understanding","prediction":"bishoprics and abbeys had been too often given to most unworthy persons in france the crown was almost supreme in such matters the queen therefore determined to appoint a council of conscience consisting of five members","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1456,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm2-tele-sp7995-ch276907-sg0009-mc02-lav-clo-dg030.wav","answer":"the first thing after redemption of the coat which mister booth hungry as he was thought of was to supply himself with snuff which he had long to his great sorrow been without on this occasion he presently missed that iron box","subset":"tele","task_type":"understanding","prediction":"the first thing after redemption of the coat which mr booth hungry as he was thought of was to supply himself with snuff which he had long to his great sorrow been without on this occasion he presently missed that iron box","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1457,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp7995\/Lab41-SRI-VOiCES-rm2-tele-sp7995-ch280250-sg0028-mc02-lav-clo-dg040.wav","answer":"hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagine that they have found it","subset":"tele","task_type":"understanding","prediction":"hold fast by this bush it is firmly rooted so here we are on spy rock you have heard of it i thought so other people have heard of it and imagined that they have found it","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1458,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8051\/Lab41-SRI-VOiCES-rm2-tele-sp8051-ch118101-sg0026-mc02-lav-clo-dg180.wav","answer":"though his stout and hearty appearance would have rendered him very desirable to a trader he fled from william wheeling of sandy hook maryland he spoke of his master as a pretty bad man who was always quarreling and would drink swear and lie","subset":"tele","task_type":"understanding","prediction":"though his stout and hearty appearance would have rendered him very desirable to a trader he fled from william whealing of sandy hook maryland he spoke of his master as a pretty bad man who was always quarrelling and would drink swear and lie","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1459,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8057\/Lab41-SRI-VOiCES-rm2-tele-sp8057-ch284428-sg0034-mc02-lav-clo-dg010.wav","answer":"and the only thing i object to is electing the boolooroo for only three hundred years it ought to be for life my successor has already been elected but he can't reign for a hundred years to come i think three hundred years is plenty long enough","subset":"tele","task_type":"understanding","prediction":"and the only thing i object to is electing the deliverer for only three hundred years it ought to be for life my successor has already been elected but he can reign for a hundred years to come i think three hundred years is plenty long enough","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1460,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8108\/Lab41-SRI-VOiCES-rm2-tele-sp8108-ch280359-sg0013-mc02-lav-clo-dg150.wav","answer":"by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death","subset":"tele","task_type":"understanding","prediction":"by making a fishing net he spied in the distance the whole company of the gods approaching his house the sight of them coming all together beautiful and noble and free pierced loki with a pang that was worse than death","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1461,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8118\/Lab41-SRI-VOiCES-rm2-tele-sp8118-ch114469-sg0033-mc01-stu-clo-dg050.wav","answer":"and there were the broad shoulders of sergeant whitley and the figures of the others he rushed through the dripping forest and shouted in a tone that could be heard above the shriek of wind and rain colonel winchester recognized the voice but the light was so dim that he did not recognize him from whom it came","subset":"tele","task_type":"understanding","prediction":"and there were the broad shoulders of sergeant whitley and the figures of the others he rushed through the dripping forest and shouted in a tone that could be heard above the shriek of wind and rain colonel winchester recognized the voice but the light was so dim that he did not recognize him from whom it came","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1462,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8222\/Lab41-SRI-VOiCES-rm2-tele-sp8222-ch274379-sg0008-mc02-lav-clo-dg160.wav","answer":"sir henry vane told the commons that if ever god appeared to them it was in the ordinances of yesterday that as he was credibly informed by many who had been present in different congregations the same lamentations and discourses which the godly preachers had made before them","subset":"tele","task_type":"understanding","prediction":"sir henry bayne told the commons that if ever god appeared to them it was in the ordinances of yesterday that as he was credibly informed by many who had been present in different congregations the same lamentations and discourses which the godly creatures had made before them","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":2}
+{"index":1463,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8222\/Lab41-SRI-VOiCES-rm2-tele-sp8222-ch274379-sg0017-mc02-lav-clo-dg040.wav","answer":"they would find it extremely difficult to supply the place of men now formed by experience to command and authority that the rank alone possessed by such as were members of either house prevented envy retained the army in obedience and gave weight to military orders","subset":"tele","task_type":"understanding","prediction":"they would find it extremely difficult to supply the place of men now formed by experience to command and authority that the rank alone possessed by such as were members of either house prevented envy retained the army in obedience and gave weight to military orders","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1464,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-tele-sp8266-ch258263-sg0036-mc01-stu-clo-dg070.wav","answer":"and said to her grieve not but take patience till thy son be grown a man when i will go to the land of the ajamis and strike off thy father's head from between his shoulders and seat thy son on the throne in his stead so she rose and kissed his hands and blessed him","subset":"tele","task_type":"understanding","prediction":"and said to her grieve not but take patience till thy son be grown a man when i will go to the land of the ajamis and strike off thy father s head from between his shoulders and seat thy son on the throne in his stead so she rose and kissed his hands and blessed him","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":1}
+{"index":1465,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8266\/Lab41-SRI-VOiCES-rm2-tele-sp8266-ch279363-sg0024-mc02-lav-clo-dg100.wav","answer":"they are in the nearer thickets cried the colonel and now they're climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest","subset":"tele","task_type":"understanding","prediction":"they are in the nearer thickets cried the colonel and now they are climbing the slopes ah you riflemen your target is there the northern army was so near now that the southern rifle fire was beating upon it like a storm never flinching the men of the west and northwest","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
+{"index":1466,"question":"Please transcribe the spoken content into written text.","audio_path":"\/workspace\/intern\/pangkaiyu\/dg\/VOiCES_Box_unzip\/Development_Data\/Automatic_Speech_Recognition\/ASR_dev.v2\/rm2\/tele\/sp_6241-8713\/sp8713\/Lab41-SRI-VOiCES-rm2-tele-sp8713-ch296159-sg0014-mc01-stu-clo-dg020.wav","answer":"his literary conscience allowed nothing to take the place of the experimental method the careful observation and arranging of minute facts intimate analytical study from the life no action was too small no emotion too insignificant","subset":"tele","task_type":"understanding","prediction":"His literary conscience allowed nothing to take the place of the experimental method, the careful observation and arranging of minute facts. Intimate, analytical study from the life. No action was too small, no emotion, too insignificant.","real_prompt":"You are a speech recognition model.\nTranscribe the English audio into text without any punctuation marks.","wer_details":0}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank0.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank0.log
new file mode 100644
index 0000000000000000000000000000000000000000..3997d10ab2dab7b5d7a5696a8ec31f7da9b602e6
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank0.log
@@ -0,0 +1,4 @@
+2025-12-21 06:57:23 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:57:23 | INFO | Msg example: {'index': 1, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0112/Lab41-SRI-VOiCES-rm1-babb-sp0112-ch123215-sg0025-mc01-stu-clo-dg080.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
+2025-12-21 07:00:25 | INFO | model Qwen2.5-Omni-7B-lora2, data voices_dev_clo, all 8 result merged to no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/Qwen2.5-Omni-7B-lora2_voices_dev_clo.jsonl.
+2025-12-21 07:00:25 | INFO | skip eval for voices_dev_clo
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank1.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank1.log
new file mode 100644
index 0000000000000000000000000000000000000000..774ad1d9060f5161f350770ff8ab52a7de05d52b
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank1.log
@@ -0,0 +1,2 @@
+2025-12-21 06:57:02 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:57:02 | INFO | Msg example: {'index': 2, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-babb-sp0122-ch121729-sg0002-mc02-lav-clo-dg060.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank2.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank2.log
new file mode 100644
index 0000000000000000000000000000000000000000..eec3ba91036a9bc9d44b699997591dd966be9b6d
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank2.log
@@ -0,0 +1,2 @@
+2025-12-21 06:57:01 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:57:01 | INFO | Msg example: {'index': 3, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0122/Lab41-SRI-VOiCES-rm1-babb-sp0122-ch121730-sg0014-mc01-stu-clo-dg000.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank3.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank3.log
new file mode 100644
index 0000000000000000000000000000000000000000..5a61ba31d2b575be0620dc2cdfff65e1a777b0e5
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank3.log
@@ -0,0 +1,2 @@
+2025-12-21 06:57:13 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:57:13 | INFO | Msg example: {'index': 4, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0159/Lab41-SRI-VOiCES-rm1-babb-sp0159-ch135897-sg0052-mc01-stu-clo-dg100.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank4.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank4.log
new file mode 100644
index 0000000000000000000000000000000000000000..33da912870cb3f3ad2a410279fb1218f9ec44e58
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank4.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:59 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:56:59 | INFO | Msg example: {'index': 5, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0174/Lab41-SRI-VOiCES-rm1-babb-sp0174-ch084280-sg0013-mc02-lav-clo-dg010.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank5.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank5.log
new file mode 100644
index 0000000000000000000000000000000000000000..d3a71c355d54b596ac88f4e38cf71c075995564c
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank5.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:58 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:56:58 | INFO | Msg example: {'index': 6, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0188/Lab41-SRI-VOiCES-rm1-babb-sp0188-ch135249-sg0029-mc01-stu-clo-dg170.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank6.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank6.log
new file mode 100644
index 0000000000000000000000000000000000000000..cfc3b75a2e2777e503792cf534592f95a4992d24
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank6.log
@@ -0,0 +1,2 @@
+2025-12-21 06:56:49 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:56:49 | INFO | Msg example: {'index': 7, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0205/Lab41-SRI-VOiCES-rm1-babb-sp0205-ch159056-sg0032-mc01-stu-clo-dg020.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
diff --git a/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank7.log b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank7.log
new file mode 100644
index 0000000000000000000000000000000000000000..574c7bce932e8eab319bda6e7d94b847f5cb0b50
--- /dev/null
+++ b/different_distribution/no_5e-6_gaussion/Qwen2.5-Omni-7B-lora2/voices_dev_clo/logs/rank7.log
@@ -0,0 +1,2 @@
+2025-12-21 06:57:00 | INFO | Running Qwen2.5-Omni-7B-lora2 on dataset: voices_dev_clo
+2025-12-21 06:57:00 | INFO | Msg example: {'index': 8, 'audio': ['/workspace/intern/pangkaiyu/dg/VOiCES_Box_unzip/Development_Data/Automatic_Speech_Recognition/ASR_dev.v2/rm1/babb/sp_0032-1182/sp0208/Lab41-SRI-VOiCES-rm1-babb-sp0208-ch126851-sg0011-mc02-lav-clo-dg070.wav'], 'text': 'Please transcribe the spoken content into written text.', 'meta': {'task': 'ASR', 'interactive': 'Audio-analysis', 'audio_type': 'Speech', 'dataset_series': 'voices', 'dataset_name': 'voices_dev_clo', 'lang': 'en', 'subset': 'babb'}}
diff --git a/different_distribution/no_5e-6_linear_-5_to_10/Qwen2.5-Omni-7B-lora5/chime4_test-simu_kimi/.ps__00000004bccedd000007602 b/different_distribution/no_5e-6_linear_-5_to_10/Qwen2.5-Omni-7B-lora5/chime4_test-simu_kimi/.ps__00000004bccedd000007602
new file mode 100644
index 0000000000000000000000000000000000000000..348ebd9491ed019f54af8f313ce8a4d782e0e609
--- /dev/null
+++ b/different_distribution/no_5e-6_linear_-5_to_10/Qwen2.5-Omni-7B-lora5/chime4_test-simu_kimi/.ps__00000004bccedd000007602
@@ -0,0 +1 @@
+done
\ No newline at end of file
+
+
+
+